The initial and updated Society of Thoracic Surgeons-European Association for Cardiothoracic Surgery (STAT and STAT 2020) and Risk Adjusted Classification for Congenital Heart Surgery-1 and Risk Adjusted Classification for Congenital Heart Surgery-2 scoring systems are validated to predict early postoperative mortality following congenital heart surgery in children; however, their ability to predict long-term mortality has not been examined. We performed a retrospective cohort study using data from the Pediatric Cardiac Care Consortium, a US-based registry of cardiac interventions in 47 participating centres between 1982 and 2011. Patients included in this cohort analysis had select congenital heart surgery representing the spectrum of severity as determined by STAT and Risk Adjusted Classification for Congenital Heart Surgery-1 and were less than 21 years of age. We applied STAT, STAT 2020, Risk Adjusted Classification for Congenital Heart Surgery-1, and Risk Adjusted Classification for Congenital Heart Surgery-2 for prediction of early mortality and long-term postoperative survival probability by surgical risk category. Long-term outcomes were obtained by matching Pediatric Cardiac Care Consortium patients with deaths reported in the National Death Index through 2021. Of 20,753 eligible patients, 18,755 survived the postoperative period and 2,058 deaths occurred over a median follow up of 24.4 years (Interquartile Range: 21–28.4). Each scoring system performed well for predicting early postoperative mortality with the following c-statistics: STAT: 0.7872, Risk Adjusted Classification for Congenital Heart Surgery-1: 0.7872, STAT 2020: 0.7724 and Risk Adjusted Classification for Congenital Heart Surgery-2: 0.7668. The predictive ability for long-term risk of death was as follows: STAT: 0.6995, Risk Adjusted Classification for Congenital Heart Surgery-1 c = 0.6741, Risk Adjusted Classification for Congenital Heart Surgery-2: 0.7156 and STAT 2020: c = 0.7156. Risk-adjusted score systems for congenital heart surgery maintain adequate but diminishing discriminative power to predict long-term mortality. Future efforts are warranted to develop a tool with improved long-term survival prediction.

Historians have written copiously about the shift to ‘germ theories’ of disease around the turn of the twentieth century, but in these accounts an entire continent has been left out: Antarctica. This article begins to rebalance our historiography by bringing cold climates back into the story of environmental medicine and germ theory. It suggests three periods of Antarctic (human) microbial research – heroic sampling, systematic studies, and viral space analogue – and examines underlying ideas about ‘purity’ and infection, the realities of fieldwork, and the use of models in biomedicine. It reveals Antarctica not as an isolated space but as a deeply complex, international, well-networked node in global science ranging from the first international consensus on pandemic-naming through to space flight.

Dynamic models of aggregate public opinion are increasingly popular, but to date they have been restricted to unidimensional latent traits. This is problematic because in many domains the structure of mass preferences is multidimensional. We address this limitation by deriving a multidimensional ordinal dynamic group-level item response theory (MODGIRT) model. We describe the Bayesian estimation of the model and present a novel workflow for dealing with the difficult problem of identification. With simulations, we show that MODGIRT recovers aggregate parameters without estimating subject-level ideal points and is robust to moderate violations of assumptions. We further validate the model by reproducing at the group level an existing individual-level analysis of British attitudes towards redistribution. We then reanalyze a recent cross-national application of a group-level item response theory model, replacing its domain-specific confirmatory approach with an exploratory MODGIRT model. We describe extensions to allow for overdispersion, differential item functioning, and group-level predictors. A publicly available R package implements these methods.

Dynamic latent variable models generally link units’ positions on a latent dimension over time via random walks. Theoretically, these trajectories are often expected to resemble a mixture of periods of stability interrupted by moments of change. In these cases, a prior distribution such as the regularized horseshoe—that allows for both stasis and change—can prove a better theoretical and empirical fit for the underlying construct than other priors. Replicating Reuning, Kenwick, and Fariss (2019), we find that the regularized horseshoe performs better than the standard normal and the Student’s t-distribution when modeling dynamic latent variable models. Overall, the use of the regularized horseshoe results in more accurate and precise estimates. More broadly, the regularized horseshoe is a promising prior for many similar applications.

