Interactions between toothbrush and toothpaste particles during simulated abrasive cleaning

Most people clean their teeth using toothpaste, consisting of abrasive particles in a carrier fluid, and a filament based toothbrush to remove plaque and stain. In order to optimise cleaning efficiency it is important to understand how toothbrush filaments, abrasive particles and fluid interact in a tooth cleaning contact. Work has been carried out to visualise, simulate, and model the processes in teeth cleaning. Laboratory cleaning contacts were created between a toothbrush and a transparent surface. Video and short duration flash photography were used to study the processes by which a toothbrush traps abrasive particles, loads them against the counterface, and removes material. Small abrasive particles tend to be trapped at the contact between the filament tip and the counterface, whilst larger particles are trapped by clumps of filaments or at the contact with the side of a bent filament. Measurements of brush friction force were recorded during cleaning for a range of operating conditions. The presence of abrasive particles in the cleaning mixture increased the coefficient of friction, but the absolute particle concentration showed a lesser effect. It is surmised that only a few particles carry any load and cause any abrasion; increasing the particle concentration does not directly increase the number of load bearing particles. Abrasive scratch tests were also carried out, using PMMA as a wearing substrate. The scratches produced during these tests were studied. The microscopy images were used to deduce how the filaments deflect and drag, and how particles are trapped by filaments and scratch the surface. Again, it was observed that few of the brush filaments loaded particles to produce scratches, and that when a filament changes direction of travel the trapped particle is lost. Results of these studies were used to develop both qualitative and quantitative models of the process by which material is removed in teeth cleaning. The quantitative model contains, by necessity, several empirical factors, but nonetheless predictions compare well with in vitro wear results from the literature. The results were also used to draw some broad conclusions on appropriate brushing techniques for optimum tooth cleaning

Perceptions and correlates of peer-victimization and bullying

The experiences of peer-victimization and bullying are often treated empirically as though they are conceptually indistinct. Both involve repeated aggression,but definitions of bullying additionally emphasize the importance of aggressor intent and imbalance of power between the aggressor and the victim (Olweus, 1978; Whitney & Smith, 1993). The present study aimed to examine the extent to which peer-victimization and bullying are empirically similar. The sample comprised 1,429 pupils (50.2% male) aged between 8 and 13 years attending mainstream Scottish schools. Self-report questionnaire assessing peer-victimization and bullying, copingstrategy use (WCCL: Hunter, 2000), situational appraisal and depressive symptomatology (Birleson, 1981). Almost one-third (30.7%) of pupils reported experiencing peer-victimization, and of these 38.1% (11.7% of whole sample) were categorized as victims of bullying. Victims of bullying perceived higher levels of threat and lower levels of perceived control. They also reported using more Wishful Thinking and Social Support coping strategies, but did not differ on Problem Focused coping. Bullied pupils also reported higher levels of depressive symptomatology. Peer-victimization and bullying appear to be qualitatively different experiences for children and adolescents, with bullying being the more serious phenomenon

CARMIL family proteins as multidomain regulators of actin-based motility

CARMILs are large multidomain proteins that regulate the actin-binding activity of capping protein (CP), a major capper of actin filament barbed ends in cells. CARMILs bind directly to CP and induce a conformational change that allosterically decreases but does not abolish its actin-capping activity. The CP-binding domain of CARMIL consists of the CP-interaction (CPI) and CARMIL-specific interaction (CSI) motifs, which are arranged in tandem. Many cellular functions of CARMILs require the interaction with CP; however, a more surprising result is that the cellular function of CP in cells appears to require binding to a CARMIL or another protein with a CPI motif, suggesting that CPI-motif proteins target CP and modulate its actin-capping activity. Vertebrates have three highly conserved genes and expressed isoforms of CARMIL with distinct and overlapping localizations and functions in cells. Various domains of these CARMIL isoforms interact with plasma membranes, vimentin intermediate filaments, SH3-containing class I myosins, the dual-GEF Trio, and other adaptors and signaling molecules. These biochemical properties suggest that CARMILs play a variety of membrane-associated functions related to actin assembly and signaling. CARMIL mutations and variants have been implicated in several human diseases. We focus on roles for CARMILs in signaling in addition to their function as regulators of CP and actin. </jats:p

Financial signal processing: a self calibrating model

Previous work on multifactor term structure models has proposed that the short rate process is a function of some unobserved diffusion process. We consider a model in which the short rate process is a function of a Markov chain which represents the 'state of the world'. This enables us to obtain explicit expressions for the prices of zero-coupon bonds and other securities. Discretizing our model allows the use of signal processing techniques from Hidden Markov Models. This means we can estimate not only the unobserved Markov chain but also the parameters of the model, so the model is self-calibrating. The estimation procedure is tested on a selection of U.S. Treasury bills and bonds.Bonds

Partial discharge testing of defective three-phase PILC cable under rated conditions

The ability to accurately monitor the health of power distribution plant is a very attractive prospect for utility companies. This capability would provide a system that engineers could use to assess the real-time state of the network. Analysis of the data produced could allow for more informed decisions to be made in the areas of asset replacement and maintenance scheduling amongst others. It is widely accepted that partial discharge activity is linked with the electrical ageing/degradation of high voltage equipment. Work at Southampton is focused on obtaining a better understanding of the characteristics and trends of partial discharge events associated with medium voltage cables under, 'real life' conditions. An experiment has been developed that allows for service conditions to be applied to defective paper insulated lead covered cable samples. The samples under investigation were exposed to mechanical damage designed to replicate typical problems found on an active circuit. Partial discharge measurement was undertaken during the stressing process

