Increased Exposure to Rigid Routines can Lead to Increased Challenging Behavior Following Changes to Those Routines

Several neurodevelopmental disorders are associated with preference for routine and challenging behavior following changes to routines. We examine individuals with Prader–Willi syndrome, who show elevated levels of this behavior, to better understand how previous experience of a routine can affect challenging behavior elicited by disruption to that routine. Play based challenges exposed 16 participants to routines, which were either adhered to or changed. Temper outburst behaviors, heart rate and movement were measured. As participants were exposed to routines for longer before a change (between 10 and 80 min; within participants), more temper outburst behaviors were elicited by changes. Increased emotional arousal was also elicited, which was indexed by heart rate increases not driven by movement. Further study will be important to understand whether current intervention approaches that limit exposure to changes, may benefit from the structured integration of flexibility to ensure that the opportunity for routine establishment is also limited.

Complexity of Inferences in Polytree-shaped Semi-Qualitative Probabilistic Networks

Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the Bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that inferences can be performed in linear time if there is a single observed node, which is a relevant practical case. Because our proof is constructive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynomial-time algorithm for SQPNs. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.

Semi-Qualitative Probabilistic Networks in Computer Vision Problems

This paper explores the application of semi-qualitative probabilistic networks (SQPNs) that combine numeric and qualitative information to computer vision problems. Our version of SQPN allows qualitative influences and imprecise probability measures using intervals. We describe an Imprecise Dirichlet model for parameter learning and an iterative algorithm for evaluating posterior probabilities, maximum a posteriori and most probable explanations. Experiments on facial expression recognition and image segmentation problems are performed using real data.

Belief Updating and Learning in Semi-Qualitative Probabilistic Networks

This paper explores semi-qualitative probabilistic networks (SQPNs) that combine numeric and qualitative information. We first show that exact inferences with SQPNs are NPPP-Complete. We then show that existing qualitative relations in SQPNs (plus probabilistic logic and imprecise assessments) can be dealt effectively through multilinear programming. We then discuss learning: we consider a maximum likelihood method that generates point estimates given a SQPN and empirical data, and we describe a Bayesian-minded method that employs the Imprecise Dirichlet Model to generate set-valued estimates.

Stiffness Analysis and Experiment of a Novel 5-DoF Parallel Kinematic Machine Considering Gravitational Effects

In order to carry out high-precision machining of aerospace structural components with large size, thin wall and complex surface, this paper proposes a novel parallel kinematic machine (PKM) and formulates its semi-analytical theoretical stiffness model considering gravitational effects that is verified by stiffness experiments. From the viewpoint of topology structure, the novel PKM consists of two substructures in terms of the redundant and overconstrained parallel mechanisms that are connected by two interlinked revolute joints. The theoretical stiffness model of the novel PKM is established based upon the virtual work principle and deformation superposition principle after mapping the stiffness models of substructures from joint space to operated space by Jacobian matrices and considering the deformation contributions of interlinked revolute joints to two substructures. Meanwhile, the component gravities are treated as external payloads exerting on the end reference point of the novel PKM resorting to static equivalence principle. This approach is proved by comparing the theoretical stiffness values with experimental stiffness values in the same configurations, which also indicates equivalent gravity can be employed to describe the actual distributed gravities in an acceptable accuracy manner. Finally, on the basis of the verified theoretical stiffness model, the stiffness distributions of the novel PKM are illustrated and the contributions of component gravities to the stiffness of the novel PKM are discussed.

Semi-interpenetrating polymer networks incorporating polygalacturonic acid for medical device applications

Background Over 20 million people in the US are living with an implantable medical device [ADDIN RW.CITE{{3114 Higgins,DavidM 2009}}1], with similar figures anticipated for Europe. Complications in the use of medical implants include the Foreign Body Response (FBR) characterised by macrophage adherence and fusion, and device-related infection due to bacterial biofilm formationADDIN RW.CITE{{3124 Harding,JacquelineL 2014}}2. Both can have detrimental consequences on the structural and functional integrity of the medical device [ADDIN RW.CITE{{3101 Anderson,JamesM 2008; 3124 Harding,JacquelineL 2014}}2,3], often necessitating removal; a painful and expensive procedure [ADDIN RW.CITE{{3121 Mah,Thien-FahC 2001}}4]. Materials are sought to attenuate both the FBR and device-related infection, leading to medical devices with improved biocompatibility and performance. Objectives The present work involves development of a semi-interpenetrating network (SIPN) hydrogel containing polygalacturonic acid (PGA), a biopolysaccharide similar in structure to hyaluronic acid. We aim to synthesise, characterise and determine the in vitro biocompatibility of the developed SIPN. Results & Discussion We have successfully incorporated PGA into a poly(HEMA) based hydrogel, which shows favourable swelling and wettability. The surface topography appears altered in comparison to the control material, with pronounced micrometer-scale features. In terms of in vitro performance, the SIPN showed increased protein adsorption, and biofilm formation (Staphylococcus epidermidis and Escherichia coli, up to 1 Log CFU/sample greater than control). However the SIPN displayed minimal cytotoxicity towards L929 fibroblasts, and was resistant to the adherence of RAW 264.7 macrophages. Conclusions The PGA incorporated SIPN lacks cytotoxicity and shows reduced macrophage adherence, however the increased biofilm formation highlights a concern regarding possible device related infection in clinical use. Future work will focus on strategies to reduce bacterial adherence, while maintaining biocompatibility.

Potential applications of shape memory alloys in seismic retrofitting of exterior RC beam-column joints

Shape memory alloys (SMAs) have the ability to undergo large deformations with minimum residual strain and also the extraordinary ability to undergo reversible hysteretic shape change known as the shape memory effect. The shape memory effect of these alloys can be utilised to develop a convenient way of actively confine concrete sections to improve their shear strength, flexural ductility and ultimate strain. Most of the previous work on active confinement of concrete using SMA has been carried out on circular sections. In this study retrofitting strategies for active confinement of non-circular sections have been proposed. The proposed schemes presented in this paper are conceived with an aim to seismically retrofit beam-column joints in non-seismically designed reinforced concrete buildings. SMAs are complex materials and their material behaviour depends on number of parameters. Depending upon the alloying elements, SMAs exhibit different behaviour in different conditions and are highly sensitive to variation in temperature, phase in which it is used, loading pattern, strain rate and pre-strain conditions. Therefore, a detailed discussion on the behaviour of SMAs under different thermo-mechanical conditions is presented first.

Experimental and numerical study of debonding in composite adhesive joints

The mode I and mode II fracture properties of the FM300-2 adhesive bond between 5HS/RTM6 laminates are determined experimentally by DCB and ELS test. The crack propagation is studied numerically by means of interface elements based on the decohesive zone model. The latter is characterized by material degradation, which is usually assumed to be linear. In the present study it is shown that if a non-linear material degradation is used with an increased magnitude of the interface relative displacement at failure it is possible to model more correctly the experimentally observed significant non-linear behaviour before the start of crack propagation. An adhesive stepped flush joint is studied experimentally and numerically. A mixed mode interaction criterion is used together with the nonlinear material degradation of the interface. Sensitivity studies are performed to study the influence of the parameters defining it.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.

A Novel Semi-Automated Method of Tracking Fetal Movements

We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I