Agent-based modelling of aircraft boarding methods

We implemented six different boarding strategies (Wilma, Steffen, Reverse Pyramid, Random, Blocks and By letter) in order to investigate boarding times for Boeing 777 and Airbus 380 aircraft. We also introduce three new boarding methods to find the optimum boarding strategy. Our models explicitly simulate the behaviour of groups of people travelling together and we explicitly simulate the timing to store their luggage as part of the boarding process. Results from the simulation demonstrates the Reverse Pyramid method is the best boarding method for Boeing 777, and the Steffen method is the best boarding method for Airbus 380. For the new suggested boarding methods, aisle first boarding method is the best boarding strategy for Boeing 777 and row arrangement method is the best boarding strategy for Airbus 380. Overall best boarding strategy is aisle first boarding method for Boeing 777 and Steffen method for Airbus 380.

Longitudinal Assessment of Neuropathy in Diabetes using novel ophthalmic MARKers (LANDMark): Baseline findings

Purpose:Over the past decade, corneal nerve morphology and corneal sensation threshold have been explored as potential surrogate markers for the evaluation of diabetic neuropathy. We present the baseline findings of a Longitudinal Assessment of Neuropathy in Diabetes using novel ophthalmic Markers (LANDMark). Methods:The LANDMark Study is a 5-year, two-site, natural history (observational) study of individuals with Type 1 diabetes stratified into those with (T1W) and without (T1WO) neuropathy according to the Toronto criteria, and control subjects. All study participants undergo detailed annual assessment of neuropathy including corneal nerve parameters measured using corneal confocal microscopy and corneal sensitivity measured using non-contact corneal esthesiometry. Results:396 eligible individuals (208 in Brisbane and 188 in Manchester) were assessed: 76 T1W, 166 T1WO and 154 controls. Corneal sensation threshold (mbars) was significantly higher in T1W (1.0 ± 1.1) than T1WO (0.7 ± 0.7) and controls (0.6 ± 0.4) (P=0.002); post-hoc analysis (PHA) revealed no difference between T1WO and controls (Tukey HSD, P=0.502). Corneal nerve fiber length (mm/mm2) (CNFL) was lower in T1W (13.8 ± 6.4) than T1WO (19.1 ± 5.8) and controls (23.2 ± 6.3) (P<0.001); PHA revealed CNFL to be lower in T1W than T1WO, and lower in both of these groups than controls (P<0.001). Corneal nerve branch density (branches/mm2) (CNBD) was significantly lower in T1W (40 ± 32) than T1WO (62 ± 37) and controls (83 ± 46) (P<0.001); PHA showed CNBD was lower in T1W than T1WO, and lower in both groups than controls (P<0.001). Alcohol and cigarette consumption did not differ between groups, although age, BMI, BP, waist circumference, HbA1c, albumin-creatinine ratio, and cholesterol were slightly greater in T1W than T1WO (p<0.05). Some site differences were observed. Conclusions:The LANDMark baseline findings confirm that corneal sensitivity and corneal nerve morphometry can detect differences in neuropathy status in individuals with Type 1 diabetes and healthy controls. Corneal nerve morphology is significantly abnormal even in diabetic patients ‘without neuropathy’ compared to control participants. Results of the longitudinal trial will assess the capability of these tests for monitoring change in these parameters over time as potential surrogate markers for neuropathy.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

Cross cultural adaptation and validation of a Spanish version of the lower limb functional index

Background: The Lower Limb Functional Index (LLFI) is a relatively recently published regional outcome measure. The development article showed the LLFI had robust and valid clinimetric properties with sound psychometric and practical characteristics when compared to the Lower Limb Extremity Scale (LEFS) criterion standard. Objective: The purpose of this study was cross cultural adaptation and validation of the LLFI Spanish-version (LLFI-Sp) in a Spanish population. Methods: A two stage observational study was conducted. The LLFI was initially cross-culturally adapted to Spanish through double forward and single backward translation; then subsequently validated for the psychometric characteristics of validity, internal consistency, reliability, error score and factor structure. Participants (n = 136) with various lower limb conditions of >12 weeks duration completed the LLFI-Sp, Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and the Euroqol Health Questionnaire 5 Dimensions (EQ-5D-3 L). The full sample was employed to determine internal consistency, concurrent criterion validity, construct validity and factor structure; a subgroup (n = 45) determined reliability at seven days concurrently completing a global rating of change scale. Results: The LLFI-Sp demonstrated high but not excessive internal consistency (α = 0.91) and high reliability (ICC = 0.96). The factor structure was one-dimensional which supported the construct validity. Criterion validity with the WOMAC was strong (r = 0.77) and with the EQ-5D-3 L fair and inversely correlated (r = -0.62). The study limitations included the lack of longitudinal data and the determination of responsiveness. Conclusions: The LLFI-Sp supports the findings of the original English version as being a valid lower limb regional outcome measure. It demonstrated similar psychometric properties for internal consistency, validity, reliability, error score and factor structure.

