Synthesize and characterization of artificial human bone developed by using nanocomposite

The combination of biopolymers with bioceramics plays vital role in development of artificial bone. Hydroxyapatite is extensively used as a material in prosthetic bone repair and replacement. In this paper synthesis of Hydroxyapatite- Polymethyl methacrylate – Zirconia (Hap-PMMA-ZrO2) composite by using powder metallurgy technique. The mechanical, morphological, In-vitro biocompatibility and tribological properties were characterized by universal testing machine, micro-vickers hardness tester, high resolution transmission electron microscope (HR-TEM), MTT assay and pin-on-disc setup. In-vitro cytotoxicity test on HeLa cell lines shows cell viability constant when doses concentration increases so material found non-toxic. Results show that micro Vickers hardness i.e. 520 approximately matches with natural human bone i.e. 400. Compressive strength is less as compared to human bone because of powder metallurgy route used for fabrication and is 74 MPa. Density of proposed composite artificial human bone i.e. 1.52 g/cc is less as compared to natural bone i.e. 2.90 g/cc. The Hap-PMMA-ZrO2 composite will be good biomaterials for bone repair and replacement wor

Efficient Detectors based on Group Detection for Massive MIMO systems

In Multiple Input Multiple Output (MIMO) systems, the complexities of detectors depend on the size of the channel matrix. In Massive MIMO systems, detection complexity becomes remarkably higher because the dimensions of the channel matrix get much larger. In order to recover the signals in the up-link of a Massive MIMO system at reduced complexities, we first divide the system into two sub-systems. After that, we apply the Minimum Mean Square Error (MMSE) and Bell Laboratory Layer Space Time (BLAST) detectors to each subsystem, resulting in the so-called MMSE-GD and BLAST-GD detectors, respectively. To further enhance the BER performance of Massive MIMO systems under the high-load conditions, we propose two additional detectors, called MMSE-IGD and BLAST-IGD by respectively applying the conventional MMSE and BLAST on the sub-systems in an iterative manner. It is shown via computer simulation and analytical results that the proposed detectors enable the system to achieve not only higher BER performance but also low detection complexities as compared to the conventional linear detectors. Moreover, the MMSE-IGD and BLAST-IGD can significantly improve BER performance of Massive MIMO systems

Characterization of Vibrio cholerae O139 of an Aquatic Isolate in Northern Vietnam

During the cholera survey in Namdinh province (northern Vietnam) in July, 2010, one strain of Vibrio cholerae O139 was isolated from 7 environmental water samples positive for ctxA, toxR, VCO139 genes and named as V. cholerae O139, ND1 strain. This strain was lysogenic harbouring a genome similar to the filamentous phage fs1. The replicative form DNA of this phage (named as ND1-fs1, 6856 bp) was sequenced and compared with the other filamentous phages. The filamentous phage ND1-fs1 integrates into the region between ctxB and rtxA genes. The genetic organization of the CTXϕ of V. cholerae O139, strain ND1 was determined and the schematic representation of the genetic organization was shown together with the ND1-fs1 prophage

EFFECTS OF SALT STRESS ON PLANT GROWTH AND BIOMASS ALLOCATION IN SOME WETLAND GRASS SPECIES IN THE MEKONG DELTA

Salt stress causes serious damage to many cellular and physiological processes that leads to yield reduction. The study induced salt stress using Hoagland solution added NaCl to evaluate its effects on plant growth and biomass allocation of some wetland grass species in order to identify salt-tolerant species for replacing and/or supplementing rice/grass in rice-shrimp model and salt-affected area in the Mekong Delta. The study also seeks to evaluate the response of leaf chlorophyll (SPAD unit) and proline content in salt-treated plants to varying application of salinity. Typha orientalis, Lepironia articulata, Eleocharis dulcis and Scirpus littoralis were studied in hydroponics condition with four levels of NaCl of 5, 10, 15, 20‰ and the control treatment (without adding NaCl). The experiment was arranged in a completely randomized design with 3 replications. The salt-treated plants showed visually clear responses of inhibited growth under salt stress condition compared to the control plants. Among the four studied species, T. orientalis produced the highest dry shoot biomass (15.5 g DW/plant), while E. dulcis had the lowest value (2.8 g DW/plant). However, only T. orientalis showed significantly decreased in biomass as salinity increased with 9.3 and 4.6 times lower of fresh and dry biomass in plants grown at the salinity level of 20‰ compared to those grown in the control treatment. The other three plant species did not affect by salinity levels. The results indicated that S. littoralis, L. articulata and E. dulcis could tolerate at high salinity of 20‰ (eq. to the EC value in the nutrient solution of 38.0 dS/m) and could be potential candidate to grow in the rice-shrimp model or in the salt-affected soils. 

