Description:
Preventing sports injuries requires behaviour change. Observational learning, or role modelling, is one way to develop self-efficacy, a key behavioural determinant. This premise underpins the social cognitive theory (SCT), and is the reason why role models have such a strong influence on behaviour. Most human behaviour is learned by observing others. Therefore, understanding role modelling and how to use it effectively could be important for sports injury prevention.
Effectiveness of online tailored advice to prevent running-related injuries and promote preventive behaviour in Dutch trail runners : A pragmatic randomised controlled trial
Description:
BACKGROUND: Trail running is popular worldwide, but there is no preventive intervention for running-related injury (RRI). AIM: To evaluate the effectiveness of adding online tailored advice (TrailS6 ) to general advice on (1) the prevention of RRIs and (2) the determinants and actual preventive behaviour in Dutch trail runners. METHODS: Two-arm randomised controlled trial over 6 months. 232 trail runners were randomly assigned to an intervention or control group. All participants received online general advice on RRI prevention 1 week after baseline. Every 2 weeks, participants in the intervention group received specific advice tailored to their RRI status. The control group received no further intervention. Bayesian mixed models were used to analyse the data. RESULTS: Trail runners in the intervention group sustained 13% fewer RRIs compared with those in the control group after 6 months of follow-up (absolute risk difference -13.1%, 95% Bayesian highest posterior credible interval (95% BCI) -23.3 to -3.1). A preventive benefit was observed in one out of eight trail runners who had received the online tailored advice for 6 months (number needed to treat 8, 95% BCI 3 to 22). No significant between-group difference was observed on the determinants and actual preventive behaviours. CONCLUSIONS: Online tailored advice prevented RRIs among Dutch trail runners. Therefore, online tailored advice may be used as a preventive component in multicomponent RRI prevention programmes. No effect was observed on determinants and actual preventive behaviours. TRIAL REGISTRATION NUMBER: The Netherlands National Trial Register (NTR5431).
Description:
BACKGROUND: Trail running is popular worldwide, but there is no preventive intervention for running-related injury (RRI). AIM: To evaluate the effectiveness of adding online tailored advice (TrailS6 ) to general advice on (1) the prevention of RRIs and (2) the determinants and actual preventive behaviour in Dutch trail runners. METHODS: Two-arm randomised controlled trial over 6 months. 232 trail runners were randomly assigned to an intervention or control group. All participants received online general advice on RRI prevention 1 week after baseline. Every 2 weeks, participants in the intervention group received specific advice tailored to their RRI status. The control group received no further intervention. Bayesian mixed models were used to analyse the data. RESULTS: Trail runners in the intervention group sustained 13% fewer RRIs compared with those in the control group after 6 months of follow-up (absolute risk difference -13.1%, 95% Bayesian highest posterior credible interval (95% BCI) -23.3 to -3.1). A preventive benefit was observed in one out of eight trail runners who had received the online tailored advice for 6 months (number needed to treat 8, 95% BCI 3 to 22). No significant between-group difference was observed on the determinants and actual preventive behaviours. CONCLUSIONS: Online tailored advice prevented RRIs among Dutch trail runners. Therefore, online tailored advice may be used as a preventive component in multicomponent RRI prevention programmes. No effect was observed on determinants and actual preventive behaviours. TRIAL REGISTRATION NUMBER: The Netherlands National Trial Register (NTR5431).
