Impacto ambiental del proyecto de regeneración de la playa de Denia, Alicante (España)

This paper show the main results of the Environmental Impact Assessment of the coastal regeneration project in Denia (Alicante).Two alternatives were evaluated. The first one implies the deposit of 3.8 millions m3 of sand along the shoreline. Meanwhile the second one involves the construction of three new docks and also the contribution of 0.9 millions of m3 of sands. All environmental features were evaluated in the sand marine deposit and in Denia shoreline. The second option, new docks plus sand contribution, appears to be more adequate from the environmental point of view.Se presentan los resultados del estudio de impacto Ambientaldel proyecto de regeneración de costas de las playas de la Almadraba les Deveses en el término municipal de Denia, Alicante.Se contemplan dos alternativas de actuación. La primera supone la regeneración mediante el vertido de arena a la playa y la segunda combinan el vertido de arenas con la construcción de espigones. Se analizan las principales variables ambientales tanto de las zonas de extracción de arenas como de la playa receptora y se procede a la evaluación ambiental de las alternativas. La segunda opción (construcción de espigones y vertido de arenas) se revela como la más adecuada desde el punto de vista ambiental

Synchronization of Energy Consumption By Human Societies Throughout the Holocene

We conduct a global comparison of the consumption of energy by human populations throughout the Holocene and statistically quantify coincident changes in the consumption of energy over space and time—an ecological phenomenon known as synchrony. When populations synchronize, adverse changes in ecosystems and social systems may cascade from society to society. Thus, to develop policies that favor the sustained use of resources, we must understand the processes that cause the synchrony of human populations. To date, it is not clear whether human societies display long-term synchrony or, if they do, the potential causes. Our analysis begins to fill this knowledge gap by quantifying the long-term synchrony of human societies, and we hypothesize that the synchrony of human populations results from (i) the creation of social ties that couple populations over smaller scales and (ii) much larger scale, globally convergent trajectories of cultural evolution toward more energy-consuming political economies with higher carrying capacities. Our results suggest that the process of globalization is a natural consequence of evolutionary trajectories that increase the carrying capacities of human societies

Synchronization of Energy Consumption By Human Societies Throughout the Holocene

We conduct a global comparison of the consumption of energy by human populations throughout the Holocene and statistically quantify coincident changes in the consumption of energy over space and time—an ecological phenomenon known as synchrony. When populations synchronize, adverse changes in ecosystems and social systems may cascade from society to society. Thus, to develop policies that favor the sustained use of resources, we must understand the processes that cause the synchrony of human populations. To date, it is not clear whether human societies display long-term synchrony or, if they do, the potential causes. Our analysis begins to fill this knowledge gap by quantifying the long-term synchrony of human societies, and we hypothesize that the synchrony of human populations results from (i) the creation of social ties that couple populations over smaller scales and (ii) much larger scale, globally convergent trajectories of cultural evolution toward more energy-consuming political economies with higher carrying capacities. Our results suggest that the process of globalization is a natural consequence of evolutionary trajectories that increase the carrying capacities of human societies

A meta-analysis of state-of-the-art electoral prediction from Twitter data

Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table

p3k14c, a synthetic global database of archaeological radiocarbon dates.

Archaeologists increasingly use large radiocarbon databases to model prehistoric human demography (also termed paleo-demography). Numerous independent projects, funded over the past decade, have assembled such databases from multiple regions of the world. These data provide unprecedented potential for comparative research on human population ecology and the evolution of social-ecological systems across the Earth. However, these databases have been developed using different sample selection criteria, which has resulted in interoperability issues for global-scale, comparative paleo-demographic research and integration with paleoclimate and paleoenvironmental data. We present a synthetic, global-scale archaeological radiocarbon database composed of 180,070 radiocarbon dates that have been cleaned according to a standardized sample selection criteria. This database increases the reusability of archaeological radiocarbon data and streamlines quality control assessments for various types of paleo-demographic research. As part of an assessment of data quality, we conduct two analyses of sampling bias in the global database at multiple scales. This database is ideal for paleo-demographic research focused on dates-as-data, bayesian modeling, or summed probability distribution methodologies

Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science

Replication is an essential requirement for scientific discovery. The current study aims to generalize and replicate 10 propositions made in previous Twitter studies using a representative dataset. Our findings suggest 6 out of 10 propositions could not be replicated due to the variations of data collection, analytic strategies employed, and inconsistent measurements. The study’s contributions are twofold: First, it systematically summarized and assessed some important claims in the field, which can inform future studies. Second, it proposed a feasible approach to generating a random sample of Twitter users and its associated ego networks, which might serve as a solution for answering social-scientific questions at the individual level without accessing the complete data archive.published_or_final_versio

Choice of the initial antiretroviral treatment for HIV-positive individuals in the era of integrase inhibitors

BACKGROUND: We aimed to describe the most frequently prescribed initial antiretroviral therapy (ART) regimens in recent years in HIV-positive persons in the Cohort of the Spanish HIV/AIDS Research Network (CoRIS) and to investigate factors associated with the choice of each regimen. METHODS: We analyzed initial ART regimens prescribed in adults participating in CoRIS from 2014 to 2017. Only regimens prescribed in >5% of patients were considered. We used multivariable multinomial regression to estimate Relative Risk Ratios (RRRs) for the association between sociodemographic and clinical characteristics and the choice of the initial regimen. RESULTS: Among 2874 participants, abacavir(ABC)/lamivudine(3TC)/dolutegavir(DTG) was the most frequently prescribed regimen (32.1%), followed by tenofovir disoproxil fumarate (TDF)/emtricitabine (FTC)/elvitegravir(EVG)/cobicistat(COBI) (14.9%), TDF/FTC/rilpivirine (RPV) (14.0%), tenofovir alafenamide (TAF)/FTC/EVG/COBI (13.7%), TDF/FTC+DTG (10.0%), TDF/FTC+darunavir/ritonavir or darunavir/cobicistat (bDRV) (9.8%) and TDF/FTC+raltegravir (RAL) (5.6%). Compared with ABC/3TC/DTG, starting TDF/FTC/RPV was less likely in patients with CD4100.000 copies/mL. TDF/FTC+DTG was more frequent in those with CD4100.000 copies/mL. TDF/FTC+RAL and TDF/FTC+bDRV were also more frequent among patients with CD4<200 cells//muL and with transmission categories other than men who have sex with men. Compared with ABC/3TC/DTG, the prescription of other initial ART regimens decreased from 2014-2015 to 2016-2017 with the exception of TDF/FTC+DTG. Differences in the choice of the initial ART regimen were observed by hospitals' location. CONCLUSIONS: The choice of initial ART regimens is consistent with Spanish guidelines' recommendations, but is also clearly influenced by physician's perception based on patient's clinical and sociodemographic variables and by the prescribing hospital location

Automatic Filtering and Substantiation of Drug Safety Signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions