A non-aqueous solution synthesis of boron carbide by control of in-situ carbon

Synthesis of high quality boron carbide (B4C) powder is achieved by carbothermal reduction of boron oxide (B2O3) from a condensed boric acid (H3BO3) / polyvinyl acetate (PVAc) product. Precursor solutions are prepared via polymerisation of vinyl acetate (VA) in methanol in the presence of dissolved H3BO3. With excess VA monomer being removed during evaporation of the solvent, the polymerisation time is then used to manage availability of carbon for reaction.

Stochastic output feedback model predictive control

This paper addresses the issue of output feedback model predictive control for linear systems with input constraints and stochastic disturbances. We show that the optimal policy uses the Kalman filter for state estimation, but the resultant state estimates are not utilized in a certainty equivalence control law

Causal factors of hot air ballooning incidents : identification, frequency, and potential impact

Background: Hot air ballooning incidents are relatively rare, however, when they do occur they are likely to result in a fatality or serious injury. Human error is commonly attributed as the cause of hot air ballooning incidents; however, error in itself is not an explanation for safety failures. This research aims to identify, and establish the relative importance of factors contributing towards hot air ballooning incidents. Methods: Twenty-two Australian Ballooning Federation (ABF) incident reports were thematically coded using a bottom up approach to identify causal factors. Subsequently, 69 balloonists (mean 19.51 years’ experience) participated in a survey to identify additional causal factors and rate (out of seven) the perceived frequency and potential impact to ballooning operations of each of the previously identified causal factors. Perceived associated risk was calculated by multiplying mean perceived frequency and impact ratings. Results: Incident report coding identified 54 causal factors within nine higher level areas: Attributes, Crew resource management, Equipment, Errors, Instructors, Organisational, Physical Environment, Regulatory body and Violations. Overall, ‘weather’, ‘inexperience’ and ‘poor/inappropriate decisions’ were rated as having greatest perceived associated risk. Discussion: Although errors were nominated as a prominent cause of hot air ballooning incidents, physical environment and personal attributes are also particularly important for safe hot air ballooning operations. In identifying a range of causal factors the areas of weakness surrounding ballooning operations have been defined; it is hoped that targeted safety and training strategies can now be put into place removing these contributing factors and reducing the chance of pilot error.

A deformable Brodmann area atlas

Functional MRI studies commonly refer to activation patterns as being localized in specific Brodmann areas, referring to Brodmann’s divisions of the human cortex based on cytoarchitectonic boundaries [3]. Typically, Brodmann areas that match regions in the group averaged functional maps are estimated by eye, leading to inaccurate parcellations and significant error. To avoid this limitation, we developed a method using high-dimensional nonlinear registration to project the Brodmann areas onto individual 3D co-registered structural and functional MRI datasets, using an elastic deformation vector field in the cortical parameter space. Based on a sulcal pattern matching approach [11], an N=27 scan single subject atlas (the Colin Holmes atlas [15]) with associated Brodmann areas labeled on its surface, was deformed to match 3D cortical surface models generated from individual subjects’ structural MRIs (sMRIs). The deformed Brodmann areas were used to quantify and localize functional MRI (fMRI) BOLD activation during the performance of the Tower of London task [7].

Load applied on a bone-anchored transfemoral prosthesis: characterisation of a prosthesis : a pilot study

The objectives of this study were (A) to record the inner prosthesis loading during activities of daily living (ADL), (B) to present a set of variables comparing loading data, and (C) to provide an example of characterisation of two prostheses. The load was measured at 200 Hz using a multi-axial transducer mounted between the residuum and the knee of an individual with unilateral transfemoral amputation fitted with a bone-anchored prosthesis. The load was measured while using two different prostheses including a mechanically (PRO1) and a microprocessor controlled (PRO2) knee during six ADL. The characterisation of prosthesis was achieved using a set of variables split into four categories, including temporal characteristics, maximum loading, loading slopes and impulse. Approximately 360 gait cycles were analysed for each prosthesis. PRO1 showed a cadence improved by 19% and 7%, a maximum force on the long axis reduced by 11% and 19%, as well as an impulse reduced by 32% and 15% during descent of incline and stairs compared to PRO2, respectively. This work confirmed that the proposed apparatus and characterisation can reveal how changes of prosthetic components are translated into inner loading.

