Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Empirical Bayes method in the study of traffic safety via heterogeneous negative multinomial model

In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

Negative mood, implicit alcohol-related memory, and alcohol use in young adults: The moderating effect of alcohol expectancy

Objective Alcohol-related implicit (preconscious) cognitive processes are established and unique predictors of alcohol use, but most research in this area has focused on alcohol-related implicit cognition and anxiety. This study extends this work into the area of depressed mood by testing a cognitive model that combines traditional explicit (conscious and considered) beliefs, implicit alcohol-related memory associations (AMAs), and self-reported drinking behavior. Method Using a sample of 106 university students, depressed mood was manipulated using a musical mood induction procedure immediately prior to completion of implicit then explicit alcohol-related cognition measures. A bootstrapped two-group (weak/strong expectancies of negative affect and tension reduction) structural equation model was used to examine how mood changes and alcohol-related memory associations varied across groups. Results Expectancies of negative affect moderated the association of depressed mood and AMAs, but there was no such association for tension reduction expectancy. Conclusion Subtle mood changes may unconsciously trigger alcohol-related memories in vulnerable individuals. Results have implications for addressing subtle fluctuations in depressed mood among young adults at risk of alcohol problems.

Countering negative country of origin effects using imagery processing

A favorable product country of origin (e.g., an automobile made in Germany) is often considered an asset by marketers. Yet a challenge in today's competitive environment is how marketers of products from less favorably regarded countries can counter negative country of origin perceptions. Three studies investigate how mental imagery can be used to reduce the effects of negative country of origin stereotypes. Study 1 reveals that participants exposed to country of origin information exhibit automatic stereotype activation. Study 2 shows that self-focused counterstereotypical mental imagery (relative to other-focused mental imagery) significantly inhibits the automatic activation of negative country of origin stereotypes. Study 3 shows that this lessening of automatic negative associations persists when measured one day later. The results offer important implications for marketing theory and practice.

Increased traffic exposure and negative birth outcomes : a prospective cohort in Australia

Background: Pregnant women exposed to traffic pollution have an increased risk of negative birth outcomes. We aimed to investigate the size of this risk using a prospective cohort of 970 mothers and newborns in Logan, Queensland. ----- ----- Methods: We examined two measures of traffic: distance to nearest road and number of roads around the home. To examine the effect of distance we used the number of roads around the home in radii from 50 to 500 metres. We examined three road types: freeways, highways and main roads.----- ----- Results: There were no associations with distance to road. A greater number of freeways and main roads around the home were associated with a shorter gestation time. There were no negative impacts on birth weight, birth length or head circumference after adjusting for gestation. The negative effects on gestation were largely due to main roads within 400 metres of the home. For every 10 extra main roads within 400 metres of the home, gestation time was reduced by 1.1% (95% CI: -1.7, -0.5; p-value = 0.001).----- ----- Conclusions: Our results add weight to the association between exposure to traffic and reduced gestation time. This effect may be due to the chemical toxins in traffic pollutants, or because of disturbed sleep due to traffic noise.

Mining positive and negative patterns for relevance feature discovery

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.

Negative Mood Regulation (NMR) expectancies, mood, and affect intensity among clients in substance disorder treatment facilities

Negative mood regulation (NMR) expectancies, stress, anxiety, depression and affect intensity were examined by means of self-report questionnaires in 158 volunteers, including 99 clients enrolled in addiction treatment programs. As expected, addicts reported significantly higher levels of stress, anxiety, depression and affect intensity and lower levels of NMR compared to non-addict controls. NMR was negatively correlated with stress, anxiety, depression and affect intensity. The findings indicate that mood self-regulation is impaired in addicts. Low NMR and high affect intensity may predispose to substance abuse and addiction, or alternatively may reflect chronic drug-induced affective dysregulation.

