Military Psychology: Time to embrace a front-line diplomatic role

The weapon systems created for the purpose of fighting the enemy in World War I caused terrible losses of human life on all sides of the conflict. However, World War I was also the event that gave birth to what became the field of Military Psychology. This position article, briefly tracing the development of the field, encourages the development of an expanded scope for this sub-discipline of Psychology. In its infancy, the role of Military Psychology was the selection and placement of soldiers based on a series of cognitive tests. After World War II, the scope of Military Psychology quickly expanded exponentially into areas such as leadership development, psychological warfare, and the enhancement of morale, motivation, resilience, and human factors, as military psychology with its sub-disciplines became integrated into national military forces to enhance the capabilities of the modern fighting soldier psychologically, physically and technologically. As the discipline matured, its present role can be described as to create soldiers whose skills sets greatly surpass those of their predecessors in meeting the ever-increasing complex demands of the modern battlefield. In recent years, Afghanistan and Iraq illustrated that conventional warfare tactics are rendered all but obsolete by small numbers of militia fighters with improvised devices and even outdated weapons in a demonstration of human ingenuity trumping advanced technology and well-equipped, superior military forces that inevitably failed dismally to subdue insurgent opposition forces. Even the destruction of the Islamic State in Libya (ISIL) and the Islamic State in Syria (ISIS) forces serves to emphasise that the world can no longer afford to continue armed conflict as a means to settle territorial and international disagreements because these eventually become the rationalisation for ongoing, unnecessary conflict. In its contribution to the defence role, alternatives to engagement in ill-advised military options must involve the strategic deployment of Military Psychology in a front-line capacity to research, comprehend and then, through diplomatic means, counter the psychological and ideological factors at play in creating the world’s current conflict areas. If not, an even greater catastrophe will arise from ongoing ill-informed, ideology-driven international military interventions around the world

Comparison of two culture techniques used to detect environmental contamination with Salmonella enterica in a large-animal hospital

Salmonellosis is a common healthcare-associated infection in large-animal hospitals, and surveillance for Salmonella is an integral part of comprehensive infection control programmes in populations at risk. The present study compares the effectiveness of two culture techniques for recovery of Salmonella from environmental samples obtained in a large-animal referral veterinary hospital during a Salmonella outbreak. Environmental samples were collected using household cleaning cloths that were incubated overnight in buffered peptone water (BPW). Aliquots of BPW were then processed using two different selective enrichment and culture techniques. In the first technique (TBG-RV-XLT4) samples were incubated at 43 °C in tetrathionate broth and then Rappaport-Vassiliadis broth before plating on XLT4 agar. The second technique (SEL-XLD) involved incubation at 37 °C in selenite broth before plating on XLD agar. Salmonella was recovered from 49.7% (73/147) of samples using the TBG-RV-XLT4 technique, but only 10.2% (15/147) of samples using the SEL-XLD method. Fourteen samples (9.5%) were culture-positive using both methods, and 73 (49.7%) were culture-negative using both techniques. There were discordant results for 60 samples, including 59 that were only culture-positive using the TBG-RV-XLT4 method, and one sample that was only culturepositive using the SEL-XLD method. Salmonella was much more likely to be recovered using the TBG-RV-XLT4 method, and there appeared to be five times more false-negative results using the SEL-XLD technique. Environmental contamination with Salmonella may be underestimated by certain culture techniques, which may impair efforts to control spread in veterinary hospitals

The systematic development of a machine vision based milking robot

Agriculture involves unique interactions between man, machines, and various elements from nature. Therefore the implementation of advanced technology in agriculture holds different challenges than in other sectors of the economy. This dissertation stems from research into the application of advanced technology in dairying - focusing on the systematic analysis and synthesis of concepts for a robotic milking machine for cows. The main subsystems of the milking robot are identified as a machine perception subsystem and a mechanical manipulator subsystem. The machine perception subsystem consists of one or more sensors and a signal processor; while the manipulator subsystem typically consists of a robot arm; a robot hand; actuators; and a controller. After the evaluation of different sensor concepts in terms of a defined set of technical performance requirements, television cameras are chosen as a suitable sensor concept for a milking robot. Therefore the signal processor is only concerned with image processing techniques. The primary task of the milking robot's image processor is to derive a computerized description of the spatial positions of the endpoints of a cow's four teats, in terms of a pre-defined frame of reference (called the word coordinates ). This process is called scene description ; and based on extensive experimental results, three-dimensional scene description - making use of a stereo-vision set-up - is shown to be feasible for application as part of a milking robot. Different processes are involved in stereo machine vision - such as data reduction, with the minimum loss of Image information (for which the Sobel edge enhancement operator is used); the accurate localisation of target objects in the two stereo images (for which the parabolic Hough transform is used); and correlation of features in the two stereo images. These aspects are all addressed for the milking robot, by means of concept analysis, trade-oft, and experimental verification. From a trade-off, based on a set of performance requirements for the manipulator subsystem, a cartesian robot arm is chosen as a suitable configuration for the milking robot; while sealed direct current servo motors are chosen as a suitable actuator concept. A robot arm and its actuators are designed by means of computer-aided design techniques; and computer simulation results are presented for the dynamic response of the arm and its actuators. A suitable robot hand is also designed - based on systematic trade-oft for different parts of a robot hand. From an analysis of the desired controller functions, and of different control concepts, it is concluded that a positional controller, making use of on-line obstruction avoidance, is required for the milking robot. Because this research project involved systematic concept exploration, there are still some details to be sorted out in a follow-up development phase. The basic principles of a machine vision based milking robot are however established; and the work in this dissertation represents a suitable baseline for further development

