Firefly bioluminescence outshines aerial predators

Bioluminescence is found across life and has many functions. Yet we understand very little about its timing and origins, particularly as a predator avoidance strategy. Understanding the timing between bioluminescence and predator origins has yet to be examined and can help elucidate the evolution of the ecologically important signal aposematism. Using the most prevalent bioluminescent group, fireflies, where bioluminescence primarily functions as aposematic and sexual signals, the timing for the origins of both potential predators of fireflies and bioluminescence is explored. Divergence time estimations were performed using a genomic-scale phylogenetic reconstruction Lampyridae, and multiple fossil calibration points, allowing for a robust estimate for the origin of beetle bioluminescence as both a terrestrial and aerial signal. Our results recover the origins of terrestrial beetle bioluminescence at 141 mya and aerial bioluminescence at 133 mya. These ages predate the origins of all known extant aerial predators (i.e., bats and birds) and support the much older terrestrial predators (frogs, ground beetles, lizards, snakes, and hunting spiders) as the most likely drivers of bioluminescence in beetles.

Unwanted or mistimed pregnancy and developmental issues in Ecuadorian children aged 3 to 5: a doubly robust estimate using data from the National Health and Nutrition Survey 2018

Aim: To estimate the effect of unwanted or mistimed pregnancy on early childhood development in Ecuadorian children aged 3 to 5, participating in the National Health and Nutrition Survey 2018.Methods: We used a design-based doubly robust estimate. First, we used propensity score matching to identify a subsample of children aged 3 to 5 equally likely to come from a desired vs. unwanted/mistimed pregnancy. Then, we used a regression model to explore the relation of maternal pregnancy intentions with early childhood development. Results: Among 1,694 observations representing 162,285 Ecuadorian children, mistimed/unwanted pregnancy associated with lagging in development (odds ratio: 1.56; 95% confidence interval: 1.06; 2.29), after adjusting for the household’s geographic area and income, the father’s perception of the pregnancy, the mother’s marital status, age, ethnicity, educational level, and depressive symptoms, and the child’s age, gender, and daycare/class attendance. Unwanted/mistimed was also negatively associated with all four early childhood development index domains, socio-emotional development being the most affected. Discussion: Our doubly robust design found evidence of the relation between the maternal perception of her pregnancy and early child development. Addressing this relation to achieve reproductive justice entails considering a wide spectrum of population health and legal interventions to allow adequate access to education, contraception, and safe abortion. Moreover, pre- and postnatal check-ups could screen for unwanted/mistimed pregnancy and provide support accordingly.

A Robust Estimate Method for Damage Detection of Concrete Structures Using Contaminated Data

Damage detection of concrete structures based on finite element model and measured response parameters has been an important research topic in recent years. It is well known that test data of mechanical behavior of concrete show great scatterness. As a result, the measured response parameters of concrete structures sometimes have gross errors. The gross error is a physical quantity that is much larger than data noise, which may lead to serious distortion of calculation results. To this end, a new robust estimate method termed as the augmented inverse estimate is proposed in this work for damage detection of concrete structures to resist gross errors in data. It has the advantages of very simple programming, convenient utilization, high computational accuracy, and broad prospect of application. Central to the augmented inverse estimate are the augmentation of coefficient matrix and the multiple computations based on feedback evaluation. A reinforced concrete beam structure is used as an example to verify the proposed method. It was found that the proposed method can successfully identify the location and extent of structural damage even if the used data have gross errors.

Electoral Rules and New Parties: Evidence from a Quasi‐experimental Design

Electoral rules are a crucial institutional factor shaping the entry and success of new parties. However, testing how they affect voting behavior is problematic when using observational data in cross-national studies. As district magnitude is usually correlated with politically salient features affecting the likelihood of voting for new (and small) parties, the latent support of small parties differs across electoral systems. Using a quasi-experimental design in Spain focused on the district viability of a new party, Vox, in two elections held within 196 days, I provide a more robust estimate of the impact of electoral systems on the success of new parties. Strong evidence that the electoral system makes a difference for new parties has been identified: strategic considerations found in the districts where Vox was not successful prevented a significant number of voters from supporting the party.

Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?

The paper provides findings on the technical efficiency of the European dairy processing industry, which is one of the most important subsectors of the food processing industry in the European Union (EU). The ability to efficiently use inputs in the production of outputs is a prerequisite for the sustainability and competitiveness of the agri-food sector as well as for food security. Thus, the aim of this paper is to provide a robust estimate of technical efficiency by employing new advances in productivity and efficiency analysis, and to investigate the efficiency of input use in 10 selected European countries. The analysis is based on two-stage stochastic frontier modelling incorporating country-specific input distance function (IDF) estimates and a meta-frontier input distance function estimate, both in specification of the four-component model, which currently represents the most advanced approach to technical efficiency analysis. To provide a robust estimate of these models, the paper employs methods that control for the potential endogeneity of netputs in the multi-step estimation procedure. The results, based on the Amadeus dataset, reveal that companies manufacturing dairy products greatly exploited their production possibilities in 2006–2018. The dairy processing industry in the analysed countries cannot generally be characterized by a considerable waste of resources. The potential cost reduction is estimated at 4–8%, evaluated on the country samples mean. The overall technical inefficiency (OTE) is mainly a result of short-term shocks and unsystematic failures. However, the meta-frontier estimates also reveal a certain degree of systematic failure, e.g., permanent managerial failures and structural problems in European dairy processing industry.

GLM based auto-regressive process to model Covid-19 pandemic in Turkey

Objectives: Our objective is to propose a robust approach to model daily new cases and daily new deaths due to covid-19 infection in Turkey. Methods: We consider the generalized linear model (GLM) approach for the autoregressive process (AR) with log link for modelling. We study the data between March 11, 2020 that is the date first confirmed case occurred and October 20, 2020. After a month of the first outbreak in Turkey, the first official curfew has been imposed during the weekend. Since then there have been curfews each weekend till June 1st. Hence, we include intervention effects as well as some outlying data points in the model where necessary. We use the data between March 11 and September 15 to build the models, and test the performance on the data from September 16 till October 20. We also study the consistency of the model statistics. Results: Estimated models fit data quite well. Results reveal that after the first curfew daily new Covid-19 cases decrease 18.5%. As expected, effect of the curfew gets more significant once a month is past, and daily new cases cut down 24.9%. Our approach also gives a robust estimate for the effective reproduction number that is approximately 2 meaning as of October 20, 2020 there is still a risk for an infected person to cause 2 secondary infections despite all the interventions, preventions, and rules. Conclusion: The GLM approach for AR process with log link produces consistent and robust estimates for the daily new cases and daily new deaths for the data covering almost the first year of the pandemic in Turkey. The proposed approach can also be used to model the cases in other countries.

Robust Bearing-Only Localization Using Total Least Absolute Residuals Optimization

Robust techniques critically improve bearing-only target localization when the relevant measurements are being corrupted by impulsive noise. Resistance to isolated gross errors refers to the conventional least absolute residual (LAR) method, and its estimate can be determined by linear programming when pseudolinear equations are set. The LAR approach, however, cannot reduce the bias attributed to the correlation between system matrices and noise vectors. In the present study, perturbations are introduced into the elements of the system matrix and the data vector simultaneously, and the total optimization problem is formulated based on least absolute deviations. Subsequently, an equivalent form of total least absolute residuals (TLAR) is obtained, and an algorithm is developed to calculate the robust estimate by dual ascent algorithms. Moreover, the performance of the proposed method is verified through the numerical simulations by using two types of localization geometries, i.e., random and linear. As revealed from the results, the TLAR algorithm is capable of exhibiting significantly higher localization accuracy as compared with the LAR method.