In-situ carbon control in the preparation of precursors to boron carbide by a non-aqueous solution technique

Synthesis of high quality boron carbide (B4C) powders is achieved by carbothermal reduction of boron oxide (B2O3) from a condensed boric acid (H3BO3)/polyvinyl acetate (PVAc) product. Precursor solutions are prepared via free radical polymerisation of vinyl acetate (VA) monomer in methanol in the presence of dissolved H3BO3. A condensed product is then formed by flash evaporation under vacuum. As excess VA monomer is removed at the evaporation step, the polymerisation time is used to manage availability of carbon for reaction. This control of carbon facilitates dispersion of H3BO3 in solution due to the presence of residual VA monomer. B4C powders with very low residual carbon are formed at temperatures as low as 1,250 °C with a 4 hour residence time.

Active learning: A step towards automating medical concept extraction

Objective This paper presents an automatic active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort, and (2) the robustness of incremental active learning framework across different selection criteria and datasets is determined. Materials and methods The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional Random Fields as the supervised method, and least confidence and information density as two selection criteria for active learning framework were used. The effect of incremental learning vs. standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. Two clinical datasets were used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Results The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared to the Random sampling baseline, the saving is at least doubled. Discussion Incremental active learning guarantees robustness across all selection criteria and datasets. The reduction of annotation effort is always above random sampling and longest sequence baselines. Conclusion Incremental active learning is a promising approach for building effective and robust medical concept extraction models, while significantly reducing the burden of manual annotation.

Comparison of visual status of Iranian military and commercial drivers

Background There is no legal requirement for Iranian military truck drivers to undergo regular visual checkups as compared to commercial truck drivers. Objectives This study aimed to evaluate the impact of drivers’ visual checkups by comparing the visual function of Iranian military and commercial truck drivers. Patients and Methods In this comparative cross-sectional study, two hundred military and 200 commercial truck drivers were recruited and their Visual Acuity (VA), Visual Field (VF), color vision and Contrast Sensitivity (CS) were assessed and compared using the Snellen chart, confrontation screening method, D15 test and Pelli-Robson letter chart, respectively. A questionnaire regarding driving exposure and history of motor-vehicle crashes (MVCs) was also filled by drivers. Results were analyzed using an independent samples t-test, one-way ANOVA (assessing difference in number of MVCs across different age groups), chi-square test and Pearson correlation at statistical significance level of P < 0.05. Results Mean age was 41.6 ± 9.2 for the military truck drivers and 43.4 ± 10.9 for commercial truck drivers (P > 0.05). No significant difference between military and commercial drivers was found in terms of driving experience, number of MVCs, binocular VA, frequency of color vision defects and CS scores. In contrast, the last ocular examination was significantly earlier in military drivers than commercial drivers (P < 0.001). In addition, 4% of military drivers did not meet the national standards to drive as opposed to 2% of commercial drivers. There was a significant but weak correlation between binocular VA and age (r = 0.175, P < 0.001). However, CS showed a significantly moderate correlation with age (r = -0.488, P < 0.001). Conclusions The absence of legal requirement for regular eye examination in military drivers caused the incompetent drivers to be missed in contrast to commercial drivers. The need for scientific revision of VA standard for Iranian drivers is also discussed. The CS measurement in visual checkups of older drivers deserves to be investigated more thoroughly.

Decision trees for detection of activity intensity in youth with cerebral palsy

PURPOSE To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP); and 2) compare the classification accuracy of the new DT models to that achieved by previously published cut-points for youth with CP. METHODS Youth with CP (GMFCS Levels I - III) (N=51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light PA (LPA) (>/=1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (>/=3 METs). Models were trained and cross-validated using the 'rpart' and 'caret' packages within R. RESULTS For the VA (VA_DT) and VM decision trees (VM_DT), a single threshold differentiated LPA from SED, while the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracy for the VC_DT was 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III, respectively. The corresponding cross-validation accuracy for the VM_DT was 80.5%, 75.6%, and 84.2%, respectively. Within each GMFCS level, the decision tree models achieved better PA intensity recognition than previously published cut-points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut-points misclassified 40% of the MVPA activity trials. CONCLUSION GMFCS-specific cut-points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.