In-situ studies of X-ray diffraction line profiles from strained copper foils

The development of an in-situ tensometer is described along with preliminary results of x-ray line profiles from copper foils under tensile stress. The tensometer was designed and constructed on the high resolution diffraction instrument, Station 2.3 at the synchrotron radiation source (SRS) Daresbury Laboratory, and is capable of collecting data in either symmetric or asymmetric geometry including transmission and reflection modes. Experiments were carried out using 18 J..Lm thick copper foil up to strain levels of 5 % using both symmetric reflection and symmetric transmission diffraction. All profiles displayed diffraction broadening and asymmetry which increased with strain. In addition, the asymmetry observed in symmetric transmission was associated with extended tails on the low angle side of the profiles, but in symmetric reflection data the opposite asymmetry was observed. In the analysis, the measured profiles were fitted using the software TOPAS, a fundamental parameters approach to profile fitting. The instrumental profile function was characterised and modelled using annealed LaB6 powder. The diffraction broadening was then determined by refining the convolution of a Voigt function, an asymmetric exponential function and a fixed instrument function to reproduce the observed broadened profiles. The integral breadth and asymmetry results display a strong order dependence and increase almost linearly with strain. The results were interpreted by assuming crystallite size broadening in combination with dislocation broadening arising from fcc a/2( 110) {Ill } dislocations.

A mathematical model for the spread of streptococcus pneumoniae with transmission due to sequence type

This paper discusses a simple mathematical model to describe the spread of Streptococcus pneumoniae. We suppose that the transmission of the bacterium is determined by multi-locus sequence type. The model includes vaccination and is designed to examine what happens in a vaccinated population if MLSTs can exist as both vaccine and non vaccine serotypes with capsular switching possible from the former to the latter. We start off with a discussion of Streptococcus pneumoniae and a review of previous work. We propose a simple mathematical model with two sequence types and then perform an equilibrium and (global) stability analysis on the model. We show that in general there are only three equilibria, the carriage-free equilibrium and two carriage equilibria. If the effective reproduction number Re is less than or equal to one, then the carriage will die out. If Re > 1, then the carriage will tend to the carriage equilibrium corresponding to the multi-locus sequence type with the largest transmission parameter. In the case where both multi-locus sequence types have the same transmission parameter then there is a line of carriage equilibria. Provided that carriage is initially present then as time progresses the carriage will approach a point on this line. The results generalize to many competing sequence types. Simulations with realistic parameter values confirm the analytical results.

Development of a laboratory-based transmission diffraction technique for in situ deformation studies of Mg alloys

A laboratory-based transmission X-ray diffraction technique was developed to measure elastic lattice strains parallel to the loading direction during in situ tensile deformation. High-quality transmission X-ray diffraction data were acquired in a time frame suitable for in situ loading experiments by application of a polycapillary X-ray optic with a conventional laboratory Cu X-ray source. Based on the measurement of two standard reference materials [lanthanum hexaboride (NIST SRM 660b) and silicon (NIST SRM 640c)], precise instrumental alignment and calibration of the transmission diffraction geometry were realized. These results were also confirmed by the equivalent data acquired using the standard Bragg-Brentano measurement geometry. An empirical Caglioti function was employed to describe the instrumental broadening, while an axis of rotation correction was used to measure and correct the specimen displacement from the centre of the goniometer axis. For precise Bragg peak position and hkil intensity information, a line profile fitting methodology was implemented, with Pawley refinement used to measure the sample reference lattice spacings (d o (hkil)). It is shown that the relatively large X-ray probe size available (7 × 714mm) provides a relatively straightforward approach for improving the grain statistics for the study of metal alloys, where grain sizes in excess of 114μm can become problematic for synchrotron-based measurements. This new laboratory-based capability was applied to study the lattice strain evolution during the elastic-plastic transition in extruded and rolled magnesium alloys. A strain resolution of 2 × 10-4 at relatively low 2θ angles (20-65° 2θ) was achieved for the in situ tensile deformation studies. In situ measurement of the elastic lattice strain accommodation with applied stress in the magnesium alloys indicated the activation of dislocation slip and twin deformation mechanisms. Furthermore, measurement of the relative change in the intensity of 0002 and 10 3 was used to quantify {10 2} 011 tensile twin onset and growth with applied load.

Multivariate adaptive autoregressive modeling and kalman filtering for motor imagery BCI

Adaptive autoregressive (AAR) modeling of the EEG time series and the AAR parameters has been widely used in Brain computer interface (BCI) systems as input features for the classification stage. Multivariate adaptive autoregressive modeling (MVAAR) also has been used in literature. This paper revisits the use of MVAAR models and propose the use of adaptive Kalman filter (AKF) for estimating the MVAAR parameters as features in a motor imagery BCI application. The AKF approach is compared to the alternative short time moving window (STMW) MVAAR parameter estimation approach. Though the two MVAAR methods show a nearly equal classification accuracy, the AKF possess the advantage of higher estimation update rates making it easily adoptable for on-line BCI systems.

