Tackling selection bias in sentencing data analysis: a new approach based on a scale of severity

For reasons of methodological convenience statistical models analysing judicial decisions tend to focus on the duration of custodial sentences. These types of sentences are however quite rare (7% of the total in England and Wales), which generates a serious problem of selection bias. Typical adjustments employed in the literature, such as Tobit models, are based on questionable assumptions and are incapable to discriminate between different types of non-custodial sentences (such as discharges, fines, community orders, or suspended sentences). Here we implement an original approach to model custodial and noncustodial sentence outcomes simultaneously avoiding problems of selection bias while making the most of the information recorded for each of them. This is achieved by employing Pina-Sánchez et al. (Br J Criminol 59:979–1001, 2019) scale of sentence severity as the outcome variable of a Bayesian regression model. A sample of 7242 theft offences sentenced in the Crown Court is used to further illustrate: (a) the pervasiveness of selection bias in studies restricted to custodial sentences, which leads us to question the external validity of previous studies in the literature limited to custodial sentence length; and (b) the inadequacy of Tobit models and similar methods used in the literature to adjust for such bias

Terrestrial impact structures as geoheritage: an assessment method of their scientific value and its application to Brazil

Terrestrial impact structures are geological and geomorphological features with particular importance to understand the history and evolution of the planet. Impact structures are scattered around the world but in many countries these features are under threat, essentially due to anthropic factors. Impact structures with higher scienti c value should be considered as geological heritage and, consequently, be subjected to geoconservation strategies. In order to select the most important impact structures to be properly conserved and managed, this paper proposes a quantitative assessment method of the scienti c value of these structures. The eight Brazilian impact structures were used to test this method that has the potential to be applied to any geological context in any country. The structures known as Araguainha Dome-MT and Serra da Cangalha-TO reached a higher scienti c value, which justi es the need to develop geoconservation strategies and a proper management.The Conselho Nacional de Pesquisa e Desenvolvimento (CNPq / National Council for Research and Development) and the Programa Ciências sem Fronteiras / Science Without Borders Programme are acknowledged for the support of the postdoctoral grant No 233209/2013-1 of the 1st author. The work was co-funded by the European Union through the European Regional Development Fund, based on COMPETE 2020 (Programa Operacional da Competitividade e Internacionalização), project ICT (UID/ GEO/04683/2013) with reference POCI-01-0145- FEDER-007690 and Portuguese funds provided by Fundação para a Ciência e Tecnologia.info:eu-repo/semantics/publishedVersio

Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network

Exact exchange-correlation potential of a ionic Hubbard model with a free surface

We use Lanczos exact diagonalization to compute the exact exchange-correlation (xc) potential of a Hubbard chain with large binding energy ("the bulk") followed by a chain with zero binding energy ("the vacuum"). Several results of density functional theory in the continuum (sometimes controversial) are verified in the lattice. In particular we show explicitly that the fundamental gap is given by the gap in the Kohn-Sham spectrum plus a contribution due to the jump of the xc-potential when a particle is added. The presence of a staggered potential and a nearest-neighbor interaction V allows to simulate a ionic solid. We show that in the ionic regime in the small hopping amplitude limit the xc-contribution to the gap equals V, while in the Mott regime it is determined by the Hubbard U interaction. In addition we show that correlations generates a new potential barrier at the surface

Optical signature of symmetry variations and spin-valley coupling in atomically thin tungsten dichalcogenides

Motivated by the triumph and limitation of graphene for electronic applications, atomically thin layers of group VI transition metal dichalcogenides are attracting extensive interest as a class of graphene-like semiconductors with a desired band-gap in the visible frequency range. The monolayers feature a valence band spin splitting with opposite sign in the two valleys located at corners of 1st Brillouin zone. This spin-valley coupling, particularly pronounced in tungsten dichalcogenides, can benefit potential spintronics and valleytronics with the important consequences of spin-valley interplay and the suppression of spin and valley relaxations. Here we report the first optical studies of WS2 and WSe2 monolayers and multilayers. The efficiency of second harmonic generation shows a dramatic even-odd oscillation with the number of layers, consistent with the presence (absence) of inversion symmetry in even-layer (odd-layer). Photoluminescence (PL) measurements show the crossover from an indirect band gap semiconductor at mutilayers to a direct-gap one at monolayers. The PL spectra and first-principle calculations consistently reveal a spin-valley coupling of 0.4 eV which suppresses interlayer hopping and manifests as a thickness independent splitting pattern at valence band edge near K points. This giant spin-valley coupling, together with the valley dependent physical properties, may lead to rich possibilities for manipulating spin and valley degrees of freedom in these atomically thin 2D materials

