Mobile app rating scale: A new tool for assessing the quality of health mobile apps

Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.

Reliability of point-of-care testing of INR in acute stroke

Background In the emergency department, portable point-of-care testing (POCT) coagulation devices may facilitate stroke patient care by providing rapid International Normalized Ratio (INR) measurement. The objective of this study was to evaluate the reliability, validity, and impact on clinical decision-making of a POCT device for INR testing in the setting of acute ischemic stroke (AIS). Methods A total of 150 patients (50 healthy volunteers, 51 anticoagulated patients, 49 AIS patients) were assessed in a tertiary care facility. The INR's were measured using the Roche Coaguchek S and the standard laboratory technique. Results The interclass correlation coefficient and 95% confidence interval between overall POCT device and standard laboratory value INRs was high (0.932 (0.69 - 0.78). In the AIS group alone, the correlation coefficient and 95% CI was also high 0.937 (0.59 - 0.74) and diagnostic accuracy of the POCT device was 94%. Conclusions When used by a trained health professional in the emergency department to assess INR in acute ischemic stroke patients, the CoaguChek S is reliable and provides rapid results. However, as concordance with laboratory INR values decreases with higher INR values, it is recommended that with CoaguChek S INRs in the > 1.5 range, a standard laboratory measurement be used to confirm the results.

Estimate of Lagrangian integral scales in shallow tidal water using high resolution GPS-tracked drifters

In estuaries and natural water channels, the estimate of velocity and dispersion coefficients is critical to the knowledge of scalar transport and mixing. This estimate is rarely available experimentally at sub-tidal time scale in shallow water channels where high frequency is required to capture its spatio-temporal variation. This study estimates Lagrangian integral scales and autocorrelation curves, which are key parameters for obtaining velocity fluctuations and dispersion coefficients, and their spatio-temporal variability from deployments of Lagrangian drifters sampled at 10 Hz for a 4-hour period. The power spectral densities of the velocities between 0.0001 and 0.8 Hz were well fitted with a slope of 5/3 predicted by Kolmogorov’s similarity hypothesis within the inertial subrange, and were similar to the Eulerian power spectral previously observed within the estuary. The result showed that large velocity fluctuations determine the magnitude of the integral time scale, TL. Overlapping of short segments improved the stability of the estimate of TL by taking advantage of the redundant data included in the autocorrelation function. The integral time scales were about 20 s and varied by up to a factor of 8. These results are essential inputs for spatial binning of velocities, Lagrangian stochastic modelling and single particle analysis of the tidal estuary.

Development of a new ultrasound-based system for tracking motion of the human lumbar spine: Reliability, stability and repeatability during forward bending movement trials

The aim of this study was to develop a new method for quantifying intersegmental motion of the spine in an instrumented motion segment L4–L5 model using ultrasound image post-processing combined with an electromagnetic device. A prospective test–retest design was employed, combined with an evaluation of stability and within- and between-day intra-tester reliability during forward bending by 15 healthy male patients. The accuracy of the measurement system using the model was calculated to be ± 0.9° (standard deviation = 0.43) over a 40° range and ± 0.4 cm (standard deviation = 0.28) over 1.5 cm. The mean composite range of forward bending was 15.5 ± 2.04° during a single trial (standard error of the mean = 0.54, coefficient of variation = 4.18). Reliability (intra-class correlation coefficient = 2.1) was found to be excellent for both within-day measures (0.995–0.999) and between-day measures (0.996–0.999). Further work is necessary to explore the use of this approach in the evaluation of biomechanics, clinical assessments and interventions.

Modelling milling train performance

This paper describes recent updates to a milling train extraction model used to assess and predict the performance of a milling train. An extension was made to the milling unit model for the bagasse mills to replace the imbibition coefficient with crushing factor and mixing efficiency. New empirical relationships for reabsorption factor, imbibition coefficient, crushing factor, mixing efficiency and purity ratio were developed. The new empirical relationships were tested against factory measurements and previous model predictions. The updated model has been implemented in the SysCAD process modelling software. New additions to the model implementation include: a shredder model to assess or predict cane preparation, mill and shredder drives for power consumption and an updated imbibition control system to add allow water to be added to intermediate mills.

