Pine invasions in the southern hemisphere: modelling interactions between organism,environment and disturbance

Current theories of plant invasion have been criticized for their limited heuristic and predictive value. We explore the heuristic and predictive potential of a model which explicitly simulates the mechanisms of plant invasion. The model, a spatially-explicit individual-based simulation, is applied to the invasion of pine trees (Pinus spp.; Pinaceae) in three vegetation types in the southern hemisphere. The model simulates factors which have been invoked as major determinants of invasive success: plant traits, environmental features and disturbance level. Results show that interactions between these determinants of invasive success are at least as important as the main effects. The complexity of invasions has promoted the belief that many factors must be invoked to explain invasions. This study shows that by incorporating interactions and mechanisms into our models we can potentially reduce the number of factors needed to predict plant invasions. The importance of interactions, however, means that predictions about invasions must be context-specific. The search for all-encompassing rules for invasions is therefore futile. The model presented here is of heuristic value since it improves our understanding of invasions, and of management value since it defines the data and models needed for predicting invasions.     

Research on Children's Environmental Programmatic Efforts Pertaining to Fatherhood

Programmatic initiatives for fathers have grown rapidly in early childhood settings during the past decade. This article reviews the research literature on attitudes about father involvement in programs, patterns of father involvement, studies about program development, outcome studies, and correlates of father involvement in programs. Recommendations for future research on fatherhood initiatives and the relevance of research for programs and policy are also discussed.     

How the Statistics of Sequential Presentation Influence the Learning of Structure

Recent work has shown that humans can learn or detect complex dependencies among variables. Even learning a simple dependency involves the identification of an underlying model and the learning of its parameters. This process represents learning a structured problem. We are interested in an empirical assessment of some of the factors that enable humans to learn such a dependency over time. More specifically, we look at how the statistics of the presentation of samples from a given structure influence learning. Participants engage in an experimental task where they are required to predict the timing of a target. At the outset, they are oblivious to the existence of a relationship between the position of a stimulus and the required temporal response to intercept it. Different groups of participants are either presented with a Random Walk where consecutive stimuli were correlated or with stimuli that were uncorrelated over time. We find that the structural relationship implicit in the task is only learned in the conditions where the stimuli are independently drawn. This leads us to believe that humans require rich and independent sampling to learn hidden structures among variables.     

Predicting the invasion success of Mediterranean alien plants from their introduction characteristics

We describe a model to predict the invasion success of alien plants on Mediterranean islands, according to their mode, frequency and time since introduction and simple species traits. The model was developed using canonical discriminant analysis to identify categories of low- and high-risk species. Whilst classifying ca 80% of the data set correctly, the type II error rate remained moderately high, which limits its value in practical terms. This level of accuracy is typical of similar models, and critical analysis of the weaknesses is necessary to develop long-term improvements in methodology. Sensitivity analysis indicates that, overall, mode of introduction had an important influence on invasiveness, with species introduced for public amenity being more likely to attain high-risk status than species introduced privately to gardens. Frequency and time since introduction had a relatively minor influence on the model outcome, but remained highly confounded with other variables. Although invasion success, as measured by the number of islands colonized, is expected to increase over time, it was not possible to estimate the rates of expansion from historical trends, which are complicated by changes in import fashions over the centuries. Many older introductions were crops, whereas there has been a recent tendency towards exotic ornamentals and weedy species. Despite a fundamental influence on the results, similar historical influences are seldom taken into account adequately during trait analyses. Unravelling such inter-correlations between predictors is therefore an important challenge for the future of screening protocols.     

Individual toluene exposure in rotary printing: increasing accuracy of estimation by linear models based on protocols of daily activity and other measures

Industrial exposure varies distinctly both between persons and for each person over time. It is often not possible to measure individual exposure repeatedly due to high costs. Therefore, a method for assessment of exposure is needed that accounts for inter- and intraindividual variability. We consider a strategy suggested by Preller et al. (1995, Scandinavian Journal of Work, Environment, and Health 21, 504-512), the idea of which is to predict exposure on several days via a linear model using additional variables as regressors. Those additional variables are easier to obtain than exposure measurements and are assumed to influence exposure. The paper gives a theoretical proof of the use of this method. An example is given using toluene exposure data from a study in a rotogravure printing plant.     