Description:
Objective: Establish the prevalence of illness symptoms, poor sleep quality, poor mental health symptoms, low energy availability and stress-recovery state in an Olympic cohort late in the 3months prior to the Summer Olympic Games. Methods: Olympic athletes (n=317) from 11 sports were invited to complete questionnaires administered 3months before the Rio 2016 Olympic Games. These questionnaires included the Depression, Anxiety and Stress Questionnaire, Perceived Stress Scale, Dispositional Resilience Scale, Recovery-Stress Questionnaire (REST-Q-52 item), Low Energy Availability in Females Questionnaire (LEAF-Q), Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index and custom-made questionnaires on probiotic usage and travel. Multiple illness (case) definitions were applied. ORs and attributable fractions in the population were used. Factor analyses were used to explore the relationships between variables. Results: The response rate was of 42% (male, n=47, age 25.8±4.1 years; female, n=85, age 24.3±3.9 years). Low energy availability was associated with sustaining an illness in the previous month (upper respiratory, OR=3.8, 95%CI 1.2 to 12). The main factor relating to illness pertained to a combination of anxiety and stress recovery states (as measured by the REST-Q-52 item). All participants reported at least one episode of illness in the last month (100% prevalence). Conclusions: All participants reported at least one illness symptom in the previous month. Low energy availability was a leading variable associated with illness in Olympic-class athletes. The estimates duration of symptoms ranged from 2 to 7 days. Factor analyses show the interdependence of various health domains and support multidisciplinary care.
Description:
Permutation is a commonly used primitive in multimedia (image/video) encryption schemes, and many permutation-only algorithms have been proposed in recent years for the protection of multimedia data. In permutation-only image ciphers, the entries of the image matrix are scrambled using a permutation mapping matrix which is built by a pseudo-random number generator. The literature on the cryptanalysis of image ciphers indicates that the permutation-only image ciphers are insecure against ciphertext-only attacks and/or known/chosenplaintext attacks. However, the previous studies have not been able to ensure the correct retrieval of the complete plaintext elements. In this paper, we revisited the previous works on cryptanalysis of permutation-only image encryption schemes and made the cryptanalysis work on chosen-plaintext attacks complete and more efficient. We proved that in all permutationonly image ciphers, regardless of the cipher structure, the correct permutation mapping is recovered completely by a chosenplaintext attack. To the best of our knowledge, for the first time, this paper gives a chosen-plaintext attack that completely determines the correct plaintext elements using a deterministic method. When the plain-images are of size M × N and with L different color intensities, the number n of required chosen plain-images to break the permutation-only image encryption algorithm is n = logL(MN). The complexity of the proposed attack is O (n · M N) which indicates its feasibility in a polynomial amount of computation time. To validate the performance of the proposed chosen-plaintext attack, numerous experiments were performed on two recently proposed permutation-only image/video ciphers. Both theoretical and experimental results showed that the proposed attack outperforms the state-of-theart cryptanalytic methods.
Description:
Permutation is a commonly used primitive in multimedia (image/video) encryption schemes, and many permutation-only algorithms have been proposed in recent years for the protection of multimedia data. In permutation-only image ciphers, the entries of the image matrix are scrambled using a permutation mapping matrix which is built by a pseudo-random number generator. The literature on the cryptanalysis of image ciphers indicates that the permutation-only image ciphers are insecure against ciphertext-only attacks and/or known/chosenplaintext attacks. However, the previous studies have not been able to ensure the correct retrieval of the complete plaintext elements. In this paper, we revisited the previous works on cryptanalysis of permutation-only image encryption schemes and made the cryptanalysis work on chosen-plaintext attacks complete and more efficient. We proved that in all permutationonly image ciphers, regardless of the cipher structure, the correct permutation mapping is recovered completely by a chosenplaintext attack. To the best of our knowledge, for the first time, this paper gives a chosen-plaintext attack that completely determines the correct plaintext elements using a deterministic method. When the plain-images are of size M × N and with L different color intensities, the number n of required chosen plain-images to break the permutation-only image encryption algorithm is n = logL(MN). The complexity of the proposed attack is O (n · M N) which indicates its feasibility in a polynomial amount of computation time. To validate the performance of the proposed chosen-plaintext attack, numerous experiments were performed on two recently proposed permutation-only image/video ciphers. Both theoretical and experimental results showed that the proposed attack outperforms the state-of-theart cryptanalytic methods.