Dynamic screening of a localized hole during photoemission from a metal cluster

Recent advances in attosecond spectroscopy techniques have fueled the interest in the theoretical description of electronic processes taking place in the subfemtosecond time scale. Here we study the coupled dynamic screening of a localized hole and a photoelectron emitted from a metal cluster using a semi-classical model. Electron density dynamics in the cluster is calculated with Time-Dependent Density Functional Theory and the motion of the photoemitted electron is described classically. We show that the dynamic screening of the hole by the cluster electrons affects the motion of the photoemitted electron. At the very beginning of its trajectory, the photoemitted electron interacts with the cluster electrons that pile up to screen the hole. Within our model, this gives rise to a significant reduction of the energy lost by the photoelectron. Thus, this is a velocity dependent effect that should be accounted for when calculating the average losses suffered by photoemitted electrons in metals.Comment: 15 pages, 5 figure

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Investigating the impact of poverty on colonization and infection with drug-resistant organisms in humans: a systematic review

Background Poverty increases the risk of contracting infectious diseases and therefore exposure to antibiotics. Yet there is lacking evidence on the relationship between income and non-income dimensions of poverty and antimicrobial resistance. Investigating such relationship would strengthen antimicrobial stewardship interventions. Methods A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Ovid, MEDLINE, EMBASE, Scopus, CINAHL, PsychINFO, EBSCO, HMIC, and Web of Science databases were searched in October 2016. Prospective and retrospective studies reporting on income or non-income dimensions of poverty and their influence on colonisation or infection with antimicrobial-resistant organisms were retrieved. Study quality was assessed with the Integrated quality criteria for review of multiple study designs (ICROMS) tool. Results Nineteen articles were reviewed. Crowding and homelessness were associated with antimicrobial resistance in community and hospital patients. In high-income countries, low income was associated with Streptococcus pneumoniae and Acinetobacter baumannii resistance and a seven-fold higher infection rate. In low-income countries the findings on this relation were contradictory. Lack of education was linked to resistant S. pneumoniae and Escherichia coli. Two papers explored the relation between water and sanitation and antimicrobial resistance in low-income settings. Conclusions Despite methodological limitations, the results suggest that addressing social determinants of poverty worldwide remains a crucial yet neglected step towards preventing antimicrobial resistance

Improving phylogeny reconstruction at the strain level using peptidome datasets

Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using in vitro approaches, laying a foundation for the development of biomarker detection and application-specific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, whole-peptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future.This research was funded by Grant AGL2013-44039-R from the Spanish “Plan Estatal de I+D+I”, and by Grant EM2014/046 from the “Plan Galego de investigación, innovación e crecemento 2011-2015”. BS was recipient of a Ramón y Cajal postdoctoral contractfrom the Spanish Ministry of Economyand Competitiveness. This work was also partially funded by the [14VI05] Contract-Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273).The research leading to these results has also received funding from the European Union’s Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement n˚ 316265, BIOCAPS. This document reflects only the authors’ views and the European Union is not liable for any use that may be made of the information contained herein. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Beyond carbon and nitrogen: how the microbial energy economy couples elemental cycles in diverse ecosystems

Microbial metabolism couples elemental reactions, driving biogeochemical cycles. Assimilatory coupling of elemental cycles, such as the carbon (C), nitrogen (N), and phosphorus cycles, occurs when these elements are incorporated into biomass or released through its decomposition. In addition, many microbes are capable of dissimilatory coupling, catalyzing energy-releasing reactions linked to transformations in the oxidation state of elements, and releasing the transformed elements to the environment. Different inorganic elements provide varying amounts of energy yield, and the interaction of these processes creates a microbial energy economy. Dissimilatory reactions involving C, N, iron, and sulfur provide particularly important examples where microbially mediated oxidation–reduction (redox) transformations affect nutrient availability for net primary production, greenhouse-gas emissions, levels of contaminants and natural toxic factors, and other ecosystem dynamics. Recent discoveries of previously unrecognized microbial dissimilatory processes are leading to reevaluation of traditional perceptions of biogeochemical cycles