Sustainability in road transport : an integrated life cycle analysis for estimating emissions

Despite of a significant contribution of transport sector in the global economy and society, it is one of the largest sources of global energy consumption, green house gas emissions and environmental pollutions. A complete look onto the whole life cycle environmental inventory of this sector will be helpful to generate a holistic understanding of contributory factors causing emissions. Previous studies were mainly based on segmental views which mostly compare environmental impacts of different modes of transport, but very few consider impacts other than the operational phase. Ignoring the impacts of non-operational phases, e.g., manufacture, construction, maintenance, may not accurately reflect total contributions on emissions. Moreover an integrated study for all motorized modes of road transport is also needed to achieve a holistic estimation. The objective of this study is to develop a component based life cycle inventory model which considers impacts of both operational and non-operational phases of the whole life as well as different transport modes. In particular, the whole life cycle of road transport has been segmented into vehicle, infrastructure, fuel and operational components and inventories have been conducted on each component. The inventory model has been demonstrated using the road transport of Singapore. Results show that total life cycle green house gas emissions from the road transport sector of Singapore is 7.8 million tons per year, among which operational phase and non-operational phases contribute about 55% and about 45%, respectively. Total amount of criteria air pollutants are 46, 8.5, 33.6, 13.6 and 2.6 thousand tons per year for CO, SO2, NOx, VOC and PM10, respectively. From the findings, it can be deduced that stringent government policies on emission control measures have a significant impact on reducing environmental pollutions. In combating global warming and environmental pollutions the promotion of public transport over private modes is an effective sustainable policy.

Behavioural changes add validity to the construct of posttraumatic growth

The research aimed to identify positive behavioural changes that people may make as a result of negotiating the aftermath of a traumatic experience, thereby extending the current cognitive model of posttraumatic growth (PTG). It was hypothesised that significant others would corroborate survivor’s cognitive and behavioural reports of PTG. The sample comprised 176 participants; 88 trauma survivors and 88 significant others. University students accounted for 64% of the sample and 36% were from the broader community. Approximately one third were male. All participants completed the Posttraumatic Growth Inventory [PTGI] and open ended questions regarding behavioural changes. PTGI scores in the survivor sample were corroborated by the significant others with only the Appreciation of Life factor of the PTGI differing between the two groups (e.g., total PTGI scores between groups explained 33.64% of variance). Nearly all of the survivors also reported positive changes in their behaviour and these changes were also corroborated by the significant others. Results provide validation of the posttraumatic growth construct and the PTGI as an instrument of measurement. Findings may also influence therapeutic practice for example, the potential usefulness of corroborating others.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Impact of physical, psychological, and sexual violence on social adjustment of school children in India

and sexual violence on the social adjustment of Grade 8 and 9 school children in the state of Tripura, India. The study participants, 160 boys and 160 girls, were randomly selected from classes in eight English and Bengali medium schools in Agartala city, Tripura. Data were collected using a self-administered Semi-structured Questionnaire for Children/Students and a Social Adjustment Inventory which were custom-made for the study based on measures in the extant research adapted for the Indian context. Findings revealed that students experienced physical (21.9%), psychological (20.9%), and sexual (18.1%) violence at home, and 29.7% of the children had witnessed family violence. Boys were more often victims of physical and psychological violence while girls were more often victims of sexual violence. The social adjustment scores of school children who experienced violence, regardless of the nature of the violence, was significantly lower when compared with scores of those who had not experienced violence (p<0.001). Social adjustment was poorer for girls than boys (p<0.001). The study speaks in favour of early detection and intervention for all child maltreatment subtypes and for children exposed to interparental violence, and highlights the crucial role of schools and school psychology in addressing the problem.

Personality and player types in Fallout New Vegas

The aim of this study was to explore the relationship between personality and videogame player types. Study participants completed an online survey that gathered information regarding the individual's personality, via the Big Five Inventory, and player types. The study was focused on understanding this relationship in the context of the action role-playing videogame, Fallout New Vegas (FNV). A relationship between personality and player type was found, specifically with respect to the personality traits of openness to experience and conscientiousness.

Simulation-based comparison of pull-push system in motorcycle assembly line

To investigate the effects of adopting a pull system in assembly lines in contrast to a push system, simulation software called “ARENA” is used as a tool in order to present numerical results from both systems. Simulation scenarios are created to evaluate the effects of attributes changing in assembly systems, with influential factors including the change of manufacturing system (push system to pull system) and variation of demand. Moreover, pull system manufacturing consists of the addition attribute, which is the number of buffer storage. This paper will provide an analysis based on a previous case study, hence process time and workflow refer to the journal name “Optimising and simulating the assembly line balancing problem in a motorcycle manufacturing company: a case study” [2]. The implementation of the pull system mechanism is to produce a system improvement in terms of the number of Work-In-Process (WIP), total time of products in the system, and the number of finished product inventory, while retaining the same throughput.

Learning processes in creative industries initiatives in developing countries : an examination of policy and practice

What does a dance group in Benin that mixes contemporary and ethnic dancing have in common with Mongolian felt producers that want to enter the design market in Europe? These are both examples of learning processes in Creative Industries initiatives in developing countries. Following the concept of sustainable development, I argue that the challenge for developing countries in contemporary society is to meet the very real need of people for economic development and opportunities for income generation, while at the same time avoiding unintended and unwanted consequences of economic development and globalisation. The concept of the Creative Industries may be a way to promote a development that is sustainable and avoids social exclusion of groups-at-risk. In line with this, I argue that the Creative Industries sector could, in fact, link economic development and the continuation and evolution of local traditions and cultural heritage. A pressing question then is: how can education and learning contribute to creating a context in which talent can flourish? This study aims to provide a comprehensive analysis of the research problem of this thesis: what elements are conducive for individual learning processes in creative development initiatives? In this, I argue that it is crucial to determine what ingredients and characteristics contribute to making these initiatives successful, that is, to meet their specific goals, in a developing context. This is explored through a staged analysis: an overview of quantitative data, an inventory and comparative case studies and, finally, the description and analysis of two in-depth case studies – felt design in Mongolia (Asia) and dance in Benin (Africa), in which I was an observer of the action phase of the local interventions. The analysis culminates in practice-related outcomes related to the operation of creative development initiatives, as well as the contribution to the academic debate on issues like the cultural gap between developed and developing countries, transformative learning and the connection of learning spaces.

NOS1AP is associated with increased severity of PTSD and depression in untreated combat veterans

Background Post traumatic stress disorder (PTSD) and depressive disorder are over represented in combat veterans. Veterans with both disorders have an increased risk of suicide. The nitric oxide synthase 1 adaptor protein (NOS1AP) gene, which modulates stress-evoked N-methyl-D-aspartate (NMDA) activity, was investigated in combat veterans. Methods A comprehensive genetic analysis of NOS1AP and its association with PTSD was investigated in Vietnam combat veterans with PTSD (n=121) and a group of healthy control individuals (n=237). PTSD patients were assessed for symptom severity and level of depression using the Mississippi Scale for Combat-Related PTSD and the Beck Depression Inventory-II (BDI). Results The G allele of NOS1AP SNP rs386231 was significantly associated with PTSD (p = 0.002). Analysis of variance revealed significant differences in BDI-II and Mississippi scores between genotypes for rs386231 with the GG genotype associated with increased severity of depression (p = 0.002 F = 6.839) and higher Mississippi Scale for Combat-Related PTSD scores (p = 0.033). Haplotype analysis revealed that the C/G haplotype (rs451275/rs386231) was significantly associated with PTSD (p = 0.001). Limitations The sample sizes in our study were not sufficient to detect SNP associations with very small effects. In addition the study was limited by its cross sectional design. Conclusions This is the first study reporting that a variant of the NOS1AP gene is associated with PTSD. Our data also suggest that a genetic variant in NOS1AP may increase the susceptibility to severe depression in patients with PTSD and increased risk for suicide.