Late Pleistocene-Holocene sequence stratigraphy of the subaqueous Red River delta and the adjacent shelf

The model of Late Pleistocene-Holocene sequence stratigraphy of the subaqueous Red River delta and the adjacent shelf is proposed by interpretation of high-resolution seismic documents and comparison with previous research results on Holocene sedimentary evolution on the delta plain. Four units (U1, U2, U3, and U4) and four sequence stratigraphic surfaces (SB1, TS, TRS and MFS) were determined. The formation of these units and surfaces is related to the global sea-level change in Late Pleistocene-Holocene. SB1, defined as the sequence boundary, was generated by subaerial processes during the Late Pleistocene regression and could be remolded partially or significantly by transgressive ravinement processes subsequently. The basal unit U1 (fluvial formations) within incised valleys is arranged into the lowstand systems tract (LST) formed in the early slow sea-level rise ~19-14.5 cal.kyr BP, the U2 unit is arranged into the early transgressive systems tract (E-TST) deposited mainly within incised-valleys under the tide-influenced river to estuarine conditions in the rapid sea-level rise ~14.5-9 cal.kyr BP, the U3 unit is arranged into the late transgressive systems tract (L-TST) deposited widely on the continental shelf in the fully marine condition during the late sea-level rise ~9-7 cal.kyr BP, and the U4 unit represents for the highstand systems tract (HST) with clinoform structure surrounding the modern delta coast, extending to the water depth of 25-30 m, developed by sediments from the Red River system in ~3-0 cal.kyr BP.ReferencesBadley M.E., 1985. Practical Seismic Interpretation. International Human Resources Development Corporation, Boston, 266p.Bergh  G.D. 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Depositional sedimentary environments with reference to terrigenous clastics. Springer-Verlag Berlin Heidelberg New York, 551p. Ross K., 2011. Fate of Red River Sediment in the Gulf of Tonkin, Vietnam. Master Thesis. North Carolina State University, 91p.Saito Y., Katayama H., Ikehara K., Kato Y., Matsumoto E., Oguri K., Oda M., Yumoto M. 1998. Transgressive and highstand systems tracts and post-glacial transgression, the East China Sea. Sedimentary Geology, 122, 217-232.Stattegger K., Tjallingii R., Saito Y., Michelli M., Nguyen T.T., Wetzel A., 2013. Mid to late Holocene sea-level reconstruction of Southeast Vietnam using beachrock and beach-ridge deposits. Global and Planetary Change, 110, 214-222.Tanabe S., Hori K., Saito Y., Haruyama S., Doanh L.Q., Sato Y., Hiraide S., 2003a. Sedimentary facies and radiocarbon dates of the Nam Dinh-1 core from the Song Hong (Red River) delta, Vietnam. 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Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A Novel Horse Racing Algorithm Based MPPT Control for Standalone PV Power Systems