Local stream habitat variables predicted from catchment scale characteristics are useful for predicting fish distribution

South-east Queensland (Australia) streams were described by 21 local habitat variables that were chosen because of their potential association with fish distribution. An Assessment by a Nearest Neighbour Analysis (ANNA) model used large-scale variables that are robust to human influence to predict what the values of each of the 21 local habitat variables at each site would be without modification from human activity. The ANNA model used elevation, stream order, distance from source and longitude to predict the local habitat variables; other candidate predictor variables (mean rainfall, latitude and catchment area) were not found to be useful. The ANNA model was able to predict five of the 21 local habitat variables (average width, sand (%), cobble (%), rocks (%) and large woody debris) with an R ² of at least 0.2. The observed values of these five local habitat variables were used to model the distributions of individual fish species. The species distribution models were developed using logistic regression based on a subset of the data (some of the data were withheld for model validation) and a forward stepwise model selection procedure. There was no difference in predictive performance of fish distribution models for model predictions based on observed values and model predictions based on ANNA predicted values of local habitat variables in the withheld data (p-value = 0.85). Therefore, it is possible to predict the suitability of sites as habitat for given fish species using estimated (estimates based on large-scale variables) natural values of local habitat variables.     

Interannual population dynamics of the green spruce aphid Elatobium abietinum (Walker) in France

The hypothesis that similar processes govern interannual dynamics of green spruce aphid in the UK and France, is generally supported by the application of a general discrete model. A simple model based on relatively few parameters was able to closely characterise interannual population dynamics from completely independent aerial and arboreal samples of aphids. Long-term field population estimates of the green spruce aphid Elatobium abietinum (Walker) in France have provided the opportunity to select and evaluate the generality of a model, which was developed in the UK to explain the year-to-year variations in peak abundance of the aphid. The objective was to observe the influence of the local climates and disturbing climate factors on the population densities of the insect in two regions of France. The model uses climate variables and aphid population data from regular samples in the two regions that were investigated. A general discrete model was used to predict aphid population densities. The model performed well in tracking the interannual patterns of population but was less likely to predict absolute population density. To improve predictions, further account would need to be taken of additional site-specific climate variables and the strength of overcompensating density dependence. Nevertheless, it is clear that broadly similar processes are at work in the population dynamics of this insect across its biogeographical range.     

子代身高性别对父母身高的回归分析

对抽样调查的身高数据进行计量分析,建立了子代对亲代身高的回归分析模型,揭示了子代身高与亲代身高的遗传率;研究结果表明,父母身高对下一代的遗传率强度不同,母亲要强于父亲;子女接受遗传的效应也不一样,女儿要强于儿子;建立了性别遗传模型,深入研究了亲代父母之间的身高差对子代性别的影响,亲代身高差越大,则生女孩的几率就越大,反之生男孩的几率就越大．     

Influence of alcohol abuse of the father on the intensity of clinical picture of posttraumatic stress disorder

The subject of the study is the influence of alcohol abusing father on the clinical picture of PTSD patient. The father plays an important identification role in the psychological development of his son. Therefore it is to be expected that an alcohol abusing father will become a (negative) role model for his son and that he will also later on in stressful situations try to reduce the anxiety and depression by consuming larger quantities of alcoholic drinks. The aim of the study is to find out whether there are differences in PTSD clinical picture in patients whose fathers abused alcohol and in those whose fathers did not have such problem. The participating patients were from the Psychiatric hospital "Sveti Ivan". Mississippi and Watson scales were applied, as well as a questionnaire named "Early traumas" from which the variable "alcohol abuse of the father" was selected. The analysis shows that the participants who in their family histories had fathers who abused alcohol developed a milder clinical picture of PTSD, i.e. they reactions to the stress later on were less sensitive compared to the control group of participants whose fathers did not abuse alcohol and whose clinical pictures of the disorder were more severe.     

A predictive dynamic yeast model based on component,energy, and electron carrier balances

The present study describes a novel yeast model for the prediction of yeast fermentation. The proposed model considers the possible metabolic pathways of yeast. For each pathway, the time evolution of components, energy (ATP/ADP), and electron carriers (NAD⁺/NADH) are expressed with limitation factors for all quantities consumed by each respective pathway. In this manner, the model can predict the partition of these pathways based on the growth conditions and their evolution over time. Several biological pathways and their stoichiometric coefficients are well known from literature. It is important to note that most of the kinetic parameters have no effect as the actual kinetics are controlled by the balance of limiting factors. The few remaining parameters were adjusted and compared with the literature when the data set was available. The model fits our experimental data from yeast fermentation on glucose in a nonaerated batch system. The predictive ability of the model and its capacity to represent the intensity of each pathway over time facilitate an improved understanding of the interactions between the pathways. The key role of energy (ATP) and electron carrier (NAD⁺) to trigger the different metabolic pathways during yeast growth is highlighted, whereas the involvement of mitochondrial respiration not being associated with the TCA cycle is also shown.     

