The dependent variable problem in quantitative studies of Active Labour Market Programmes: uncovering hidden dynamics?

The question of what explains variation in expenditures on Active Labour Market Programs (ALMPs) has attracted significant scholarship in recent years. Significant insights have been gained with respect to the role of employers, unions and dual labour markets, openness, and partisanship. However, there remain significant disagreements with respects to key explanatory variables such the role of unions or the impact of partisanship. Qualitative studies have shown that there are both good conceptual reasons as well as historical evidence that different ALMPs are driven by different dynamics. There is little reason to believe that vastly different programs such as training and employment subsidies are driven by similar structural, interest group or indeed partisan dynamics. The question is therefore whether different ALMPs have the same correlation with different key explanatory variables identified in the literature? Using regression analysis, this paper shows that the explanatory variables identified by the literature have different relation to distinct ALMPs. This refinement adds significant analytical value and shows that disagreements are at least partly due to a dependent variable problem of ‘over-aggregation’.

A generalised Bayesian instrumental variable approach under student t-distributed errors with application

Bayesian analysis is given of an instrumental variable model that allows for heteroscedasticity in both the structural equation and the instrument equation. Specifically, the approach for dealing with heteroscedastic errors in Geweke (1993) is extended to the Bayesian instrumental variable estimator outlined in Rossi et al. (2005). Heteroscedasticity is treated by modelling the variance for each error using a hierarchical prior that is Gamma distributed. The computation is carried out by using a Markov chain Monte Carlo sampling algorithm with an augmented draw for the heteroscedastic case. An example using real data illustrates the approach and shows that ignoring heteroscedasticity in the instrument equation when it exists may lead to biased estimates.

Variable binding and coreference in sentence comprehension: evidence from eye movements

The hypothesis that pronouns can be resolved via either the syntax or the discourse representation has played an important role in linguistic accounts of pronoun interpretation (e.g. Grodzinsky & Reinhart, 1993). We report the results of an eye-movement monitoring study investigating the relative timing of syntactically-mediated variable binding and discourse-based coreference assignment during pronoun resolution. We examined whether ambiguous pronouns are preferentially resolved via either the variable binding or coreference route, and in particular tested the hypothesis that variable binding should always be computed before coreference assignment. Participants’ eye movements were monitored while they read sentences containing a pronoun and two potential antecedents, a c-commanding quantified noun phrase and a non c-commanding proper name. Gender congruence between the pronoun and either of the two potential antecedents was manipulated as an experimental diagnostic for dependency formation. In two experiments, we found that participants’ reading times were reliably longer when the linearly closest antecedent mismatched in gender with the pronoun. These findings fail to support the hypothesis that variable binding is computed before coreference assignment, and instead suggest that antecedent recency plays an important role in affecting the extent to which a variable binding antecedent is considered. We discuss these results in relation to models of memory retrieval during sentence comprehension, and interpret the antecedent recency preference as an example of forgetting over time.

Selection of potential probiotic lactic acid bacteria from fermented olives by in vitro tests

The present study aims to evaluate the probiotic potential of lactic acid bacteria (LAB) isolated from naturally fermented olives and select candidates to be used as probiotic starters for the improvement of the traditional fermentation process and the production of newly added value functional foods. Seventy one (71) lactic acid bacterial strains (17 Leuconostoc mesenteroides, 1 Ln. pseudomesenteroides, 13 Lactobacillus plantarum, 37 Lb. pentosus, 1 Lb. paraplantarum, and 2 Lb. paracasei subsp. paracasei) isolated from table olives were screened for their probiotic potential. Lb. rhamnosus GG and Lb. casei Shirota were used as reference strains. The in vitro tests included survival in simulated gastrointestinal tract conditions, antimicrobial activity (against Listeria monocytogenes, Salmonella Enteritidis, Escherichia coli O157:H7), Caco-2 surface adhesion, resistance to 9 antibiotics and haemolytic activity. Three (3) Lb. pentosus, 4 Lb. plantarum and 2 Lb. paracasei subsp. paracasei strains demonstrated the highest final population (>8 log cfu/ml) after 3 h of exposure at low pH. The majority of the tested strains were resistant to bile salts even after 4 h of exposure, while 5 Lb. plantarum and 7 Lb. pentosus strains exhibited partial bile salt hydrolase activity. None of the strains inhibited the growth of the pathogens tested. Variable efficiency to adhere to Caco-2 cells was observed. This was the same regarding strains' susceptibility towards different antibiotics. None of the strains exhibited β-haemolytic activity. As a whole, 4 strains of Lb. pentosus, 3 strains of Lb. plantarum and 2 strains of Lb. paracasei subsp. paracasei were found to possess desirable in vitro probiotic properties similar to or even better than the reference probiotic strains Lb. casei Shirota and Lb. rhamnosus GG. These strains are good candidates for further investigation both with in vivo studies to elucidate their potential health benefits and in olive fermentation processes to assess their technological performance as novel probiotic starters.

