MD investigations for mechanical properties of copper nanowires with and without surface defects

Based on the molecular dynamics (MD) method, the single-crystalline copper nanowire with different surface defects is investigated through tension simulation. For comparison, the MD tension simulations of perfect nanowire are firstly carried out under different temperatures, strain rates, and sizes. It has concluded that the surface-volume ratio significantly affects the mechanical properties of nanowire. The surface defects on nanowires are then systematically studied in considering different defect orientation and distribution. It is found that the Young’s modulus is insensitive of surface defects. However, the yield strength and yield point show a significant decrease due to the different defects. Different defects are observed to serve as a dislocation source.

Knee extensor strength differences in obese and healthy-weight 10-13 year olds

The purpose of this study was to investigate if obese children have reduced knee extensor (KE) strength and to explore the relationship between adiposity and KE strength. An observational case-control study was conducted in three Australian states, recruiting obese [n=107 (51 female, 56 male)] and healthy-weight [n=132 (56 female, 76 male)] 10–13 year old children. Body mass index, body composition (dual energy X-ray absorptiometry), isokinetic/isometric peak KE torques (dynamometry) and physical activity (accelerometry) were assessed. Results revealed that compared with their healthy-weight peers, obese children had higher absolute KE torques (P≤0.005), equivocal KE torques when allometrically normalized for fat-free mass (FFM) (P≥0.448) but lower relative KE torques when allometrically normalized for body mass (P≤0.008). Adjustments for maternal education, income and accelerometry had little impact on group differences, except for isometric KE torques relative to body mass which were no longer significantly lower in obese children (P≥0.013, not significant after controlling for multiple comparisons). Percent body fat was inversely related to KE torques relative to body mass (r= -0.22 to -0.35, P≤0.002), irrespective of maternal education, income or accelerometry. In conclusion, while obese children have higher absolute KE strength and FFM, they have less functional KE strength (relative to mass) available for weight-bearing activities than healthy-weight children. The finding that FFM-normalized KE torques did not differ suggests that the intrinsic contractile properties of the KE muscles are unaffected by obesity. Future research is needed to see if deficits in KE strength relative to mass translate into functional limitations in weight-bearing activities.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Properties of hand-made clay balls used as a novel filter media

Filtration using granular media such as quarried sand, anthracite and granular activated carbon is a well-known technique used in both water and wastewater treatment. A relatively new prefiltration method called pebble matrix filtration (PMF) technology has been proved effective in treating high turbidity water during heavy rain periods that occur in many parts of the world. Sand and pebbles are the principal filter media used in PMF laboratory and pilot field trials conducted in the UK, Papua New Guinea and Serbia. However during first full-scale trials at a water treatment plant in Sri Lanka in 2008, problems were encountered in sourcing the required uniform size and shape of pebbles due to cost, scarcity and Government regulations on pebble dredging. As an alternative to pebbles, hand-made clay pebbles (balls) were fired in a kiln and their performance evaluated for the sustainability of the PMF system. These clay balls within a filter bed are subjected to stresses due to self-weight and overburden, therefore, it is important that clay balls should be able to withstand these stresses in water saturated conditions. In this paper, experimentally determined physical properties including compression failure load (Uniaxial Compressive Strength) and tensile strength at failure (theoretical) of hand-made clay balls are described. Hand-made clay balls fired between the kiln temperatures of 875oC to 960oC gave failure loads of between 3.0 kN and 7.1 kN. In another test when clay balls were fired to 1250oC the failure load was 35.0 kN compared to natural Scottish cobbles with an average failure load of 29.5 kN. The uniaxial compressive strength of clay balls obtained by experiment has been presented in terms of the tensile yield stress of clay balls. Based on the effective stress principle in soil mechanics, a method for the estimation of maximum theoretical load on clay balls used as filter media is proposed and compared with experimental failure loads.

