Description:
A discrete version of state transition algorithm is proposed to solve the traveling salesman problem. Three special operators named swap, shift and symmetry transformations are presented for discrete optimization problem. Convergence analysis and time complexity of the algorithm are also considered. To make the algorithm efficient, a parametric study is investigated. Experiments are carried out to test its performance, and comparisons with simulated annealing and ant colony optimization have demonstrated the effectiveness of the proposed algorithm. The results also show that the discrete state transition algorithm consumes much less time and has better search ability than other traditional combinatorial optimization methods, indicating that state transition algorithm has strong adaptability.
Description:
In this paper, we propose a new type of adaptive fuzzy inference system with a view to achieve improved performance for forecasting nonlinear time series data by dynamically adapting the fuzzy rules with arrival of new data. The structure of the fuzzy model utilized in the proposed system is developed based on the log-likelihood value of each data vector generated by a trained Hidden Markov Model. As part of its adaptation process, our system checks and computes the parameter values and generates new fuzzy rules as required, in response to new observations for obtaining better performance. In addition, it can also identify the most appropriate fuzzy rule in the system that covers the new data; and thus requires to adapt the parameters of the corresponding rule only, while keeping the rest of the model unchanged. This intelligent adaptive behavior enables our adaptive fuzzy inference system (FIS) to outperform standard FISs. We evaluate the performance of the proposed approach for forecasting stock price indices. The experimental results demonstrate that our approach can predict a number of stock indices, e.g., Dow Jones Industrial (DJI) index, NASDAQ index, Standard and Poor500 (S&P500) index and few other indices from UK (FTSE100), Germany (DAX) , Australia (AORD) and Japan (NIKKEI) stock markets, accurately compared with other existing computational and statistical methods.
Description:
Wetland managers are faced with an array of challenges when restoring ecosystems at risk from changing climate and human impacts, especially as many of these processes have been operating over decadal-millennial timescales. Variations in the level and salinity of the large crater lakes of western Victoria, as revealed over millennia by the physical, chemical and biological evidence archived in sediments, attest to extended periods of positive rainfall balance and others of rainfall deficit. The recent declines in the depth of these lakes have been attributed to a 15% decline in effective rainfall since AD 1859. Whilst some sites reveal state shifts following past droughts, the response of most wetlands to millennial-scale climatic variations is muted. Regional wetland condition has changed comprehensively, however, since European settlement, on account of extensive catchment modifications. These modifications appear to have reduced the resilience of wetlands limiting their capacity to recover from the recent 'big dry'. These sedimentary archives reveal most modern wetlands to be outside their historical range of variability. This approach provides a longer-term context when assessing wetland condition and better establishes the restoration challenge posed by the impact of climate change and variability and human impacts.
Description:
Background The over consumption of fossil fuels has led to growing concerns over climate change and global warming. Increasing research activities have been carried out towards alternative viable biofuel sources. Of several different biofuel platforms, cyanobacteria possess great potential, for their ability to accumulate biomass tens of times faster than traditional oilseed crops. The cyanobacterium Cyanothece sp. ATCC 51142 has recently attracted lots of research interest as a model organism for such research. Cyanothece can perform efficiently both photosynthesis and nitrogen fixation within the same cell, and has been recently shown to produce biohydrogen--a byproduct of nitrogen fixation--at very high rates of several folds higher than previously described hydrogen-producing photosynthetic microbes. Since the key enzyme for nitrogen fixation is very sensitive to oxygen produced by photosynthesis, Cyanothece employs a sophisticated temporal separation scheme, where nitrogen fixation occurs at night and photosynthesis at day. At the core of this temporal separation scheme is a robust clocking mechanism, which so far has not been thoroughly studied. Understanding how this circadian clock interacts with and harmonizes global transcription of key cellular processes is one of the keys to realize the inherent potential of this organism. Results In this paper, we employ several state of the art bioinformatics techniques for studying the core circadian clock in Cyanothece sp. ATCC 51142, and its interactions with other key cellular processes. We employ comparative genomics techniques to map the circadian clock genes and genetic interactions from another cyanobacterial species, namely Synechococcus elongatus PCC 7942, of which the circadian clock has been much more thoroughly investigated. Using time series gene expression data for Cyanothece, we employ gene regulatory network reconstruction techniques to learn this network de novo, and compare the reconstructed network against the interactions currently reported in the literature. Next, we build a computational model of the interactions between the core clock and other cellular processes, and show how this model can predict the behaviour of the system under changing environmental conditions. The constructed models significantly advance our understanding of the Cyanothece circadian clock functional mechanisms.
