Artificial neural networks to predict activity type and energy expenditure in youth

Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

Reconstruction of critical-sized ovine mandibular defects - a pilot study

Establishing the sheep model for translational research of mandible (jaw) segmental defect regeneration. Providing a framework from which additional experimentation and evaluation of novel tissue engineered constructs may be undertaken, compared and collated. For current and future novel approaches to mandible segmental defect reconstruction that may be transferable to the human condition and, ultimately, the operative table.

On helical shear of a compressible elastic circular cylindrical tube

In this paper we examine the combined azimuthal and axial shear of a compressible isotropic elastic circular cylindrical tube of finite extent, otherwise referred to as helical shear (which is an isochoric deformation). The equilibrium equations are formulated in terms of the principal stretches, and explicit necessary and sufficient conditions on the strain-energy function for the material to support this deformation are obtained and compared with those obtained previously for this problem. Several classes of strain-energy functions are derived and in some general cases complete solutions of the equilibrium equations are obtained. Existing results are recovered as special cases and some new results for the strain-energy functions derived are determined and discussed.

Selective neuronal differentiation of neural stem cells induced by nanosecond microplasma agitation

An essential step for therapeutic and research applications of stem cells is their ability to differentiate into specific cell types. Neuronal cells are of great interest for medical treatment of neurodegenerative diseases and traumatic injuries of central nervous system (CNS), but efforts to produce these cells have been met with only modest success. In an attempt of finding new approaches, atmospheric-pressure room-temperature microplasma jets (MPJs) are shown to effectively direct in vitro differentiation of neural stem cells (NSCs) predominantly into neuronal lineage. Murine neural stem cells (C17.2-NSCs) treated with MPJs exhibit rapid proliferation and differentiation with longer neurites and cell bodies eventually forming neuronal networks. MPJs regulate ~. 75% of NSCs to differentiate into neurons, which is a higher efficiency compared to common protein- and growth factors-based differentiation. NSCs exposure to quantized and transient (~. 150. ns) micro-plasma bullets up-regulates expression of different cell lineage markers as β-Tubulin III (for neurons) and O4 (for oligodendrocytes), while the expression of GFAP (for astrocytes) remains unchanged, as evidenced by quantitative PCR, immunofluorescence microscopy and Western Blot assay. It is shown that the plasma-increased nitric oxide (NO) production is a factor in the fate choice and differentiation of NSCs followed by axonal growth. The differentiated NSC cells matured and produced mostly cholinergic and motor neuronal progeny. It is also demonstrated that exposure of primary rat NSCs to the microplasma leads to quite similar differentiation effects. This suggests that the observed effect may potentially be generic and applicable to other types of neural progenitor cells. The application of this new in vitro strategy to selectively differentiate NSCs into neurons represents a step towards reproducible and efficient production of the desired NSC derivatives. © 2013.

Defects induced ferromagnetism in plasma-enabled graphene nanopetals

Ferromagnetism in graphene is fascinating, but it is still a big challenge for practical applications due to the weak magnetization. In order to enhance the magnetization, here, we design plasma-enabled graphene nanopetals with ultra-long defective edges of up to 105 m/g, ultra-dense lattice vacancies, and hydrogen chemisorptions. The designed graphene nanopetals display robust ferromagnetism with large saturation magnetization of up to 2 emu/g at 5 K and 1.2 emu/g at room temperatures. This work identifies the plasma-enabled graphene nanopetals as a promising candidate for graphene-based magnetic devices.

