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Stereo vision-based 3D positioning and tracking
No full textKhyam, MO ORCiD: 0000-0002-1988-2328The evolution of technologies for the capture of human movement has been motivated by a number of potential applications across a wide variety of fields. However, capturing human motion in 3D is difficult in an outdoor environment when it is performed without controlled surroundings. In this paper, a stereo camera rig with an ultra-wide baseline distance and conventional cameras with fish-eye lenses is proposed. Its cameras provide a wide field of view (FOV) which increases the coverage area and also enables the baseline distance to be increased to cover the common area required for both cameras’ views to perform as a stereo camera. We propose a passive marker-based approach to track the motion of the object. In this method, an adaptive thresholding method is applied to extract each small pink polyester marker from the video frames. As the cameras have fish-eye lenses, it is difficult to estimate the depth information using a pinhole camera model. We use a unique method to restore the 3D positions by developing a relationship between the pixel dimensions and distances in an image and real world coordinates. In this paper, occlusion detection is considered because, in the marker-based capturing of articulated human kinematics, the occlusion of a marker is one of the major challenges. The detection algorithm differentiates among types of occlusions and predicts any missing marker position where necessary. As this design is intended to be mounted on a moving carrier, such as a drone or car, a method for compensating the camera’s ego-motion is proposed. The proposed 3D positioning and tracking system is tested in different situations to validate its applicability as a stereo camera rig as well as its performance for motion capture. The performance of the proposed system is compared with that of a standard motion capture system called Vicon and is shown to have the same order of accuracy while incurring less cost
Targeted achilles tendon training and rehabilitation using personalized and real-time multiscale models of the neuromusculoskeletal system
No full textObst, SJ ORCiD: 0000-0003-4299-9628Musculoskeletal tissues, including tendons, are sensitive to their mechanical environment, with both excessive and insufficient loading resulting in reduced tissue strength. Tendons appear to be particularly sensitive to mechanical strain magnitude, and there appears to be an optimal range of tendon strain that results in the greatest positive tendon adaptation. At present, there are no tools that allow localized tendon strain to be measured or estimated in training or a clinical environment. In this paper, we first review the current literature regarding Achilles tendon adaptation, providing an overview of the individual technologies that so far have been used in isolation to understand in vivo Achilles tendon mechanics, including 3D tendon imaging, motion capture, personalized neuromusculoskeletal rigid body models, and finite element models. We then describe how these technologies can be integrated in a novel framework to provide real-time feedback of localized Achilles tendon strain during dynamic motor tasks. In a proof of concept application, Achilles tendon localized strains were calculated in real-time for a single subject during walking, single leg hopping, and eccentric heel drop. Data was processed at 250 Hz and streamed on a smartphone for visualization. Achilles tendon peak localized strains ranged from 3 to 11% for walking, 5 to 15% during single leg hop, and 2 to 9% during single eccentric leg heel drop, overall showing large strain variation within the tendon. Our integrated framework connects, across size scales, knowledge from isolated tendons and whole-body biomechanics, and offers a new approach to Achilles tendon rehabilitation and training. A key feature is personalization of model components, such as tendon geometry, material properties, muscle geometry, muscle-tendon paths, moment arms, muscle activation, and movement patterns, all of which have the potential to affect tendon strain estimates. Model personalization is important because tendon strain can differ substantially between individuals performing the same exercise due to inter-individual differences in these model components
Fungal biocontrol against Meloidogyne spp. in agricultural crops: A systematic review and meta-analysis
