Identification, distribution, and probability of infection in sympatric gastropods by digenean parasites at Pa-hay-okee, Everglades National Park using molecules and morphology

In this study, I determined the identity, taxonomic placement, and distribution of digenetic trematodes parasitizing the snails Pomacea paludosa and Planorbella duryi at Pa-hay-okee, Everglades National Park. I also characterized temporal and geographic variation in the probability of parasite infection for these snails based on two years of sampling. Although studies indicate that digenean parasites may have important effects both on individual species and the structure of communities, there have been no studies of digenean parasitism on snails within the Everglades ecosystem. For example, the endangered Everglade Snail Kite, a specialist that feeds almost exclusively on Pomacea paludosa, and is known to be a definitive host of digenean parasites, may suffer direct and indirect effects from consumption of parasitized apple snails. Therefore, information on the diversity and abundance of parasites harbored in snail populations in the Everglades should be of considerable interest for management and conservation of wildlife. Juvenile digeneans (cercariae) representing 20 species were isolated from these two snails, representing a quadrupling of the number of species known. Species were characterized based on morphological, morphometric, and sequence data (18S rDNA, COI, and ITS). Species richness of shed cercariae from P. duryi was greater than P. paludosa, with 13 and 7 species respectively. These species represented 14 families. P. paludosa and P. duryi had no digenean species in common. Probability of digenean infection was higher for P. duryi than P. paludosa and adults showed a greater risk of infection than juveniles for both of these snails. Planorbella duryi showed variation in probability of infection between sampling sites and hydrological seasons. The number of unique combinations of multi-species infections was greatest among P. duryi individuals, while the overall percentage of multi-species infections was greatest in P. paludosa. Analyses of six frequently-observed multiple infections from P. duryi suggest the presence of negative interactions, positive interactions, and neutral associations between larval digeneans. These results should contribute to an understanding of the factors controlling the abundance and distribution of key species in the Everglades ecosystem and may in particular help in the management and recovery planning for the Everglade Snail Kite.

Think before you eat: Calories and exercise equivalents presented on menus at point-of-choice

Although calorie information at the point-of-purchase at fast food restaurants is proposed as a method to decrease calorie choices and combat obesity, research results have been mixed. Much of the supportive research has weak methodology, and is limited. There is a demonstrated need to develop better techniques to assist consumers to make lower calorie food choices. Eating at fast food restaurants has been positively associated with weight gain. The current study explored the possibility of adding exercise equivalents (EE) (physical activity required to burn off the calories in the food), along with calorie information as a possible way to facilitate lower calorie choice at the point-of-choice in fast food restaurants. This three-group experimental study, in 18-34 year old, overweight and obese women, examines whether presenting caloric information in the form of EE at the point-of-choice at fast food restaurants, will lead to lower calorie food choices compared to presenting simple caloric information or no information at all. Methods. A randomized repeated measures experiment was conducted. Participants ordered a fast food meal from Burger King with menus that contained only the names of the food choices (Lunch 1). One week later (Lunch 2), study participants were given one of three menus that varied: no information, calorie information, or calorie information and EE. Study participants included 62 college aged students. Additionally, the study controlled for dietary restraint by blocking participants, before randomization, to the three groups. Results. A repeated measures analysis of variance was conducted. The study was not sufficiently powered, and while the study was designed to determine large effect sizes, a small effect size of .026, was determined. No significant differences were found in the foods ordered among the various menu conditions. Conclusion. Menu labeling alone might not be enough to reduce calories at the point-of-choice at restaurants. Additional research is necessary to determine if calorie information and EE at the point-of-choice would lead to fewer calories chosen at a meal. Studies should also look at long-term, repeated exposure to determine the effectiveness of calories and or EE at the point-of-choice at fast food restaurants.

Teams: Vehicle of Choice for Transporting the Organizational Future

Teamwork is much more than lip service paid to the concept. This article was writ- ten for the executive, the educator and the student to broaden awareness of the vast potential of teams and teamwork.