The impact of a line probe assay based diagnostic algorithm on time to treatment initiation and treatment outcomes for multidrug resistant TB patients in Arkhangelsk region, Russia

BACKGROUND: In the Arkhangelsk region of Northern Russia, multidrug-resistant (MDR) tuberculosis (TB) rates in new cases are amongst the highest in the world. In 2014, MDR-TB rates reached 31.7% among new cases and 56.9% among retreatment cases. The development of new diagnostic tools allows for faster detection of both TB and MDR-TB and should lead to reduced transmission by earlier initiation of anti-TB therapy. STUDY AIM: The PROVE-IT (Policy Relevant Outcomes from Validating Evidence on Impact) Russia study aimed to assess the impact of the implementation of line probe assay (LPA) as part of an LPA-based diagnostic algorithm for patients with presumptive MDR-TB focusing on time to treatment initiation with time from first-care seeking visit to the initiation of MDR-TB treatment rather than diagnostic accuracy as the primary outcome, and to assess treatment outcomes. We hypothesized that the implementation of LPA would result in faster time to treatment initiation and better treatment outcomes.

METHODS: A culture-based diagnostic algorithm used prior to LPA implementation was compared to an LPA-based algorithm that replaced BacTAlert and Löwenstein Jensen (LJ) for drug sensitivity testing. A total of 295 MDR-TB patients were included in the study, 163 diagnosed with the culture-based algorithm, 132 with the LPA-based algorithm.

RESULTS: Among smear positive patients, the implementation of the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 50 and 66 days compared to the culture-based algorithm (BacTAlert and LJ respectively, p<0.001). In smear negative patients, the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 78 days when compared to the culture-based algorithm (LJ, p<0.001). However, several weeks were still needed for treatment initiation in LPA-based algorithm, 24 days in smear positive, and 62 days in smear negative patients. Overall treatment outcomes were better in LPA-based algorithm compared to culture-based algorithm (p = 0.003). Treatment success rates at 20 months of treatment were higher in patients diagnosed with the LPA-based algorithm (65.2%) as compared to those diagnosed with the culture-based algorithm (44.8%). Mortality was also lower in the LPA-based algorithm group (7.6%) compared to the culture-based algorithm group (15.9%). There was no statistically significant difference in smear and culture conversion rates between the two algorithms.

CONCLUSION: The results of the study suggest that the introduction of LPA leads to faster time to MDR diagnosis and earlier treatment initiation as well as better treatment outcomes for patients with MDR-TB. These findings also highlight the need for further improvements within the health system to reduce both patient and diagnostic delays to truly optimize the impact of new, rapid diagnostics.

Control-oriented modeling of a polymeric soft robot

This article describes an efficient control-oriented model of a soft robot made of electroactive polymers. The proposed soft robot is constructed from two flexible links and has a multiphysics dynamic model consisting of both an electrochemical and electromechanical model. The electrochemical model is based on a distributed RC line approach, and the electromechanical model, considering the continuum vibration of the robot, is derived based on Hamilton's principle. The governing equation of the soft robot is solved by means of the Rayleigh-Ritz-Meirovitch substructure synthesis method, and the Laplace operator is used to obtain the transfer function of the soft robot as a 2 by 2 multiple-input multiple-output system.

Rainfall-runoff modeling using dynamic evolving neural fuzzy inference system with online learning

This is an open access article under the CC BY-NC-ND license.Neuro-Fuzzy Systems (NFS) are computational intelligence tools that have recently been employed in hydrological modeling. In many of the common NFS the learning algorithms used are based on batch learning where all the parameters of the fuzzy system are optimized off-line. Although these models have frequently been used, there is a criticism on such learning process as the number of rules are needed to be predefined by the user. This will reduce the flexibility of the NFS architecture while dealing with different data with different level of complexity. On the other hand, online or local learning evolves through local adjustments in the model as new data is introduced in sequence. In this study, dynamic evolving neural fuzzy inference system (DENFIS) is used in which an evolving, online clustering algorithm called the Evolving Clustering Method (ECM) is implemented. ECM is an online, maximum distance-based clustering method which is able to estimate the number of clusters in a data set and find their current centers in the input space through its fast, one-pass algorithm. The 10-minutes rainfall-runoff time series from a small (23.22 km2) tropical catchment named Sungai Kayu Ara in Selangor, Malaysia, was used in this study. Out of the 40 major events, 12 were used for training and 28 for testing. Results obtained by DENFIS were then compared with the ones obtained by physically-based rainfall-runoff model HEC-HMS and a regression model ARX. It was concluded that DENFIS results were comparable to HEC-HMS and superior to ARX model. This indicates a strong potential for DENFIS to be used in rainfall-runoff modeling.