Description:
Using a key station approach, statistical downscaling of monthly general circulation model outputs to monthly precipitation, evaporation, minimum temperature and maximum temperature at 17 observation stations located in Victoria, Australia was performed. Using the observations of each predictand, over the period 1950-2010, correlations among all stations were computed. For each predictand, the station which showed the highest number of correlations above 0.80 with other stations was selected as the first key station. The stations that were highly correlated with that key station were considered as the member stations of the first cluster. By employing this same procedure on the remaining stations, the next key station was found. This procedure was performed until all stations were segregated into clusters. Thereafter, using the observations of each predictand, regression equations (inter-station regression relationships) were developed between the key stations and the member stations for each calendar month. The downscaling models at the key stations were developed using reanalysis data as inputs to them. The outputs of HadCM3 pertaining to A2 emission scenario were introduced to these downscaling models to produce projections of the predictands over the period 2000-2099. Then the outputs of these downscaling models were introduced to the inter-station regression relationships to produce projections of predictands at all member stations.
Description:
In this paper, a purely displacement-based formulation is presented within the framework of the scaled boundary finite element method to model compressible and nearly incompressible materials. A selective reduced integration technique combined with an analytical treatment in the nearly incompressible limit is employed to alleviate volumetric locking. The stiffness matrix is computed by solving the scaled boundary finite element equation. The salient feature of the proposed technique is that it neither requires a stabilization parameter nor adds additional degrees of freedom to handle volumetric locking. The efficiency and the robustness of the proposed approach is demonstrated by solving various numerical examples in two and three dimensions.
Description:
Tendinopathy can be resistant to treatment and often recurs, implying that current treatment approaches are suboptimal. Rehabilitation programmes that have been successful in terms of pain reduction and return to sport outcomes usually include strength training. Muscle activation can induce analgesia, improving self-efficacy associated with reducing one's own pain. Furthermore, strength training is beneficial for tendon matrix structure, muscle properties and limb biomechanics. However, current tendon rehabilitation may not adequately address the corticospinal control of the muscle, which may result in altered control of muscle recruitment and the consequent tendon load, and this may contribute to recalcitrance or symptom recurrence. Outcomes of interest include the effect of strength training on tendon pain, corticospinal excitability and short interval cortical inhibition. The aims of this concept paper are to: (1) review what is known about changes to the primary motor cortex and motor control in tendinopathy, (2) identify the parameters shown to induce neuroplasticity in strength training and (3) align these principles with tendon rehabilitation loading protocols to introduce a combination approach termed as tendon neuroplastic training. Strength training is a powerful modulator of the central nervous system. In particular, corticospinal inputs are essential for motor unit recruitment and activation; however, specific strength training parameters are important for neuroplasticity. Strength training that is externally paced and akin to a skilled movement task has been shown to not only reduce tendon pain, but modulate excitatory and inhibitory control of the muscle and therefore, potentially tendon load. An improved understanding of the methods that maximise the opportunity for neuroplasticity may be an important progression in how we prescribe exercise-based rehabilitation in tendinopathy for pain modulation and potentially restoration of the corticospinal control of the muscle-tendon complex.
Description:
Tendinopathy can be resistant to treatment and often recurs, implying that current treatment approaches are suboptimal. Rehabilitation programmes that have been successful in terms of pain reduction and return to sport outcomes usually include strength training. Muscle activation can induce analgesia, improving self-efficacy associated with reducing one's own pain. Furthermore, strength training is beneficial for tendon matrix structure, muscle properties and limb biomechanics. However, current tendon rehabilitation may not adequately address the corticospinal control of the muscle, which may result in altered control of muscle recruitment and the consequent tendon load, and this may contribute to recalcitrance or symptom recurrence. Outcomes of interest include the effect of strength training on tendon pain, corticospinal excitability and short interval cortical inhibition. The aims of this concept paper are to: (1) review what is known about changes to the primary motor cortex and motor control in tendinopathy, (2) identify the parameters shown to induce neuroplasticity in strength training and (3) align these principles with tendon rehabilitation loading protocols to introduce a combination approach termed as tendon neuroplastic training. Strength training is a powerful modulator of the central nervous system. In particular, corticospinal inputs are essential for motor unit recruitment and activation; however, specific strength training parameters are important for neuroplasticity. Strength training that is externally paced and akin to a skilled movement task has been shown to not only reduce tendon pain, but modulate excitatory and inhibitory control of the muscle and therefore, potentially tendon load. An improved understanding of the methods that maximise the opportunity for neuroplasticity may be an important progression in how we prescribe exercise-based rehabilitation in tendinopathy for pain modulation and potentially restoration of the corticospinal control of the muscle-tendon complex.
