Crystal structure of N,N-diethylbenzene-1,4-diaminium dinitrate

In the structure of the title compound, (C10H18N2)2+, 2(NO3)-, the nitrate salt of 4-(N,N-diethylamino)aniline, the two ethyl groups lie almost perpendicular to the plane of the benzene ring [ring to ethyl C-C-N-C torsion angles, -59.5(2) and 67.5(3)deg.]. The aminium groups of the cation form inter-species N-H...O hydrogen bonds with the nitro O-atoms of both anions giving one-dimensional chains extending along c and are extended into a two-dimensional network structure lying parallel to (010). Weak C-H...O hydrogen-bonding associations are also present.

Understanding classroom trouble through regulative gravity and instructional elasticity

This paper aims to develop a more nuanced analytic vocabulary to typify how and where classroom trouble can manifest in pedagogic discourse. It draws on classroom ethnographies conducted in non-academic secondary school pathways and alternative programs in Australian communities with high youth unemployment, where the policy of ‘earning or learning’ till age 17 has effectively extended compulsory schooling. Three concepts are developed and exemplified: ‘regulative flares’, being moments when teachers resort to explicitly reasserting the lesson’s social order; ‘moral gravity’ to describe the degree to which the moral order underpinning the regulative discourse is tied to the immediate context or beyond; and ‘instructional elasticity’ to account for trouble originating in the instructional register.

One step closer into the design of fall protective device for individuals fitted with a bone-anchored prosthesis

The consequences of falls are often dreadful for individuals with lower limb amputation using bone-anchored prosthesis.[1-5] Typically, the impact on the fixation is responsible for bending the intercutaneous piece that could lead to a complete breakage over time. .[3, 5-8] The surgical replacement of this piece is possible but complex and expensive. Clearly, there is a need for solid data enabling an evidence-based design of protective devices limiting impact forces and torsion applied during a fall. The impact on the fixation during an actual fall is obviously difficult to record during a scientific experiment.[6, 8-13] Consequently, Schwartze and colleagues opted for one of the next best options science has to offer: simulation with an able-bodied participant. They recorded body movements and knee impacts on the floor while mimicking several plausible falling scenarios. Then, they calculated the forces and moments that would be applied at four levels along the femur corresponding to amputation heights.[6, 8-11, 14-25] The overall forces applied during the falls were similar regardless of the amputation height indicating that the impact forces were simply translated along the femur. As expected, they showed that overall moments generally increased with amputation height due to changes in lever arm. This work demonstrates that devices preventing only against force overload do not require considering amputation height while those protecting against bending moments should. Another significant contribution is to provide, for the time, the magnitude of the impact load during different falls. This loading range is crucial to the overall design and, more precisely, the triggering threshold of protective devices. Unfortunately, the analysis of only a single able-bodied participant replicating falls limits greatly the generalisation of the findings. Nonetheless, this case study is an important milestone contributing to a better understanding of load impact during a fall. This new knowledge will improve the treatment, the safe ambulation and, ultimately, the quality of life of individuals fitted with bone-anchored prosthesis.

Clinical data warehousing

Clinical Data Warehousing: A Business Analytic approach for managing health data

Evaluation of a patient-specific finite-element model to simulate conservative treatment in adolescent idiopathic scoliosis