Development of the 'rich club' in brain connectivity networks from 438 adolescents & adults aged 12 to 30

The 'rich club' coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how the rich club emerges in the living brain, or how it changes as our brain networks develop. Here we chart the developmental trajectory of the rich club in anatomical brain networks from 438 subjects aged 12-30. Cortical networks were constructed from 68×68 connectivity matrices of fiber density, using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). The adult and younger cohorts had rich clubs that included different nodes; the rich club effect intensified with age. Rich-club organization is a sign of a network's efficiency and robustness. These concepts and findings may be advantageous for studying brain maturation and abnormal brain development.

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.

Translation and psychometric properties of the Chinese version of the Leeds Attitudes to Concordance II scale

Background Concordance is characterised as a negotiation-like health communication approach based on an equal and collaborative partnership between patients and health professionals. The Leeds Attitudes to Concordance II (LATCon II) scale was developed to measure the attitudes towards concordance. The purpose of this study was to translate the LATCon II into Chinese and psychometrically test the Chinese version of LATCon II (C-LATCon II). Methods The study involved three phases: i) translation and cross-cultural adaptation; ii) pilot study, and; iii) a cross-sectional survey (n = 366). Systematic random sampling was used to recruit hypertensive patients from nine communities covering around 78,000 residents in China. Tests of psychometric properties included content validity, construct validity, criteria-related validity (correlation between the C-LATCon II and the Therapeutic Adherence Scale for Hypertensive Patients (TASHP)), internal reliability, and test-retest reliability (n = 30). Results The study found that the C-LATCon II had a satisfactory content validity (item-level Content Validity Index (CVI) = 0.83-1, scale-level CVI/universal agreement = 0.89, and scale-level CVI/averaging calculation = 0.98), construct validity (four components extracted explained 56.66% of the total variance), internal reliability (Cronbach’s alpha of overall scale and four components was 0.78 and 0.66-0.84, respectively), and test-retest reliability (Pearson’s correlation coefficient = 0.82, p < 0.001; interclass correlation coefficient = 0.82, p < 0.001; linear weighted kappa3 statistic for each item = 0.40-0.65, p < 0.05). Criteria-related validity showed a weak association (Pearson’s correlation coefficient = 0.11, p < 0.05) between patients’ attitudes towards concordance during health communication and their health behaviours for hypertension management. Conclusions The C-LATCon II is a validated and reliable instrument which can be used to evaluate the attitudes to concordance in Chinese populations. Four components (health professionals’ attitudes, partnership between two parties, therapeutic decision making, and patients’ involvement) describe the attitudes towards concordance during health communication.

Multifunctional SA-PProDOT binder for lithium ion batteries

An environmentally benign, highly conductive, and mechanically strong binder system can overcome the dilemma of low conductivity and insufficient mechanical stability of the electrodes to achieve high performance lithium ion batteries (LIBs) at a low cost and in a sustainable way. In this work, the naturally occurring binder sodium alginate (SA) is functionalized with 3,4-propylenedioxythiophene-2,5-dicarboxylic acid (ProDOT) via a one-step esterification reaction in a cyclohexane/dodecyl benzenesulfonic acid (DBSA)/water microemulsion system, resulting in a multifunctional polymer binder, that is, SA-PProDOT. With the synergetic effects of the functional groups (e.g., carboxyl, hydroxyl, and ester groups), the resultant SA-PProDOT polymer not only maintains the outstanding binding capabilities of sodium alginate but also enhances the mechanical integrity and lithium ion diffusion coefficient in the LiFePO4 (LFP) electrode during the operation of the batteries. Because of the conjugated network of the PProDOT and the lithium doping under the battery environment, the SA-PProDOT becomes conductive and matches the conductivity needed for LiFePO4 LIBs. Without the need of conductive additives such as carbon black, the resultant batteries have achieved the theoretical specific capacity of LiFePO4 cathode (ca. 170 mAh/g) at C/10 and ca. 120 mAh/g at 1C for more than 400 cycles.