Polymerisation stress modelling in acrylic bone cement

Fatigue failure of the cement mantle has been proposed as one of the failure processes contributing to aseptic loosening of cemented joint replacements. It has also been suggested that fatigue failure is dramatically accelerated by residual stress generated during the cement polymerisation process. Previous computational models of the polymerisation process have investigated only the latter part of polymerisation by assuming both instantaneous hardening of the material (a stress locking point) and that all residual stress results from thermal shrinkage after this stress locking point. In this study, finite element models which use the local degree of polymerisation to calculate material properties and shrinkage have been used to predict residual stresses in two models of total hip replacement cement mantles. Results indicate that the final value of cement mantle stress may not be the highest stresses that the cement is subjected to during the polymerisation process. Two models are presented, a 2-dimensional model, which was adapted from a similar model in the literature (Lennon and Prendergast, 2002) and a 3-dimensional concentric-cylinders model. In both cases a chemical kinetics model was used to predict the progress of the polymerisation reaction and a second linear model used to predict cement mechanical properties and density, and so stress generation and volume change, over time. There was good agreement of the results of the 2D model with its counterpart in the literature. For the 3D model, the final residual stress magnitudes and patterns showed good agreement with similar physical and computational models in the literature.     

Determining the roles of father absence and age at menarche in female psychosocial acceleration

Paternal investment theory and psychosocial acceleration theory hold that father absence and stressful experiences, respectively, accelerate reproductive development. Accumulating evidence is consistent with these theories yet important questions remain. In this study, we use a two-part structural equation model and data from 342 female undergraduates to address two of these questions: First, what is the role of father absence in female psychosocial acceleration, controlling potentially confounding aspects of environment and family structure? Second, to what extent does age at menarche mediate environmental and family structure effects on sexual debut? Findings indicated that many aspects of environment and family structure could be summarized with two factors—socio-economic status (SES) and fragmented family structure. We found that among those who had experienced sexual debut, exposure to temporary father departure (one year or more) in the context of an intact family hastened menarche, which in turn accelerated sexual debut. However, this type of father absence did not predict experience of sexual debut (or not). Fragmented family structure (which also implies some degree of father absence) appeared to increase the likelihood that participants had experienced sexual debut, but did not predict age at menarche or age at sexual debut among who had debuted. SES was not associated with any aspects of reproductive development, controlling for fragmented family structure and age. We discuss our findings in relation to paternal investment theory, psychosocial acceleration theory, and life history theory. We then lay out future directions for researchers aiming to clarify the role of environment in reproductive trajectories.     

Weekly carbon dioxide exchange trend predictions in deciduous broadleaf forests from site-specific influencing variables

Weekly net-ecosystem-exchange (NEE) data recorded and verified over multiple years, together with site-specific influential ecological variables, for distinct deciduous-broadleaf-forest (DBF) sites in North America can reveal useful relationships regarding their functions as long-term carbon dioxide (CO2) sources and sinks. Machine learning (ML) and regression models have greater success at predicting weekly NEE from some DBF sites than others, from the available site variables. In particular, support vector regression (SVR) and extreme gradient boosting (XGG) ML methods perform better than multi-linear regression in the weekly NEE predictions they generate using up to 24 influential variables. The DBF sites studied are distinguished into those that have followed distinctive, albeit fluctuating seasonal NEE trends, and those that are characterized by abrupt fluctuations in NEE across the leaf-on season. ML models predict weekly NEE for the former sites more reliably than for the latter sites. Consideration of the relative influence of the variables on the XGB and regression model NEE predictions identifies which variables are most influential at specific sites. Short wave radiation (in and out) and air temperature are found to be variables exerting substantial influence on the prediction models for the sites studied. From the prediction results and the relative influences of the available environmental variables, it is concluded that complex processes are involved at those sites showing rapid NEE fluctuations in the leaf-on seasons that are not readily detectable from the environmental variables currently being continuously recorded at those sites.     

The effect of vessel element structure on element conductivity

Summary A number of structural variables influence the conductivity of simple and scalariform perforation plates, and of vessel lumina. Using a previously developed computer model, the effects on conductivity of over 8,000 permutations of different lumen radii, perforation plate angles, perforation plate rim widths, scalariform slit pore heights, and scalariform bar thicknesses are considered. By taking advantage of basic patterns of similarity in the data, and by using scaling techniques, it has proved possible to calculate a series of factors which may be used to predict the conductivity of a vessel element or perforation plate of known dimensions. A number of previous workers have sought relationships between element structure and evolutionary or adaptive trends. Some important variables have been ignored in these studies in the past.     

