Blast waves have been produced in solid target by irradiation with short-pulse high-intensity lasers. The mechanism of production relies on energy deposition from the hot electrons produced by laser–matter interaction, producing a steep temperature gradient inside the target. Hot electrons also produce preheating of the material ahead of the blast wave and expansion of the target rear side, which results in a complex blast wave propagation dynamic. Several diagnostics have been used to characterize the hot electron source, the induced preheating and the velocity of the blast wave. Results are compared to numerical simulations. These show how blast wave pressure is initially very large (more than 100 Mbar), but it decreases very rapidly during propagation.

While elections are an instrument to hold politicians accountable, corrupt politicians are often re-elected. A potential explanation for this paradox is that citizens trade-off integrity for competence. Voters may forgive corruption if corrupt politicians manage to deliver desirable outcomes. While previous studies have examined whether politicians’ competence moderates the negative effect of corruption, this paper focuses on voters’ priorities and directly assesses what citizens value more: integrity or favourable outcomes. Using a survey experiment, we assess citizens’ support for politicians who violate the law in order to improve the welfare of their community and, in some cases, benefit personally from these violations. The results indicate that citizens prefer a politician who follows the law, even if this leads to a suboptimal outcome. However, voters are more likely to overlook violations of the law that benefit the community if these do not result in a personal gain for politicians (i.e., in the absence of corruption). These findings suggest that the mild electoral punishment of corruption may be due to the public’s unawareness of private gains from malfeasance, or to the delay in these private benefits becoming apparent by election day.

Landscape changes affect species abundance and drive biodiversity loss. Here we explored if habitat amount and patch aggregation shape the abundance of forest passerines within the south-western Palaearctic (Morocco). As forests in this region are affected by increasing drought and temperature, we also forecasted their trends according to current predictions of climate change and explored how landscape changes could affect bird distribution. We recorded geo-referenced occurrences of seven forest passerines that were modelled with a set of environmental variables with Maxent to predict their distribution. The occurrence probabilities provided by the models were used as surrogates for the current distribution of habitat amount and patch aggregation within the country. In addition, 190 500-m line transects scattered within the country were used to estimate local bird abundance. Results showed that bird abundance recorded in line transects was positively correlated with habitat amount and patch aggregation of landscape around transects. This supports the idea that changes in these landscape metrics affect the abundance of the study species. Climate-change projections suggest that habitat amount and patch aggregation will decline in southern sectors but will be maintained or will increase at higher elevations. Given their relationship to abundance, these landscape changes suggest that forest birds will have to shift to the northernmost and elevated sectors. These results showed that landscape management can play an important role in the conservation of rear-edge populations of forest birds and suggest that any increase in forest amount and connectivity will improve bird resilience under a global change scenario.

LiDAR coverage of a large contiguous area within the Mirador-Calakmul Karst Basin (MCKB) of northern Guatemala has identified a concentration of Preclassic Maya sites (ca. 1000 b.c.–a.d. 150) connected by causeways, forming a web of implied social, political, and economic interactions. This article is an introduction to one of the largest, contiguous, regional LiDAR studies published to date in the Maya Lowlands. More than 775 ancient Maya settlements are identified within the MCKB, and 189 more in the surrounding karstic ridge, which we condensed into 417 ancient cities, towns, and villages of at least six preliminary tiers based on surface area, volumetrics, and architectural configurations. Many tiered sites date to the Middle and Late Preclassic periods, as determined by archaeological testing, and volumetrics of contemporaneously constructed and/or occupied architecture with similar morphological characteristics. Monumental architecture, consistent architectural formats, specific site boundaries, water management/collection facilities, and 177 km of elevated Preclassic causeways suggest labor investments that defy organizational capabilities of lesser polities and potentially portray the strategies of governance in the Preclassic period. Settlement distributions, architectural continuities, chronological contemporaneity, and volumetric considerations of sites provide evidence for early centralized administrative and socio-economic strategies within a defined geographical region.

