Central Queensland University

Human life histories, as compared to those of other primates and mammals, have at least four distinctive characteristics: an exceptionally long lifespan, an extended period of juvenile dependence, support of reproduction by older post-reproductive individuals, and male support of reproduction through the provisioning of females and their offspring. Another distinctive feature of our species is a large brain, with its associated psychological attributes: increased capacities for learning, cognition, and insight. In this paper, we propose a theory that unites and organizes these observations and generates many theoretical and empirical predictions. We present some tests of those predictions and outline new predictions that can be tested in future research by comparative biologists, archeologists, paleontologists, biological anthropologists, demographers, geneticists, and cultural anthropologists.

This research examines the effect of participation in an enterprise education program on perceptions of the desirability and feasibility of starting a business. Changes in the perceptions of a sample of secondary school students enrolled in the Young Achievement Australia (YAA) enterprise program are analysed using a pre–test post–test control group research design. After completing the enterprise program, participants reported significantly higher perceptions of both desirability and feasibility. The degree of change in perceptions is related to the positiveness of prior experience and to the positiveness of the experience in the enterprise education program. Self–efficacy theory is used to explain the impact of the program. Overall, the study provides empirical evidence to support including exposure to entrepreneurship education as an additional exposure variable in entrepreneurial intentions models.

This note is concerned with event-triggered <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller design for networked control systems. A novel event-triggering scheme is proposed, which has some advantages over some existing schemes. A delay system model for the analysis is firstly constructed by investigating the effect of the network transmission delay. Then, based on this model, criteria for stability with an <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> norm bound and criteria for co-designing both the feedback gain and the trigger parameters are derived. These criteria are formulated in terms of linear matrix inequalities. Simulation results have shown that the proposed event-triggering scheme is superior to some existing event-triggering schemes in the literature.

Background: Low back pain is highly prevalent and the main cause of years lived with disability (YLDs). We present the most up-to-date global, regional, and national data on prevalence and YLDs for low back pain from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021. Methods: Population-based studies from 1980 to 2019 identified in a systematic review, international surveys, US medical claims data, and dataset contributions by collaborators were used to estimate the prevalence and YLDs for low back pain from 1990 to 2020, for 204 countries and territories. Low back pain was defined as pain between the 12th ribs and the gluteal folds that lasted a day or more; input data using alternative definitions were adjusted in a network meta-regression analysis. Nested Bayesian meta-regression models were used to estimate prevalence and YLDs by age, sex, year, and location. Prevalence was projected to 2050 by running a regression on prevalence rates using Socio-demographic Index as a predictor, then multiplying them by projected population estimates. Findings: In 2020, low back pain affected 619 million (95% uncertainty interval 554-694) people globally, with a projection of 843 million (759-933) prevalent cases by 2050. In 2020, the global age-standardised rate of YLDs was 832 per 100 000 (578-1070). Between 1990 and 2020, age-standardised rates of prevalence and YLDs decreased by 10·4% (10·9-10·0) and 10·5% (11·1-10·0), respectively. A total of 38·8% (28·7-47·0) of YLDs were attributed to occupational factors, smoking, and high BMI. Interpretation: Low back pain remains the leading cause of YLDs globally, and in 2020, there were more than half a billion prevalent cases of low back pain worldwide. While age-standardised rates have decreased modestly over the past three decades, it is projected that globally in 2050, more than 800 million people will have low back pain. Challenges persist in obtaining primary country-level data on low back pain, and there is an urgent need for more high-quality, primary, country-level data on both prevalence and severity distributions to improve accuracy and monitor change. Funding: Bill and Melinda Gates Foundation.

The novel coronavirus (COVID-19) has enforced dramatic changes to daily living including economic and health impacts. Evidence for the impact of these changes on our physical and mental health and health behaviors is limited. We examined the associations between psychological distress and changes in selected health behaviors since the onset of COVID-19 in Australia. An online survey was distributed in April 2020 and included measures of depression, anxiety, stress, physical activity, sleep, alcohol intake and cigarette smoking. The survey was completed by 1491 adults (mean age 50.5 ± 14.9 years, 67% female). Negative change was reported for physical activity (48.9%), sleep (40.7%), alcohol (26.6%) and smoking (6.9%) since the onset of the COVID-19 pandemic. Significantly higher scores in one or more psychological distress states were found for females, and those not in a relationship, in the lowest income category, aged 18-45 years, or with a chronic illness. Negative changes in physical activity, sleep, smoking and alcohol intake were associated with higher depression, anxiety and stress symptoms. Health-promotion strategies directed at adopting or maintaining positive health-related behaviors should be utilized to address increases in psychological distress during the pandemic. Ongoing evaluation of the impact of lifestyle changes associated with the pandemic is needed.

