Lattice Boltzmann parallel simulation of microflow dynamics over structured surfaces

In the present work, a parallel lattice Boltzmann multiphase model was developed to investigate the effects of surface structures on wettabilities and flow dynamics in a microchannel. The theory of wetting transition was firstly discussed. Then three types including triangular, rectangle and hierarchical shaped microstructures were constructed on the surface to examine the effects on wettabilities and drag reduction. It was found that flow behaviour is strongly affected by the surface morphology of the channel. The results indicated that hierarchical structures on the surface could improve the hydrophobicity significantly. For rectangular structures, they can improve the hydrophobicity with the increase of height and distance ratio h/d of the structures, and the improvement will reach its optimal hydrophobicity when the value h/d is over a certain value of 0.6. Moreover, to accelerate computational speed, the Open Multi-Processing (OpenMP) was employed for the parallelization of the model. A maximum speedup of 2.95 times was obtained for 4 threads on a multi-core CPU platform

Gender-Based Deep Learning Firefly Optimization Method for Test Data Generation.

Software testing is a widespread validation means of software quality assurance in industry. Intelligent optimization algorithms have been proved to be an effective way of automatic test data generation. Firefly algorithm has received extensive attention and been widely used to solve optimization problems because of less parameters and simple implement. To overcome slow convergence rate and low accuracy of the firefly algorithm, a novel firefly algorithm with deep learning is proposed to generate structural test data. Initially, the population is divided into male subgroup and female subgroup. Following the randomly attracted model, each male firefly will be attracted by another randomly selected female firefly to focus on global search in whole space. Each female firefly implements local search under the leadership of the general center firefly, constructed based on historical experience with deep learning. At the final period of searching, chaos search is conducted near the best firefly to improve search accuracy. Simulation results show that the proposed algorithm can achieve better performance in terms of success coverage rate, coverage time, and diversity of solutions

Three dimensional lattice Boltzmann simulation for mixed convection of nanofluids in the presence of magnetic field

In the present study, a three dimensional thermal lattice Boltzmann model was developed to investigate the flow dynamics and mixed convection heat transfer of Al2O3/water nanofluid in a cubic cavity in the presence of magnetic field. The model was first validated with previous numerical and experimental results. Satisfactory agreement was obtained. Then the effects of Rayleigh number, nanoparticle volume fraction, Hartmann number and Richardson number on nanofluid flow dynamics and heat transfer were examined. Numerical results indicate that adding nanoparticles to pure water leads to heat transfer enhancement for low Rayleigh numbers. However, this enhancement might be weakened and even reversed for high Rayleigh numbers. In addition, the results show the external applied magnetic field has an effect of suppressing the convective heat transfer in the cavity. Moreover, the results demonstrate that the Richardson number in mixed convection has significant influences on both streamlines and temperature field

Metabolic engineering of Saccharomyces cerevisiae for production of very long chain fatty acid-derived chemicals

Production of chemicals and biofuels through microbial fermentation is an economical and sustainable alternative for traditional chemical synthesis. Here we present the construction of a Saccharomyces cerevisiae platform strain for high-level production of very-long-chain fatty acid (VLCFA)-derived chemicals. Through rewiring the native fatty acid elongation system and implementing a heterologous Mycobacteria FAS I system, we establish an increased biosynthesis of VLCFAs in S. cerevisiae. VLCFAs can be selectively modified towards the fatty alcohol docosanol (C22H46O) by expressing a specific fatty acid reductase. Expression of this enzyme is shown to impair cell growth due to consumption of VLCFA-CoAs. We therefore implement a dynamic control strategy for separating cell growth from docosanol production. We successfully establish high-level and selective docosanol production of 83.5 mg l(-1) in yeast. This approach will provide a universal strategy towards the production of similar high value chemicals in a more scalable, stable and sustainable manner

Molecular dynamics simulation of surfactant induced wettability alteration of shale reservoirs

Shale oil has recently received considerable attention as a promising energy source due to its substantial reserves. However, the recovery of shale oil presents numerous challenges due to the low-porosity and low-permeability characteristics of shale reservoirs. To tackle this challenge, the introduction of surfactants capable of modifying wettability has been employed to enhance shale oil recovery. In this study, we perform molecular dynamics simulations to investigate the influence of surfactants on the alteration of wettability in shale reservoirs. Firstly, surfaces of kaolinite, graphene, and kerogen are constructed to represent the inorganic and organic constituents of shale reservoirs. The impact and underlying mechanisms of two types of ionic surfactants, namely, the anionic surfactant sodium dodecylbenzene sulfonate (SDBS) and cationic surfactant dodecyltrimethylammonium bromide (DTAB), on the wettability between oil droplets and surfaces are investigated. The wettability are analyzed from different aspects, including contact angle, centroid ordinates, and self-diffusion coefficient. Simulation results show that the presence of surfactants can modify the wetting characteristics of crude oil within shale reservoirs. Notably, a reversal of wettability has been observed for oil-wet kaolinite surfaces. As for kerogen surfaces, it is found that an optimal surfactant concentration exists, beyond which the further addition of surfactant may not enhance the efficiency of wettability alteration

Differential Deployment of REST and CoREST Promotes Glial Subtype Specification and Oligodendrocyte Lineage Maturation