A novel method for cold region streamflow hydrograph separation using GRACE satellite observations

Streamflow hydrograph analysis has long been used for separating streamflow into baseflow and surface-runoff components, providing critical information for studies in hydrology, climate and water resources. Defects known with established methods include the lack of physics and arbitrary choice of separation parameters, problems in identifying snowmelt runoff, and limitations on watershed size and hydrogeological conditions. In this study, a GRACE-based model was developed to address these weaknesses and improve hydrograph separation. The model is physically based and does not require a priori parametrisation. The new model was compared with six hydrograph separation methods provided with the U.S. Geological Survey Groundwater Toolbox. The results demonstrated robust estimate by the new model particularly in filtering out the bias of snowmelt runoff in baseflow estimate. This new model is specifically suitable for applications over large watersheds which is complementary to the traditional methods that are limited by watershed size. The output from the model also includes estimates for watershed hydraulic conductivity and drainable water storage, which are useful parameters in evaluating aquifer properties, calibrating and validating hydrological and climate models, and assessing regional water resources.

Combined epidemiological and genomic analysis of nosocomial SARS-CoV-2 transmission identifies community social distancing as the dominant intervention reducing outbreaks

ABSTRACTMany healthcare facilities report SARS-CoV-2 outbreaks but transmission analysis is complicated by the high prevalence of infection and limited viral genetic diversity. The contribution of different vectors to nosocomial infection or the effectiveness of interventions is therefore currently unclear. Detailed epidemiological and viral nanopore sequence data were analysed from 574 consecutive patients with a PCR positive SARS-CoV-2 test between March 13th and March 31st, when the pandemic first impacted on a large, multisite healthcare institution in London. During this time the first major preventative interventions were introduced, including progressive community social distancing (CSD) policies leading to mandatory national lockdown, exclusion of hospital visitors, and introduction of universal surgical facemask-use by healthcare-workers (HCW). Incidence of nosocomial cases, community SARS-CoV-2 cases and infection in a cohort of 228 HCWs followed the same dynamic course, decreasing shortly after introduction of CSD measures and prior to the main hospital-based interventions. We investigated clusters involving nosocomial cases based on overlapping ward-stays during the 14-day incubation period and SARS-CoV-2 genome sequence similarity. Our method placed 63 (79%) of 80 sequenced probable and definite nosocomial cases into 14 clusters containing a median of 4 patients (min 2, max 19) No genetic support was found for the majority of epidemiological clusters (31/44, 70%) and genomics revealed multiple contemporaneous outbreaks within single epidemiological clusters. We included a measure of hospital enrichment compared to community cases to increase confidence in our clusters, which were 1-14 fold enriched. Applying genomics, we could provide a robust estimate of the incubation period for nosocomial transmission, with a median lower bound and upper bound of 6 and 9 days respectively. Six (43%) clusters spanned multiple wards, with evidence of cryptic transmission, and community-onset cases could not be identified in more than half the clusters, particularly on the elective hospital site, implicating HCW as vectors of transmission. Taken together these findings suggest that CSD had the dominant impact on reducing nosocomial transmission by reducing HCW infection.

Dynamical traceback age of the β Pictoris moving group

Context. The β Pictoris moving group is one of the most well-known young associations in the solar neighbourhood and several members are known to host circumstellar discs, planets, and comets. Measuring its age precisely is essential to the study of several astrophysical processes, such as planet formation and disc evolution, which are strongly age-dependent. Aims. We aim to determine a precise and accurate dynamical traceback age for the β Pictoris moving group. Methods. Our sample combines the extremely precise Gaia DR2 astrometry with ground-based radial velocities measured in an homogeneous manner. We use an updated version of our algorithm to determine dynamical ages. The new approach takes into account a robust estimate of the spatial and kinematic covariance matrices of the association to improve the sample selection process and to perform the traceback analysis. Results. We estimate a dynamical age of 18.5−2.4+2.0 Myr for the β Pictoris moving group. We investigated the spatial substructure of the association at the time of birth and we propose the existence of a core of stars that is more concentrated. We also provide precise radial velocity measurements for 81 members of β Pic, including ten stars with the first determinations of their radial velocities. Conclusions. Our dynamical traceback age is three times more precise than previous traceback age estimates and, more importantly, for the first time it reconciles the traceback age with the most recent estimates of other dynamical, lithium depletion boundaries and isochronal ages. This has been possible thanks to the excellent astrometric and spectroscopic precisions, the homogeneity of our sample, and the detailed analysis of binaries and membership.