The Sierra Madre Sparrow Xenospiza baileyi is an endangered Mexican endemic and a bunchgrassland specialist with a disjunct range: a relatively larger population in the south-eastern Trans-Mexican Volcanic Belt, and a smaller and poorly studied population in the Sierra Madre Occidental. In the latter, known distribution and abundance consists of four localities with a maximum of 28 individuals recorded in one of them. We surveyed the Sierra Madre Sparrow in 30 sites with suitable habitat, meadows or “bajíos” with bunchgrasses, in the municipalities of Durango, Pueblo Nuevo, San Dimas, and Canatlán in the Sierra Madre Occidental of Durango. We detected a total of 193 individuals in nine (30%) of the sites (392 ha), conducting intensive searches throughout them. Bunchgrasses in confirmed meadows were composed mainly of Muhlenbergia macroura, M. rigida, M. speciosa, M. rigens, and Piptochaetium fimbriatum. Total bunchgrass area within a meadow was a significant positive predictor of the Sierra Madre Sparrow presence, while total meadow area was not a significant predictor of its abundance. Seven of the confirmed localities were previously unknown, and two of them harboured 55% of the observed individuals: Ex Hacienda Coyotes (Pueblo Nuevo) and La Lobera (San Dimas). The estimated population size is at least four times higher than any previous record (28) or suggested (40–50) for the Sierra Madre Occidental and raises an opportunity and a challenge for conserving this genetically distinct population of the Sierra Madre Sparrow in the region.

This paper presents a methodology that permits to automate binary classification using the minimum possible number of attributes. In this methodology, the success of the binary prediction does not lie in the accuracy of an algorithm but in the evaluation metrics, which give information about the goodness of fit; which is an important factor when the data batch is unbalanced. The proposed methodology assesses the possible biases in identifying one algorithm as the best performer when considering the goodness of fit of an algorithm through evaluation metrics. The dimension of data has been reduced through the cumulative explained variance. Then, the performance of six machine learning classification models has been compared through Matthew correlation coefficient (MCC), area under curve – receiver operating characteristic (ROC-AUC), and area under curve – precision-recall (AUC-PR). The results show graphically and numerically how the evaluation metrics interfere with the most optimal outcome of an algorithm. The algorithms with the best performance in terms of evaluation metrics have been random forest and gradient boosting. In the imbalanced datasets, MCC has provided better prediction results than ROC-AUC or AUC-PR. The proposed methodology is adapted to the case of bankruptcy prediction.

The complete larval development of the spider crab Maguimithrax spinosissimus (Lamarck, 1818) is re-described and illustrated in detail from laboratory-reared material. The development consisted of the typical pattern reported for the Majoidea, two zoeal stages and one megalopa. The complete larval development from hatching to first crab lasted 5–6 days at temperatures that ranged between 24–28 °C. Both zoeal stages of M. spinosissimus exhibited moderate reduction in the number of setae in the maxilla and maxillipeds, from the first to the second zoeal stage, when compared with other closely related species. Maguimithrax spinosissimus can be easily distinguished from other species belonging to the closely related genus Mithrax by the (i) setation of the endopod of the maxillule, maxilla and second maxilliped in both zoeal stages; (ii) setation of the scaphognathite of the maxilla in the first zoeal stage; (iii) setation of the basis of maxilliped I in the second zoeal stage and megalopa; (iv) morphology of the antennule and antenna in the second zoeal stage; and (v) setation of the antennule, coxal endite of maxilla, and exopod of second maxilliped in the megalopa. All these characters support the recent generic status of Maguimithrax within the Mithracidae. Additional morphological details, not available previously, are provided. This study will provide support for conservation strategies in this species.

Depressive symptoms are diagnosed by physicians using scales but their pathophysiology is unclear. Low serotonin (5–HT) levels play an important role in depression, and the 5–HT transporter (5–HTT) is an important regulator of plasma serotonin levels and reuptake. Additionally, the 5–HTT gene-linked polymorphic region (5–HTTLPR) is associated with depression. The aim was to clarify the roles of plasma serotonin levels in plasma and the 5HTTPLR polymorphism in depressive symptoms in older adults. A total of 84 older adult participants were evaluated. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale of 20 items (CESD–20). The plasma serotonin levels were determined by ELISA, and the 5–HTTLPR genotype was analyzed by PCR. Depressive symptoms were present in 39.3% (N = 33) of the participants. The median plasma serotonin level was 204.34 ng/mL (SD = 93.88). A significant correlation was found between the CESD–20 scale and plasma serotonin levels (r = –.256; p = .019). Low serotonin levels were associated with the presence of depressive symptoms (p = .001). The 5–HTTLPR analysis showed that of the 84 older adults, 35.7% had the SS genotype, 10.7% had the LL genotype, and 53.6% were heterozygous. The 5–HTTLPR polymorphism was not associated with depressive symptoms (p = .587) and plasma serotonin levels (p = 0.391). Depressive symptoms correlate with low serotonin levels in plasma, but not with the 5–HTTLPR polymorphism in older Mexican adults.

