The making of mistakes by organisms and other living systems is a theoretically and empirically unifying feature of biological investigation. Mistake theory is a rigorous and experimentally productive way of understanding this widespread phenomenon. It does, however, run up against the long-standing ‘functions’ debate in philosophy of biology. Against the objection that mistakes are just a kind of malfunction, and that without a position on functions there can be no theory of mistakes, we reply that this is to misunderstand the theory. In this paper we set out the basic concepts of mistake theory and then argue that mistakes are a distinctive phenomenon in their own right, not just a kind of malfunction.

We assess emerging relationships between production decisions and market channel selection among a small sample of hemp growers (22) in Colorado and Kentucky using qualitative interviews. We found producers differences by market channel, product and state. For instance, producers who relied on intermediated marketing strategies cultivated more acres on average and used fewer distinct market channels and strategies than those relying on direct markets. Product differences were found regarding processing, storage and perishability. Respondents identified four factors critical to their choice of market channels for their hemp products: research, profitability, trust and knowledge. The findings can help inform public and private decision-making regarding best hemp marketing practices and future needs of the hemp industry.

Compositionalists hold that God the Son became human by acquiring all the parts that ordinarily compose a human being (his ‘human nature’). To be orthodox, though, they must deny that Christ's human nature is a person, even though it has all the parts that human persons ordinarily have. One way to do this is by appealing to the principle that no member of a natural kind can have another member of the same kind as a proper part. Since Christ is a person, he cannot have another person as a part, so if his human nature is a part of him, it cannot be a person. This principle is defended on the grounds that it can resolve metaphysical problems involving apparently multiple individuals of the same natural kind that share the same space. I argue that this is a weak strategy. First, it leaves unanswered key questions about how and why the principle applies to the incarnation. Second, counter-examples to the principle exist, suggesting that it is not true. Third, there is a better solution to the kinds of metaphysical paradoxes for which this principle is usually invoked, but this solution cannot be applied to the case of Christ. Consequently, compositionalists should not rely on this principle as a means of avoiding Nestorianism.

Diet is a modifiable risk factor for chronic disease and a potential modulator of telomere length (TL). The study aim was to investigate associations between diet quality and TL in Australian adults after a 12-week dietary intervention with an almond-enriched diet (AED). Participants (overweight/obese, 50–80 years) were randomised to an AED (n 62) or isoenergetic nut-free diet (NFD, n 62) for 12 weeks. Diet quality was assessed using a Dietary Guideline Index (DGI), applied to weighed food records, that consists of ten components reflecting adequacy, variety and quality of core food components and discretionary choices within the diet. TL was measured by quantitative PCR in samples of lymphocytes, neutrophils, and whole blood. There were no significant associations between DGI scores and TL at baseline. Diet quality improved with AED and decreased with NFD after 12 weeks (change from baseline AED + 9·8 %, NFD − 14·3 %; P < 0·001). TL increased in neutrophils (+9·6 bp, P = 0·009) and decreased in whole blood, to a trivial extent (–12·1 bp, P = 0·001), and was unchanged in lymphocytes. Changes did not differ between intervention groups. There were no significant relationships between changes in diet quality scores and changes in lymphocyte, neutrophil or whole blood TL. The inclusion of almonds in the diet improved diet quality scores but had no impact on TL mid-age to older Australian adults. Future studies should investigate the impact of more substantial dietary changes over longer periods of time.