To increase or decrease dosage of antimicrobials in septic patients during continuous renal replacement therapy: the eternal doubt

Critical illness, acute renal failure and continuous renal replacement therapy (CRRT) are associated with changes in pharmacokinetics. Initial antibiotic dose should be based on published volume of distribution and generally be at least the standard dose, as volume of distribution is usually unchanged or increased. Subsequent doses should be based on total clearance. Total clearance varies with the CRRT clearance which mainly depends on effluent flow rate, sieving coefficient/saturation coefficient. As antibiotic clearance by healthy kidneys is usually higher than clearance by CRRT, except for colistin, subsequent doses should generally be lower than given to patients without renal dysfunction. In the future therapeutic drug monitoring, together with sophisticated pharmacokinetic models taking into account the pharmacokinetic variability, may enable more appropriate individualized dosing.

Enhanced electron lifetime of CdSe/CdS quantum dot (QD) sensitized solar cells using ZnSe core–shell structure with efficient regeneration of quantum Ddots

Research on development of efficient passivation materials for high performance and stable quantum dot sensitized solar cells (QDSCs) is highly important. While ZnS is one of the most widely used passivation material in QDSCs, an alternative material based on ZnSe which was deposited on CdS/CdSe/TiO2 photoanode to form a semi-core/shell structure has been found to be more efficient in terms of reducing electron recombination in QDSCs in this work. It has been found that the solar cell efficiency was improved from 1.86% for ZnSe0 (without coating) to 3.99% using 2 layers of ZnSe coating (ZnSe2) deposited by successive ionic layer adsorption and reaction (SILAR) method. The short circuit current density (Jsc) increased nearly 1-fold (from 7.25 mA/cm2 to13.4 mA/cm2), and the open circuit voltage (Voc) was enhanced by 100 mV using ZnSe2 passivation layer compared to ZnSe0. Studies on the light harvesting efficiency (ηLHE) and the absorbed photon-to-current conversion efficiency (APCE) have revealed that the ZnSe coating layer caused the enhanced ηLHE at wavelength beyond 500 nm and a significant increase of the APCE over the spectrum 400−550 nm. A nearly 100% APCE was obtained with ZnSe2, indicating the excellent charge injection and collection process in the device. The investigation on charge transport and recombination of the device has indicated that the enhanced electron collection efficiency and reduced electron recombination should be responsible for the improved Jsc and Voc of the QDSCs. The effective electron lifetime of the device with ZnSe2 was nearly 6 times higher than ZnSe0 while the electron diffusion coefficient was largely unaffected by the coating. Study on the regeneration of QDs after photoinduced excitation has indicated that the hole transport from QDs to the reduced species (S2−) in electrolyte was very efficient even when the QDs were coated with a thick ZnSe shell (three layers). For comparison, ZnS coated CdS/CdSe sensitized solar cell with optimum shell thickness was also fabricated, which generated a lower energy conversion efficiency (η = 3.43%) than the ZnSe based QDSC counterpart due to a lower Voc and FF. This study suggests that ZnSe may be a more efficient passivation layer than ZnS, which is attributed to the type II energy band alignment of the core (CdS/CdSe quantum dots) and passivation shell (ZnSe) structure, leading to more efficient electron−hole separation and slower electron recombination.

Improved shear design rules of cold-formed steel beams

Light gauge cold-formed steel sections have been developed as more economical building solutions to the alternative heavier hot-rolled sections in the commercial and residential markets. Cold-formed lipped channel beams (LCB), LiteSteel beams (LSB) and triangular hollow flange beams (THFB) are commonly used as flexural members such as floor joists and bearers while rectangular hollow flange beams (RHFB) are used in small scale housing developments through to large building structures. However, their shear capacities are determined based on conservative design rules. For the shear design of cold-formed steel beams, their elastic shear buckling strength and the potential post-buckling strength must be determined accurately. Hence experimental and numerical studies were conducted to investigate the shear behaviour and strength of LCBs, LSBs, THFBs and RHFBs. Improved shear design rules including the direct strength method (DSM) based design equations were developed to determine the ultimate shear capacities of these open and hollow flange steel beams. An improved equation for the higher elastic shear buckling coefficient of cold-formed steel beams was proposed based on finite element analysis results and included in the design equations. A new post-buckling coefficient was also introduced in the design equations to include the available post-buckling strength of cold-formed steel beams. This paper presents the details of this study on cold-formed steel beams subject to shear, and the results. It proposes generalised and improved shear design rules that can be used for any type of cold-formed steel beam.