Description:
Background The over consumption of fossil fuels has led to growing concerns over climate change and global warming. Increasing research activities have been carried out towards alternative viable biofuel sources. Of several different biofuel platforms, cyanobacteria possess great potential, for their ability to accumulate biomass tens of times faster than traditional oilseed crops. The cyanobacterium Cyanothece sp. ATCC 51142 has recently attracted lots of research interest as a model organism for such research. Cyanothece can perform efficiently both photosynthesis and nitrogen fixation within the same cell, and has been recently shown to produce biohydrogen--a byproduct of nitrogen fixation--at very high rates of several folds higher than previously described hydrogen-producing photosynthetic microbes. Since the key enzyme for nitrogen fixation is very sensitive to oxygen produced by photosynthesis, Cyanothece employs a sophisticated temporal separation scheme, where nitrogen fixation occurs at night and photosynthesis at day. At the core of this temporal separation scheme is a robust clocking mechanism, which so far has not been thoroughly studied. Understanding how this circadian clock interacts with and harmonizes global transcription of key cellular processes is one of the keys to realize the inherent potential of this organism. Results In this paper, we employ several state of the art bioinformatics techniques for studying the core circadian clock in Cyanothece sp. ATCC 51142, and its interactions with other key cellular processes. We employ comparative genomics techniques to map the circadian clock genes and genetic interactions from another cyanobacterial species, namely Synechococcus elongatus PCC 7942, of which the circadian clock has been much more thoroughly investigated. Using time series gene expression data for Cyanothece, we employ gene regulatory network reconstruction techniques to learn this network de novo, and compare the reconstructed network against the interactions currently reported in the literature. Next, we build a computational model of the interactions between the core clock and other cellular processes, and show how this model can predict the behaviour of the system under changing environmental conditions. The constructed models significantly advance our understanding of the Cyanothece circadian clock functional mechanisms.
Description:
Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.
Description:
Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.
Description:
Genetically hypertensive mice (BPH/2J) are hypertensive because of an exaggerated contribution of the sympathetic nervous system to blood pressure. We hypothesize that an additional contribution to elevated blood pressure is via sympathetically mediated activation of the intrarenal renin-angiotensin system. Our aim was to determine the contribution of the renin-angiotensin system and sympathetic nervous system to hypertension in BPH/2J mice. BPH/2J and normotensive BPN/3J mice were preimplanted with radiotelemetry devices to measure blood pressure. Depressor responses to ganglion blocker pentolinium (5 mg/kg i.p.) in mice pretreated with the angiotensin-converting enzyme inhibitor enalaprilat (1.5 mg/kg i.p.) revealed a 2-fold greater sympathetic contribution to blood pressure in BPH/2J mice during the active and inactive period. However, the depressor response to enalaprilat was 4-fold greater in BPH/2J compared with BPN/3J mice, but only during the active period (P=0.01). This was associated with 1.6-fold higher renal renin messenger RNA (mRNA; P=0.02) and 0.8-fold lower abundance of micro-RNA-181a (P=0.03), identified previously as regulating human renin mRNA. Renin mRNA levels correlated positively with depressor responses to pentolinium (r=0.99; P=0.001), and BPH/2J mice had greater renal sympathetic innervation density as identified by tyrosine hydroxylase staining of cortical tubules. Although there is a major sympathetic contribution to hypertension in BPH/2J mice, the renin-angiotensin system also contributes, doing so to a greater extent during the active period and less during the inactive period. This is the opposite of the normal renin-angiotensin system circadian pattern. We suggest that renal hyperinnervation and enhanced sympathetically induced renin synthesis mediated by lower micro-RNA-181a contributes to hypertension in BPH/2J mice.
Description:
The authors have previously proposed a solution to the twin problems of wheel scuffing and off-tracking of B-double truck–trailer vehicles thereby reducing tyre wear and environmental damage as well as improving maneuverability. The solution to the scuffing problem requires that trailer axles in excess of one per trailer must have steerable wheels. However, if all trailer wheels are steerable, then the off-tracking problem can also be solved. The previous work devised an algorithm for a B-double in forward motion, whereby an on-board computer would be used to calculate the correct wheel and hitch angles and a control system would implement these angles. The purpose of the present technical note is to complete the study of a numerical algorithm for navigating a B-double truck–trailer vehicle by considering travel in the reverse direction. In this case the angle of the front wheels of the truck must also be controlled by the on-board computer. The algorithm for determining the effective angle of the truck’s steerable wheels is derived using an innovative combination of vector geometry and calculus and completes the total control system for these B-double vehicles. The paper concludes with a simulation study of the control algorithm demonstrating its versatility for reversing along twisting paths and effectiveness in reducing off-tracking.