Learning from Samples of Variable Quality

Training labels are expensive to obtain and may be of varying quality, as some may be from trusted expert labelers while others might be from heuristics or other sources of weak supervision such as crowd-sourcing. This creates a fundamental quality-versus-quantity trade-off in the learning process. Do we learn from the small amount of high-quality data or the potentially large amount of weakly-labeled data? We argue that if the learner could somehow know and take the label-quality into account, we could get the best of both worlds. To this end, we introduce “fidelity-weighted learning” (FWL), a semi-supervised student-teacher approach for training deep neural networks using weakly-labeled data. FWL modulates the parameter updates to a student network, trained on the task we care about on a per-sample basis according to the posterior confidence of its label-quality estimated by a teacher, who has access to limited samples with high-quality labels

Learning from Samples of Variable Quality

Training labels are expensive to obtain and may be of varying quality, as some may be from trusted expert labelers while others might be from heuristics or other sources of weak supervision such as crowd-sourcing. This creates a fundamental quality-versus-quantity trade-off in the learning process. Do we learn from the small amount of high-quality data or the potentially large amount of weakly-labeled data? We argue that if the learner could somehow know and take the label-quality into account, we could get the best of both worlds. To this end, we introduce “fidelity-weighted learning” (FWL), a semi-supervised student-teacher approach for training deep neural networks using weakly-labeled data. FWL modulates the parameter updates to a student network, trained on the task we care about on a per-sample basis according to the posterior confidence of its label-quality estimated by a teacher, who has access to limited samples with high-quality labels

Progress and challenges in modelling country-level HIV/AIDS epidemics: the UNAIDS Estimation and Projection Package 2007

The UNAIDS Estimation and Projection Package (EPP) was developed to aid in country-level estimation and short-term projection of HIV/AIDS epidemics. This paper describes advances reflected in the most recent update of this tool (EPP 2007), and identifies key issues that remain to be addressed in future versions. The major change to EPP 2007 is the addition of uncertainty estimation for generalised epidemics using the technique of Bayesian melding, but many additional changes have been made to improve the user interface and efficiency of the package. This paper describes the interface for uncertainty analysis, changes to the user interface for calibration procedures and other user interface changes to improve EPP’s utility in different settings. While formal uncertainty assessment remains an unresolved challenge in low-level and concentrated epidemics, the Bayesian melding approach has been applied to provide analysts in these settings with a visual depiction of the range of models that may be consistent with their data. In fitting the model to countries with longer-running epidemics in sub-Saharan Africa, a number of limitations have been identified in the current model with respect to accommodating behaviour change and accurately replicating certain observed epidemic patterns. This paper discusses these issues along with their implications for future changes to EPP and to the underlying UNAIDS Reference Group model

Humans are not fooled by size illusions in attractiveness judgements

Could signallers use size contrast illusions to dishonestly exaggerate their attractiveness to potential mates? Using composite photographs of women from three body mass index (BMI) categories designed to simulate small groups, we show that target women of medium size are judged as thinner when surrounded by larger women than when surrounded by thinner women. However, attractiveness judgements of the same target women were unaffected by this illusory change in BMI, despite small true differences in the BMIs of the target women themselves producing strong effects on attractiveness. Thus, in the context of mate choice decisions, the honesty of female body size as a signal of mate quality appears to have been maintained by the evolution of assessment strategies that are immune to size contrast illusions. Our results suggest that receiver psychology is more flexible than previously assumed, and that illusions are unlikely to drive the evolution of exploitative neighbour choice in human sexual displays. © 2014 The Authors

A spatio-temporal, landscape perspective on Acacia dealbata invasions and broader land use and cover changes in the northern Eastern Cape, South Africa

Biological invasions and human land use both have the potential to drastically alter the patterns and processes of landscapes, driving habitat fragmentation and altering natural disturbance regimes. The proliferation of an invasive species depends on composition and configuration of the landscape, as well as the invasiveness of the species. To effectively manage a highly invasive species, such as Acacia dealbata, it is crucial to understand the historical progression of the invasion within the landscape. This study sought to examine the landscape dynamics of biological invasions by tracking the historical spread of A. dealbata and broader land use/land cover (LULC) changes at different spatiotemporal scales in the northern Eastern Cape. A timeseries of aerial photographs were systematically classified according to designated A. dealbata and LULC categories in ArcGIS to track the changes in the extent and rate of spread of A. dealbata. Markedly dynamic, multi-directional, and spatio-temporally variable LULC transitions were observed across the northern Eastern Cape over the last six decades. A. dealbata frequently retained a high proportion of cover over time, and despite the loss of cover to other LULC classes, a net increase in A. dealbata cover occurred as it spread at an overall annual rate of 0.11–0.21%, occupying approximately 8–18% of land cover across all sampled sites by 2013