Poisson Indices of Segregation

Existing indices of residential segregation are based on an arbitrary partition of the city in neighborhoods: given a spatial distribution of racial groups, the index provides different levels of segregation for different partitions. This paper proposes a method in which individual locations are mapped to aggregate levels of segregation, avoiding arbitrary partitions. Assuming a simple spatial process driving the locations of different racial groups, I define a location-specific segregation index and measure the city-level segregation as average of the individual index. After deriving several distributional results for this family of indices, I apply the idea to US Census data, using nonparametric estimation techniques. This approach provides different levels and rankings of cities' segregation than traditional indices. I show that high aggregate levels of spatial separation are the result of very few locations with extremely high local segregation. I replicate the study of Cutler and Glaeser (1997) showing that their results change when segregation is measured using my approach. These findings potentially challenge the robustness of previous studies about the impact of segregation on socioeconomic outcomes.spatial segregation, spatial processes, nonparametric estimation

The Urban Metabolism of Lima: Perspectives and Policy Indications for GHG Emission Reductions

The urban metabolism of Metropolitan Lima, the largest urban agglomeration in Peru, which has recently surpassed 10 million inhabitants, was analyzed in this study. This coastal megacity, located within the Rimac, Chillón, and Lurin watersheds constitutes the socioeconomic center of the country and is the hub of the main import and export routes. A multi-layer approach was used to explore material and energy flows in the Peruvian capital for a 10-year timeframe. Results show that in 2006 the GDP of the 49 districts that shape the metropolitan area of Lima was 105.2 billion USD-PPP, while in 2014 it reached about 200 billion USD-PPP. Based on this growth, we highlight that energy, electricity and water flows experienced a linear increase with respect to GDP, being the electricity consumption in years 2006, 2011 and 2014, 7295, 10,112, and 11,465 GWh, respectively. Regarding demographics, population growth ratios of GDP (650%), electricity consumption (400%), solid waste production (250%), and water (100%) confirm the results of super linear scaling found by Kennedy et al. (2015) for the other megacities. Finally, the increase in greenhouse gas (GHG) emissions was computed following an important shift in the primary energy sources to produce electricity. The most important change was linked to the shift from hydropower to natural gas, a trend that initiated in 2006. For instance, in 2001 79% of the total electricity production came from hydropower, whereas in 2014 69% was linked to natural gas. This shift produced an increase of GHG emissions of more than 200% in 2014 when compared to the electricity generation mix of 2001. Following these results, we strongly encourage policies for the decarbonization of the electricity production sector, as well as for mobility infrastructures, e.g., electric public and transport sector, with a progressive shift toward electric mobility

Poisson Indices of Segregation

Existing indices of residential segregation are based on an arbitrary partition of the city in neighborhoods: given a spatial distribution of racial groups, the index provides different levels of segregation for different partitions. This paper proposes a method in which individual locations are mapped to aggregate levels of segregation, avoiding arbitrary partitions. Assuming a simple spatial process driving the locations of different racial groups, I define a location-specific segregation index and measure the city-level segregation as average of the individual index. After deriving several distributional results for this family of indices, I apply the idea to US Census data, using nonparametric estimation techniques. This approach provides different levels and rankings of cities' segregation than traditional indices. I show that high aggregate levels of spatial separation are the result of very few locations with extremely high local segregation. I replicate the study of Cutler and Glaeser (1997) showing that their results change when segregation is measured using my approach. These findings potentially challenge the robustness of previous studies about the impact of segregation on socioeconomic outcomes

A Structural Model of Segregation in Social Networks

In this paper, I develop and estimate a dynamic model of strategic network formation with heterogeneous agents. The main theoretical result is the existence of a unique stationary equilibrium, which characterizes the probability of observing a specific network in the data. As a consequence, the structural parameters can be estimated using only one observation of the network at a single point in time. The estimation is challenging, since the exact evaluation of the likelihood function is computationally infeasible even for very small networks. To overcome this problem, I propose a Bayesian Markov Chain Monte Carlo algorithm that avoids the direct evaluation of the likelihood. This method drastically reduces the computational burden of estimating the posterior distribution and allows inference in high dimensional models. I present an application to the study of segregation in school friendship networks, using data from Add Health. The latter contains the actual social network of each student in a representative sample of US schools. My results suggest that for White students, the value of a same-race friend decreases with the fraction of whites in the school. This relationship is of opposite sign for African American students. The model is used to study how different desegregation policies may affect the structure of the network in equilibrium. I find an inverted U-shape relationship between the fraction of students belonging to a racial group and the expected equilibrium segregation levels. These results suggests that these policies should be carefully designed in order to be effective

A Gravitational Model for Estimate the Determinants of Outward Foreign Direct Investment of China

Gravity models utilize the attractive force concept as an analogy to explain volume of trade or capital flows. This paper aims at proving that direct investment flows between China and a group of South-Est Asian countries are determined by standard variables included in gravity models such as: gross domestic products of home and host economy and distance between them. In our gravity model on foreign direct investment (FDI) we include not only gravity variables but also other variables that may explain what factors affecting Chinese outward foreign direct investment (OFDI): political risk, cultural proximity, the degree of openness to international trade and a proxy for natural resources. This paper, after having defined the variables that are capable of influencing Chinese OFDI, will suggest a method of econometric calculation of the gravitational model based on Prais-Winsten regression; Correlated panels corrected standard errors (PCSEs). Keywords: FDI, gravity model, Chinese OFDI JEL Classifications: F14, F15, F2

