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In this paper we analyze the role of pollution for industry location and residence choice. We present a new economic geography (NEG) model in which manufacturing generates local pollution (that does not accumulate) and uses two types of labour input: unskilled workers that cannot migrate and work where they live; and high-skilled entrepreneurs that choose where to produce and where to live. Taking on board costless commuting or, in alternative, distance working, entrepreneurs can live in a different location from production. Both types of households enjoy utility from consuming all commodities (locally and imported variants) and suffer from local pollution. The resulting model is of the footloose entrepreneur variant, but involves two dynamic equations: the standard one governing the residential choice of entrepreneurs, and another one governing where production is located. The current paper analyses the discrete time dynamic process defined by a two-dimensional piecewise smooth map. Depending on parameters this map can have possibly coexisting attractors of various types (fixed points, cycles, closed curves as well as chaotic attractors). We analytically obtain stability conditions for the fixed points. Using numerical methods we describe also some global dynamic properties of the considered map. Finally, we propose an economic interpretation of the results concerning local stability analysis and global dynamics.

Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations in situations where genetic data is not available is appropriate. Although empirical evidence for this has been found across... Accurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. Seventeen traits were selected based on sample size, distribution, and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or nonmorphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.

Over the last few years water scarcity and pollution have been rapidly growing at both regional and global level. This has generated in many cases increasing intersectoral competition over the use of a limited amount of water resources. To examine the dynamics that such competition may generate in the economy, the present paper proposes a simple dynamic evolutionary model in which two sectors ( A and B ) compete for the use of water and studies the impact of water pricing on the dynamics of the two sectors in the presence of a population of interacting economic agents characterized by imitative behaviors. As it emerges from the model, when water is underpriced a self-enforcing process may be observed driving the economy towards a Pareto-dominated equilibrium. In such equilibrium the economy fully specializes in sector A , characterized by the highest negative impact on the water resource, at the expenses of sector B . The paper shows that a policy of fine tuning that increases water price through the endogenous water pricing mechanism examined in the model can inhibit the convergence of the economy to such an equilibrium point and can progressively shift the system towards the less water-consuming sector. Finally, assuming a Leontief production function and performing numerical simulations, it is shown how a change in water price can affect the dynamics of the model, and that the same results hold also in a more general, three-sector context.

Accurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. 17 traits were selected based on sample size, distribution and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or non-morphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.

Accurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. 17 traits were selected based on sample size, distribution and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or non-morphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.

Treatment of circulatory shock in critically ill patients requires management of blood pressure using invasive monitoring, but uncertainty remains as to optimal individual blood pressure targets. Critical closing pressure, which refers to the arterial pressure when blood flow stops, can provide a fundamental measure of vascular tone in response to disease and therapy, but it has not previously been possible to measure this parameter routinely in clinical care. Here we describe a method to continuously measure critical closing pressure in the systemic circulation using readily available blood pressure monitors and then show that tissue perfusion pressure (TPP), defined as the difference between mean arterial pressure and critical closing pressure, provides unique information compared to other hemodynamic parameters. Using analyses of 5,988 admissions to a modern cardiac intensive care unit, and externally validated with 864 admissions to another institution, we show that TPP can predict the risk of mortality, length of hospital stay and peak blood lactate levels. These results indicate that TPP may provide an additional target for blood pressure optimization in patients with circulatory shock. A newly developed hemodynamic parameter, termed tissue perfusion pressure, can be determined from standard blood pressure monitors and has additive value compared to mean arterial pressure for predicting the risk of mortality and other outcomes for patients in the cardiac intensive care unit.

In the present work, the compared effect of milk base and starter culture on acidification, texture, growth, and stability of probiotic bacteria in fermented milk processing, was studied. Two strains of probiotic bacteria were used, Lactobacillus acidophilus LA5 and L. rhamnosus LR35, with two starter cultures. One starter culture consisted only of Streptococcus thermophilus ST7 (single starter culture); the other was a yogurt mixed culture with S. thermophilus ST7 and L. bulgaricus LB12 (mixed starter culture). For the milk base preparation, four commercial dairy ingredients were tested (two milk protein concentrates and two casein hydrolysates). The resulting fermented milks were compared to those obtained with control milk (without enrichment) and milk added with skim milk powder. The performance of the two probiotic strains were opposite. L. acidophilus LA5 grew well on milk but showed a poor stability during storage. L. rhamnosus LR35 grew weakly on milk but was remarkably stable during storage. With the strains tested in this study, the use of the single starter culture and the addition of casein hydrolysate gave the best probiotic cell counts. The fermentation time was of about 11h, and the probiotic level after five weeks of storage was greater than 106 cfu/ml for L. acidophilus LA5 and 107 cfu/ml for L. rhamnosus LR35. However, an optimization of the level of casein hydrolysate added to milk base has to be done, in order to improve texture and flavor when using this dairy ingredient.