Jujuy Province (NW Argentina): STR Markers Unveil Microgeographic Differentiation Over a Steep Mountainous Landscape

This study explores potential signals of microdifferentiation on the gene pool of three high-altitude populations from Jujuy province (NW Argentina) using highly polymorphic markers. These human communities are characterized by extreme living conditions and very low population densities owing to considerable height above sea level and steep orography. A set of autosomal STRs located at chromosome 6 (6p21.3) was typed in samples from Quebrada Baja (~2,500 m), Quebrada Alta (~ 3,300 m), and Puna (\u3e 3,500 m). Genetic diversity was estimated through the observed (Ho) and expected (He) heterozygosities, and the haplotype diversity. Analyses of the molecular variance (AMOVA) and population differentiation tests based on allele and haplotype frequencies were performed to assess genetic heterogeneity among subgroups. No deviation from HWE expectations was detected for each separate subpopulation; yet, significant departures were detected in the analysis considering the whole area (D6S2792 and D6S105 loci). Overall, genetic diversity showed a decreasing trend as the altitude increases. Thus, allele and haplotype frequencies showed the most significant differences between Puna and Quebrada Baja, which are the populations sited at the edges of the altitude range. The trend to the reduction of the heterozygosity with altitude proves to be compatible with historical patterns of colonization, interregional migration trends, population density, and genetic admixture. The main consequence of the complex mountainous landscape of Jujuy would be an imbalance in the interplay gene flow-genetic drift favoring the latter. The combined effect of restricted gene flow with intense genetic drift would have promoted local genetic differentiation between Jujuy highlands\u27 subpopulations, leading to spatial patterning of the allele frequencies not entirely attributable to geographic distance. Our findings corroborate the effectiveness of STRs to identify microevolutionary changes

Known by the company we keep: `Triadic influence' as a proxy for compatibility in social relationships

Networks of social interactions are the substrate upon which civilizations are built. Often, we create new bonds with people that we like or feel that our relationships are damaged through the intervention of third parties. Despite their importance and the huge impact that these processes have in our lives, quantitative scientific understanding of them is still in its infancy, mainly due to the difficulty of collecting large datasets of social networks including individual attributes. In this work, we present a thorough study of real social networks of 13 schools, with more than 3,000 students and 60,000 declared positive and negative relations, including tests for personal traits of all the students. We introduce a metric -- the `triadic influence' -- that measures the influence of nearest-neighbors in the relationships of their contacts. We use neural networks to predict the relationships and to extract the probability that two students are friends or enemies depending on their personal attributes or the triadic influence. We alternatively use a high-dimensional embedding of the network structure to also predict the relationships. Remarkably, the triadic influence (a simple one-dimensional metric) achieves the highest accuracy at predicting the relationship between two students. We postulate that the probabilities extracted from the neural networks -- functions of the triadic influence and the personalities of the students -- control the evolution of real social networks, opening a new avenue for the quantitative study of these systems

Completeness of the Trajectories of Particles Coupled to a General Force Field

We analyze the extendability of the solutions to a certain second order differential equation on a Riemannian manifold $(M,g)$, which is defined by a general class of forces (both prescribed on $M$ or depending on the velocity). The results include the general time-dependent anholonomic case, and further refinements for autonomous systems or forces derived from a potential are obtained. These extend classical results for Lagrangian and Hamiltonian systems. Several examples show the optimality of the assumptions as well as the applicability of the results, including an application to relativistic pp-waves.Comment: Archive for Rational Mechanics and Analysis (to appear

A New Approach to Energy Calculation of Road Accidents against Fixed Small Section Elements Based on Close-Range Photogrammetry

[EN] This paper presents a new approach for energetic analyses of traffic accidents against fixed road elements using close-range photogrammetry. The main contributions of the developed approach are related to the quality of the 3D photogrammetric models, which enable objective and accurate energetic analyses through the in-house tool CRASHMAP. As a result, security forces can reconstruct the accident in a simple and comprehensive way without requiring spreadsheets or external tools, and thus avoid the subjectivity and imprecisions of the traditional protocol. The tool has already been validated, and is being used by the Local Police of Salamanca (Salamanca, Spain) for the resolution of numerous accidents. In this paper, a real accident of a car against a fixed metallic pole is analysed, and significant discrepancies are obtained between the new approach and the traditional protocol of data acquisition regarding collision speed and absorbed energy.S

Further properties of causal relationship: causal structure stability, new criteria for isocausality and counterexamples

Recently ({\em Class. Quant. Grav.} {\bf 20} 625-664) the concept of {\em causal mapping} between spacetimes --essentially equivalent in this context to the {\em chronological map} one in abstract chronological spaces--, and the related notion of {\em causal structure}, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as: (i) causal mappings --and, thus, abstract chronological ones-- do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on $\R^2$, (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries.Comment: 33 pages, 9 figures, final version (the paper title has been changed). To appear in Classical and Quantum Gravit

GadCap: A GADGET multispecies model for the Flemish Cap cod, redfish and shrimp.

