A survey of knowledge and practice of simulation among health tutors in selected health training institutions

AIM

The aim of the study was to describe the knowledge and practice of simulation among health tutors with a view to promoting the use of simulation in health training institutions in the Northern and Upper East Regions of Ghana.

DESIGN

The study was quantitative research that utilized a descriptive cross-sectional survey to describe the knowledge and practice of simulation in teaching.

METHODS

A structured questionnaire was used to collect data from 138 health tutors who were enumerated through the census for the study. The return rate was 87%, representing 120 health tutors who finally completed the study. The data were presented by means of descriptive statistics.

RESULTS

The findings of the study revealed that few participants had adequate knowledge of simulation. The study also found that a slight majority of the participants practiced simulation in teaching. The study further found that there was a positive correlation between health tutors' knowledge and the practice of simulation. Indicating that an increase in the health tutors' knowledge of simulation is associated with an increase in their practice of simulation.

Rational Design of the N-Terminal Coding Sequence for Regulating Enzyme Expression in Bacillus subtilis

Synonymous mutation of the N-terminal coding sequence (NCS) has been used to regulate gene expression. We here developed a statistical model to predict the effect of the NCSs on protein expression in Bacillus subtilis WB600. First, a synonymous mutation was performed within the first 10 residues of a superfolder green fluorescent protein to generate a library of 172 NCS synonymous mutants with different expression levels. A prediction model was then developed, which adopted G/C frequency at the third position of each codon and minimum free energy of mRNA as the independent variables, using multiple regression analysis between the 11 sequence parameters of the NCS and their fluorescence intensities. By designing the NCS of the 10 signal peptides de novo according to the model, the extracellular yield of B. subtilis pullulanase fused to each signal peptide was up-regulated by up to 515% or down-regulated by at most 79%. This work provided a candidate tool for fine-tuning gene expression or enzyme production in B. subtilis.

Quantitative Description of External Force Induced Phase Transformation in Silicon-Manganese (Si-Mn) Transformation Induced Plasticity (TRIP) Steels

Transformation Induced Plasticity (TRIP) steels with silicon–manganese (Si–Mn) as the main element have attracted a lot of attention and great interest from steel companies due to their low price, high strength, and high plasticity. Retained austenite is of primary importance as the source of high strength and high plasticity in Si–Mn TRIP steels. In this work, the cold rolled sheets of Si–Mn low carbon steel were treated with TRIP and Dual Phase (DP) treatment respectively. Then, the microstructure and composition of the Si–Mn low carbon steel were observed and tested. The static tensile test of TRIP steel and DP steel was carried out by a CMT5305 electronic universal testing machine. The self-built true stress–strain curve model of TRIP steel was verified. The simulation results were in good agreement with the experimental results. In addition, the phase transformation energy of retained austenite and the work borne by austenite in the sample during static stretching were calculated. The work done by austenite was 14.5 J, which was negligible compared with the total work of 217.8 J. The phase transformation energy absorption of retained austenite in the sample was 9.12 J. The role of retained austenite in TRIP steel is the absorption of excess energy at the key place where the fracture will occur, thereby increasing the elongation, so that the ferrite and bainite in the TRIP steel can absorb energy for a longer time and withstand more energy.

Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.

Quantitative description of collagen fibre network on trabecular bone surfaces based on AFM imaging

The collagen fibre network is an important part of extracellular matrix (ECM) on trabecular bone surface. The geometry features of the network can provide us insights into its physical and physiological properties. However, previous researches have not focused on the geometry and the quantitative description of the collagen fibre network on trabecular bone surface. In this study,we developed a procedure to quantitatively describe the network and verified the validity of the procedure. The experiment proceeds as follow. Atomic force microscopy (AFM) was used to acquire submicron resolution images of the trabecular surface. Then, an image analysing procedure was built to extract important parameters, including, fibre orientation, fibre density, fibre width, fibre crossing numbers, the number of holes formed by fibre s, and the area of holes from AFM images. In order to verify the validity of the parameters extracted by image analysing methods, we adopted two other methods, which are statistical geometry model and computer simulation, to calculate those same parameters and check the consistency of the three methods' results. Statistical tests indicate that there is no significant difference between three groups. We conclude that, (a) the ECM on trabecular surface mainly consists of random collagen fibre network with oriented fibres; (b) our method based on image analysing can be used to characterize quantitative geometry features of the collagen fibre network effectively. This method may provide a basis for quantitative investigating the architecture and function of collagen fibre network.