Diet and the gut microbiota may underpin numerous human diseases. A major metabolic product of commensal bacteria are short-chain fatty acids (SCFAs) that derive from fermentation of dietary fibre. Here we show that diets deficient or low in fibre exacerbate colitis development, while very high intake of dietary fibre or the SCFA acetate protects against colitis. SCFAs binding to the ‘metabolite-sensing’ receptors GPR43 and GPR109A in non-haematopoietic cells mediate these protective effects. The inflammasome pathway has hitherto been reported as a principal pathway promoting gut epithelial integrity. SCFAs binding to GPR43 on colonic epithelial cells stimulates K+ efflux and hyperpolarization, which lead to NLRP3 inflammasome activation. Dietary fibre also shapes gut bacterial ecology, resulting in bacterial species that are more effective for inflammasome activation. SCFAs and metabolite receptors thus explain health benefits of dietary fibre, and how metabolite signals feed through to a major pathway for gut homeostasis. Dietary fibre is metabolized into short-chain fatty acids by gut bacteria. Here the authors show that these metabolites activate the NLRP3 inflammasome in gut epithelial cells and protect mice from injury-induced colitis, suggesting a mechanism for the benefits of a high-fibre diet.

There has been an enormous amount of research in recent years in the area of thermo-chemical conversion of biomass into bio-fuels (bio-oil, bio-char and bio-gas) through pyrolysis technology due to its several socio-economic advantages as well as the fact it is an efficient conversion method compared to other thermo-chemical conversion technologies. However, this technology is not yet fully developed with respect to its commercial applications. In this study, more than two hundred publications are reviewed, discussed and summarized, with the emphasis being placed on the current status of pyrolysis technology and its potential for commercial applications for bio-fuel production. Aspects of pyrolysis technology such as pyrolysis principles, biomass sources and characteristics, types of pyrolysis, pyrolysis reactor design, pyrolysis products and their characteristics and economics of bio-fuel production are presented. It is found from this study that conversion of biomass to bio-fuel has to overcome challenges such as understanding the trade-off between the size of the pyrolysis plant and feedstock, improvement of the reliability of pyrolysis reactors and processes to become viable for commercial applications. Further study is required to achieve a better understanding of the economics of biomass pyrolysis for bio-fuel production, as well as resolving issues related to the capabilities of this technology in practical application.

The interest in the systematic study of the circadian typology (CT) is relatively recent and has developed rapidly in the two last decades. All the existing data suggest that this individual difference affects our biological and psychological functioning, not only in health, but also in disease. In the present study, we review the current literature concerning the psychometric properties and validity of CT measures as well as individual, environmental and genetic factors that influence the CT. We present a brief overview of the biological markers that are used to define differences between CT groups (sleep-wake cycle, body temperature, cortisol and melatonin), and we assess the implications for CT and adjustment to shiftwork and jet lag. We also review the differences between CT in terms of cognitive abilities, personality traits and the incidence of psychiatric disorders. When necessary, we have emphasized the methodological limitations that exist today and suggested some future avenues of work in order to overcome these. This is a new field of interest to professionals in many different areas (research, labor, academic and clinical), and this review provides a state of the art discussion to allow professionals to integrate chronobiological aspects of human behavior into their daily practice.

Design work and design knowledge in Information Systems (IS) is important for both research and practice. Yet there has been comparatively little critical attention paid to the problem of specifying design theory so that it can be communicated, justified, and developed cumulatively. In this essay we focus on the structural components or anatomy of design theories in IS as a special class of theory. In doing so, we aim to extend the work of Walls, Widemeyer and El Sawy (1992) on the specification of information systems design theories (ISDT), drawing on other streams of thought on design research and theory to provide a basis for a more systematic and useable formulation of these theories. We identify eight separate components of design theories: (1) purpose and scope, (2) constructs, (3) principles of form and function, (4) artifact mutability, (5) testable propositions, (6) justificatory knowledge (kernel theories), (7) principles of implementation, and (8) an expository instantiation. This specification includes components missing in the Walls et al. adaptation of Dubin (1978) and Simon (1969) and also addresses explicitly problems associated with the role of instantiations and the specification of design theories for methodologies and interventions as well as for products and applications. The essay is significant as the unambiguous establishment of design knowledge as theory gives a sounder base for arguments for the rigor and legitimacy of IS as an applied discipline and for its continuing progress. A craft can proceed with the copying of one example of a design artifact by one artisan after another. A discipline cannot.