Think Before You Eat: Calories and Exercise Equivalents Presented on Menus at Point-of-Choice

Although calorie information at the point-of-purchase at fast food restaurants is proposed as a method to decrease calorie choices and combat obesity, research results have been mixed. Much of the supportive research has weak methodology, and is limited. There is a demonstrated need to develop better techniques to assist consumers to make lower calorie food choices. Eating at fast food restaurants has been positively associated with weight gain. The current study explored the possibility of adding exercise equivalents (EE) (physical activity required to burn off the calories in the food), along with calorie information as a possible way to facilitate lower calorie choice at the point-of-choice in fast food restaurants. This three-group experimental study, in 18-34 year old, overweight and obese women, examines whether presenting caloric information in the form of EE at the point-of-choice at fast food restaurants, will lead to lower calorie food choices compared to presenting simple caloric information or no information at all. Methods: A randomized repeated measures experiment was conducted. Participants ordered a fast food meal from Burger King with menus that contained only the names of the food choices (Lunch 1). One week later (Lunch 2), study participants were given one of three menus that varied: no information, calorie information, or calorie information and EE. Study participants included 62 college aged students. Additionally, the study controlled for dietary restraint by blocking participants, before randomization, to the three groups. Results: A repeated measures analysis of variance was conducted. The study was not sufficiently powered, and while the study was designed to determine large effect sizes, a small effect size of .026, was determined. No significant differences were found in the foods ordered among the various menu conditions. Conclusion: Menu labeling alone might not be enough to reduce calories at the point-of-choice at restaurants. Additional research is necessary to determine if calorie information and EE at the point-of-choice would lead to fewer calories chosen at a meal. Studies should also look at long-term, repeated exposure to determine the effectiveness of calories and or EE at the point-of-choice at fast food restaurants.

Achievable rates and outage probability of cognitive radio with dynamic frequency hopping under imperfect spectrum sensing

In this study, the authors propose simple methods to evaluate the achievable rates and outage probability of a cognitive radio (CR) link that takes into account the imperfectness of spectrum sensing. In the considered system, the CR transmitter and receiver correlatively sense and dynamically exploit the spectrum pool via dynamic frequency hopping. Under imperfect spectrum sensing, false-alarm and miss-detection occur which cause impulsive interference emerged from collisions due to the simultaneous spectrum access of primary and cognitive users. That makes it very challenging to evaluate the achievable rates. By first examining the static link where the channel is assumed to be constant over time, they show that the achievable rate using a Gaussian input can be calculated accurately through a simple series representation. In the second part of this study, they extend the calculation of the achievable rate to wireless fading environments. To take into account the effect of fading, they introduce a piece-wise linear curve fitting-based method to approximate the instantaneous achievable rate curve as a combination of linear segments. It is then demonstrated that the ergodic achievable rate in fast fading and the outage probability in slow fading can be calculated to achieve any given accuracy level.

The book of choice ferns for the garden, conservatory, and stove. Describing and giving explicit cultural directions for the best and most striking ferns and selaginellas in cultivation. Illustrated with coloured plates and numerous wood engravings, specially prepared for this work.

vol.I. Introduction to Athyrium.--vol.II. Blechnum to Nothochlaena.--vol.III. Ochropteris to Woodwardia, and Selaginella.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

Compensating variation and the young Portuguese emigrants: A study on how to keep our own

Emigration has been a very present word in Portugal. Due to the effects of the Economic Crisis and the Memorandum of Understanding policies, we have witnessed a significant yearly migration outflow of people searching for better conditions. This study aims to measure the factors affecting this flow as well as how much the probability of emigrating has evolved during the years bridging 2006 to 2012. I shall consider the decision of emigrating as Discrete Choice Random Utility maximization use a conditional Logit framework to model the probability choice for 31 OECD countries of destination. Moreover I will ascertain the compensating variation required such that the probability of choice in 2012 is adjusted back to 2007 values, keeping all other variables constant. I replicate this exercise using the unemployment rate instead of income. The most likely country of destination is Luxembourg throughout the years analyzed and the values obtained for the CV is of circa 1.700€ in terms of Income per capita and -11% in terms of the unemployment rate adjustment.

Small-area variation in health care affecting the choice of cesarean delivery: the case of a Colombian health insurer

In the midst of health care reform, Colombia has succeeded in increasing health insurance coverage and the quality of health care. In spite of this, efficiency continues to be a matter of concern, and small-area variations in health care are one of the plausible causes of such inefficiencies. In order to understand this issue, we use individual data of all births from a Contributory-Regimen insurer in Colombia. We perform two different specifications of a multilevel logistic regression model. Our results reveal that hospitals account for 20% of variation on the probability of performing cesarean sections. Geographic area only explains 1/3 of the variance attributable to the hospital. Furthermore, some variables from both demand and supply sides are found to be also relevant on the probability of undergoing cesarean sections. This paper contributes to previous research by using a hierarchical model and by defining hospitals as cluster. Moreover, we also include clinical and supply induced demand variables.