Microstructures and strengthening mechanisms of Cu/Ni/W nanolayered composites

Cu/Ni/W nanolayered composites with individual layer thickness ranging from 5nm to 300nm were prepared by a magnetron sputtering system. Microstructures and strength of the nanolayered composites were investigated by using the nanoindentation method combined with theoretical analysis. Microstructure characterization revealed that the Cu/Ni/W composite consists of a typical Cu/Ni coherent interface and Cu/W and Ni/W incoherent interfaces. Cu/Ni/W composites have an ultrahigh strength and a large strengthening ability compared with bi-constituent Cu–X(X¼Ni, W, Au, Ag, Cr, Nb, etc.) nanolayered composites. Summarizing the present results and those reported in the literature, we systematically analyze the origin of the ultrahigh strength and its length scale dependence by taking into account the constituent layer properties, layer scales and heterogeneous layer/layer interface characteristics, including lattice and modulus mismatch as well as interface structure.

Mechanical properties of bioinspired bicontinuous nanocomposites

Inspired by the wonderful properties of some biological composites in nature, we performed molecular dynamics simulations to investigate the mechanical behavior of bicontinuous nanocomposites. Three representative types of bicontinuous composites, which have regular network, random network, and nacre inspired microstructures respectively, were studied and the results were compared with those of a honeycomb nanocomposite with only one continuous phase. It was found that the mechanical strength of nanocomposites in a given direction strongly depends on the connectivity of microstructure in that direction. Directional isotropy in mechanical strength and easy manufacturability favor the random network nanocomposites as a potentially great bioinspired composite with balanced performances. In addition, the tensile strength of random network nanocomposites is less sensitive to the interfacial failure, owing to its super high interface-to-volume ratio and random distribution of internal interfaces. The results provide a useful guideline for design and optimization of advanced nanocomposites with superior mechanical properties.

Ultimate flexural limit states analysis of prestressed concrete sleeper

Railway is one of the most important, reliable and widely used means of transportation, carrying freight, passengers, minerals, grains, etc. Thus, research on railway tracks is extremely important for the development of railway engineering and technologies. The safe operation of a railway track is based on the railway track structure that includes rails, fasteners, pads, sleepers, ballast, subballast and formation. Sleepers are very important components of the entire structure and may be made of timber, concrete, steel or synthetic materials. Concrete sleepers were first installed around the middle of last century and currently are installed in great numbers around the world. Consequently, the design of concrete sleepers has a direct impact on the safe operation of railways. The "permissible stress" method is currently most commonly used to design sleepers. However, the permissible stress principle does not consider the ultimate strength of materials, probabilities of actual loads, and the risks associated with failure, all of which could lead to the conclusion of cost-ineffectiveness and over design of current prestressed concrete sleepers. Recently the limit states design method, which appeared in the last century and has been already applied in the design of buildings, bridges, etc, is proposed as a better method for the design of prestressed concrete sleepers. The limit states design has significant advantages compared to the permissible stress design, such as the utilisation of the full strength of the member, and a rational analysis of the probabilities related to sleeper strength and applied loads. This research aims to apply the ultimate limit states design to the prestressed concrete sleeper, namely to obtain the load factors of both static and dynamic loads for the ultimate limit states design equations. However, the sleepers in rail tracks require different safety levels for different types of tracks, which mean the different types of tracks have different load factors of limit states design equations. Therefore, the core tasks of this research are to find the load factors of the static component and dynamic component of loads on track and the strength reduction factor of the sleeper bending strength for the ultimate limit states design equations for four main types of tracks, i.e., heavy haul, freight, medium speed passenger and high speed passenger tracks. To find those factors, the multiple samples of static loads, dynamic loads and their distributions are needed. In the four types of tracks, the heavy haul track has the measured data from Braeside Line (A heavy haul line in Central Queensland), and the distributions of both static and dynamic loads can be found from these data. The other three types of tracks have no measured data from sites and the experimental data are hardly available. In order to generate the data samples and obtain their distributions, the computer based simulations were employed and assumed the wheel-track impacts as induced by different sizes of wheel flats. A valid simulation package named DTrack was firstly employed to generate the dynamic loads for the freight and medium speed passenger tracks. However, DTrack is only valid for the tracks which carry low or medium speed vehicles. Therefore, a 3-D finite element (FE) model was then established for the wheel-track impact analysis of the high speed track. This FE model has been validated by comparing its simulation results with the DTrack simulation results, and with the results from traditional theoretical calculations based on the case of heavy haul track. Furthermore, the dynamic load data of the high speed track were obtained from the FE model and the distributions of both static and dynamic loads were extracted accordingly. All derived distributions of loads were fitted by appropriate functions. Through extrapolating those distributions, the important parameters of distributions for the static load induced sleeper bending moment and the extreme wheel-rail impact force induced sleeper dynamic bending moments and finally, the load factors, were obtained. Eventually, the load factors were obtained by the limit states design calibration based on reliability analyses with the derived distributions. After that, a sensitivity analysis was performed and the reliability of the achieved limit states design equations was confirmed. It has been found that the limit states design can be effectively applied to railway concrete sleepers. This research significantly contributes to railway engineering and the track safety area. It helps to decrease the failure and risks of track structure and accidents; better determines the load range for existing sleepers in track; better rates the strength of concrete sleepers to support bigger impact and loads on railway track; increases the reliability of the concrete sleepers and hugely saves investments on railway industries. Based on this research, many other bodies of research can be promoted in the future. Firstly, it has been found that the 3-D FE model is suitable for the study of track loadings and track structure vibrations. Secondly, the equations for serviceability and damageability limit states can be developed based on the concepts of limit states design equations of concrete sleepers obtained in this research, which are for the ultimate limit states.

