An imagery-based road map to tackle maladaptive motivation in clinical disorders

There is now a widespread recognition of the importance of mental imagery in a range of clinical disorders (1). This provides the potential for a transdiagnostic route to integrate some aspects of these disorders and their treatment within a common framework. This opinion piece argues that we need to understand why imagery is such a central and recurring feature, if we are to progress theories of the origin and maintenance of disorders. This will aid us in identifying therapeutic techniques that are not simply targeting imagery as a symptom, but as a manifestation of an underlying problem. As papers in this issue highlight, imagery is a central feature across many clinical disorders, but has been ascribed varying roles. For example, the involuntary occurrence of traumatic memories is a diagnostic criterion for PTSD (2), and it has been suggested that multisensory imagery of traumatic events normally serves a functional role in allowing the individual to reappraise the situation (3), but that this re-appraisal is disabled by extreme affective responses. In contrast to the disabling flashbacks associated with PTSD, depressed adults who experience suicidal ideation often report “flash forward” imagery related to suicidal acts (4), motivating them to self-harm. Socially anxious individuals who engage in visual imagery about giving a talk in public become more anxious and make more negative predictions about future performance than others who engage in more abstract, semantic processing of the past event (5). People with Obsessive Compulsive Disorder (OCD) frequently report imagery of past adverse events, and imagery seems to be associated with severity (6). The content of intrusive imagery has been related to psychotic symptoms (7), including visual images of the catastrophic fears associated with paranoia and persecution. Imagery has been argued (8) to play a role in the maintenance of psychosis through negative appraisals of imagined voices, misattribution of sensations to external sources, by the induction of negative mood states that trigger voices, and through maintenance of negative schemas. In addiction and substance dependence, Elaborated Intrusion (EI) Theory (9, 10) emphasizes the causal role that imagery plays in substance use, through its role in motivating an individual to pursue goals directed toward achieving the pleasurable outcomes associated with substance use...

Development of an EMR implementation framework for public hospitals in Saudi Arabia

An Electronic Medical Record (EMR) is a system that has been embraced by healthcare providers worldwide. However, the implementation success of EMRs has varied widely. Studies have identified both barriers to and facilitators for implementing EMRs within healthcare organisations. In Saudi Arabia (SA), the majority of healthcare providers manage patient records manually. As public hospitals are a major provider of health services in SA and have been shown to face more EMR implementation barriers than private hospitals, there is a need for an implementation framework to guide EMR implementation in Saudi public hospitals. This doctoral project therefore aimed to develop an evidence-based EMR implementation framework for public hospitals in SA informed by those who work at the micro-implementation level and the macro-implementation level and the extant literature sensitive to the cultural, resource-related, and technological, organisational, and environmental issues of SA.

Can we safely deform a plate to fit every bone? Population-based fit assessment and finite element deformation of a distal tibial plate

Anatomically precontoured plates are commonly used to treat periarticular fractures. A well-fitting plate can be used as a tool for anatomical reduction of the fractured bone. Recent studies highlighted that some plates fit poorly for many patients due to considerable shape variations between bones of the same anatomical site. While it is impossible to design one shape that fits all, it is also burdensome for the manufacturers and hospitals to produce, store and manage multiple plate shapes without the certainty of utilization by a patient population. In this study, we investigated the number of shapes required for maximum fit within a given dataset, and if they could be obtained by manually deforming the original plate. A distal medial tibial plate was automatically positioned on 45 individual tibiae, and the optimal deformation was determined iteratively using finite element analysis simulation. Within the studied dataset, we found that: (i) 89% fit could be achieved with four shapes, (ii) 100% fit was impossible through mechanical deformation, and (iii) the deformations required to obtain the four plate shapes were safe for the stainless steel plate for further clinical use. The proposed framework is easily transferable to other orthopaedic plates.

PMU measurement based dynamic load modeling using SVC devices in online environment

Online dynamic load modeling has become possible with the availability of Static Voltage Compensator (SVC) and Phasor Measurement Unit (PMU) devices. The power of the load response to the small random bounded voltage fluctuations caused from SVC can be measured by PMU for modelling purposes. The aim of this paper is to illustrate the capability of identifying an aggregated load model from high voltage substation level in the online environment. The induction motor is used as the main test subject since it contributes the majority of the dynamic loads. A test system representing simple electromechanical generator model serving dynamic loads through the transmission network is used to verify the proposed method. Also, dynamic load with multiple induction motors are modeled to achieve a better realistic load representation.

An Advanced Pharmacy Practice Framework for Australia

The need to develop An Advanced Pharmacy Practice Framework for Australia (the “APPF”) was identified during the 2010 review of the competency standards for Australian pharmacists. The Advanced Pharmacy Practice Framework Steering Committee, a collaborative profession-wide committee comprised of representatives of ten pharmacy organisations, examined and adapted existing advanced practice frameworks, all of which were found to have been based on the Competency Development and Evaluation Group (CoDEG) Advanced and Consultant Level Framework (the “CoDEG Framework”) from the United Kingdom. Its competency standards were also found to align well with the Domains of the National Competency Standards Framework for Pharmacists in Australia (the “National Framework”). Adaptation of the CoDEG Framework created an APPF that is complementary to the National Framework, sufficiently flexible to customise for recognising advanced practice in any area of professional practice and has been approved by the boards/councils of all participating organisations. The primary purpose of the APPF is to assist the development of the profession to meet the changing health care needs of the community. However, it is also a valuable tool for assuring members of the public of the competence of an advanced practice pharmacist and the quality and safety of the services they deliver.