No full textBrown, PH ORCiD: 0000-0001-6272-5507 0000-0002-4033-6719; Li, YJ ORCiD: 0000-0003-3807-7110Root-knot nematodes are the most damaging nematode pest for worldwide agricultural production. Chemical control is the most popular method; however, the risks of chemical nematicides to environment and health have made some effective nematicides being removed from the use for some crops. Comprehensive literature searches were conducted to identify the most potential and consistent alternative strategies. Biological control has been a popular option with various, bacteria, fungi and other predators (e.g. mites). Among all the natural enemies of nematodes, nematophagous fungi are the most diverse and they use a variety of mechanisms to capture and kill nematodes. Many studies of nematophagous fungi have been published, but no cohesive analysis of these studies has been attempted. Therefore, a systematic review and meta-analysis were conducted to identify biocontrol fungi with the most consistent effects against root-knot nematodes. Pochonia spp., Trichoderma spp. and Paecilomyces spp. were the most studied fungal genera against root-knot nematodes. In general, most of the fungal genera controlled root-knot nematodes and improved plant growth and yield. However, the results showed that fungi alone cannot achieve a high level of suppression. In general, fungal bio-agents could reduce root-knot nematode population and damage levels by 45% compared to untreated conditions. Arthrobotrys spp. and Acremonium spp. were found to be comparatively more effective in root-knot nematode damage reduction than other species. The relationship of fungal biocontrol with soil properties could not be developed as the data were insufficient, highlighting the importance of reporting such data in future biological control studies. © 2020 Elsevier Inc
Interspecific plant competition increases soil labile organic carbon and nitrogen contents
No full textPlant competition can impose species-specific effects on the dynamics of soil carbon (C) and nitrogen (N) through rhizosphere processes and litter input. Therefore, it is crucial to quantify these effects in various terrestrial ecosystems for a better understanding of the mechanisms. Here, we collected subsoils containing low N from a subtropical forest and planted eight dominant tree species (two deciduous and six evergreens) in these soils in a greenhouse to explore the effects of interspecific plant competition on plant growth, soil C and N contents, and soil C and N mineralization rates after the plants had grown for 12 months. Soil labile organic C and N contents were represented by soil extractable organic C (EOC) and extractable organic N (EON) contents. We assessed the magnitude of the interspecific plant competition via the relative interaction intensity (RII) index, which was calculated from the biomass of seedlings in the mixed treatments compared with the single treatments. Our results showed that interspecific plant competition had species-specific effects on plant biomass and soil total C and N contents as well as soil C mineralization rates, whereas it tended to decrease soil N mineralization rates. However, interspecific plant competition significantly decreased plant C and N contents, and significantly increased soil EOC and EON contents with increasing RII. After classifying the communities into two functional types (i.e., deciduous–evergreen versus evergreen–evergreen), similar relationships were observed. These findings address the importance of quantifying interspecific plant competition on soil labile organic C and N contents, which is helpful for understanding soil C and N cycling in forest ecosystems. © 2020 Elsevier B.V
Progression of motivation models in exercise science: Where we have been and where we are heading
No full textRebar, A ORCiD: 0000-0003-3164-993XThe aim of this chapter is to highlight four progressions in the theoretical approaches to motivational models in exercise science. Our aim is not to address the efficacy of any given theoretical approach, as the other
chapters in this section of the book provide detail in that domain. Neither is the aim of this chapter to put forth a new model of physical activity motivation. Rather, our aim is to highlight how and why the field is changing. We start the chapter by describing that the theoretical perspective driving most physical activity motivation research has been expectancy‐value models originating from social, sport, and education psychology. Following that, we present our perspectives on how and why the field is being invigorated by “new” perspectives, which are really just a reinvigoration of old ideas that got lost in translation amongst exercise science across the years. These progressions of theory include consideration for how a person’s context can impact their motivation
(ecological models), that motivation is not a static onceoff phenomenon (temporal dynamic models), that motivation encompasses automatic processes as well as deliberative beliefs and values (dual process models), and that there are processes and factors that determine whether intention translates into behavior (action control models)
Digital health innovation enhancing patient experience in medical travel
No full textMedhekar, A ORCiD: 0000-0002-6791-4056Digital health technological innovations are disrupting every sector of the economy, including medical travel/tourism. Global patients as medical tourists are using patient-centric digital health technologies,
enhancing patient/medical tourists experience and making it more transparent and engaging with healthcare providers and medical tourists. Digital communication tools such as e-mail, online appointments,