In many species with encapsulated larval development, the larvae play an active role in hatching. However, the factors that control when the larvae hatch from each egg-capsule within an egg-mass are largely unknown. Advanced egg-masses of the gastropod Crepipatella peruviana were used to determine the hatching time of capsules from each egg-mass. After each female was detached, the egg-mass was also removed from the substrate and all capsules were then counted and measured. All capsules were examined to determine the time of hatching and the order in which capsules hatched from each egg-mass. Larvae were collected from each hatched egg-capsule and the number, size and weight of larvae from each capsule were determined. After 50–60% of the capsules from each egg-mass had hatched, the same characteristics of the remaining unhatched larvae from sister capsules were documented. Larvae were found to have hatched when they reached a size of 354 ± 22 μm (n = 245). Larvae from capsules within the same egg-mass hatched over a period of up to 12-days. The order of hatching in capsules from the same egg-mass was determined by larval content: capsules with fewer larvae and smaller capsules with heavier larvae hatched first. The hatching from one capsule in any given egg-mass did not induce the hatching of its sister capsules. Furthermore, hatching also occurred successfully in the mother absence, suggesting that this process is largely or completely controlled by the encapsulated larvae, although a possible maternal role in synchronizing hatching cannot be excluded.

Ionella fimbriata sp. nov. is described from a pair of bopyrid isopods attached to a male specimen of the ghost shrimp Neocallichirus grandimana collected in Veracruz, Mexico. This is the fifth species belonging to Ionella but the first one recorded from the Atlantic Ocean, which represents an important extension of its distribution range because until now all Ionella species were known from the Pacific Ocean. Females of I. fimbriata sp. nov. can be differentiated from the others of the genus by a barbula with one stout, acute, falcate projection on each side and medial margin with triangular rounded projections; seven pairs of pereopods with elongate cuticular extensions on bases and ischia, and five pairs of tuberculated biramous pleopods of pinnate shape. Males can be recognized by five pairs of globose biramous pleopods, in which endopods are longer than exopods, and uropods longer than pleopods. Description and illustrations of both the female and male I. fimbriata sp. nov. are provided, as well as keys for both sexes of all species in the genus. The fecundity, embryo size and volume of I. fimbriata sp. nov. are reported.

Successful language-based interaction depends on the reciprocal interplay of two or more speakers. The production of structural fragments rather than ‘full’ clausal units plays a crucial role for this interplay. This article provides an outline of a descriptive framework labeled ‘dual-mind syntax’, which is designed for describing the social signature in spoken syntax. Fragments are not analyzed as deficient and ‘incomplete’ syntactic units, but as a communicative practice used to design structures in a responsive-contingent fashion in social interaction. Based on empirical data coming from recorded natural interactions, it will be shown how speakers use syntactic fragments for coordinating actions and collaborative structure-building and for contributing to the emergence of a structurally integrated, coherent whole.

This study focused on a detailed mineralogical and crystal-chemical analysis of Mg-smectites from four bentonite samples from Turkey. Mg-rich smectites, mainly associated with alkaline and evaporitic depositional conditions, are formed in environments such as salt lakes, brine springs, and sabkhas, as well as in hydrothermal systems, in some cases by transformation from other phyllosilicates. Saponite has also been documented on the surface of Mars. The systems that produce Mg-smectites are less common than those that produce dioctahedral Al-smectites and consequently Mg-rich smectites are less abundant than dioctahedral smectites. For this reason, information on nanoscale mineralogy and crystal chemistry of Mg-smectites is relatively lacking. In this study, X-ray diffraction, thermal analysis and electron microscopy were used to study Mg-smectites. The crystal chemistry of single crystals determined with analytical electron microscopy in transmission electron microscopy (AEM-TEM) revealed that all samples had notable variability in the composition of individual crystals, such that no point analysis resulted in ideal structural formulae for saponite, stevensite, sepiolite, or palygorskite. They contain SiO2 content greater than that corresponding to a Mg-smectite, even stevensite, and often are intermediate to Mg-smectites and the sepiolite-palygorskite series. Meanwhile, the number of octahedral cations is small for fibrous clay minerals. Neither the point analysis of smectitic particles nor the mean structural formula fit properly for Mg-smectites showing crystallochemistry complexity. The results of these point analyses, in which no contamination has been observed, suggest that these smectites have intermediate compositions between trioctahedral smectites and sepiolite-palygorskite, indicating nanometer-scale intergrowths of these minerals in Mg-rich clay deposits.