A numerical study on the effect of the balance assumption in one-warehouse multi-retailer inventory systems

One-warehouse multi-retailer systems under periodic review have been studied extensively in the literature. The optimal policy has not been characterized yet. It would require solving a multi-dimensional dynamic program, which is hard due to the curse of dimensionality. In order to let the dynamic program decompose, researchers often make the so-called balance assumption. All available heuristics for periodic review distribution systems are based on some form of this assumption. For these heuristics, often further approximate steps are applied. We investigate the pure effect of the balance assumption in this paper. The balance assumption is the relaxation of a set of constraints in the original dynamic program and yields a lower bound model, which we solve exactly. This gives us a lower bound for the optimal cost of the original model. An upper bound for the true optimal cost is obtained by simulating the optimal policy for the relaxed problem with a slightly modified allocation rule. This modified policy is referred to as the LB heuristic policy. We use the relative gap between the upper and lower bound as a measure to assess the impact of the balance assumption. Based on extensive testing, we identify when the gap is small, and when not. For those instances with small gaps, both the lower bound is tight and the performance of the LB heuristic policy is close to the optimal. We also identify many practically relevant settings under which the balance assumption yields large gaps. For these instances, either the lower bound is poor or the LB heuristic policy is far from optimal, or both. In any case, it implies that more research is needed to develop better lower bounds and/or better heuristics for these instances.     

The evolution of parent–offspring conflict over mate choice

In human societies, parents often have a strong influence on the mate choice of their offspring. Moreover, empirical studies show that conflict over mate choice between parents and offspring is widespread across human cultures. Here we provide the first theoretical investigation into this conflict, showing that it may result from an underlying evolutionary conflict over parental resource distribution. We present a series of evolutionary simulations in which we gradually expand a standard model of sexual selection by the stepwise addition of elements of parental involvement. In our model, females obtain resources enhancing their fecundity from both their chosen mate and their parents. Potential mates differ in their ability to provide resources and may signal this ability. Both females and their parents can develop a preference for the signal, with both preferences influencing the realized mate choice of the female. Parents may differentially allocate resources among their daughters depending on the resource-provisioning abilities of their sons-in-law. When fecundity returns on investment are diminishing, we find that parents invest most in daughters whose mates provide few resources. Subsequently, the daughters evolve to exploit this allocation rule through their mate choice, which is not in the parents' best interests. This results in a conflict over mate choice between parents and their offspring, manifested as an on-going divergence of offspring and parental preferences. We predict that the conflict should be most pronounced when fathers, as opposed to mothers, control resource allocation.     

Presence of the father and parental experience have differentiated effects on pup development in Mongolian gerbils (Meriones unguiculatus)

Conflicting data exist on the importance of the father and parental experience during development in rodents. The purpose of this study was to investigate the effects of these two variables on development in Mongolian gerbils. Forty pairs of males and females with a litter size of between 4 and 7 pups were used as subjects. Twenty couples had no experience in raising young. After the birth of their pups, four experimental groups were formed: (I) inexperienced mother and father; (II) inexperienced mother; (III) experienced mother and father and (IV) experienced mother. When the pups reached 10 days of age, pup and parental behavior was recorded in experimental sessions of 15 min on 11 consecutive days. Through the statistical analysis it was found that the presence of the father significantly increased the physical contact between pups and parents and that pups opened their eyes earlier in comparison to the groups without the father. On the other hand, parental experience had a significant influence on the behavior of the pups (locomotion inside and outside the nest, and self-grooming). The results of this study suggest that parental experience and the presence of the father have differentiated effects on development in Mongolian gerbils.     

A computational model for the prediction of total knee replacement kinematics in the sagittal plane

A computational model has been developed using a current generation computer-aided engineering (CAE) package to predict total knee replacement (TKR) kinematic in the sagittal plane. The model includes friction and soft tissue restraint varying according to the flexion angle. The model was validated by comparing the outcomes of anterior-posterior (A-P) laxity tests of two contemporary knee replacements against data obtained from a knee simulating machine. It was also validated against predictions from a computer model reported in the literature. Results show good agreement in terms of A-P displacements. Further tests were performed to determined the influence of the soft tissue restraints varying with flexion angle. This work represents the first attempt to use a sophisticated commercial CAE package to predict TKR motions and the advantages of the modelling procedure chosen are discussed.     

Stylized facts in microalgal growth: interpretation in a dynamic energy budget context

A dynamic energy budget (DEB) model for microalgae is proposed. This model deviates from the standard DEB model as it needs more reserves to cope with the variation of assimilation pathways, requiring a different approach to growth based on the synthesizing unit (SU) theory for multiple substrates. It is shown that the model is able to accurately predict experimental data in constant and light-varying conditions with most of the parameter values taken directly from the literature. Also, model simulations are shown to be consistent with stylized facts (SFs) concerning NC ratio. These SFs are reinterpreted and the general conclusion is that all forcing variables (dilution rate, temperature and irradiance) impose changes in the nitrogen or carbon limitation status of the population, and consequently on reserve densities. Model predictions are also evaluated in comparison with SFs on chlorophyll concentration. It is proposed that an extra structure, more dependent on the nitrogen reserve, is required to accurately model chlorophyll dynamics. Finally, SFs concerning extracellular polymeric substances (EPSs) production by benthic diatoms are collected and interpreted and a formulation based on product synthesis and rejection flux is proposed for the EPSs production rate.