Description:
It is now widely recognised that it is important to involve a full range of stakeholders and other research end-users, from the outset when designing and implementing prevention programmes. As long ago as 2003, my team recognised that the views of those actively involved in sport should also be considered when setting research priorities. Findings from our survey of coaches and sports administrators have since informed the direction of much of our sports injury research over the following decade in community Australian Football. There will be similar examples from other sports, even if they have not been formally documented in the sports medicine literature.
Description:
In this paper, we develop and put into practice an automatic optical inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device, and charge-coupled device cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5 mu m could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole, and the incorrect location of the holes. However, previous work only focuses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes, and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users to analyze the causes of errors and immediately correct the problems. In addition, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1-mm image resolution, which is better than others used in industry. We set a detecting standard based on 2-mm diameter of circles to diagnose the quality of the holes within 10 s.
Description:
In this paper, we develop and put into practice an automatic optical inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device, and charge-coupled device cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5 mu m could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole, and the incorrect location of the holes. However, previous work only focuses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes, and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users to analyze the causes of errors and immediately correct the problems. In addition, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1-mm image resolution, which is better than others used in industry. We set a detecting standard based on 2-mm diameter of circles to diagnose the quality of the holes within 10 s.
Description:
Flexible operation has the potehtial to significantly improve the economic viability of post-combustion CO2 capture (PCC). However, the impact of disturbances from flexible operation of the PCC process is unclear. The purpose of this study was to investigate the effects of flexible operation in a PCC pilot plant by implementing step-changes for improved dynamic data reliability. The flexible operation campaign was conducted at the CSIRO PCC pilot plant at AGL Loy Yang using monoethanolamine (MEA) absorbent. The pilot plant was operated under a broad range of transient conditions (changing flue gas flow, liquid absorbent flow and steam pressure) to capture the dynamics of a PCC process during flexible operation. The study demonstrated that the dynamics of flue gas flow rate was faster than absorbent flow rate. The greatest CO2 removal% was achieved at the lowest flue gas flow rate or at the highest absorbent flow rate; however, the latter provided improved energy efficiency. The steam pressure parameter could adjust the temperature of all columns simultaneously which can be used to compensate for effects from ambient conditions or heat losses. These results verify the technical feasibility of flexible PCC operation and provide a suitable dataset for dynamic model validation. (C) 2015 Elsevier Ltd. All rights reserved.
Description:
Flexible operation has the potehtial to significantly improve the economic viability of post-combustion CO2 capture (PCC). However, the impact of disturbances from flexible operation of the PCC process is unclear. The purpose of this study was to investigate the effects of flexible operation in a PCC pilot plant by implementing step-changes for improved dynamic data reliability. The flexible operation campaign was conducted at the CSIRO PCC pilot plant at AGL Loy Yang using monoethanolamine (MEA) absorbent. The pilot plant was operated under a broad range of transient conditions (changing flue gas flow, liquid absorbent flow and steam pressure) to capture the dynamics of a PCC process during flexible operation. The study demonstrated that the dynamics of flue gas flow rate was faster than absorbent flow rate. The greatest CO2 removal% was achieved at the lowest flue gas flow rate or at the highest absorbent flow rate; however, the latter provided improved energy efficiency. The steam pressure parameter could adjust the temperature of all columns simultaneously which can be used to compensate for effects from ambient conditions or heat losses. These results verify the technical feasibility of flexible PCC operation and provide a suitable dataset for dynamic model validation. (C) 2015 Elsevier Ltd. All rights reserved.