A preconditioned numerical solver for stiff nonlinear reaction-diffusion equations with fractional Laplacians that avoids dense matrices

The numerical solution of fractional partial differential equations poses significant computational challenges in regard to efficiency as a result of the spatial nonlocality of the fractional differential operators. The dense coefficient matrices that arise from spatial discretisation of these operators mean that even one-dimensional problems can be difficult to solve using standard methods on grids comprising thousands of nodes or more. In this work we address this issue of efficiency for one-dimensional, nonlinear space-fractional reaction–diffusion equations with fractional Laplacian operators. We apply variable-order, variable-stepsize backward differentiation formulas in a Jacobian-free Newton–Krylov framework to advance the solution in time. A key advantage of this approach is the elimination of any requirement to form the dense matrix representation of the fractional Laplacian operator. We show how a banded approximation to this matrix, which can be formed and factorised efficiently, can be used as part of an effective preconditioner that accelerates convergence of the Krylov subspace iterative solver. Our approach also captures the full contribution from the nonlinear reaction term in the preconditioner, which is crucial for problems that exhibit stiff reactions. Numerical examples are presented to illustrate the overall effectiveness of the solver.

Household carbon emission research: An analytical review of measurement, influencing factors and mitigation prospects

Greenhouse gas (GHG) emissions are simultaneously exhausting the world's supply of fossil fuels and threatening the global climate. In many developing countries, significant improvement in living standards in recent years due to the accelerating development of their economies has resulted in a disproportionate increase in household energy consumption. Therefore, a major reduction in household carbon emissions (HCEs) is essential if global carbon reduction targets are to be met. To do this, major Organisation for Economic Co-operation and Development (OECD) states have already implemented policies to alleviate the negative environmental effects of household behaviors and less carbon-intensive technologies are also proposed to promote energy efficiency and reduce carbon emissions. However, before any further remedial actions can be contemplated, though, it is important to fully understand the actual causes of such large HCEs and help researchers both gain deep insights into the development of the research domain and identify valuable research topics for future study. This paper reviews existing literature focusing on the domain of HCEs. This critical review provides a systematic understanding of current work in the field, describing the factors influencing HCEs under the themes of household income, household size, age, education level, location, gender and rebound effects. The main quantification methodologies of input–output models, life cycle assessment and emission coefficient methods are also presented, and the proposed measures to mitigate HCEs at the policy, technology and consumer levels. Finally, the limitations of work done to date and further research directions are identified for the benefit of future studies.

Resampling-based approaches to study variation in morphological modularity

Modularity has been suggested to be connected to evolvability because a higher degree of independence among parts allows them to evolve as separate units. Recently, the Escoufier RV coefficient has been proposed as a measure of the degree of integration between modules in multivariate morphometric datasets. However, it has been shown, using randomly simulated datasets, that the value of the RV coefficient depends on sample size. Also, so far there is no statistical test for the difference in the RV coefficient between a priori defined groups of observations. Here, we (1), using a rarefaction analysis, show that the value of the RV coefficient depends on sample size also in real geometric morphometric datasets; (2) propose a permutation procedure to test for the difference in the RV coefficient between a priori defined groups of observations; (3) show, through simulations, that such a permutation procedure has an appropriate Type I error; (4) suggest that a rarefaction procedure could be used to obtain sample-size-corrected values of the RV coefficient; and (5) propose a nearest-neighbor procedure that could be used when studying the variation of modularity in geographic space. The approaches outlined here, readily extendable to non-morphometric datasets, allow study of the variation in the degree of integration between a priori defined modules. A Java application – that will allow performance of the proposed test using a software with graphical user interface – has also been developed and is available at the Morphometrics at Stony Brook Web page (http://life.bio.sunysb.edu/morph/).