Since late 1980s, the demersal community of Flemish Cap (NAFO area 3M) has experienced large variations (including the collapse) in the abundance and population structure of its main fishing resources: cod Gadus morhua, redfish Sebastes sp. and shrimp Pandalus borealis, with alternation in their dominant role in the ecosystem. GadCap is an EU project dealing with the development of a GADGET multispecies model for the Flemish Cap cod, redfish and shrimp, as part of the NAFO roadmap for the EAF. The effect of fishing, trophic interactions (including cannibalism) and water temperature in the dynamic of these three major fishing resources has been modeled. The results highlight the interdependent dynamic of these stocks, and reveals strong interactions between recruitment, fishing and predation (including cannibalism), with marked changes in their relative importance by species-age-length over time. The multispecies model shows that disregarding the species interactions would lead to serious underestimates of natural mortality, overestimations of the exploitable biomass, and highlights the need to move beyond single-species management in this highly coupled ecosystem. Preliminary estimates of total SSB and MSY, under different combinations of fishing mortality for all the three stocks, are also presented.Postprint0,000

Simplified immunosuppressive and neuroprotective agents based on gracilin A

The architecture and bioactivity of natural products frequently serve as embarkation points for the exploration of biologically relevant chemical space. Total synthesis followed by derivative synthesis has historically enabled a deeper understanding of structure–activity relationships. However, synthetic strategies towards a natural product are not always guided by hypotheses regarding the structural features required for bioactivity. Here, we report an approach to natural product total synthesis that we term ‘pharmacophore-directed retrosynthesis’. A hypothesized, pharmacophore of a natural product is selected as an early synthetic target and this dictates the retrosynthetic analysis. In an ideal application, sequential increases in the structural complexity of this minimal structure enable development of a structure–activity relationship profile throughout the course of the total synthesis effort. This approach enables the identification of simpler congeners retaining bioactivity at a much earlier stage of a synthetic effort, as demonstrated here for the spongiane diterpenoid, gracilin A, leading to simplified derivatives with potent neuroprotective and immunosuppressive activityThe authors acknowledge support from the NIH (R37 GM052964 to D.R.), NSF (CHE1800411, to D.R.) the Robert A. Welch Foundation (AA-1280 to D.R.), FEDER co-funded grants from CONSELLERIA DE Cultura, EDUCACION e ordenación Universitaria Xunta de Galicia (2017 GRC GI-1682, ED431C 2017/01), CDTI and Technological Funds, supported by Ministerio de Economía, Industria y Competitividad (AGL2014- 58210-R, AGL2016-78728-R, AEI/FEDER, UE) (to L.M.B.), ISCIII/PI1/01830 (to A.A.) and RTC-2016-5507-2 and ITC-20161072, from EU POCTEP 0161-Nanoeaters-1-E-1, Interreg AlertoxNet EAPA-317-2016 and H2020 778069-EMERTOX (to L.M.B.) and from the European Union’s Seventh Framework Programme managed by the Research Executive Agency (FP7/2007-2013 under grant agreement 312184 PHARMASEA to L.M.B. and M.J.). N. Bhuvanesh and J. Reibenspies (Center for X-ray Analysis, TAMU) secured X-ray data and W. Russell (Laboratory for Biological Mass Spectrometry, TAMU) provided mass data. Correspondence and requests for materials should be directed to D. Romo (chemistry) and L. Botana (biology).S

Loss of smell and taste can accurately predict COVID-19 infection: a machine-learning approach

The COVID-19 outbreak has spread extensively around the world. Loss of smell and taste have emerged as main predictors for COVID-19. The objective of our study is to develop a comprehensive machine learning (ML) modelling framework to assess the predictive value of smell and taste disorders, along with other symptoms, in COVID-19 infection. A multicenter case-control study was performed, in which suspected cases for COVID-19, who were tested by real-time reversetranscription polymerase chain reaction (RT-PCR), informed about the presence and severity of their symptoms using visual analog scales (VAS). ML algorithms were applied to the collected data to predict a COVID-19 diagnosis using a 50-fold cross-validation scheme by randomly splitting the patients in training (75%) and testing datasets (25%). A total of 777 patients were included. Loss of smell and taste were found to be the symptoms with higher odds ratios of 6.21 and 2.42 for COVID-19 positivity. The ML algorithms applied reached an average accuracy of 80%, a sensitivity of 82%, and a specificity of 78% when using VAS to predict a COVID-19 diagnosis. This study concludes that smell and taste disorders are accurate predictors, with ML algorithms constituting helpful tools for COVID-19 diagnostic prediction.Junta de Andalucí

Solar photovoltaic technology in isolated rural communities in Latin America and the Caribbean

The main characteristics of photovoltaic (PV) energy and its current development in Latin American and Caribbean countries (LAC); its impact on the electrification of homes, health institutions, and schools in isolated or difficult-to-access communities; and, the advantages thereof are presented and discussed by replacing the use of traditional fuels such as firewood and kerosene in order to improve inhabitants ’health as well as reducing CO2 emissions. Countries like Nicaragua, Peru, Brazil, Argentina, and Chile stand out for their growing PV energy development in the region. A case study of the electrification process by PV systems shows very positive changes are manifested in terms of improving the quality of life of the inhabitants, and especially their physical and mental health state. In addition, CO2 emission reductions from electrifying 216 houses in the nine communities reach an annual amount of 2,164.19 t/yr, reducing firewood consumption by 2,123.39 t/yr and kerosene consumption by 40.80 t/yr However, LAC countries must adopt laws and regulations that regulate the use of PV energy, with an emphasis on recycling systems at the end of their life cycle