Look before you leap : a confidence-based method for selecting species criticality while avoiding negative populations in τ-leaping

The stochastic simulation algorithm was introduced by Gillespie and in a different form by Kurtz. There have been many attempts at accelerating the algorithm without deviating from the behavior of the simulated system. The crux of the explicit τ-leaping procedure is the use of Poisson random variables to approximate the number of occurrences of each type of reaction event during a carefully selected time period, τ. This method is acceptable providing the leap condition, that no propensity function changes “significantly” during any time-step, is met. Using this method there is a possibility that species numbers can, artificially, become negative. Several recent papers have demonstrated methods that avoid this situation. One such method classifies, as critical, those reactions in danger of sending species populations negative. At most, one of these critical reactions is allowed to occur in the next time-step. We argue that the criticality of a reactant species and its dependent reaction channels should be related to the probability of the species number becoming negative. This way only reactions that, if fired, produce a high probability of driving a reactant population negative are labeled critical. The number of firings of more reaction channels can be approximated using Poisson random variables thus speeding up the simulation while maintaining the accuracy. In implementing this revised method of criticality selection we make use of the probability distribution from which the random variable describing the change in species number is drawn. We give several numerical examples to demonstrate the effectiveness of our new method.

Negative affect-induced food intake in non-dieting women is reward driven and associated with restrained-disinhibited eating subtype

In humans the presence of negative affect is thought to promote food intake, but there is widespread variability. Susceptibility to negative affect-induced eating may depend on trait eating behaviours, notably ‘emotional eating’, ‘restrained eating’ and ‘disinhibited eating’, but the evidence is not consistent. In the present study, 30 non-obese, non-dieting women were given access to palatable food whilst in a state of negative or neutral affect, induced by a validated autobiographical recall technique. As predicted, food intake was higher in the presence of negative affect; however, this effect was moderated by the pattern of eating behaviour traits and enhanced wanting for the test food. Specifically, the High Restraint-High Disinhibition subtype in combination with higher scores on emotional eating and food wanting was able to predict negative-affect intake (adjusted R2 = .61). In the absence of stress, individuals who are both restrained and vulnerable to disinhibited eating are particularly susceptible to negative affect food intake via stimulation of food wanting. Identification of traits that predispose individuals to overconsume and a more detailed understanding of the specific behaviours driving such overconsumption may help to optimise strategies to prevent weight gain.

Negative determinant of Hessian features

Local image feature extractors that select local maxima of the determinant of Hessian function have been shown to perform well and are widely used. This paper introduces the negative local minima of the determinant of Hessian function for local feature extraction. The properties and scale-space behaviour of these features are examined and found to be desirable for feature extraction. It is shown how this new feature type can be implemented along with the existing local maxima approach at negligible extra processing cost. Applications to affine covariant feature extraction and sub-pixel precise corner extraction are demonstrated. Experimental results indicate that the new corner detector is more robust to image blur and noise than existing methods. It is also accurate for a broader range of corner geometries. An affine covariant feature extractor is implemented by combining the minima of the determinant of Hessian with existing scale and shape adaptation methods. This extractor can be implemented along side the existing Hessian maxima extractor simply by finding both minima and maxima during the initial extraction stage. The minima features increase the number of correspondences by two to four fold. The additional minima features are very distinct from the maxima features in descriptor space and do not make the matching process more ambiguous.

Feedback information and consumer motivation : the moderation role of positive and negative reference values in self-regulation

Marketers spend considerable resources to motivate people to consume their products and services as a means of goal attainment (Bagozzi and Dholakia, 1999). Why people increase, decrease, or stop consuming some products is based largely on how well they perceive they are doing in pursuit of their goals (Carver and Scheier, 1992). Yet despite the importance for marketers in understanding how current performance influences a consumer’s future efforts, this topic has received little attention in marketing research. Goal researchers generally agree that feedback about how well or how poorly people are doing in achieving their goals affects their motivation (Bandura and Cervone, 1986; Locke and Latham, 1990). Yet there is less agreement about whether positive and negative performance feedback increases or decreases future effort (Locke and Latham, 1990). For instance, while a customer of a gym might cancel his membership after receiving negative feedback about his fitness, the same negative feedback might cause another customer to visit the gym more often to achieve better results. A similar logic can apply to many products and services from the use of cosmetics to investing in mutual funds. The present research offers managers key insights into how to engage customers and keep them motivated. Given that connecting customers with the company is a top research priority for managers (Marketing Science Institute, 2006), this article provides suggestions for performance metrics including four questions that managers can use to apply the findings.