Amidst strong efforts to promote the therapeutic benefits of physical activity for reducing depression and anxiety in clinical populations, little focus has been directed towards the mental health benefits of activity for non-clinical populations. The objective of this meta-meta-analysis was to systematically aggregate and quantify high-quality meta-analytic findings of the effects of physical activity on depression and anxiety for non-clinical populations. A systematic search identified eight meta-analytic outcomes of randomised trials that investigated the effects of physical activity on depression or anxiety. The subsequent meta-meta-analyses were based on a total of 92 studies with 4310 participants for the effect of physical activity on depression and 306 study effects with 10,755 participants for the effect of physical activity on anxiety. Physical activity reduced depression by a medium effect [standardised mean difference (SMD) = −0.50; 95% CI: −0.93 to −0.06] and anxiety by a small effect (SMD = −0.38; 95% CI: −0.66 to −0.11). Neither effect showed significant heterogeneity across meta-analyses. These findings represent a comprehensive body of high-quality evidence that physical activity reduces depression and anxiety in non-clinical populations.

Automatic machine-based Facial Expression Analysis (FEA) has made substantial progress in the past few decades driven by its importance for applications in psychology, security, health, entertainment, and human–computer interaction. The vast majority of completed FEA studies are based on nonoccluded faces collected in a controlled laboratory environment. Automatic expression recognition tolerant to partial occlusion remains less understood, particularly in real-world scenarios. In recent years, efforts investigating techniques to handle partial occlusion for FEA have seen an increase. The context is right for a comprehensive perspective of these developments and the state of the art from this perspective. This survey provides such a comprehensive review of recent advances in dataset creation, algorithm development, and investigations of the effects of occlusion critical for robust performance in FEA systems. It outlines existing challenges in overcoming partial occlusion and discusses possible opportunities in advancing the technology. To the best of our knowledge, it is the first FEA survey dedicated to occlusion and aimed at promoting better-informed and benchmarked future work.

The annual world photovoltaic (PV) cell/module production is growing at almost an exponential rate and has reached 1727 MW in 2005. Building integrated PV (BIPV) projects are emerging as the strongest part of the PV market and grid interactive inverters are a key component in determining the total system cost. Module integrated converter (MIC) technology has become a global trend in grid interactive PV applications and may assist in driving down the balance of system costs to secure an improved total system cost. This paper concentrates on the topology study of the PV MICs in the power range below 500 W and covers most topologies recently proposed for MIC applications. The MIC topologies are classified into three different arrangements based on the dc link configurations. A systematic discussion is also provided at the end of the paper that focuses on the major advantages and disadvantages of each MIC arrangement. These are considered in detail and will provide a useful framework and point of reference for the next generation MIC designs and applications.

BACKGROUND: Health and fitness applications (apps) have gained popularity in interventions to improve diet, physical activity and sedentary behaviours but their efficacy is unclear. This systematic review examined the efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour in children and adults. METHODS: Systematic literature searches were conducted in five databases to identify papers published between 2006 and 2016. Studies were included if they used a smartphone app in an intervention to improve diet, physical activity and/or sedentary behaviour for prevention. Interventions could be stand-alone interventions using an app only, or multi-component interventions including an app as one of several intervention components. Outcomes measured were changes in the health behaviours and related health outcomes (i.e., fitness, body weight, blood pressure, glucose, cholesterol, quality of life). Study inclusion and methodological quality were independently assessed by two reviewers. RESULTS: Twenty-seven studies were included, most were randomised controlled trials (n = 19; 70%). Twenty-three studies targeted adults (17 showed significant health improvements) and four studies targeted children (two demonstrated significant health improvements). Twenty-one studies targeted physical activity (14 showed significant health improvements), 13 studies targeted diet (seven showed significant health improvements) and five studies targeted sedentary behaviour (two showed significant health improvements). More studies (n = 12; 63%) of those reporting significant effects detected between-group improvements in the health behaviour or related health outcomes, whilst fewer studies (n = 8; 42%) reported significant within-group improvements. A larger proportion of multi-component interventions (8 out of 13; 62%) showed significant between-group improvements compared to stand-alone app interventions (5 out of 14; 36%). Eleven studies reported app usage statistics, and three of them demonstrated that higher app usage was associated with improved health outcomes. CONCLUSIONS: This review provided modest evidence that app-based interventions to improve diet, physical activity and sedentary behaviours can be effective. Multi-component interventions appear to be more effective than stand-alone app interventions, however, this remains to be confirmed in controlled trials. Future research is needed on the optimal number and combination of app features, behaviour change techniques, and level of participant contact needed to maximise user engagement and intervention efficacy.