Prevalence of malnutrition in community-dwelling adults with Parkinson's disease

People with Parkinson’s disease (PD) have been reported to be at higher risk of malnutrition than an age-matched population due to PD motor and non-motor symptoms and pharmacotherapy side effects. The prevalence of malnutrition in PD has yet to be well-defined. Community-dwelling people with PD, aged > 18 years, were recruited (n = 97, 61 M, 36 F). The Patient-Generated Subjective Global Assessment (PGSGA) was used to assess nutritional status, the Parkinson’s Disease Questionnaire (PDQ-39) was used to assess quality of life, and the Beck’s Depression Inventory (BDI) was used to measure depression. Levodopa equivalent doses (LEDs) were calculated based on reported Parkinson’s disease medication. Weight, height, mid-arm circumference (MAC) and calf circumference were measured. Cognitive function was measured using the Addenbrooke’s Cognitive Examination. Average age was 70.0 (9.1, 35–92) years. Based on SGA, 16 (16.5%) were moderately malnourished (SGA B) while none were severely malnourished (SGA C). The well-nourished participants (SGA A) had a better quality of life, t(90) = −2.28, p < 0.05, and reported less depressive symptoms, t(94)= −2.68, p < 0.05 than malnourished participants. Age, years since diagnosis, cognitive function and LEDs did not signifi cantly differ between the groups. The well-nourished participants had lower PG-SGA scores, t(95) = −5.66, p = 0.00, higher BMIs, t(95) = 3.44, p < 0.05, larger MACs, t(95) = 3.54, p < 0.05 and larger calf circumferences, t(95) = 2.29, p < 0.05 than malnourished participants. Prevalence of malnutrition in community-dwelling adults with PD in this study is comparable to that in other studies with community-dwelling adults without PD and is higher than other PD studies where a nutritional status assessment tool was used. Further research is required to understand the primary risk factors for malnutrition in this group.

Risk factors for malnutrition in community-dwelling people with Parkinson’s disease

In the elderly, the risks for protein-energy malnutrition from older age, dementia, depression and living alone have been well-documented. Other risk factors including anorexia, gastrointestinal dysfunction, loss of olfactory and taste senses and early satiety have also been suggested to contribute to poor nutritional status. In Parkinson’s disease (PD), it has been suggested that the disease symptoms may predispose people with PD to malnutrition. However, the risks for malnutrition in this population are not well-understood. The current study’s aim was to determine malnutrition risk factors in community-dwelling adults with PD. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA). Data about age, time since diagnosis, medications and living situation were collected. Levodopa equivalent doses (LDED) and LDED per kg body weight (mg/kg) were calculated. Depression and anxiety were measured using the Beck’s Depression Inventory (BDI) and Spielberger Trait Anxiety questionnaire, respectively. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination (ACE-R). Non-motor symptoms were assessed using the Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) and Modified Constipation Assessment Scale (MCAS). A total of 125 community-dwelling people with PD were included, average age of 70.2±9.3(35-92) years and average time since diagnosis of 7.3±5.9(0–31) years. Average body mass index (BMI) was 26.0±5.5kg/m2. Of these, 15% (n=19) were malnourished (SGA-B). Multivariate logistic regression analysis revealed that older age (OR=1.16, CI=1.02-1.31), more depressive symptoms (OR=1.26, CI=1.07-1.48), lower levels of anxiety (OR=.90, CI=.82-.99), and higher LDED per kg body weight (OR=1.57, CI=1.14-2.15) significantly increased malnutrition risk. Cognitive function, living situation, number of prescription medications, LDED, years since diagnosis and the severity of non-motor symptoms did not significantly influence malnutrition risk. Malnutrition results in poorer health outcomes. Proactively addressing the risk factors can help prevent declines in nutritional status. In the current study, older people with PD with depression and greater amounts of levodopa per body weight were at increased malnutrition risk.

The impact of anxiety on processing efficiency : implications for the attentional control theory

The Attentional Control Theory (ACT) proposes that high-anxious individuals maintain performance effectiveness (accuracy) at the expense of processing efficiency (response time), in particular, the two central executive functions of inhibition and shifting. In contrast, research has generally failed to consider the third executive function which relates to the function of updating. In the current study, seventy-five participants completed the Parametric Go/No-Go and n-back tasks, as well as the State-Trait Anxiety Inventory in order to explore the effects of anxiety on attention. Results indicated that anxiety lead to decay in processing efficiency, but not in performance effectiveness, across all three Central Executive functions (inhibition, set-shifting and updating). Interestingly, participants with high levels of trait anxiety also exhibited impaired performance effectiveness on the n-back task designed to measure the updating function. Findings are discussed in relation to developing a new model of ACT that also includes the role of preattentive processes and dual-task coordination when exploring the effects of anxiety on task performance.