Description:
Despite growing interest over recent years in applying reinforcement learning to multiobjective problems, there has been little research into the applicability and effectiveness of exploration strategies within the multiobjective context. This work considers several widely-used approaches to exploration from the single-objective reinforcement learning literature, and examines their incorporation into multiobjective Q-learning. In particular this paper proposes two novel approaches which extend the softmax operator to work with vector-valued rewards. The performance of these exploration strategies is evaluated across a set of benchmark environments. Issues arising from the multiobjective formulation of these benchmarks which impact on the performance of the exploration strategies are identified. It is shown that of the techniques considered, the combination of the novel softmax–epsilon exploration with optimistic initialisation provides the most effective trade-off between exploration and exploitation.
Description:
Despite growing interest over recent years in applying reinforcement learning to multiobjective problems, there has been little research into the applicability and effectiveness of exploration strategies within the multiobjective context. This work considers several widely-used approaches to exploration from the single-objective reinforcement learning literature, and examines their incorporation into multiobjective Q-learning. In particular this paper proposes two novel approaches which extend the softmax operator to work with vector-valued rewards. The performance of these exploration strategies is evaluated across a set of benchmark environments. Issues arising from the multiobjective formulation of these benchmarks which impact on the performance of the exploration strategies are identified. It is shown that of the techniques considered, the combination of the novel softmax–epsilon exploration with optimistic initialisation provides the most effective trade-off between exploration and exploitation.
Description:
In this paper, the stable trajectory of Logistic Map has been investigated by canonical duality theory from the perspective of global optimization. Numerical result of our method shows that it totally differs from traditional chaotic solution solved by Euler method. In addition, we have applied our method to three well-known standard benchmarks in global optimization. Numerical simulations are given to illustrate the effectiveness of the main results.
Description:
Wireless sensor networks (WSNs) will be an integral part of the future Internet of Things (loT) environment and generate large volumes of data. However, these data would only be of benefit if useful knowledge can be mined from them. A data mining framework for WSNs includes data extraction, storage and mining techniques, and must be efficient and dependable. In this paper, we propose a new type of behavioral pattern mining technique from sensor data called regularly frequent sensor patterns (RFSPs). RFSPs can identify a set of temporally correlated sensors which can reveal significant knowledge from the monitored data. A distributed data extraction model to prepare the data required for mining RFSPs is proposed, as the distributed scheme ensures higher availability through greater redundancy. The tree structure for RFSP is compact requires less memory and can be constructed using only a single scan through the dataset, and the mining technique is efficient with low runtime. Current mining techniques in the literature on sensor data employ a single memory-based sequential approach and hence are not efficient. Moreover, usage of the. MapReduce model for the distributed solution has not been explored extensively. Since MapReduce is becoming the de facto model for computation on large data, we also propose a parallel implementation of the RFSP mining algorithm, called RFSP on Hadoop (RFSP-H), which uses a MapReduce-based framework to gain further efficiency. Experiments conducted to evaluate the compactness and performance of the data extraction model, RFSP-tree and RFSP-H mining show improved results. (C) 2016 Elsevier Inc. All rights reserved.
Description:
The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.
Description:
The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.
Description:
Effects of different boundary conditions prescribed across the boundaries of radiofrequency ablation (RFA) models of liver cancer are investigated for the case where the tumour is at the liver boundary. Ground and Robin-type conditions (electrical field) and body temperature and thermal insulation (thermal field) conditions are examined. 3D models of the human liver based on publicly-available CT images of the liver are developed. An artificial tumour is placed inside the liver at the boundary. Simulations are carried out using the finite element method. The numerical results indicated that different electrical and thermal boundary conditions led to different predictions of the electrical potential, temperature and thermal coagulation distributions. Ground and body temperature conditions presented an unnatural physical conditions around the ablation site, which results in more intense Joule heating and excessive heat loss from the tissue. This led to thermal damage volumes that are smaller than the cases when the Robin type or the thermal insulation conditions are prescribed. The present study suggests that RFA simulations in the future must take into consideration the choice of the type of electrical and thermal boundary conditions to be prescribed in the case where the tumour is located near to the liver boundary.