This paper proposes a novel maximum power point tracking (MPPT) method inspired by the horse racing game for standalone photovoltaic (PV) power systems, such that the highest PV power conversion efficiency is obtained. From the horse racing game rules, we develop the horse racing algorithm (HRA) with the qualifying stage and final ranking stage. The MPP can be searched even if there exist multiple local MPPs for the PV power system. Moreover, from the proposed horse racing algorithm, the calculation is reduced, so that the transient searching points are less than traditional methods, i.e., the transient oscillation is less during the MPPT control. Therefore, the HRA based MPPT method avoids local maximum power traps and achieves the MPP quickly even if considering partial shading influence and varying environment for PV panels. Evidence of the accuracy and effectiveness of the proposed HRA method is exhibited by simulation results. These results are also compared with typical particle swarm optimization (PSO) and grey wolf optimization (GWO) methods and shown better convergence time as well as transient oscillation. Within the range from 0.34 to 0.58 s, the proposed method has effectively tracked the global maximum power point, which is from 0.42 to 0.48 s faster than the conventional PSO technique and from 0.36 to 0.74 s faster than the GWO method. Finally, the obtained findings proved the effectiveness and superiority of the proposed HRA technique through experimental results. The fast response in terms of good transient oscillation and global power tracking time of the proposed method are from 0.40 to 1.0 s, while the PSO and GWO methods are from 1.56 to 1.6 s and from 1.9 to 2.2 s, respectively

A Novel Horse Racing Algorithm Based MPPT Control for Standalone PV Power Systems

This paper proposes a novel maximum power point tracking (MPPT) method inspired by the horse racing game for standalone photovoltaic (PV) power systems, such that the highest PV power conversion efficiency is obtained. From the horse racing game rules, we develop the horse racing algorithm (HRA) with the qualifying stage and final ranking stage. The MPP can be searched even if there exist multiple local MPPs for the PV power system. Moreover, from the proposed horse racing algorithm, the calculation is reduced, so that the transient searching points are less than traditional methods, i.e., the transient oscillation is less during the MPPT control. Therefore, the HRA based MPPT method avoids local maximum power traps and achieves the MPP quickly even if considering partial shading influence and varying environment for PV panels. Evidence of the accuracy and effectiveness of the proposed HRA method is exhibited by simulation results. These results are also compared with typical particle swarm optimization (PSO) and grey wolf optimization (GWO) methods and shown better convergence time as well as transient oscillation. Within the range from 0.34 to 0.58 s, the proposed method has effectively tracked the global maximum power point, which is from 0.42 to 0.48 s faster than the conventional PSO technique and from 0.36 to 0.74 s faster than the GWO method. Finally, the obtained findings proved the effectiveness and superiority of the proposed HRA technique through experimental results. The fast response in terms of good transient oscillation and global power tracking time of the proposed method are from 0.40 to 1.0 s, while the PSO and GWO methods are from 1.56 to 1.6 s and from 1.9 to 2.2 s, respectively

Ensemble learning using traditional machine learning and deep neural network for diagnosis of Alzheimer’s disease

In recent years, Alzheimer’s disease (AD) diagnosis using neuroimaging and deep learning has drawn great research attention. However, due to the scarcity of training neuroimaging data, many deep learning models have suffered from severe overfitting. In this study, we propose an ensemble learning framework that combines deep learning and machine learning. The deep learning model was based on a 3D-ResNet to exploit 3D structural features of neuroimaging data. Meanwhile, Extreme Gradient Boosting (XGBoost) machine learning was applied on a voxel-wise basis to draw the most significant voxel groups out of the image. The 3D-ResNet and XGBoost predictions were combined with patient demographics and cognitive test scores (Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR)) to give a final diagnosis prediction. Our proposed method was trained and validated on brain MRI brain images of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. During the training phase, multiple data augmentation methods were employed to tackle overfitting. Our test set contained only baseline scans, i.e., the first visit scans since we aimed to investigate the ability of our approach in detecting AD during the first visit of AD patients. Our 5-fold cross-validation implementation achieved an average AUC of 100% during training and 96% during testing. Using the same computer, our method was much faster in scoring a prediction, approximately 10 min, than feature extraction-based machine learning methods, which often take many hours to score a prediction. To make the prediction explainable, we visualized the brain MRI image regions that primarily affected the 3D-ResNet model’s prediction via heatmap. Lastly, we observed that proper generation of test sets was critical to avoiding the data leakage issue and ensuring the validity of results