Harnessing the influence of reactive edges and defects of graphene substrates for achieving complete cycle of room-temperature molecular sensing

Molecular doping and detection are at the forefront of graphene research, a topic of great interest in physical and materials science. Molecules adsorb strongly on graphene, leading to a change in electrical conductivity at room temperature. However, a common impediment for practical applications reported by all studies to date is the excessively slow rate of desorption of important reactive gases such as ammonia and nitrogen dioxide. Annealing at high temperatures, or exposure to strong ultraviolet light under vacuum, is employed to facilitate desorption of these gases. In this article, the molecules adsorbed on graphene nanoflakes and on chemically derived graphene-nanomesh flakes are displaced rapidly at room temperature in air by the use of gaseous polar molecules such as water and ethanol. The mechanism for desorption is proposed to arise from the electrostatic forces exerted by the polar molecules, which decouples the overlap between substrate defect states, molecule states, and graphene states near the Fermi level. Using chemiresistors prepared from water-based dispersions of single-layer graphene on mesoporous alumina membranes, the study further shows that the edges of the graphene flakes (showing p-type responses to NO2 and NH3) and the edges of graphene nanomesh structures (showing n-type responses to NO2 and NH3) have enhanced sensitivity. The measured responses towards gases are comparable to or better than those which have been obtained using devices that are more sophisticated. The higher sensitivity and rapid regeneration of the sensor at room temperature provides a clear advancement towards practical molecule detection using graphene-based materials.

Dopamine transporter genotype predicts behavioural and neural measures of response inhibition

The ability to inhibit unwanted actions is a heritable executive function that may confer risk to disorders such as attention deficit hyperactivity disorder (ADHD). Converging evidence from pharmacology and cognitive neuroscience suggests that response inhibition is instantiated within frontostriatal circuits of the brain with patterns of activity that are modulated by the catecholamines dopamine and noradrenaline. A total of 405 healthy adult participants performed the stop-signal task, a paradigmatic measure of response inhibition that yields an index of the latency of inhibition, termed the stop-signal reaction time (SSRT). Using this phenotype, we tested for genetic association, performing high-density single-nucleotide polymorphism mapping across the full range of autosomal catecholamine genes. Fifty participants also underwent functional magnetic resonance imaging to establish the impact of associated alleles on brain and behaviour. Allelic variation in polymorphisms of the dopamine transporter gene (SLC6A3: rs37020; rs460000) predicted individual differences in SSRT, after corrections for multiple comparisons. Furthermore, activity in frontal regions (anterior frontal, superior frontal and superior medial gyri) and caudate varied additively with the T-allele of rs37020. The influence of genetic variation in SLC6A3 on the development of frontostriatal inhibition networks may represent a key risk mechanism for disorders of behavioural inhibition.

Beneficial defects : exploiting the intrinsic polishing-induced wafer roughness for the catalyst-free growth of Ge in-plane nanowires

We outline a metal-free fabrication route of in-plane Ge nanowires on Ge(001) substrates. By positively exploiting the polishing-induced defects of standard-quality commercial Ge(001) wafers, micrometer-length wires are grown by physical vapor deposition in ultra-high-vacuum environment. The shape of the wires can be tailored by the epitaxial strain induced by subsequent Si deposition, determining a progressive transformation of the wires in SiGe faceted quantum dots. This shape transition is described by finite element simulations of continuous elasticity and gives hints on the equilibrium shape of nanocrystals in the presence of tensile epitaxial strain.

A comparative study of Sr-incorporated mesoporous bioactive glass scaffolds for regeneration of osteopenic bone defects