Study design Retrospective validation study. Objectives To propose a method to evaluate, from a clinical standpoint, the ability of a finite-element model (FEM) of the trunk to simulate orthotic correction of spinal deformity and to apply it to validate a previously described FEM. Summary of background data Several FEMs of the scoliotic spine have been described in the literature. These models can prove useful in understanding the mechanisms of scoliosis progression and in optimizing its treatment, but their validation has often been lacking or incomplete. Methods Three-dimensional (3D) geometries of 10 patients before and during conservative treatment were reconstructed from biplanar radiographs. The effect of bracing was simulated by modeling displacements induced by the brace pads. Simulated clinical indices (Cobb angle, T1–T12 and T4–T12 kyphosis, L1–L5 lordosis, apical vertebral rotation, torsion, rib hump) and vertebral orientations and positions were compared to those measured in the patients' 3D geometries. Results Errors in clinical indices were of the same order of magnitude as the uncertainties due to 3D reconstruction; for instance, Cobb angle was simulated with a root mean square error of 5.7°, and rib hump error was 5.6°. Vertebral orientation was simulated with a root mean square error of 4.8° and vertebral position with an error of 2.5 mm. Conclusions The methodology proposed here allowed in-depth evaluation of subject-specific simulations, confirming that FEMs of the trunk have the potential to accurately simulate brace action. These promising results provide a basis for ongoing 3D model development, toward the design of more efficient orthoses.

A new twist on mode indicator functions

Mode indicator functions (MIFs) are used in modal testing and analysis as a means of identifying modes of vibration, often as a precursor to modal parameter estimation. Various methods have been developed since the MIF was introduced four decades ago. These methods are quite useful in assisting the analyst to identify genuine modes and, in the case of the complex mode indicator function, have even been developed into modal parameter estimation techniques. Although the various MIFs are able to indicate the existence of a mode, they do not provide the analyst with any descriptive information about the mode. This paper uses the simple summation type of MIF to develop five averaged and normalised MIFs that will provide the analyst with enough information to identify whether a mode is longitudinal, vertical, lateral or torsional. The first three functions, termed directional MIFs, have been noted in the literature in one form or another; however, this paper introduces a new twist on the MIF by introducing two MIFs, termed torsional MIFs, that can be used by the analyst to identify torsional modes and, moreover, can assist in determining whether the mode is of a pure torsion or sway type (i.e., having a rigid cross-section) or a distorted twisting type. The directional and torsional MIFs are tested on a finite element model based simulation of an experimental modal test using an impact hammer. Results indicate that the directional and torsional MIFs are indeed useful in assisting the analyst to identify whether a mode is longitudinal, vertical, lateral, sway, or torsion.

A kinematic analysis of the hand function

Background The evaluation of the hand function is an essential element within the clinical practice. The usual assessments are focus on the ability to perform activities of daily life. The inclusion of instruments to measure kinematic variables provides a new approach to the assessment. Inertial sensors adapted to the hand could be used as a complementary instrument to the traditional assessment. Material: clinimetric assessment (Upper Limb Functional Index, Quick Dash), antrophometric variables (eight and weight), dynamometry (palm preasure) was taken. Functional analysis was made with Acceleglove system for the right hand and computer system. The glove has six acceleration sensor, one on each finger and another one on the reverse palm. Method Analytic, transversal approach. Ten healthy subject made six task on evaluation table (tripod pinch, lateral pinch and tip pinch, extension grip, spherical grip and power grip). Each task was made and measure three times, the second one was analyze for the results section. A Matlab script was created for the analysis of each movement and detection phase based on module vector. Results The module acceleration vector offers useful information of the hand function. The data analysis obtained during the performance of functional gestures allows to identify five different phases within the movement, three static phase and tow dynamic, each module vector was allied to one task. Conclusion Module vector variables could be used for the analysis of the different task made by the hand. Inertial sensor could be use as a complement for the traditional assessment system.

Probabilistic multi-tensor estimation using the tensor distribution function

Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of 6 directions, second-order tensors can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve crossing fiber tracts. Recently, a number of high-angular resolution schemes with greater than 6 gradient directions have been employed to address this issue. In this paper, we introduce the Tensor Distribution Function (TDF), a probability function defined on the space of symmetric positive definite matrices. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the diffusion orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function.

Influence of pipe length and flow rate on nano-particle deposition in laminar circular pipe flows

The Lagrangian particle tracking provides an effective method for simulating the deposition of nano- particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. The aim of this paper is to study the deposition of nano-particles in cylindrical tubes under laminar condition using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different pipe lengths and flow rates are examined. The results show good agreement between the calculated deposition efficiency and different analytic correlations in the literature. Furthermore, for the nano-particles with higher diameters and when the effect of inertia has a higher importance, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.

