Boundary layer flow of nanofluid over an exponentially stretching surface

The steady boundary layer flow of nanofluid over an exponential stretching surface is investigated analytically. The transport equations include the effects of Brownian motion parameter and thermophoresis parameter. The highly nonlinear coupled partial differential equations are simplified with the help of suitable similarity transformations. The reduced equations are then solved analytically with the help of homotopy analysis method (HAM). The convergence of HAM solutions are obtained by plotting h-curve. The expressions for velocity, temperature and nanoparticle volume fraction are computed for some values of the parameters namely, suction injection parameter α, Lewis number Le, the Brownian motion parameter Nb and thermophoresis parameter Nt

A semi-analytic method with an effect of memory for solving fractional differential equations

In this paper, we propose a new modification of the multistage generalized differential transform method (MsGDTM) for solving fractional differential equations. In MsGDTM, it is the key how to impose an initial condition in each sub-domain to obtain an accurate approximate solution. In several literature works (Odibat et al. in Comput. Math. Appl. 59:1462-1472, 2010; Alomari in Comput. Math. Appl. 61:2528-2534, 2011; Gokdoğan et al. in Math. Comput. Model. 54:2132-2138, 2011), authors have updated an initial condition in each sub-domain by using the approximate solution in the previous sub-domain. However, we point out that this approach is hard to apply an effect of memory which is the basic property of fractional differential equations. Here we provide a new algorithm to impose the initial conditions by using the integral operator that enhances accuracy. Several illustrative examples are demonstrated, and it is shown that the proposed technique is robust and accurate for solving fractional differential equations.close0

Burden of musculoskeletal disorders in the Eastern Mediterranean Region, 1990-2013: findings from the Global Burden of Disease Study 2013.

OBJECTIVES: We used findings from the Global Burden of Disease Study 2013 to report the burden of musculoskeletal disorders in the Eastern Mediterranean Region (EMR). METHODS: The burden of musculoskeletal disorders was calculated for the EMR's 22 countries between 1990 and 2013. A systematic analysis was performed on mortality and morbidity data to estimate prevalence, death, years of live lost, years lived with disability and disability-adjusted life years (DALYs). RESULTS: For musculoskeletal disorders, the crude DALYs rate per 100 000 increased from 1297.1 (95% uncertainty interval (UI) 924.3-1703.4) in 1990 to 1606.0 (95% UI 1141.2-2130.4) in 2013. During 1990-2013, the total DALYs of musculoskeletal disorders increased by 105.2% in the EMR compared with a 58.0% increase in the rest of the world. The burden of musculoskeletal disorders as a proportion of total DALYs increased from 2.4% (95% UI 1.7-3.0) in 1990 to 4.7% (95% UI 3.6-5.8) in 2013. The range of point prevalence (per 1000) among the EMR countries was 28.2-136.0 for low back pain, 27.3-49.7 for neck pain, 9.7-37.3 for osteoarthritis (OA), 0.6-2.2 for rheumatoid arthritis and 0.1-0.8 for gout. Low back pain and neck pain had the highest burden in EMR countries. CONCLUSIONS: This study shows a high burden of musculoskeletal disorders, with a faster increase in EMR compared with the rest of the world. The reasons for this faster increase need to be explored. Our findings call for incorporating prevention and control programmes that should include improving health data, addressing risk factors, providing evidence-based care and community programmes to increase awareness

Modern approach to numerical modelling of anchored protective structures

radu je opisan suvremeni pristup numeričkom modeliranju sidrenih zaštitnih konstrukcija s osvrtom na iskustva u primjeni računalnog programa Plaxis 2D i modela tla s izotropnim očvršćivanjem. Objašnjena su osnovna obilježja u ponašanju tla u dreniranim i nedreniranim uvjetima za naprezanja koja se pojavljuju pri iskopu građevne jame. Prikazan je primjer simulacije sidrene zaštitne konstrukcije i dane su smjernice za strategiju odabira parametara materijala HSs modela tla.modern approach to numerical modelling of anchored protective structures is presented in the paper, and an overview is given of experience gained in the use of the Plaxis 2D computer program, and soil model with isotropic strengthening. Basic properties of soil in drained and undrained conditions, due to stress occurring during foundation pit excavation, are explained. An example involving simulation of an anchored protective structure is presented, and guidelines for the selection of soil materials for the HSs soil model are given

Source degenerate identification problems with smoothing overdetermination

Abstract We consider degenerate identification problems with smoothing overdetermination in abstract spaces. We establish an identifiability result using a projection method and suitable hypotheses on the operators involved and develop an identification method by reformulating the problem into a nondegenerate problem. Then we use perturbation results for linear operators to solve the regular problem. The introduced identification method permits one to solve the problems under the minimum restrictions on the input data. Finally, we provide applications to degenerate differential equations that appear in mathematical physics to support the theoretical results

Advances in CRISPR-Cas9 for the Baculovirus Vector System: A Systematic Review

The baculovirus expression vector systems (BEVS) have been widely used for the recombinant production of proteins in insect cells and with high insert capacity. However, baculovirus does not replicate in mammalian cells; thus, the BacMam system, a heterogenous expression system that can infect certain mammalian cells, was developed. Since then, the BacMam system has enabled transgene expression via mammalian-specific promoters in human cells, and later, the MultiBacMam system enabled multi-protein expression in mammalian cells. In this review, we will cover the continual development of the BEVS in combination with CRPISPR-Cas technologies to drive genome-editing in mammalian cells. Additionally, we highlight the use of CRISPR-Cas in glycoengineering to potentially produce a new class of glycoprotein medicines in insect cells. Moreover, we anticipate CRISPR-Cas9 to play a crucial role in the development of protein expression systems, gene therapy, and advancing genome engineering applications in the future

DAMTRNN: A Delta attention-based multi-task RNN for intention recognition

Recognizing human intentions from electroencephalographic (EEG) signals is attracting extraordinary attention from the artificial intelligence community because of its promise in providing non-muscular forms of communication and control to those with disabilities. So far, studies have explored correlations between specific segments of an EEG signal and an associated intention. However, there are still challenges to be overcome on the road ahead. Among these, vector representations suffer from the enormous amounts of noise that characterize EEG signals. Identifying the correlations between signals from adjacent sensors on a headset is still difficult. Further, research not yet reached the point where learning models can accept decomposed EEG signals to capture the unique biological significance of the six established frequency bands. In pursuit of a more effective intention recognition method, we developed DAMTRNN, a delta attention-based multi-task recurrent neural network, for human intention recognition. The framework accepts divided EEG signals as inputs, and each frequency range is modeled separately but concurrently with a series of LSTMs. A delta attention network fuses the spatial and temporal interactions across different tasks into high-impact features, which captures correlations over longer time spans and further improves recognition accuracy. Comparative evaluations between DAMTRNN and 14 state-of-the-art methods and baselines show DAMTRNN with a record-setting performance of 98.87% accuracy