The repressor element-1 (RE1) silencing transcription factor/neuron-restrictive silencer factor (REST/NRSF) is a master transcriptional regulator that binds to numerous genomic RE1 sites where it acts as a molecular scaffold for dynamic recruitment of modulatory and epigenetic cofactors, including corepressor for element-1-silencing transcription factor (CoREST). CoREST also acts as a hub for various cofactors that play important roles in epigenetic remodeling and transcriptional regulation. While REST can recruit CoREST to its macromolecular complex, CoREST complexes also function at genomic sites independently of REST. REST and CoREST perform a broad array of context-specific functions, which include repression of neuronal differentiation genes in neural stem cells (NSCs) and other non-neuronal cells as well as promotion of neurogenesis. Despite their involvement in multiple aspects of neuronal development, REST and CoREST are not believed to have any direct modulatory roles in glial cell maturation.We challenged this view by performing the first study of REST and CoREST in NSC-mediated glial lineage specification and differentiation. Utilizing ChIP on chip (ChIP-chip) assays, we identified distinct but overlapping developmental stage-specific profiles for REST and CoREST target genes during astrocyte (AS) and oligodendrocyte (OL) lineage specification and OL lineage maturation and myelination, including many genes not previously implicated in glial cell biology or linked to REST and CoREST regulation. Amongst these factors are those implicated in macroglial (AS and OL) cell identity, maturation, and maintenance, such as members of key developmental signaling pathways and combinatorial transcription factor codes.Our results imply that REST and CoREST modulate not only neuronal but also glial lineage elaboration. These factors may therefore mediate critical developmental processes including the coupling of neurogenesis and gliogenesis and neuronal-glial interactions that underlie synaptic and neural network plasticity and homeostasis in health and in specific neurological disease states

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

Longitudinal Imaging of the Ageing Mouse

Several non-invasive imaging techniques are used to investigate the effect of pathologies and treatments over time in mouse models. Each preclinical in vivo technique provides longitudinal and quantitative measurements of changes in tissues and organs, which are fundamental for the evaluation of alterations in phenotype due to pathologies, interventions and treatments. However, it is still unclear how these imaging modalities can be used to study ageing with mice models. Almost all age related pathologies in mice such as osteoporosis, arthritis, diabetes, cancer, thrombi, dementia, to name a few, can be imaged in vivo by at least one longitudinal imaging modality. These measurements are the basis for quantification of treatment effects in the development phase of a novel treatment prior to its clinical testing. Furthermore, the non-invasive nature of such investigations allows the assessment of different tissue and organ phenotypes in the same animal and over time, providing the opportunity to study the dysfunction of multiple tissues associated with the ageing process. This review paper aims to provide an overview of the applications of the most commonly used in vivo imaging modalities used in mouse studies: micro-computed-tomography, preclinical magnetic-resonance-imaging, preclinical positron-emission-tomography, preclinical single photon emission computed tomography, ultrasound, intravital microscopy, and whole body optical imaging

NUMERICAL INVESTIGATION ON INTERFACIAL PHENOMENA OF FERROFLUID BY LATTICE BOLTZMANN METHOD

ABSTRACT Ferrofluid, also known as magnetic fluid, is a new-type fluid whose property and morphology can be controlled by the external magnetic field. It mainly consists of carrier fluid and suspended magnetic particles (diameter usually 10 nanometers or less). Ferrofluids behave as a smart or functional fluid and has been finding more and more applications in a variety of fields such as electronic packing, mechanical engineering, aerospace, bioengineering, and thermal engineering. It has therefore recently attracted many researchers' interest. Due to the nanosize particles and complex interactions between the nanoparticles and carrier fluid, it is difficult to get insights into ferrofluid by pure experimental or theoretical study. To fully understand the mechanism of ferrofluid, efficient and robust computational methods for the numerical simulation of their dynamical behavior are constantly in high demand. Several numerical models have been proposed for ferrofluid. Over the last decade, lattice Boltzmann method, a new mesoscopic approach, has emerged as a powerful tool for the numerical investigation of a broad class of complex flow, including multicomponent and multiphase flows. Compared with other numerical methods, lattice Boltzmann method, which is based on kinetic theory, has advantages to deal with the interfacial interactions of multiphase flow in micro/nano scale. In the present study, we present a multicomponent lattice Boltzmann model to simulate ferrofluid. In this model, the interactions between internal and external forces of ferrofluid are considered. To validate the coupling of the magnetic field, the velocity field and the evolution of the interface, the steadystate shape of the ferrofluid droplet is analysed. Then the influence of the external magnetic field on the ferrofluid droplet formation and deformation process is numerically investigated. The parameters affecting the interfacial phenomena of ferrofluid, including the magnetic Bond number and the susceptibility, are discussed in this paper. The change in the droplet size and the magnetic strength is simulated. The simulation results show the ferrofluid droplet size increases with increasing magnetic strength. All the results are also compared with previous numerical or experimental studies. The simulation results presented in this paper indicate that lattice Boltzmann method is a capable method to study complex magnetic fluid phenomena. It is also hoped that the simulation results offer helpful information on controlling ferrofluid in our practical applications