The association of early life supplemental nutrition with lean body mass and grip strength in adulthood : evidence from APCAPS

In the present study, we examined the associations of early nutrition with adult lean body mass (LBM) and muscle strength in a birth cohort that was established to assess the long-term impact of a nutrition program. Participants (n = 1,446, 32% female) were born near Hyderabad, India, in 29 villages from 1987 to 1990, during which time only intervention villages (n = 15) had a government program that offered balanced protein-calorie supplementation to pregnant women and children. Participants’ LBM and appendicular skeletal muscle mass were measured using dual energy x-ray absorptiometry; grip strength and information on lifestyle indicators, including diet and physical activity level, were also obtained. Ages (mean = 20.3 years) and body mass indexes (weight (kg)/height (m)2; mean = 19.5) of participants in 2 groups were similar. Current dietary energy intake was higher in the intervention group. Unadjusted LBM and grip strength were similar in 2 groups. After adjustment for potential confounders, the intervention group had lower LBM (β = −0.75; P = 0.03), appendicular skeletal muscle mass, and grip strength than did controls, but these differences were small in magnitude (<0.1 standard deviation). Multivariable regression analyses showed that current socioeconomic position, energy intake, and physical activity level had a positive association with adult LBM and muscle strength. This study could not detect a “programming” effect of early nutrition supplementation on adult LBM and muscle strength.

Groundwater table response to sea level rise and its impact on pavement structure

It has been predicted that sea level will rise about 0.8 m by 2100. Consequently, seawater can intrude into the coastal aquifers and change the level of groundwater table. A raise in groundwater table due to seawater intrusion threats the coastal infrastructure such as road pavements. The mechanical properties of subgrade materials will change due to elevated rise of groundwater table, leading to pavement weakening and decreasing the subgrade strength and stiffness. This paper presents an assessment of the vulnerability of subgrade in coastal areas to change in groundwater table due to sea-level rise. A simple bathtub approach is applied for estimating the groundwater level changes according to sea-level rise. Then the effect of groundwater level changes on the soil water content (SWC) of a single column of fine-sand soil is simulated using MIKE SHE. The impact of an increase in moisture content on subgrade strength/stiffness is assessed for a number of scenarios.

Comparison of mechanical and ultrasound elastic modulus of ovine tibial cortical bone

Finite element models of bones can be created by deriving geometry from anx-ray CT scan. Material properties such as the elastic modulus can then be applied using either a single or set of homogeneous values, or individual elements can have local values mapped onto them. Values for the elastic modulus can be derived from the CT density values using an elasticityversus density relationship. Many elasticity–density relationships have been reported in the literature for human bone. However, while ovine in vivo models are common in orthopaedic research, no work has been done to date on creating FE models of ovine bones. To create these models and apply relevant material properties, an ovine elasticity-density relationship needs to be determined. Using fresh frozen ovine tibias the apparent density of regions of interest was determined from a clinical CT scan. The bones were the sectioned into cuboid samples of cortical bone from the regions of interest. Ultrasound was used to determine the elastic modulus in each of three directions – longitudinally, radially and tangentially. Samples then underwent traditional compression testing in each direction. The relationships between apparent density and both ultrasound, and compression modulus in each directionwere determined. Ultrasound testing was found to be a highly repeatable non-destructive method of calculating the elastic modulus, particularly suited to samples of this size. The elasticity-density relationships determined in the longitudinal direction were very similar between the compression and ultrasound data over the density range examined.A clear difference was seen in the elastic modulus between the longitudinal and transverse directions of the bone samples, and a transverse elasticity-density relationship is also reported.