The Distribution of Mixing Times in Markov Chains

The distribution of the "mixing time" or the "time to stationarity" in a discrete time irreducible Markov chain, starting in state i, can be defined as the number of trials to reach a state sampled from the stationary distribution of the Markov chain. Expressions for the probability generating function, and hence the probability distribution of the mixing time starting in state i are derived and special cases explored. This extends the results of the author regarding the expected time to mixing [J.J. Hunter, Mixing times with applications to perturbed Markov chains, Linear Algebra Appl. 417 (2006) 108-123], and the variance of the times to mixing, [J.J. Hunter, Variances of first passage times in a Markov chain with applications to mixing times, Linear Algebra Appl. 429 (2008) 1135-1162]. Some new results for the distribution of recurrence and first passage times in three-state Markov chain are also presented.Comment: 24 page

Label-free proteomics identifies Calreticulin and GRP75/Mortalin as peripherally accessible protein biomarkers for spinal muscular atrophy

BACKGROUND: Spinal muscular atrophy (SMA) is a neuromuscular disease resulting from mutations in the survival motor neuron 1 (SMN1) gene. Recent breakthroughs in preclinical research have highlighted several potential novel therapies for SMA, increasing the need for robust and sensitive clinical trial platforms for evaluating their effectiveness in human patient cohorts. Given that most clinical trials for SMA are likely to involve young children, there is a need for validated molecular biomarkers to assist with monitoring disease progression and establishing the effectiveness of therapies being tested. Proteomics technologies have recently been highlighted as a potentially powerful tool for such biomarker discovery. METHODS: We utilized label-free proteomics to identify individual proteins in pathologically-affected skeletal muscle from SMA mice that report directly on disease status. Quantitative fluorescent western blotting was then used to assess whether protein biomarkers were robustly changed in muscle, skin and blood from another mouse model of SMA, as well as in a small cohort of human SMA patient muscle biopsies. RESULTS: By comparing the protein composition of skeletal muscle in SMA mice at a pre-symptomatic time-point with the muscle proteome at a late-symptomatic time-point we identified increased expression of both Calreticulin and GRP75/Mortalin as robust indicators of disease progression in SMA mice. We report that these protein biomarkers were consistently modified in different mouse models of SMA, as well as across multiple skeletal muscles, and were also measurable in skin biopsies. Furthermore, Calreticulin and GRP75/Mortalin were measurable in muscle biopsy samples from human SMA patients. CONCLUSIONS: We conclude that label-free proteomics technology provides a powerful platform for biomarker identification in SMA, revealing Calreticulin and GRP75/Mortalin as peripherally accessible protein biomarkers capable of reporting on disease progression in samples of muscle and skin

Partial discharge analysis of defective three-phase cable

Power distribution cable networks represent a dynamic and complex challenge with regard to the issues of maintenance and providing a reliable, high quality supply of electrical power. Utilities historically used regular off-line testing to investigate the health of their assets. This method of testing is reasonably effective for this purpose but does have certain drawbacks associated with it; customer supply can be interrupted during the testing process and the cables are generally not tested under normal operating conditions. Meaning that the test data is not representative of the Partial discharge (PD) activity that is apparent under on-line conditions and the testing activity itself could trigger previously dormant PD sources. The modern approach for understanding the health of medium voltage (MV) cable distribution networks is to continuously monitor the assets whilst on-line. Analysis if the field data is then used to inform decisions regarding asset replacement and maintenance strategies. PD activity is widely recognised as a symptom linked to the degradation of the dielectric properties of high voltage plant. UK Power Networks sponsored research is being undertaken to investigate the evolution of PD activity within three-phase paper insulated lead covered (PILC) cables containing introduced defects. An experiment has been designed to stress cable lengths in a manner that is representative of the conditions met by on-line circuits [1]. A cable section containing a defect that is known to lead to the premature failure of in-service cables has been PD tested over a range of operating temperatures. The experiment utilizes three-phase energization at rated voltage as well as thermal cycling of the cable to replicate the daily load pattern experienced by circuits in the field. The extension to this work involves PD testing cable samples containing a range of defects to produce a data set consisting of PD pulses produced by varied sources. Analysis of this data should lead to a better understanding of the signals produced by the premature ageing of these types of cable

A new method for automatic Multiple Partial Discharge Classification

A new wavelet based feature parameter have been developed to represent the characteristics of PD activities, i.e. the wavelet decomposition energy of PD pulses measured from non-conventional ultra wide bandwidth PD sensors such as capacitive couplers (CC) or high frequency current transformers (HFCT). The generated feature vectors can contain different dimensions depending on the length of recorded pulses. These high dimensional feature vectors can then be processed using Principal Component Analysis (PCA) to map the data into a three dimensional space whilst the first three most significant components representing the feature vector are preserved. In the three dimensional mapped space, an automatic Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is then applied to classify the data cluster(s) produced by the PCA. As the procedure is undertaken in a three dimensional space, the obtained clustering results can be easily assessed. The classified PD sub-data sets are then reconstructed in the time domain as phase-resolved patterns to facilitate PD source type identification. The proposed approach has been successfully applied to PD data measured from electrical machines and power cables where measurements were undertaken in different laboratories