Identifying network ties from panel data: theory and an application to tax competition

Social interactions determine many economic behaviors, but information on social ties does not exist in most publicly available and widely used datasets. We present results on the identi…cation of social networks from observational panel data that contains no information on social ties between agents. In the context of a canonical social interactions model, we provide su¢cient conditions under which the social interactions matrix, endogenous and exogenous social e¤ect parameters are all globally identi…ed. While this result is relevant across di¤erent estimation strategies, we then describe how high-dimensional estimation techniques can be used to estimate the interactions model based on the Adaptive Elastic Net GMM method. We employ the method to study tax competition across US states. We …nd the identi…ed social interactions matrix implies tax competition di¤ers markedly from the common assumption of competition between geographically neighboring states, providing further insights for the long-standing debate on the relative roles of factor mobility and yardstick competition in driving tax setting behavior across states. Most broadly, our identi…cation and application show the analysis of social interactions can be extended to economic realms where no network data exists. JEL Codes: C31, D85, H71

ANTIMYCOBACTERIAL AND CYTOTOXICITY ACTIVITIES OF FREE AND LIPOSOME-ENCAPSULATED 3-(4 '-BROMO[1,1 '-BIPHENYL-4-YL)-3-(4-BROMO-PHENYL)-N,N-DIMETHYL-2-PROPEN-1-AMINE

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The antimycobacterial activity of 3-(4'-bromo[1,1'-bipheny1-4-yl)-3-(4-bromo-phenyl-N,N-dimethyl-2-propen-1-amine (BBAP), free or incorporated in preformed liposomes, on extracellular M. tuberculosis H37Rv was 8 and 25 mu M (MIC), respectively. Extracellular antimycobacterial activity was not significantly improved by entrapment of BBAP in liposomes, but there was a 6.1-fold reduction of BBAP cytotoxicity on J774 macrophages. Liposomal BBAP or its free form showed IC(50) values of 165 and 27 mu M, resulting in a selectivity index (SI=IC(50)/MIC) of 3.4 and 6.6, respectively. Free BBAP in concentrations from 10 to 80 mu M were quite effective in eliminating intracellular M. tuberculosis while liposomal formulation was less effective at these concentrations.334871874Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 1. Map construction and localization of loci showing distorted segregation

Microsatellites have become the most important class of markers for mapping procedures. Primarily based on restriction fragment length polymorphism (RFLP) markers, several molecular genetic maps of maize have been developed, mainly using temperate inbred maize lines. To characterize the level of polymorphism of microsatellite loci and construct a genetic map in tropical maize, two elite inbred lines, L-08-05F and L-14-4B, were crossed to produce 400 F-2 individuals that were used as a mapping population. A survey of 859 primer pair sequences of microsatellites was used. The polymorphism screens of each microsatellite and genotype assignment were performed using high-resolution agarose gels. About 54 % of the primer sets gave clearly scorable amplification products, 13 % did not amplify and 33% could not be scored on agarose gels. A total of 213 polymorphic markers were identified and used to genotype the mapping population. Among the polymorphic markers, 40 showed loci deviating from expected Mendelian ratios and clusters of deviating markers were located in three chromosome regions. Non-Mendelian scoring was present in 19 markers. The final genetic map with 117 markers spanned 1634 cM in length with an average interval of 14 cM between adjacent markers.13929610

Dermatological remedies in the traditional pharmacopoeia of Vulture-Alto Bradano, inland southern Italy

Dermatological remedies make up at least one-third of the traditional pharmacopoeia in southern Italy. The identification of folk remedies for the skin is important both for the preservation of traditional medical knowledge and in the search for novel antimicrobial agents in the treatment of skin and soft tissue infection (SSTI). Our goal is to document traditional remedies from botanical, animal, mineral and industrial sources for the topical treatment of skin ailments. In addition to SSTI remedies for humans, we also discuss certain ethnoveterinary applications. Field research was conducted in ten communities in the Vulture-Alto Bradano area of the Basilicata province, southern Italy. We randomly sampled 112 interviewees, stratified by age and gender. After obtaining prior informed consent, we collected data through semi-structured interviews, participant-observation, and small focus groups techniques. Voucher specimens of all cited botanic species were deposited at FTG and HLUC herbaria located in the US and Italy. We report the preparation and topical application of 116 remedies derived from 38 plant species. Remedies are used to treat laceration, burn wound, wart, inflammation, rash, dental abscess, furuncle, dermatitis, and other conditions. The pharmacopoeia also includes 49 animal remedies derived from sources such as pigs, slugs, and humans. Ethnoveterinary medicine, which incorporates both animal and plant derived remedies, is addressed. We also examine the recent decline in knowledge regarding the dermatological pharmacopoeia. The traditional dermatological pharmacopoeia of Vulture-Alto Bradano is based on a dynamic folk medical construct of natural and spiritual illness and healing. Remedies are used to treat more than 45 skin and soft tissue conditions of both humans and animals. Of the total 165 remedies reported, 110 have never before been published in the mainland southern Italian ethnomedical literature

Phosphoproteomic differences in major depressive disorder postmortem brains indicate effects on synaptic function

There is still a lack in the molecular comprehension of major depressive disorder (MDD) although this condition affects approximately 10% of the world population. Protein phosphorylation is a posttranslational modification that regulates approximately one-third of the human proteins involved in a range of cellular and biological processes such as cellular signaling. Whereas phosphoproteome studies have been carried out extensively in cancer research, few such investigations have been carried out in studies of psychiatric disorders. Here, we present a comparative phosphoproteome analysis of postmortem dorsolateral prefrontal cortex tissues from 24 MDD patients and 12 control donors. Tissue extracts were analyzed using liquid chromatography mass spectrometry in a data-independent manner (LC-MSE). Our analyses resulted in the identification of 5,195 phosphopeptides, corresponding to 802 non-redundant proteins. Ninety of these proteins showed differential levels of phosphorylation in tissues from MDD subjects compared to controls, being 20 differentially phosphorylated in at least 2 peptides. The majority of these phosphorylated proteins were associated with synaptic transmission and cellular architecture not only pointing out potential biomarker candidates but mainly shedding light to the comprehension of MDD pathobiology

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. / Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. / Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. / Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America

Lipidic characterization of Santa Ines lamb shoulder

The edible portion of the shoulder of 12 castrated and 12 non-castrated Santa Ines lambs slaughtered at different ages (84, 168, 210, 252 days) were used. The shoulders were chemically analyzed to determine the quantity of total lipids, cholesterol, and fatty acids composition. Castrated and non-castrated lambs gained body weight (p = 0.0393, p = 0.0017) and half carcass weight (p = 0.0240, p = 0.0017), respectively. The shoulder weight was increased in the carcasses of non-castrated lambs (p = 0.0110). The edible portion of the shoulder of castrated lambs presented higher total lipids (16.09 g.100 g(-1)). The cholesterol content was influenced by castration (p = 0.0001) reducing with age. Castrated animals presented higher content of C18:1 T11, CLA, and C18:0. The shoulder weight is only increased with increasing age in the carcasses of non-castrated lambs. Castration influences the cholesterol content of the shoulder; however, both castrated and non-castrated lambs had their cholesterol contents reduced with increasing age. Castration and age interfered in the estearic acid concentration of the edible portion of lamb shoulder.31250851