Designing atmospheric-pressure plasma sources for surface engineering of nanomaterials

Atmospheric-pressure plasma processing techniques emerge as efficient and convenient tools to engineer a variety of nanomaterials for advanced applications in nanoscience and nanotechnology. This work presents different methods, including using a quasi-sinusoidal high-voltage generator, a radio-frequency power supply, and a uni-polar pulse generator, to generate atmospheric-pressure plasmas in the jet or dielectric barrier discharge configurations. The applicability of the atmospheric-pressure plasma is exemplified by the surface modification of nanoparticles for polymeric nanocomposites. Dielectric measurements reveal that representative nanocomposites with plasma modified nanoparticles exhibit notably higher dielectric breakdown strength and a significantly extended lifetime.

Dielectric performance of polymer nanocomposites synthesized by atmospheric-pressure plasma-treated silica nanoparticles

In this study, atmospheric-pressure plasmas were applied to modify the surface of silane-coated silica nanoparticles. Subsequently nanocomposites were synthesized by incorporating plasma-treated nanoparticles into an epoxy resin matrix. Electrical testing showed that such novel dielectric materials obtained high partial discharge resistance, high dielectric breakdown strength, and enhanced endurance under highly stressed electric field. Through spectroscopic and microscopic analysis, we found surface groups of nanoparticles were activated and radicals were created after the plasma treatment. Moreover, a uniform dispersion of nanoparticles in nanocomposites was observed. It was expected that the improved dielectric performance of the nanocomposites can attribute to stronger chemical bonds formed between surface groups of plasma-treated nanoparticles and molecules in the matrix. This simple yet effective and environmentally friendly approach aims to synthesize the next generation of high-performance nanocomposite dielectric insulation materials for applications in high-voltage power systems.

Silica nanoparticles treated by cold atmospheric-pressure plasmas improve the dielectric performance of organic–inorganic nanocomposites

We report on the application of cold atmospheric-pressure plasmas to modify silica nanoparticles to enhance their compatibility with polymer matrices. Thermally nonequilibrium atmospheric-pressure plasma is generated by a high-voltage radio frequency power source operated in the capacitively coupled mode with helium as the working gas. Compared to the pure polymer and the polymer nanocomposites with untreated SiO2, the plasma-treated SiO2–polymer nanocomposites show higher dielectric breakdown strength and extended endurance under a constant electrical stress. These improvements are attributed to the stronger interactions between the SiO2 nanoparticles and the surrounding polymer matrix after the plasma treatment. Our method is generic and can be used in the production of high-performance organic–inorganic functional nanocomposites.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Normal reference values of strength in pelvic floor muscle of women: A descriptive and inferential study

Background To describe the clinical, functional and quality of life characteristics in women with Stress Urinary Incontinence (SUI). In addition, to analyse the relationship between the variables reported by the patients and those informed by the clinicians, and the relationship between instrumented variables and the manual pelvic floor strength assessment. Methods Two hundred and eighteen women participated in this observational, analytical study. An interview about Urinary Incontinence and the quality of life questionnaires (EuroQoL-5D and SF-12) were developed as outcomes reported by the patients. Manual muscle testing and perineometry as outcomes informed by the clinician were assessed. Descriptive and correlation analysis were carried out. Results The average age of the subjects was (39.93?±?12.27 years), (24.49?±?3.54 BMI). The strength evaluated by manual testing of the right levator ani muscles was 7.79?±?2.88, the strength of left levator ani muscles was 7.51?±?2.91 and the strength assessed with the perineometer was 7.64?±?2.55. A positive correlation was found between manual muscle testing and perineometry of the pelvic floor muscles (p?and outcomes of functional capacity informed by the physiotherapist. Conclusion A stratification of the strength of pelvic floor muscles in a normal distribution of a large sample of women with SUI was done, which provided the clinic with a baseline. There is a relationship between the strength of the pelvic muscles assessed manually and that obtained by a perineometer in women with SUI. There was no relationship between these values of strength and quality of life perceived.