This article analyzes individuals’ preferences for a consensus or a majoritarian type of democracy. We theorize that variation in these preferences is a function of both institutional learning (long term) and individuals’ position as a political minority or majority (short term). First, as a result of institutional learning, we expect that individuals living in democracies characterized by coalition governments will favor consensus democracy. Conversely, those living in countries characterized by single-party executives will favor majoritarian democracy. Second, we expect that individuals’ position as an electoral minority or majority will affect these beliefs. Those who vote for small parties will favor a consensus democracy, while those who vote for large parties will support a majoritarian system. However, whether institutional learning or individuals’ position as a political minority or majority prevail in influencing these preferences about the ideal model of democracy will be a function of the democratic trajectory of each country. We test these arguments drawing on data from the European Social Survey.

There is a growing interest in analyzing what citizens think about democracy. However, gauging citizens’ opinions about a complex concept such as democracy might be hindered by the apparent low levels of political sophistication of mass publics. This paper contributes to the emerging literature on citizens’ views and evaluations of democracy by analyzing to what extent ordinary citizens are capable of developing structured opinions about democracy and its constitutive principles. For this purpose, the paper adapts Converse’s notion of political belief systems to analyze the articulation of individuals’ democracy belief systems (DBS). The first goal of this paper is to conceptualize and operationalize the main components of individuals’ DBS: cognitive availability, horizontal constraint, and vertical constraint. Drawing on data from the sixth round of the European Social Survey, the second goal is to describe the articulation of DBS in Europe. The third and final aim of this paper is to trace the most relevant individual- and country-level correlates of the articulation of the three components of DBS. In line with recent findings about political belief systems in other policy domains, the results indicate that most Europeans have coherently structured attitudes about democracy. However, even if the results imply that Europeans have a relatively articulated DBS, the empirical analysis also reveals some individual- and country-level variation in the articulation of specific components of DBS.

An increasing number of studies exploit the occurrence of unexpected events during the fieldwork of public opinion surveys to estimate causal effects. In this paper, we discuss the use of this identification strategy based on unforeseen and salient events that split the sample of respondents into treatment and control groups: the Unexpected Event during Survey Design. In particular, we focus on the assumptions under which unexpected events can be exploited to estimate causal effects and we discuss potential threats to identification, paying especial attention to the observable and testable implications of these assumptions. We propose a series of best practices in the form of various estimation strategies and robustness checks that can be used to lend credibility to the causal estimates. Drawing on data from the European Social Survey, we illustrate the discussion of this method with an original study of the impact of the Charlie Hebdo terrorist attacks (Paris, 01/07/2015) on French citizens’ satisfaction with their national government.

The regulatory framework of the red octopus (Octopus maya) fishery includes total allowable catches (TAC), which are based on studies conducted on the population that occurs in shallow waters. In fact, most of the biological studies of this species refer to the fraction of the population that occupies waters less than 30 m deep; however, O. maya can occur up to a 60 m depth. The aim of this study is to assess the stock of O. maya that occupies waters between 30 m and 60 m deep. Four research cruises were carried out during the closed and fishing seasons, from May 2016 to January 2017. An average of 29 sampling sites were surveyed in each cruise (±2 sampling sites) using a commercial vessel with a uniform sampling effort. In each sampling site, the swept area, the total number of octopuses captured, the total weight of the catch, and the individual weight of octopuses were recorded. Biomass was obtained with four methods: stratified random method, swept area method, geostatistical biomass model, and an unpublished method of weighted swept area. The four methods provided consistent results. The distribution pattern of species was in patches, although before the fishing season started it was more homogeneous. The fraction of the population that occurs between 30 m and 60 m deep consisted mostly of adult organisms, so it could be contributing significantly to the recruitment of the entire population, even to the fraction that is exploited.