Multilingualism and speech-language competence in early childhood: Impact on academic and social-emotional outcomes at school

This large-scale longitudinal population study provided a rare opportunity to consider the interface between multilingualism and speech-language competence on children’s academic and social-emotional outcomes and to determine whether differences between groups at 4 to 5 years persist, deepen, or disappear with time and schooling. Four distinct groups were identified from the Kindergarten cohort of the Longitudinal Study of Australian Children (LSAC) (1) English-only + typical speech and language (n = 2,012); (2) multilingual + typical speech and language (n = 476); (3) English-only + speech and language concern (n = 643); and (4) multilingual + speech and language concern (n = 109). Two analytic approaches were used to compare these groups. First, a matched case-control design was used to randomly match multilingual children with speech and language concern (group 4, n = 109) to children in groups 1, 2, and 3 on gender, age, and family socio-economic position in a cross-sectional comparison of vocabulary, school readiness, and behavioral adjustment. Next, analyses were applied to the whole sample to determine longitudinal effects of group membership on teachers’ ratings of literacy, numeracy, and behavioral adjustment at ages 6 to 7 and 8 to 9 years. At 4 to 5 years, multilingual children with speech and language concern did equally well or better than English-only children (with or without speech and language concern) on school readiness tests but performed more poorly on measures of English vocabulary and behavior. At ages 6 to 7 and 8 to 9, the early gap between English-only and multilingual children had closed. Multilingualism was not found to contribute to differences in literacy and numeracy outcomes at school; instead, outcomes were more related to concerns about children’s speech and language in early childhood. There were no group differences for socio-emotional outcomes. Early evidence for the combined risks of multilingualism plus speech and language concern was not upheld into the school years.

The tensor distribution function

Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.

Cost-effectiveness of hospital infection control interventions in resource-limited settings

The aim of this project was to evaluate the cost-effectiveness of hand hygiene interventions in resource-limited hospital settings. Using data from north-east Thailand, the research found that such interventions are likely to be very cost-effective in intensive care unit settings as a result of reduced incidence of methicillin-resistant Staphylococcus aureus bloodstream infection alone. This study also found evidence showing that the World Health Organization's (WHO) multimodal intervention is effective and when adding either goal-setting, reward incentives, or accountability strategies to the WHO intervention, compliance could be further improved.

A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production

Oleaginous microorganisms have potential to be used to produce oils as alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-criteria analysis (MCA) using analytic hierarchy process (AHP) and preference ranking organization method for the enrichment of evaluations (PROMETHEE) with graphical analysis for interactive aid (GAIA), was used to rank and select the preferred microorganisms for oil production for biodiesel application. This was based on a number of criteria viz., oil concentration, content, production rate and yield, substrate consumption rate, fatty acids composition, biomass harvesting and nutrient costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the most prospective species for oil production. However, further analysis by GAIA Webs identified A. oryzae and M. plumbeus as the best performing microorganisms.

An investigation of Nano-particle deposition in cylindrical tubes under Laminar condition using Lagrangian transport model

Aerosol deposition in cylindrical tubes is a subject of interest to researchers and engineers in many applications of aerosol physics and metrology. Investigation of nano-particles in different aspects such as lungs, upper airways, batteries and vehicle exhaust gases is vital due the smaller size, adverse health effect and higher trouble for trapping than the micro-particles. The Lagrangian particle tracking provides an effective method for simulating the deposition of nano-particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. In this paper, the deposition of nano-particles in cylindrical tubes under laminar condition is studied using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different flow rates are examined. The point analysis in a uniform flow is performed for validating the Brownian motion. The results show good agreement between the calculated deposition efficiency and the analytic correlations in the literature. Furthermore, for the nano-particles with the diameter more than 40 nm, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.

Improving Near-Miss Event Detection Rate at Railway Level Crossings

Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.