Abstract The growing integration of artificial intelligence (AI) dialogue systems within educational and research settings highlights the importance of learning aids. Despite examination of the ethical concerns associated with these technologies, there is a noticeable gap in investigations on how these ethical issues of AI contribute to students’ over-reliance on AI dialogue systems, and how such over-reliance affects students’ cognitive abilities. Overreliance on AI occurs when users accept AI-generated recommendations without question, leading to errors in task performance in the context of decision-making. This typically arises when individuals struggle to assess the reliability of AI or how much trust to place in its suggestions. This systematic review investigates how students’ over-reliance on AI dialogue systems, particularly those embedded with generative models for academic research and learning, affects their critical cognitive capabilities including decision-making, critical thinking, and analytical reasoning. By using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, our systematic review evaluated a body of literature addressing the contributing factors and effects of such over-reliance within educational and research contexts. The comprehensive literature review spanned 14 articles retrieved from four distinguished databases: ProQuest, IEEE Xplore, ScienceDirect, and Web of Science. Our findings indicate that over-reliance stemming from ethical issues of AI impacts cognitive abilities, as individuals increasingly favor fast and optimal solutions over slow ones constrained by practicality. This tendency explains why users prefer efficient cognitive shortcuts, or heuristics, even amidst the ethical issues presented by AI technologies.

Abstract Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can be applied across various sectors. Specifically, it possesses the ability to utilize two or more levels of non-linear feature transformation of the given data via representation learning in order to overcome limitations posed by large datasets. As a multidisciplinary field that is still in its nascent phase, articles that survey DL architectures encompassing the full scope of the field are rather limited. Thus, this paper comprehensively reviews the state-of-art DL modelling techniques and provides insights into their advantages and challenges. It was found that many of the models exhibit a highly domain-specific efficiency and could be trained by two or more methods. However, training DL models can be very time-consuming, expensive, and requires huge samples for better accuracy. Since DL is also susceptible to deception and misclassification and tends to get stuck on local minima, improved optimization of parameters is required to create more robust models. Regardless, DL has already been leading to groundbreaking results in the healthcare, education, security, commercial, industrial, as well as government sectors. Some models, like the convolutional neural network (CNN), generative adversarial networks (GAN), recurrent neural network (RNN), recursive neural networks, and autoencoders, are frequently used, while the potential of other models remains widely unexplored. Pertinently, hybrid conventional DL architectures have the capacity to overcome the challenges experienced by conventional models. Considering that capsule architectures may dominate future DL models, this work aimed to compile information for stakeholders involved in the development and use of DL models in the contemporary world.

Deciding when to return to sport after injury is complex and multifactorial-an exercise in risk management. Return to sport decisions are made every day by clinicians, athletes and coaches, ideally in a collaborative way. The purpose of this consensus statement was to present and synthesise current evidence to make recommendations for return to sport decision-making, clinical practice and future research directions related to returning athletes to sport. A half day meeting was held in Bern, Switzerland, after the First World Congress in Sports Physical Therapy. 17 expert clinicians participated. 4 main sections were initially agreed upon, then participants elected to join 1 of the 4 groups-each group focused on 1 section of the consensus statement. Participants in each group discussed and summarised the key issues for their section before the 17-member group met again for discussion to reach consensus on the content of the 4 sections. Return to sport is not a decision taken in isolation at the end of the recovery and rehabilitation process. Instead, return to sport should be viewed as a continuum, paralleled with recovery and rehabilitation. Biopsychosocial models may help the clinician make sense of individual factors that may influence the athlete's return to sport, and the Strategic Assessment of Risk and Risk Tolerance framework may help decision-makers synthesise information to make an optimal return to sport decision. Research evidence to support return to sport decisions in clinical practice is scarce. Future research should focus on a standardised approach to defining, measuring and reporting return to sport outcomes, and identifying valuable prognostic factors for returning to sport.