Impact of variable atmospheric and oceanic form drag on simulations of Arctic sea ice

Over Arctic sea ice, pressure ridges and floe andmelt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides

Current European Union regulatory risk assessment allows application of pesticides provided that recovery of nontarget arthropods in-crop occurs within a year. Despite the long-established theory of source-sink dynamics, risk assessment ignores depletion of surrounding populations and typical field trials are restricted to plot-scale experiments. In the present study, the authors used agent-based modeling of 2 contrasting invertebrates, a spider and a beetle, to assess how the area of pesticide application and environmental half-life affect the assessment of recovery at the plot scale and impact the population at the landscape scale. Small-scale plot experiments were simulated for pesticides with different application rates and environmental half-lives. The same pesticides were then evaluated at the landscape scale (10 km × 10 km) assuming continuous year-on-year usage. The authors' results show that recovery time estimated from plot experiments is a poor indicator of long-term population impact at the landscape level and that the spatial scale of pesticide application strongly determines population-level impact. This raises serious doubts as to the utility of plot-recovery experiments in pesticide regulatory risk assessment for population-level protection. Predictions from the model are supported by empirical evidence from a series of studies carried out in the decade starting in 1988. The issues raised then can now be addressed using simulation. Prediction of impacts at landscape scales should be more widely used in assessing the risks posed by environmental stressors.

Consumer acceptability and sensory profile of cooked broccoli with mustard seeds added to improve chemoprotective properties

Broccoli, a rich source of glucosinolates, is a commonly consumed vegetable of the Brassica family. Hydrolysis products of glucosinolates, isothiocyanates, have been associated with health benefits and contribute to the flavour of Brassica. However, boiling broccoli causes the myrosinase enzyme needed for hydrolysis to denature. In order to ensure hydrolysis, broccoli must either be mildly cooked or active sources of myrosinase, such as mustard seed powder, can be added post-cooking. In this study, samples of broccoli were prepared in six different ways; standard boiling with and without mustard seeds, sous-vide cooking at low temperature (70 °C) and sous-vide cooking at higher temperature (100 ºC) without mustard and with mustard at two different concentrations. The majority of consumers disliked the mildly cooked broccoli samples (70 ºC, 12 min, sous-vide) which had a hard and stringy texture. The highest mean consumer liking was for standard boiled samples (100 ºC, 7 min). Addition of 1% mustard seed powder developed sensory attributes such as pungency, burning sensation, mustard odour and flavour. One cluster of consumers (32%) found mustard seeds to be a good complement to cooked broccoli, however, the majority disliked the mustard-derived sensory attributes. Where the mustard seeds were partially processed, doubling the addition to 2% led to only the same level of mustard flavour and pungency as 1% unprocessed seeds, and mean consumer liking remained unaltered. This suggests that optimisation of the addition level of partially processed mustard seeds may be a route to enhance bioactivity of cooked broccoli without compromising consumer acceptability.