smartphones, instant messaging applications, social media tools, user-generated content by online patient communities, tele-medicine, tele-radiology, my-Health records, Skype consultation, WhatsApp, health
video, electronic health records, health data analytics tools, and artificial intelligence-enabled health technologies enhance the medical travel decision-making process, reduce cost, improve patient care and transparency of communication, and engage the relationship between the patient and the healthcare provider with positive outcomes, medical tourist experience, and empowerment.Associated Grant Code:N/
Roses by other names? Empathy, sympathy, and compassion in mental health nursing
No full textGerace, A ORCiD: 0000-0001-8272-8799Empathy and related concepts such as sympathy and compassion are considered fundamental to mental health nurses' work with consumers. However, there is often little consensus on the relationship between these interpersonal interaction factors and their similarities and differences. In this paper, these three concepts are discussed. Theoretical frameworks of empathy, sympathy, and compassion are presented with a social psychological model of empathy focused upon. From this, discussion is undertaken of how the mental health nursing process may be explained by such frameworks, as well as what unique aspects of the nursing relationship need to be considered. It is contended that precise definitions and understandings of empathy, sympathy, and compassion are vital, and the use of models allows researchers to consider where gaps are in current knowledge, and to identify what might be important to consider from a nurse education perspective
Demographic profile of the intellectual disability nursing workforce in Australia: Findings from a national survey
No full textHowie, VA ORCiD: 0000-0003-4902-7194Background: Nurses provide technical and relational skills that are ntegral to the care of people with intellectual disability (ID) in Australia. However, little is known about the demographic profile of this section of the nursing workforce. Method: Administration of a survey to nurses whose primary role it is to care for people with ID nationwide
Results: This brief report provides a description of the demographics of participants in the national survey. Of 101 participants, 78% were women and the mean age was 53.21 years. Participants held a variety of educational qualifications to prepare them for the care of people with ID.
Conclusion: The findings suggest the need to consider the future unmet needs of people with ID given the ageing of this workforce. The ongoing support needs of people with ID depend upon the ongoing presence of nurses well prepared to meet the need of this group of people
Mid-infrared spectroscopy for entomological purposes: A review
No full textJohnson, JB ORCiD: 0000-0002-9172-8587; Naiker, M ORCiD: 0000-0002-6844-8325Mid-infrared spectroscopy (MIRS) is a well-established technique in the field of chemical analysis. Although it has been applied to problems in the entomological field for over 65 years, MIRS typically remains underutilised in this discipline. Potential applications of MIRS include profiling of cuticular hydrocarbons, taxonomic discrimination between cryptic species, sex discrimination, age prediction, detection of endosymbionts such as Wolbachia, and characterisation of the surface chemistry of insect body parts and products. The number of potential applications is expected to continue rising rapidly as MIR technology advances and it is adopted by more members of the entomological community
Dezert-Smarandache theory-based fusion for human activity recognition in body sensor networks
No full textKhyam, MO ORCiD: 0000-0002-1988-2328Multi-sensor fusion strategies have been widely applied in Human Activity Recognition (HAR) in Body Sensor Networks (BSNs). However, the sensory data collected by BSNs systems are often uncertain or even incomplete. Thus, designing a robust and intelligent sensor fusion strategy is necessary for high-quality activity recognition. In this paper, Dezert-Smarandache Theory (DSmT) is used to develop a novel sensor fusion strategy for HAR in BSNs, which can effectively improve the accuracy of recognition. Specifically, in the training stage, the Kernel Density Estimation (KDE) based models are first built and then precisely selected for each specific activity according to the proposed discriminative functions. After that, a structure of Basic Belief Assignment (BBA) can be constructed, using the relationship between the test data of unknown class and the selected KDE models of all considered types of activities. In order to deal with the conflict between the obtained BBAs, Proportional Conflict Redistribution-6 (PCR6) is applied to fuse the acquired BBAs. Moreover, the missing data of the involved sensors are addressed as ignorance in the framework of the DSmT without manual interpolation or intervention. Experimental studies on two real-world activity recognition datasets (The OPPORTUNITY dataset; Daily and Sports Activity Dataset (DSAD)) were conducted, and the results showed the superiority of our proposed method over some state-of-the-art approaches proposed in the literature