Social networks and occupational choice: the endogenous formation of attitudes and beliefs about tax compliance

The paper analyses the emergence of group-specific attitudes and beliefs about tax compliance when individuals interact in a social network. It develops a model in which taxpayers possess a range of individual characteristics – including attitude to risk, potential for success in self-employment, and the weight attached to the social custom for honesty – and make an occupational choice based on these characteristics. Occupations differ in the possibility for evading tax. The social network determines which taxpayers are linked, and information about auditing and compliance is transmitted at meetings between linked taxpayers. Using agent-based simulations, the analysis demonstrates how attitudes and beliefs endogenously emerge that differ across sub-groups of the population. Compliance behaviour is different across occupational groups, and this is reinforced by the development of group-specific attitudes and beliefs. Taxpayers self-select into occupations according to the degree of risk aversion, the subjective probability of audit is sustained above the objective probability, and the weight attached to the social custom differs across occupations. These factors combine to lead to compliance levels that differ across occupations.

Kindergarten students' understanding of probability concepts

This study explored kindergarten students’ intuitive strategies and understandings in probabilities. The paper aims to provide an in depth insight into the levels of probability understanding across four constructs, as proposed by Jones (1997), for kindergarten students. Qualitative evidence from two students revealed that even before instruction pupils have a good capacity of predicting most and least likely events, of distinguishing fair probability situations from unfair ones, of comparing the probability of an event in two sample spaces, and of recognizing conditional probability events. These results contribute to the growing evidence on kindergarten students’ intuitive probabilistic reasoning. The potential of this study for improving the learning of probability, as well as suggestions for further research, are discussed.

Conducting statistical tests of hypotheses : five common misconceptions found in transportation research

Most statistical methods use hypothesis testing. Analysis of variance, regression, discrete choice models, contingency tables, and other analysis methods commonly used in transportation research share hypothesis testing as the means of making inferences about the population of interest. Despite the fact that hypothesis testing has been a cornerstone of empirical research for many years, various aspects of hypothesis tests commonly are incorrectly applied, misinterpreted, and ignored—by novices and expert researchers alike. On initial glance, hypothesis testing appears straightforward: develop the null and alternative hypotheses, compute the test statistic to compare to a standard distribution, estimate the probability of rejecting the null hypothesis, and then make claims about the importance of the finding. This is an oversimplification of the process of hypothesis testing. Hypothesis testing as applied in empirical research is examined here. The reader is assumed to have a basic knowledge of the role of hypothesis testing in various statistical methods. Through the use of an example, the mechanics of hypothesis testing is first reviewed. Then, five precautions surrounding the use and interpretation of hypothesis tests are developed; examples of each are provided to demonstrate how errors are made, and solutions are identified so similar errors can be avoided. Remedies are provided for common errors, and conclusions are drawn on how to use the results of this paper to improve the conduct of empirical research in transportation.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

The role of organisational concern for workplace fairness in the choice of a performance mesaurement system

Prior studies linking performance management systems (PMS) and organisational justice have examined how PMS influence procedural fairness. Our investigation differs from these studies. First, it examines fairness as an antecedent (instead of as a consequence) of the choice of PMS. Second, instead of conceptualising organisational fairness as procedural fairness, it relies on the impression management interpretation of organisational fairness. Hence, the study investigates how the need of senior managers to cultivate an impression of being fair is related to the choice of PMS systems and employee outcomes. Based on a sample of 276 employees, the results indicate that the need of senior management to cultivate an impression of being fair is associated with employee performance. They also indicate that a substantial component of these effects is indirect through the choice of comprehensive performance measures (CPM) and employee job satisfaction. These findings highlight the importance of organisational concern for workplace fairness as an antecedent of choice of CPM. From a theoretical perspective, the adoption of the impression management interpretation of organisational fairness contributes by providing new insights into the relationship between fairness and choice of PMS from a perspective that is different from those used in prior management accounting research.

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.