We have used multiple regression analyses to develop a series of metabolisable energy prediction equations from chemical analyses of pig diets that can be extended to murine diets. We compiled four datasets from an extensive range of published metabolism studies with grower/finisher and adult pigs. The analytes in the datasets were increasingly complex, comprising (1) the proximate or Weende analysis, (2) the previous analysis but with neutral detergent fibre replacing crude fibre, (3) the neutral detergent fibre package plus starch and (4) the neutral detergent fibre package plus starch and sugars. Diet manufacturers routinely provide most of the analytes for batches of murine diet, or they are easily obtainable. The study uniquely compares the four analytical packages side by side. The number of records in the datasets varies from 367 to 827. With increasing analytical complexity, adjusted R2 values for metabolisable energy prediction improved from 0·751 to 0·869 and the mean absolute error from 0·422 to 0·289 kJ/g. Overall, the models’ prediction interval improved from 1 to 0·7 kJ/g, which is ± 7 to 5 % for a typical dietary metabolisable energy density of 14·8 kJ/g. Although prediction accuracy increases as one extends the range and complexity of the analytes measured, the improvement is slight and may not justify the substantial increase in analytical cost. The equations were validated for use on future datasets by k-fold analysis. Although the equations are developed from pig data, they are suitable for rat and mouse diets, based on comparable digestibility measurements, and substantially improve existing methods.

Prokaryotic microorganisms, comprising Bacteria and Archaea, exhibit a fascinating diversity of cell envelope structures reflecting their adaptations that contribute to their resilience and survival in diverse environments. Among these adaptations, surface layers (S-layers) composed of monomolecular protein or glycoprotein lattices are one of the most observed envelope components. They are the most abundant cellular proteins and represent the simplest biological membranes that have developed during evolution. S-layers provide organisms with a great variety of selective advantages, including acting as an antifouling layer, protective coating, molecular sieve, ion trap, structure involved in cell and molecular adhesion, surface recognition and virulence factor for pathogens. In Archaea that possess S-layers as the exclusive cell wall component, the (glyco)protein lattices function as a cell shape-determining/maintaining scaffold. The wealth of information available on the structure, chemistry, genetics and in vivo and in vitro morphogenesis has revealed a broad application potential for S-layers as patterning elements in a molecular construction kit for bio- and nanotechnology, synthetic biology, biomimetics, biomedicine and diagnostics. In this review, we try to describe the scientifically exciting early days of S-layer research with a special focus on the ‘Vienna-S-Layer-Group’. Our presentation is intended to illustrate how our curiosity and joy of discovery motivated us to explore this new structure and to make the scientific community aware of its relevance in the realm of prokaryotes, and moreover, how we developed concepts for exploiting this unique self-assembly structure. We hope that our presentation, with its many personal notes, is also of interest from the perspective of the history of S-layer research.

Confidence intervals are ubiquitous in the presentation of social science models, data, and effects. When several intervals are plotted together, one natural inclination is to ask whether the estimates represented by those intervals are significantly different from each other. Unfortunately, there is no general rule or procedure that would allow us to answer this question from the confidence intervals alone. It is well known that using the overlaps in 95% confidence intervals to perform significance tests at the 0.05 level does not work. Recent scholarship has developed and refined a set of tools for inferential confidence intervals that permit inference on confidence intervals with the appropriate type I error rate in many different bivariate contexts. These are all based on the same underlying idea of identifying the multiple of the standard error (i.e., a new confidence level) such that the overlap in confidence intervals matches the desired type I error rate. These procedures remain stymied by multiple simultaneous comparisons. We propose an entirely new procedure for developing inferential confidence intervals that decouples the testing and visualization that can overcome many of these problems in any visual testing scenario. We provide software in R and Stata to accomplish this goal.