The subjective experience of negative symptoms : characteristics of emotional withdrawal

According to the diagnosis of schizophrenia in the DSM-IV-TR (American Psychiatric Association, 2000), negative symptoms are those personal characteristics that are thought to be reduced from normal functioning, while positive symptoms are aspects of functioning that exist as an excess or distortion of normal functioning. Negative symptoms are generally considered to be a core feature of people diagnosed with schizophrenia. However, negative symptoms are not always present in those diagnosed, and a diagnosis can be made with only negative or only positive symptoms, or with a combination of both. Negative symptoms include an observed loss of emotional expression (affective flattening), loss of motivation or self directedness (avolition), loss of speech (alogia), and also a loss of interests and pleasures (anhedonia). Positive symptoms include the perception of things that others do not perceive (hallucinations), and extraordinary explanations for ordinary events (delusions) (American Psychiatric Association, 2000). Both negative and positive symptoms are derived from watching the patient and thus do not consider the patient’s subjective experience. However, aspects of negative symptoms, such as observed affective flattening are highly contended. Within conventional psychiatry, the absence of emotional expression is assumed to coincide with an absence of emotional experience. Contrasting research findings suggests that patients who were observed to score low on displayed emotional expression, scored high on self ratings of emotional experience. Patients were also observed to be significantly lower on emotional expression when compared with others (Aghevli, Blanchard, & Horan, 2003; Selton, van der Bosch, & Sijben, 1998). It appears that there is little correlation between emotional experience and emotional expression in patients, and that observer ratings cannot help us to understand the subjective experience of the negative symptoms. This chapter will focus on research into the subjective experiences of negative symptoms. A framework for these experiences will be used from the qualitative research findings of the primary author (Le Lievre, 2010). In this study, the primary author found that subjective experiences of the negative symptoms belonged to one of the two phases of the illness experience; “transitioning into emotional shutdown” or “recovering from emotional shutdown”. This chapter will use the six themes from the phase of “transitioning into emotional shutdown”. This phase described the experience of turning the focus of attention away from the world and onto the self and the past, thus losing contact with the world and others (emotional shutdown). Transitioning into emotional shutdown involved; “not being acknowledged”, “relational confusion”, “not being expressive”, “reliving the past”, “detachment”, and “no sense of direction” (Le Lievre, 2010). Detail will be added to this framework of experience from other qualitative research in this area. We will now review the six themes that constitute a “transition into emotional shutdown” and corresponding previous research findings.

Comparative study of coagulase negative Staphylococci (CoNS) from clinical isolates, skin and nasal sources

Staphylococci are important pathogenic bacteria responsible for a range of diseases in humans. The most frequently isolated microorganisms in a hospital microbiology laboratory are staphylococci. The general classification of staphylococci divides them into two major groups; Coagulase-positive staphylococci (e.g. Staphylococcus aureus) and Coagulase-negative staphylococci (e.g. Staphylococcus epidermidis). Coagulase-negative staphylococcal (CoNS) isolates include a variety of species and many different strains but are often dominated by the most important organism of this group, S. epidermidis. Currently, these organisms are regarded as important pathogenic organisms causing infections related to prosthetic materials and surgical wounds. A significant number of S. epidermidis isolates are also resistant to different antimicrobial agents. Virulence factors in CoNS are not very clearly established and not well documented. S. epidermidis is evolving as a resistant and powerful microbe related to nosocomial infections because it has different properties which independently, and in combination, make it a successful infectious agent, especially in the hospital environment. Such characteristics include biofilm formation, drug resistance and the evolution of genetic variables. The purpose of this project was to develop a novel SNP genotyping method to genotype S. epidermidis strains originating from hospital patients and healthy individuals. High-Resolution Melt Analysis was used to assign binary typing profiles to both clinical and commensal strains using a new bioinformatics approach. The presence of antibiotic resistance genes and biofilm coding genes were also interrogated in these isolates.