Free vibration analysis of functionally graded shell panels with various geometric shapes in thermal environment

This paper presents free vibration analysis of functionally graded materials (FGMs) shell panels with various geometric shapes in thermal environments. The shell panels are made from a mixture of metal and ceramic. Material properties are assumed to be temperature-dependent and graded in the thickness direction according to a power law function. A formulation of eight-nodded middle surface shell elements based on Reissner-Mindlin assumptions is developed for modeling FGM shell panels under the effect of temperature, which changes nonlinearly across the thickness. Numerical results obtained by the proposed model are in good agreement with those available in the literature. The effects of geometric properties, material composition, boundary conditions and temperature on the natural frequencies are investigated

Mitigating effect of embankment to adjacent pipe with CDM columns

Pipelines are valuable infrastructures that covering a large area or expanding to long distance for the transporting function. This leads to the variety of loads and effects applied on such buried structures. A thread to pipeline integrity is the construction of the embankment on the soft soil which leads to the displacement of the pipe adjacent to the slope. This displacement will effect to the increase of internal force or causing failure of the near-by pipes. The use of concrete pile to improve the soil properties may be a solution; however, the cost for this is expensive. To propose an alternative solution for the problem, this study uses a system of cement deep mixing, CDM, columns as the solution for protecting the pipe. A simple 2D Finite Element, FE, model using Plaxis software has been established based on the equivalent soil approach which considering the CDM columns and their surrounding soil as an unified soil. The effectiveness of the proposed solution has been numerically investigated and proven. The lateral displacement of pipe and the maximum ring bending moment and other internal forces are significantly reduced with the appearance of the CDM columns. The selective parametric study has been implemented revealing the critical input variables are the distance of pipe to the slope and the length of the CDM column

Aquilaria yunnanensis S.C. Huang (Thymelaeaceae), A New Record for the Flora of Vietnam

Aquilaria yunnanensis S.C. Huang (Thymelaeaceae), known to be endemic to Yunnan, is recorded for the first time from Dong Son Ky Thuong Nature Reserve, Quang Ninh Province, Vietnam. A taxonomic description and DNA analysis based on our Vietnamese collections are presented, together with information on its distribution, habitat and colour photographs

High Proportion of Genome-Wide Homology and Increased Pretreatment pvcrt Levels in Plasmodium vivax Late Recurrences: a Chloroquine Therapeutic Efficacy Study.

Chloroquine (CQ) is the first-line treatment for Plasmodium vivax malaria in most countries where malaria is endemic. Monitoring P. vivax CQ resistance (CQR) is critical but remains challenged by the difficulty to distinguish real treatment failure from reinfection or liver relapse. The therapeutic efficacy of CQ against uncomplicated P. vivax malaria was evaluated in Gia Lai Province, Vietnam. Sixty-seven patients were enrolled and followed for 42 days using microscopy and quantitative PCR. Adequate clinical and parasitological response (ACPR) was 100% (66/66) on day 28 but 75.4% (49/65) on day 42. Eighteen recurrences (27.7%) were detected, with a median time to recurrence of 42 days (interquartile range [IQR], 35 to 42) and blood CQ concentration of 98% identity by descent to paired day 0 samples. This study shows that CQ remained largely efficacious to treat P. vivax in Gia Lai; i.e., recurrences occurred late (>day 28) and in the presence of low blood CQ concentrations. However, the combination of both WGS and gene expression analysis (pvcrt) data with clinical data (PCT) allowed us to identify potential emergence of low-grade CQR, which should be closely monitored. (This study has been registered at ClinicalTrials.gov under identifier NCT02610686.)

Speech enhancement based on nonnegative matrix factorization with mixed group sparsity constraint

International audienceThis paper addresses a challenging single-channel speech enhancement problem in real-world environment where speech signal is corrupted by high level background noise. While most state-of-the-art algorithms tries to estimate noise spectral power and filter it from the observed one to obtain enhanced speech, the paper discloses another approach inspired from audio source separation technique. In the considered method, generic spectral characteristics of speech and noise are first learned from various training signals by non-negative matrix factorization (NMF). They are then used to guide the similar factorization of the observed power spectrogram into speech part and noise part. Additionally, we propose to combine two existing group sparsity-inducing penalties in the optimization process and adapt the corresponding algorithm for parameter estimation based on mul-tiplicative update (MU) rule. Experiment results over different settings confirm the effectiveness of the proposed approach

Mitigating effect of embankment to adjacent pipe with CDM columns

Pipelines are valuable infrastructures that covering a large area or expanding to long distance for the transporting function. This leads to the variety of loads and effects applied on such buried structures. A thread to pipeline integrity is the construction of the embankment on the soft soil which leads to the displacement of the pipe adjacent to the slope. This displacement will effect to the increase of internal force or causing failure of the near-by pipes. The use of concrete pile to improve the soil properties may be a solution; however, the cost for this is expensive. To propose an alternative solution for the problem, this study uses a system of cement deep mixing, CDM, columns as the solution for protecting the pipe. A simple 2D Finite Element, FE, model using Plaxis software has been established based on the equivalent soil approach which considering the CDM columns and their surrounding soil as an unified soil. The effectiveness of the proposed solution has been numerically investigated and proven. The lateral displacement of pipe and the maximum ring bending moment and other internal forces are significantly reduced with the appearance of the CDM columns. The selective parametric study has been implemented revealing the critical input variables are the distance of pipe to the slope and the length of the CDM column

Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections

The main aim of this study is to develop different hybrid artificial intelligence (AI) approaches, such as an adaptive neuro-fuzzy inference system (ANFIS) and two ANFISs optimized by metaheuristic techniques, namely simulated annealing (SA) and biogeography-based optimization (BBO) for predicting the critical buckling load of structural members under compression, taking into account the influence of initial geometric imperfections. With this aim, the existing results of compression tests on steel columns were collected and used as a dataset. Eleven input parameters, representing the slenderness ratios and initial geometric imperfections, were considered. The predicted target was the critical buckling load of columns. Statistical criteria, namely the correlation coefficient (R), the root mean squared error (RMSE), and the mean absolute error (MAE) were used to evaluate and validate the three proposed AI models. The results showed that SA and BBO were able to improve the prediction performance of the original ANFIS. Excellent results using the BBO optimization technique were achieved (i.e., an increase in R by 7.15%, RMSE by 40.48%, and MAE by 38.45%), and those using the SA technique were not much different (i.e., an increase in R by 5.03%, RMSE by 26.68%, and MAE by 20.40%). Finally, sensitivity analysis was performed, and the most important imperfections affecting column buckling capacity was found to be the initial in-plane loading eccentricity at the top and bottom ends of the columns. The methodology and the developed AI models herein could pave the way to establishing an advanced approach to forecasting damages of columns under compression