SUMMARY: Recently, the use of the pharmacological agent strontium ranelate has come to prominence for the treatment of osteoporosis. While much investigation is focused on preventing disease progression, here we fabricate strontium-containing scaffolds and show that they enhance bone defect healing in the femurs of rats induced by ovariectomy. INTRODUCTION: Recently, the use of the pharmacological agent strontium ranelate has come to prominence for the treatment of osteoporosis due to its ability to prevent bone loss in osteoporotic patients. Although much emphasis has been placed on using pharmacological agents for the prevention of disease, much less attention has been placed on the construction of biomaterials following osteoporotic-related fracture. The aim of the present study was to incorporate bioactive strontium (Sr) trace element into mesoporous bioactive glass (MBG) scaffolds and to investigate their in vivo efficacy for bone defect healing in the femurs of rats induced by ovariectomy. METHODS: In total, 30 animals were divided into five groups as follows: (1) empty defect (control), (2) empty defects with estrogen replacement therapy, (3) defects filled with MBG scaffolds alone, (4) defects filled with MBG + estrogen replacement therapy, and (5) defects filled with strontium-incorporated mesopore-bioglass (Sr-MBG) scaffolds. RESULTS: The two groups demonstrating the highest levels of new bone formation were the defects treated with MBG + estrogen replacement therapy and the defects receiving Sr-MBG scaffolds as assessed by μ-CT and histological analysis. Furthermore, Sr scaffolds had a reduced number of tartrate-resistant acid phosphatase-positive cells when compared to other modalities. CONCLUSION: The results from the present study demonstrate that the local release of Sr from bone scaffolds may improve fracture repair. Future large animal models are necessary to investigate the future relationship of Sr incorporation into biomaterials.

Characterization of a DC-driven microplasma between a capillary tube and water surface

A microplasma generated between a stainless-steel capillary and water surface in ambient air with flowing argon as working gas appears as a bright spot at the tube orifice and expands to form a larger footprint on the water surface, and the dimensions of the bell-shaped microplasma are all below 1 mm. The electron density of the microplasma is estimated to be ranging from 5.32 × 109 cm−3 to 2.02 × 1014 cm−3 for the different operating conditions, which is desirable for generating abundant amounts of reactive species. A computational technique is adopted to fit the experimental emission from the N2 second positive system with simulation results. It is concluded that the vibrational temperature (more than 2000 K) is more than twice the gas temperature (more than 800 K), which indicates the non-equilibrium state of the microplasma. Both temperatures showed dependence on the discharge parameters (i.e., gas flow and discharge current). Such a plasma device could be arranged in arrays for applications utilizing plasmainduced liquid chemistry.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Particle size distribution effects on preferential deposition areas in metal foam wrapped tube bundle

This paper presents a numerical model for understanding particle transport and deposition in metal foam heat exchangers. Two-dimensional steady and unsteady numerical simulations of a standard single row metal foam-wrapped tube bundle are performed for different particle size distributions, i.e. uniform and normal distributions. Effects of different particle sizes and fluid inlet velocities on the overall particle transport inside and outside the foam layer are also investigated. It was noted that the simplification made in the previously-published numerical works in the literature, e.g. uniform particle deposition in the foam, is not necessarily accurate at least for the cases considered here. The results highlight the preferential particle deposition areas both along the tube walls and inside the foam using a developed particle deposition likelihood matrix. This likelihood matrix is developed based on three criteria being particle local velocity, time spent in the foam, and volume fraction. It was noted that the particles tend to deposit near both front and rear stagnation points. The former is explained by the higher momentum and direct exposure of the particles to the foam while the latter only accommodate small particles which can be entrained in the recirculation region formed behind the foam-wrapped tubes.

Facial emotion modulates the neural mechanisms responsible for short interval time perception

Emotionally arousing events can distort our sense of time. We used mixed block/event-related fMRI design to establish the neural basis for this effect. Nineteen participants were asked to judge whether angry, happy and neutral facial expressions that varied in duration (from 400 to 1,600 ms) were closer in duration to either a short or long duration they learnt previously. Time was overestimated for both angry and happy expressions compared to neutral expressions. For faces presented for 700 ms, facial emotion modulated activity in regions of the timing network Wiener et al. (NeuroImage 49(2):1728–1740, 2010) namely the right supplementary motor area (SMA) and the junction of the right inferior frontal gyrus and anterior insula (IFG/AI). Reaction times were slowest when faces were displayed for 700 ms indicating increased decision making difficulty. Taken together with existing electrophysiological evidence Ng et al. (Neuroscience, doi: 10.3389/fnint.2011.00077, 2011), the effects are consistent with the idea that facial emotion moderates temporal decision making and that the right SMA and right IFG/AI are key neural structures responsible for this effect.