Asthma is prevalent in Western countries, and recent explanations have evoked the actions of the gut microbiota. Here we show that feeding mice a high-fibre diet yields a distinctive gut microbiota, which increases the levels of the short-chain fatty acid, acetate. High-fibre or acetate-feeding led to marked suppression of allergic airways disease (AAD, a model for human asthma), by enhancing T-regulatory cell numbers and function. Acetate increases acetylation at the Foxp3 promoter, likely through HDAC9 inhibition. Epigenetic effects of fibre/acetate in adult mice led us to examine the influence of maternal intake of fibre/acetate. High-fibre/acetate feeding of pregnant mice imparts on their adult offspring an inability to develop robust AAD. High fibre/acetate suppresses expression of certain genes in the mouse fetal lung linked to both human asthma and mouse AAD. Thus, diet acting on the gut microbiota profoundly influences airway responses, and may represent an approach to prevent asthma, including during pregnancy. Growing evidence suggests that environmental rather than genetic factors are major contributors to asthma development. Here the authors show that high intake of dietary fibre by pregnant mice increases resistance of their progeny to the development of allergic airways disease.

A fast terminal dynamics is proposed and used in the design of the sliding-mode control for single-input single-output nonlinear dynamical systems. The inherent dynamic properties of the fast terminal sliding modes are explored and conditions to ensure its applicability for control designs are obtained.

This paper is concerned with the controller design of networked control systems (NCS). A new model of the NCSs is provided under consideration of both the network-induced delay and the data packet dropout in the transmission. In terms of the given model, a controller design method is proposed based on a delay-dependent approach. The feedback gain of a memoryless controller and the maximum allowable value of the network-induced delay can be derived by solving a set of linear matrix inequalities. Two examples are given to show the effectiveness of our method.

Position statement The International Society of Sports Nutrition (ISSN) provides an objective and critical review related to the intake of protein for healthy, exercising individuals. Based on the current available literature, the position of the Society is as follows:An acute exercise stimulus, particularly resistance exercise, and protein ingestion both stimulate muscle protein synthesis (MPS) and are synergistic when protein consumption occurs before or after resistance exercise. For building muscle mass and for maintaining muscle mass through a positive muscle protein balance, an overall daily protein intake in the range of 1.4–2.0 g protein/kg body weight/day (g/kg/d) is sufficient for most exercising individuals, a value that falls in line within the Acceptable Macronutrient Distribution Range published by the Institute of Medicine for protein. There is novel evidence that suggests higher protein intakes (>3.0 g/kg/d) may have positive effects on body composition in resistance-trained individuals (i.e., promote loss of fat mass). Recommendations regarding the optimal protein intake per serving for athletes to maximize MPS are mixed and are dependent upon age and recent resistance exercise stimuli. General recommendations are 0.25 g of a high-quality protein per kg of body weight, or an absolute dose of 20–40 g. Acute protein doses should strive to contain 700–3000 mg of leucine and/or a higher relative leucine content, in addition to a balanced array of the essential amino acids (EAAs). These protein doses should ideally be evenly distributed, every 3–4 h, across the day. The optimal time period during which to ingest protein is likely a matter of individual tolerance, since benefits are derived from pre- or post-workout ingestion; however, the anabolic effect of exercise is long-lasting (at least 24 h), but likely diminishes with increasing time post-exercise. While it is possible for physically active individuals to obtain their daily protein requirements through the consumption of whole foods, supplementation is a practical way of ensuring intake of adequate protein quality and quantity, while minimizing caloric intake, particularly for athletes who typically complete high volumes of training. Rapidly digested proteins that contain high proportions of essential amino acids (EAAs) and adequate leucine, are most effective in stimulating MPS. Different types and quality of protein can affect amino acid bioavailability following protein supplementation. Athletes should consider focusing on whole food sources of protein that contain all of the EAAs (i.e., it is the EAAs that are required to stimulate MPS). Endurance athletes should focus on achieving adequate carbohydrate intake to promote optimal performance; the addition of protein may help to offset muscle damage and promote recovery. Pre-sleep casein protein intake (30–40 g) provides increases in overnight MPS and metabolic rate without influencing lipolysis.