A comparison of two dust uplift schemes within the same general circulation model

Aeolian dust modelling has improved significantly over the last ten years and many institutions now consistently model dust uplift, transport and deposition in general circulation models (GCMs). However, the representation of dust in GCMs is highly variable between modelling communities due to differences in the uplift schemes employed and the representation of the global circulation that subsequently leads to dust deflation. In this study two different uplift schemes are incorporated in the same GCM. This approach enables a clearer comparison of the dust uplift schemes themselves, without the added complexity of several different transport and deposition models. The global annual mean dust aerosol optical depths (at 550 nm) using two different dust uplift schemes were found to be 0.014 and 0.023—both lying within the estimates from the AeroCom project. However, the models also have appreciably different representations of the dust size distribution adjacent to the West African coast and very different deposition at various sites throughout the globe. The different dust uplift schemes were also capable of influencing the modelled circulation, surface air temperature, and precipitation despite the use of prescribed sea surface temperatures. This has important implications for the use of dust models in AMIP-style (Atmospheric Modelling Intercomparison Project) simulations and Earth-system modelling.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

Bound Variable, Split Antecedent and Ellipsis Interpretations in L2 Portuguese: Implications for L2 Acquisition Theories.

Recently, in light of minimalist assumptions, some partial UG accessibility accounts to adult second language acquisition have made a distinction between the post-critical period ability to acquire new features based on their LF-interpretability (i.e. interpretable vs. uninterpretable features) (HAWKINS, 2005; HAWKINS; HATTORI, 2006; TSIMPLI; MASTROPAVLOU, 2007; TSIMPLI; DIMITRAKOPOULOU, 2007). The Interpretability Hypothesis (TSIMPLI; MASTROPAVLOU, 2007; TSIMPLI; DIMITRAKOPOULOU, 2007) claims that only uninterpretable features suffer a post-critical period failure and, therefore, cannot be acquired. Conversely, Full Access approaches claim that L2 learners have full access to UG’s entire inventory of features, and that L1/L2 differences obtain outside the narrow syntax. The phenomenon studied herein, adult acquisition of the Overt Pronoun Constraint (OPC) (MONTALBETTI, 1984) and inflected infinitives in nonnative Portuguese, challenges the Interpretability hypothesis insofar as it makes the wrong predictions for what is observed. The present data demonstrate that advanced learners of L2 Portuguese acquire the OPC and the syntax and semantics of inflected infinitives with native-like accuracy. Since inflected infinitives require the acquisition of new uninterpretable φ-features, the present data provide evidence in contra Tsimpli and colleagues’ Interpretability Hypothesis.

Soil quality assessment based on carbon stratification index in different olive grove management practices in Mediterranean areas

In Mediterranean areas, conventional tillage increases soil organic matter losses, reduces soil quality, and contributes to climate change due to increased CO2 emissions. CO2 sequestration rates in soil may be enhanced by appropriate agricultural soil management and increasing soil organic matter content. This study analyzes the stratification ratio (SR) index of soil organic carbon (SOC), nitrogen (N) and C:N ratio under different management practices in an olive grove (OG) in Mediterranean areas (Andalusia, southern Spain). Management practices considered in this study are conventional tillage (CT) and no tillage (NT). In the first case, CT treatments included addition of alperujo (A) and olive leaves (L). A control plot with no addition of olive mill waste was considered (CP). In the second case, NT treatments included addition of chipped pruned branches (NT1) and chipped pruned branches and weeds (NT2). The SRs of SOC increased with depth for all treatments. The SR of SOC was always higher in NT compared to CT treatments, with the highest SR of SOC observed under NT2. The SR of N increased with depth in all cases, ranging between 0.89 (L-SR1) and 39.11 (L-SR3 and L-SR4).The SR of C:N ratio was characterized by low values, ranging from 0.08 (L-SR3) to 1.58 (NT1-SR2) and generally showing higher values in SR1 and SR2 compared to those obtained in SR3 and SR4. This study has evaluated several limitations to the SR index such as the fact that it is descriptive but does not analyze the behavior of the variable over time. In addition, basing the assessment of soil quality on a single variable could lead to an oversimplification of the assessment. Some of these limitations were experienced in the assessment of L, where SR1 of SOC was the lowest of the studied soils. In this case, the higher content in the second depth interval compared to the first was caused by the intrinsic characteristics of this soil's formation process rather than by degradation. Despite the limitations obtained SRs demonstrate that NT with the addition of organic material improves soil quality.