Description:
The authors have previously proposed a solution to the twin problems of wheel scuffing and off-tracking of B-double truck–trailer vehicles thereby reducing tyre wear and environmental damage as well as improving maneuverability. The solution to the scuffing problem requires that trailer axles in excess of one per trailer must have steerable wheels. However, if all trailer wheels are steerable, then the off-tracking problem can also be solved. The previous work devised an algorithm for a B-double in forward motion, whereby an on-board computer would be used to calculate the correct wheel and hitch angles and a control system would implement these angles. The purpose of the present technical note is to complete the study of a numerical algorithm for navigating a B-double truck–trailer vehicle by considering travel in the reverse direction. In this case the angle of the front wheels of the truck must also be controlled by the on-board computer. The algorithm for determining the effective angle of the truck’s steerable wheels is derived using an innovative combination of vector geometry and calculus and completes the total control system for these B-double vehicles. The paper concludes with a simulation study of the control algorithm demonstrating its versatility for reversing along twisting paths and effectiveness in reducing off-tracking.
Description:
Objective: To investigate changes in mental health and other needs, as well as clinical and diagnostic 'caseness', in a sample of adolescents over a 6-month period following entry into a Young Offenders Institution in the UK. Design: Prospective cohort study. Setting: One Young Offenders Institution between November 2006 and August 2009. Participants: 219 male adolescents aged 15-18 years (M=16.56; SD=0.6) were assessed at baseline (median=4; range 0-26 days following reception into custody) on the Salford Needs Assessment Schedule for Adolescents (SNASA) and Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS). Participants were then reassessed at 3-month and 6-month postbaseline to document any change in mental health. Results: Of the initial baseline sample, 132 were still in the study at 3-month postbaseline and 63 were still available for assessment at 6 months. There were no differences between those who were not available for assessment at the three key stages in terms of demographic and criminological data. Over time there was a general improvement in mental health. While the proportion of participants with a mental health need (SNASA) did not change over time, symptom severity as measured by the SNASA did reduce significantly. When we assessed diagnostic 'caseness' using the K-SADS, three young people showed significant mental health deterioration. Conclusions: In line with previous studies, we found that symptoms in prison generally improved over time. Prison may provide an opportunity for young people previously leading chaotic lifestyles to settle into a stable routine and engage with services; however, it is unclear if these would be maintained either within the prison or on release into the community.
Description:
Culturally and linguistically diverse (CALD) migrants face significant health risks as they adapt to new cultures. These risks are exacerbated by their limited participation in preventative behaviours such as sports and physical activity. The review aimed to identify studies that examined the correlates of sport and physical activity participation in migrants. The systematic review identified 72 papers, including 6 interventions, 18 qualitative and 48 quantitative studies. The 44 identified correlates highlight the complexities involved in working with migrants. The correlates were grouped in four themes using the social ecological model; acculturation, demographic, psychosocial and environmental/organisational. The social ecological model identified general correlates such as social support and safety. However, there were unique correlates relating to individuals who are facing cultural changes such as acculturation and language. Overall, there is a lack of contextualisation of CALD migrants' sport and physical activity experiences because many studies fail to consider acculturation comprehensively.
Description:
Culturally and linguistically diverse (CALD) migrants face significant health risks as they adapt to new cultures. These risks are exacerbated by their limited participation in preventative behaviours such as sports and physical activity. The review aimed to identify studies that examined the correlates of sport and physical activity participation in migrants. The systematic review identified 72 papers, including 6 interventions, 18 qualitative and 48 quantitative studies. The 44 identified correlates highlight the complexities involved in working with migrants. The correlates were grouped in four themes using the social ecological model; acculturation, demographic, psychosocial and environmental/organisational. The social ecological model identified general correlates such as social support and safety. However, there were unique correlates relating to individuals who are facing cultural changes such as acculturation and language. Overall, there is a lack of contextualisation of CALD migrants' sport and physical activity experiences because many studies fail to consider acculturation comprehensively.
A systematic review of the psychological and social benefits of participation in sport for adults : Informing development of a conceptual model of health through sport
A systematic review of the psychological and social benefits of participation in sport for children and adolescents: Informing development of a conceptual model of health through sport