An observational analysis of the impact of board dynamics and directors’ participation on perceived board effectiveness

This study addresses calls for closer examination of board dynamics by offering an inside view of director interactions. Video-observations of three board meetings at each of two Australian corporations matched with director interviews and secondary data reveal distinct patterns of director interactions, their sources of variation and impact on perceived board effectiveness. Our data reveal that director interactions are multi-dimensional and dynamic: while group interactions across agenda items are similar, with a few directors leading the discussion, the contributing directors change across items. Moreover, directors’ inclusiveness and evenness of participation are associated with higher perceptions of board effectiveness. Last, we find that director interactions change with the nature of the items, board climate and board meeting arrangements. The study contributes to the literature by moving beyond the individual-level analysis of directors’ skills or independence, and offering a detailed view of how the joint group and individual dimensions of board dynamics affect board functioning.

Application of meshfree methods to numerically simulate microscale deformations of different plant food materials during drying

Plant food materials have a very high demand in the consumer market and therefore, improved food products and efficient processing techniques are concurrently being researched in food engineering. In this context, numerical modelling and simulation techniques have a very high potential to reveal fundamentals of the underlying mechanisms involved. However, numerical modelling of plant food materials during drying becomes quite challenging, mainly due to the complexity of the multiphase microstructure of the material, which undergoes excessive deformations during drying. In this regard, conventional grid-based modelling techniques have limited applicability due to their inflexible grid-based fundamental limitations. As a result, meshfree methods have recently been developed which offer a more adaptable approach to problem domains of this nature, due to their fundamental grid-free advantages. In this work, a recently developed meshfree based two-dimensional plant tissue model is used for a comparative study of microscale morphological changes of several food materials during drying. The model involves Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) to represent fluid and solid phases of the cellular structure. Simulation are conducted on apple, potato, carrot and grape tissues and the results are qualitatively and quantitatively compared and related with experimental findings obtained from the literature. The study revealed that cellular deformations are highly sensitive to cell dimensions, cell wall physical and mechanical properties, middle lamella properties and turgor pressure. In particular, the meshfree model is well capable of simulating critically dried tissues at lower moisture content and turgor pressure, which lead to cell wall wrinkling. The findings further highlighted the potential applicability of the meshfree approach to model large deformations of the plant tissue microstructure during drying, providing a distinct advantage over the state of the art grid-based approaches.

Cross-cultural adaptation, reliability and validity of the Spanish version of the upper limb functional index

Background The Upper Limb Functional Index (ULFI) is an internationally widely used outcome measure with robust, valid psychometric properties. The purpose of study is to develop and validate a ULFI Spanish-version (ULFI-Sp). Methods A two stage observational study was conducted. The ULFI was cross-culturally adapted to Spanish through double forward and backward translations, the psychometric properties were then validated. Participants (n = 126) with various upper limb conditions of >12 weeks duration completed the ULFI-Sp, QuickDASH and the Euroqol Health Questionnaire 5 Dimensions (EQ-5D-3 L). The full sample determined internal consistency, concurrent criterion validity, construct validity and factor structure; a subgroup (n = 35) determined reliability at seven days. Results The ULFI-Sp demonstrated high internal consistency (α = 0.94) and reliability (r = 0.93). Factor structure was one-dimensional and supported construct validity. Criterion validity with the EQ-5D-3 L was fair and inversely correlated (r = −0.59). The QuickDASH data was unavailable for analysis due to excessive missing responses. Conclusions The ULFI-Sp is a valid upper limb outcome measure with similar psychometric properties to the English language version.

Emerging methods in using GIS to analyse Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is an emerging mosquito-borne disease in Australia. We aimed to outline some recent methods in using GIS for the analysis of BFV disease in Queensland, Australia. A large database of geocoded BFV cases has been established in conjunction with population data. The database has been used in recently published studies conducted by the authors to determine spatio-temporal BFV disease hotspots and spatial patterns using spatial autocorrelation and semi-variogram analysis in conjunction with the development of interpolated BFV disease standardised incidence maps. This paper briefly outlines spatial analysis methodologies using GIS tools used in those studies. This paper summarises methods and results from previous studies by the authors, and presents a GIS methodology to be used in future spatial analytical studies in attempt to enhance the understanding of BFV disease in Queensland. The methodology developed is useful in improving the analysis of BFV disease data and will enhance the understanding of the BFV disease distribution in Queensland, Australia.