This study investigates the influence of release timing on the trajectory of internal store separation through numerical solutions of continuity, momentum, energy equations and six degrees of freedom equations in a coupled manner. The internal store separation process in advanced fighter aircraft is analysed using computational fluid dynamics (CFD) and six degrees of freedom equations of motion. Initially, the equations of motion are validated by reenacting the Eglin Air Force Base study, an external store separation example with documented experimental results. Subsequently, validation is extended to the M219 cavity problem. In the internal store separation analysis, a cavity with an L/D ratio of 5, a freestream velocity of 0.85 Mach, and a generic store are utilised. Detached eddy simulation (DES) is applied using both static and dynamic mesh techniques in all numerical solutions. The generic store, positioned within a clean cavity with a 90-degree flap angle, was released at two distinct times, corresponding to the points of maximum and minimum gravitational forces. Interestingly, the results show that releasing the store when the normal force acting on it is at its maximum does not necessarily provide an optimal separation. Specifically, when the force coefficient was at its maximum (0.14), the store collided with the cavity door flap after 0.171465 seconds. In contrast, when the force coefficient was at its minimum (-0.04), the store contacted the cavity door after 0.170295 seconds at the same location. Despite the differences in force magnitudes, the trajectories were nearly identical, suggesting that the timing of the release may not have a significant effect on preventing collision. This further emphasises the need for flow control methods to ensure safe and effective store separation.

This article first poses a skeptical challenge to clinical trials in medicine. The efficacy of treatments is measured against placebo, but placebo responses are not constant. They fluctuate with demographic variables, and they seem to be increasing over time. We therefore find ourselves measuring with the equivalent of what Wittgenstein termed an “elastic ruler.”

I then propose a “skeptical solution” to the problem. Elastic rulers are suitable tools for measuring dynamic, floating networks of values, like foreign currency exchanges. We can assuage the skeptical concerns by understanding clinical trials in this way; I suggest several practical guidelines for doing so.

In this paper, we compare the $\mathbb J$-stratification (or the semi-module stratification) and the Ekedahl–Oort stratification of affine Deligne–Lusztig varieties in the superbasic case. In particular, we classify the cases where the $\mathbb J$-stratification gives a refinement of the Ekedahl–Oort stratification, which include many interesting cases such that the affine Deligne-Lusztig variety admits a simple geometric structure.

In this presidential address I offer a critical examination of how Africa was misrepresented in the Global North’s imaginations and media reporting during the COVID-19 pandemic. Such biased imaginings of Africa as a site of inevitable catastrophe account for the racialized under-accounting of the history of African scientists’ pioneering success in biomedical research and with epidemics. The global archives of COVID-19 pandemics must acknowledge these scientists, as well as the humanistic contributions of African artists who collaborated with health experts and produced poetic/musical performances in local and world languages to tackle biomedical and social pandemics.

The Currency of Politics is a major contribution to the history of economic thought, a history too often neglected by political theorists. Especially important are Eich’s arguments about the fragility of trust, and the way in which money both enables and undermines such trust. In his words, monetary trust “does not simply imply the enforcement of existing contracts but the realization of a more fundamental, and more equitable, social contract that requires a sharing of sacrifices and benefits. … In a democratic society monetary trust must be tied to a negotiation over justice” (18). In discussing Aristotle and the Greek world, Eich retrieves claims about the role of currency in contributing to reciprocal justice, especially if not exclusively in democracies. Money is a tool of reciprocity and equality—coinage can enable the spread of a “specifically egalitarian political ideology” (37). Money enables us to recognize injustices, and “possibly, amend them. Currency contains within itself the necessary condition for its own improvement” (27).