Plant Cellular and Molecular Biotechnology: Following Mariotti's Steps

This review is dedicated to the memory of Prof. Domenico Mariotti, who significantly contributed to establishing the Italian research community in Agricultural Genetics and carried out the first experiments of Agrobacterium-mediated plant genetic transformation and regeneration in Italy during the 1980s. Following his scientific interests as guiding principles, this review summarizes the recent advances obtained in plant biotechnology and fundamental research aiming to: (i) Exploit in vitro plant cell and tissue cultures to induce genetic variability and to produce useful metabolites; (ii) gain new insights into the biochemical function of Agrobacterium rhizogenes rol genes and their application to metabolite production, fruit tree transformation, and reverse genetics; (iii) improve genetic transformation in legume species, most of them recalcitrant to regeneration; (iv) untangle the potential of KNOTTED1-like homeobox (KNOX) transcription factors in plant morphogenesis as key regulators of hormonal homeostasis; and (v) elucidate the molecular mechanisms of the transition from juvenility to the adult phase in Prunus tree species

A Structural Model of Segregation in Social Networks

In this paper, I develop and estimate a dynamic model of strategic network formation with heterogeneous agents. The main theoretical result is the existence of a unique stationary equilibrium, which characterizes the probability of observing a specific network in the data. As a consequence, the structural parameters can be estimated using only one observation of the network at a single point in time. The estimation is challenging, since the exact evaluation of the likelihood function is computationally infeasible even for very small networks. To overcome this problem, I propose a Bayesian Markov Chain Monte Carlo algorithm that avoids the direct evaluation of the likelihood. This method drastically reduces the computational burden of estimating the posterior distribution and allows inference in high dimensional models. I present an application to the study of segregation in school friendship networks, using data from Add Health. The latter contains the actual social network of each student in a representative sample of US schools. My results suggest that for White students, the value of a same-race friend decreases with the fraction of whites in the school. This relationship is of opposite sign for African American students. The model is used to study how different desegregation policies may affect the structure of the network in equilibrium. I find an inverted U-shape relationship between the fraction of students belonging to a racial group and the expected equilibrium segregation levels. These results suggests that these policies should be carefully designed in order to be effective

Cryopreservation of adipose tissue with and without cryoprotective agent addition for breast lipofilling: A cytological and histological study.

Abstract In the second reconstructive phase of the breast after mastectomy, lipofilling is often necessary. Currently, lipofilling occurs immediately after autologous adipose tissue harvesting procedure, but most of the patients, usually, require multiple sessions to obtain a satisfactory result. Therefore, the need of repeated surgical harvesting outputs implies high risk of patients' morbidity and discomfort as well as increasing medical time and costs. The aim of our pilot study was to find out a feasible method to cryopreserve adipose tissue, in order to avoid reiterated liposuctions. Lipoaspirates samples have been harvested from 10 women and preserved by three methods: (1) the first one, using 10% Me2SO and 20% human albumin from human plasma as cryoprotective agents; (2) the second one, adding 5% Me2SO as cryoprotective agent; 3) the last one, without any cryoprotective agent. Fresh and cryopreserved fat samples, obtained through the aforementioned processes, have been analyzed ex vivo. The efficiency of the cryopreservation methods used was determined by adipocyte viability and the expression of adipocytes surface markers. Lipoaspirates stored at −196 °C for 3 months, after thawing, retained comparable adipocyte viability and histology to fresh tissue and no significant differences were found between the three methods used. Although the current results, differences between the methodologies in terms of viability may not become evident until breast lipofilling using frozen-thawed cryopreserved tissue

High innate attractiveness to black targets in the blue blowfly, Calliphora vomitoria (L.) (Diptera: Calliphoridae)

Calliphora vomitoria is a myiasis-causing fly in many animal species including humans. The control of blowflies is still anchored on the use of chemicals. However, mass trapping and lure-and-kill techniques represent a promising alternative to pesticides. Visual and olfactory cues are the main stimuli routing the fly's landing behavior. Notably, color attractiveness has been barely explored in flies of medical and veterinary importance, with special reference to blowflies. In this study, we investigated the innate color preferences in C. vomitoria adults, testing binary combinations of painted targets under laboratory conditions. The identity of tested species C. vomitoria was confirmed by DNA sequencing (18S and cox1 genes). C. vomitoria flies showed a significant preference for black colored targets in all tested binary color combinations, after 5, 15, 30 and 60 min of exposure. Black targets were significantly preferred over blue, red, yellow and white ones. Spectral characteristics of all tested color combinations were quantified and the innate attraction of blowflies towards black targets was discussed in relation to their behavioral ecology. To the best of our knowledge, this is the first report on innate color preferences in the Calliphora genus. Our findings can be useful to develop new, cheap and reliable monitoring traps as well as â\u80\u9clure and killâ\u80\u9d tools to control blowfly pests