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Towards vision-based deep reinforcement learning for robotic motion control

This paper introduces a machine learning based system for controlling a robotic manipulator with visual perception only. The capability to autonomously learn robot controllers solely from raw-pixel images and without any prior knowledge of configuration is shown for the first time. We build upon the success of recent deep reinforcement learning and develop a system for learning target reaching with a three-joint robot manipulator using external visual observation. A Deep Q Network (DQN) was demonstrated to perform target reaching after training in simulation. Transferring the network to real hardware and real observation in a naive approach failed, but experiments show that the network works when replacing camera images with synthetic images.

Employee green behavior: A theoretical framework, multilevel review, and future research agenda

We propose a conceptual model based on person–environment interaction, job performance, and motivational theories to structure a multilevel review of the employee green behavior (EGB) literature and agenda for future research. We differentiate between required EGB prescribed by the organization and voluntary EGB performed at the employees’ discretion. The review investigates institutional-, organizational-, leader-, team-, and employee-level antecedents and outcomes of EGB and factors that mediate and moderate these relationships. We offer suggestions to facilitate the development of the field, and call for future research to adopt a multilevel perspective and to investigate the outcomes of EGB.

Educators’ perspectives about how older hospital patients can engage in a falls prevention education programme: A qualitative process evaluation

- Objectives Falls are the most frequent adverse event reported in hospitals. Patient and staff education delivered by trained educators significantly reduced falls and injurious falls in an older rehabilitation population. The purpose of the study was to explore the educators’ perspectives of delivering the education and to conceptualise how the programme worked to prevent falls among older patients who received the education. - Design A qualitative exploratory study. - Methods Data were gathered from three sources: conducting a focus group and an interview (n=10 educators), written educator notes and reflective researcher field notes based on interactions with the educators during the primary study. The educators delivered the programme on eight rehabilitation wards for periods of between 10 and 40 weeks. They provided older patients with individualised education to engage in falls prevention and provided staff with education to support patient actions. Data were thematically analysed and presented using a conceptual framework. - Results Falls prevention education led to mutual understanding between staff and patients which assisted patients to engage in falls prevention behaviours. Mutual understanding was derived from the following observations: the educators perceived that they could facilitate an effective three-way interaction between staff actions, patient actions and the ward environment which led to behaviour change on the wards. This included engaging with staff and patients, and assisting them to reconcile differing perspectives about falls prevention behaviours. - Conclusions Individualised falls prevention education effectively provides patients who receive it with the capability and motivation to develop and undertake behavioural strategies that reduce their falls, if supported by staff and the ward environment.

A new type of high-order elements based on the mesh-free interpolations

We propose a new type of high-order elements that incorporates the mesh-free Galerkin formulations into the framework of finite element method. Traditional polynomial interpolation is replaced by mesh-free interpolations in the present high-order elements, and the strain smoothing technique is used for integration of the governing equations based on smoothing cells. The properties of high-order elements, which are influenced by the basis function of mesh-free interpolations and boundary nodes, are discussed through numerical examples. It can be found that the basis function has significant influence on the computational accuracy and upper-lower bounds of energy norm, when the strain smoothing technique retains the softening phenomenon. This new type of high-order elements shows good performance when quadratic basis functions are used in the mesh-free interpolations and present elements prove advantageous in adaptive mesh and nodes refinement schemes. Furthermore, it shows less sensitive to the quality of element because it uses the mesh-free interpolations and obeys the Weakened Weak (W2) formulation as introduced in [3, 5].

Organizational competencies and dynamic Accounting Information System capability: Impact on AIS processes and firm performance

Accounting information systems (AIS) capture and process accounting data and provide valuable information for decision-makers. However, in a rapidly changing environment, continual management of the AIS is necessary for organizations to optimise performance outcomes. We suggest that building a dynamic AIS capability enables accounting process and organizational performance. Using the dynamic capabilities framework (Teece 2007) we propose that a dynamic AIS capability can be developed through the synergy of three competencies: a flexible AIS, having a complementary business intelligence system and accounting professionals with IT technical competency. Using survey data, we find evidence of a positive association between a dynamic AIS capability, accounting process performance, and overall firm performance. The results suggest that developing a dynamic AIS resource can add value to an organization. This study provides guidance for organizations looking to leverage the performance outcomes of their AIS environment.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

The PerCues framework and its application for sustainable mobility

This paper presents a framework, design and study of an ambient persuasive interface. We introduce a novel framework of persua sive Cues in Ambient Intelligence (perCues). Based on this framework we designed an application for mobile devices. The application aims to persuade people to abstain from using their cars and to use public mass transportation instead in order to reduce emissions. It contains a bus schedule and information about the pollution status. We evaluated the application in two successive studies regarding user acceptance, oppor tune moments of use and persuasive effects. The perCues received a high acceptance due to its benefit for the users. The results confirm the im portance of opportune moment and user acceptance for persuasion. The findings also indicate the persuasive potential of perCues.

Development of a robust framework for an outdoor mobile manipulation UAV

There is a growing interest to autonomously collect or manipulate objects in remote or unknown environments, such as mountains, gullies, bush-land, or rough terrain. There are several limitations of conventional methods using manned or remotely controlled aircraft. The capability of small Unmanned Aerial Vehicles (UAV) used in parallel with robotic manipulators could overcome some of these limitations. By enabling the autonomous exploration of both naturally hazardous environments, or areas which are biologically, chemically, or radioactively contaminated, it is possible to collect samples and data from such environments without directly exposing personnel to such risks. This paper covers the design, integration, and initial testing of a framework for outdoor mobile manipulation UAV. The framework is designed to allow further integration and testing of complex control theories, with the capability to operate outdoors in unknown environments. The results obtained act as a reference for the effectiveness of the integrated sensors and low-level control methods used for the preliminary testing, as well as identifying the key technologies needed for the development of an outdoor capable system.

Uncertainty based online planning for UAV target finding in cluttered and GPS-denied environments

There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.