Parental bonding, family systems, and environmental predictors of adolescent homelessness

A multicausal model of adolescent homelessness is proposed, based upon the notion that homeless youth suffer from emotional, social, and cultural deprivation. The model was tested in a sample of homeless adolescents (n = 54) and a similar, but not homeless, control group (n = 58). Emotional deprivation was assessed on the Parental Bonding Inventory (Parker, Tupling,&Brown, 1979), whereas social and cultural deprivation were assessed on the Family Environment Scale (Moos&Moos, 1981). The homeless adolescents were found to be significantly more deprived emotionally, socially, and culturally than the controls. The results indicate support for a deprivation model of adolescent homelessness with implications for public policy and intervention planning.

Discrimination experienced by HIV/AIDS infected persons and its associations with mental health in an Indian sample

Purpose The purpose of this study was to investigate the nature and prevalence of discrimination against people living with HIV/AIDS in West Bengal, India, and how discrimination is associated with depression, suicidal ideation and suicidal attempts. Method Semi-structured interviews and the Beck Depression Inventory were administered to 105 HIV infected persons recruited by incidental sampling, at an Integrated Counseling and Testing Center (ICTC) and through Networks of People Living with HIV/AIDS, in the West Bengal area. Results Findings showed that 40.8% of the sample has experienced discrimination at least in one social setting – such as family (29.1%), health centers (18.4%), community (17.5%) and workplace (6.8%). About two-fifths (40.8%) reported experiencing discrimination in multiple social settings. Demographic factors associated with discrimination were gender, age, occupation, education, and current residence. More than half of the sample was suffering from severe depression while 8.7% had attempted suicide. Discrimination in most areas was significantly associated with suicidal ideation and suicidal attempts. Conclusions Prevalence of discrimination associated with HIV/AIDS is high in our sample from West Bengal. While discrimination was not associated with depressive symptomatology, discrimination was associated with suicidal ideation and attempts. These findings suggest that there is an urgent need for interventions to reduce discrimination of HIV/AIDS in the West Bengal region.

When does change begin following screening and brief intervention among depressed problem drinkers?

Brief interventions are effective for problem drinking and reductions are known to occur in association with screening and assessment. The present study sought to assess, among participants (N=202) in a clinical trial, how much change occurred between baseline assessment and a one-session brief intervention (S1), and the predictors of early change. The primary focus was on changes in the Beck Depression Inventory Fast Screen scores and alcohol consumption (standard drinks per week) prior to random allocation to nine further sessions addressing either depression, alcohol, or both problems. There were large and clinically significant reductions between baseline and S1, with the strongest predictors being baseline scores in the relevant domain and change in the other domain. Client engagement was also predictive of early depression changes. Monitoring progress in both domains from first contact, and provision of empathic care, followed by brief intervention appear to be useful for this high prevalence comorbidity.

Utility of the Mild Brain Injury Atypical Symptoms Scale to detect symptom exaggeration : an analogue simulation study

Brief self-report symptom checklists are often used to screen for postconcussional disorder (PCD) and posttraumatic stress disorder (PTSD) and are highly susceptible to symptom exaggeration. This study examined the utility of the five-item Mild Brain Injury Atypical Symptoms Scale (mBIAS) designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist–Civilian (PCL–C). Participants were 85 Australian undergraduate students who completed a battery of self-report measures under one of three experimental conditions: control (i.e., honest responding, n = 24), feign PCD (n = 29), and feign PTSD (n = 32). Measures were the mBIAS, NSI, PCL–C, Minnesota Multiphasic Personality Inventory–2, Restructured Form (MMPI–2–RF), and the Structured Inventory of Malingered Symptomatology (SIMS). Participants instructed to feign PTSD and PCD had significantly higher scores on the mBIAS, NSI, PCL–C, and MMPI–2–RF than did controls. Few differences were found between the feign PCD and feign PTSD groups, with the exception of scores on the NSI (feign PCD > feign PTSD) and PCL–C (feign PTSD > feign PCD). Optimal cutoff scores on the mBIAS of ≥8 and ≥6 were found to reflect “probable exaggeration” (sensitivity = .34; specificity = 1.0; positive predictive power, PPP = 1.0; negative predictive power, NPP = .74) and “possible exaggeration” (sensitivity = .72; specificity = .88; PPP = .76; NPP = .85), respectively. Findings provide preliminary support for the use of the mBIAS as a tool to detect symptom exaggeration when administering the NSI and PCL–C.