Longitudinal studies report that regular nut consumption is associated with reduced risk of coronary heart disease and better cognitive function. Thus, nuts may improve cardiovascular and neurocognitive health – especially in ‘at-risk’ populations (e.g. overweight/obese). This study examined the effect of supplementing habitual diets of overweight/obese individuals for 12 weeks with either almonds or carbohydrate rich (CHO-rich) snack foods on biomarkers of cardiovascular and metabolic health, mood and cognitive performance. Participants (n = 151; overweight/obese, 50–80 years) were randomised to replace 15% energy intake with either almonds (Almond) or isocaloric CHO-rich snack foods (Comparator). Body weight, blood lipids, glucose, insulin, blood pressure (BP), arterial stiffness, mood and cognitive performance (memory, executive function, speed of processing) were measured at baseline and 12 weeks. One hundred and twenty eight participants (78F:50M, n = 63 almond, n = 65 control) completed the intervention (M ± SD: age 64 ± 8years, BMI 30.3 ± 3.6kg/m2, stable medication use: 32% BP and 19% lipid lowering). Compared with the CHO-rich comparator foods, there were a number of significant improvements associated with almond consumption. These included reduced serum triglycerides (M ± SEM, almond: 1.30 ± 0.062 to 1.16 ± 0.062 mmol/L vs CHO-rich 1.13 ± 0.061 to 1.17 ± 0.061 mmol/L, p = 0.005 whole population). In those with cholesterol below the ATPIII cut point of < 6.2mmol/L (84% of sample), almond consumption reduced total cholesterol (almond: 5.12 ± 0.13 to 4.93 ± 0.12 mmol/L vs CHO-rich 5.24 ± 0.13 to 5.21 ± 0.11 mmol/L, p < 0.001) and LDL-cholesterol (almond: 3.03 ± 0.11 to 2.87 ± 0.11 mmol/L vs CHO-rich 2.98 ± 0.10 to 3.07 ± 0.10 mmol/L, p = 0.002).). Additionally in a non-BP medicated subgroup only (n = 87, 68% of sample), there was a reduction in systolic BP (almond: 130.73 ± 2.19 to 127.02 ± 2.19 mmHg vs control:128.63 ± 2.32 to 129.48 ± 2.32mmHg, p = 0.035; and improved self-rated alertness (almond 54.73 ± 2.32 to 58.64 ± 2.32 vs CHO-rich 61.75 ± 2.28 to 61.13 ± 2.28, p = 0.048). The inclusion of almonds in the diet has the ability to improve aspects of cardiometabolic health and mood in overweight/obese adults. The lack of change in cognitive performance may reflect the fact that the study population was cognitively high performing at baseline. Future research should be directed at examining the effects of this relatively simple, cost-effective nutritional intervention in populations at greater risk of cardiometabolic and cognitive decline.

We present a new robust bootstrap method for a test when there is a nuisance parameter under the alternative, and some parameters are possibly weakly or nonidentified. We focus on a Bierens (1990, Econometrica 58, 1443–1458)-type conditional moment test of omitted nonlinearity for convenience. Existing methods include the supremum p-value which promotes a conservative test that is generally not consistent, and test statistic transforms like the supremum and average for which bootstrap methods are not valid under weak identification. We propose a new wild bootstrap method for p-value computation by targeting specific identification cases. We then combine bootstrapped p-values across polar identification cases to form an asymptotically valid p-value approximation that is robust to any identification case. Our wild bootstrap procedure does not require knowledge of the covariance structure of the bootstrapped processes, whereas Andrews and Cheng’s (2012a, Econometrica 80, 2153–2211; 2013, Journal of Econometrics 173, 36–56; 2014, Econometric Theory 30, 287–333) simulation approach generally does. Our method allows for robust bootstrap critical value computation as well. Our bootstrap method (like conventional ones) does not lead to a consistent p-value approximation for test statistic functions like the supremum and average. Therefore, we smooth over the robust bootstrapped p-value as the basis for several tests which achieve the correct asymptotic level, and are consistent, for any degree of identification. They also achieve uniform size control. A simulation study reveals possibly large empirical size distortions in nonrobust tests when weak or nonidentification arises. One of our smoothed p-value tests, however, dominates all other tests by delivering accurate empirical size and comparatively high power.

This article presents a bootstrapped p-value white noise test based on the maximum correlation, for a time series that may be weakly dependent under the null hypothesis. The time series may be prefiltered residuals. The test statistic is a normalized weighted maximum sample correlation coefficient $ \max _{1\leq h\leq \mathcal {L}_{n}}\sqrt {n}|\hat {\omega }_{n}(h)\hat {\rho }_{n}(h)|$, where $\hat {\omega }_{n}(h)$ are weights and the maximum lag $ \mathcal {L}_{n}$ increases at a rate slower than the sample size n. We only require uncorrelatedness under the null hypothesis, along with a moment contraction dependence property that includes mixing and nonmixing sequences. We show Shao’s (2011, Annals of Statistics 35, 1773–1801) dependent wild bootstrap is valid for a much larger class of processes than originally considered. It is also valid for residuals from a general class of parametric models as long as the bootstrap is applied to a first-order expansion of the sample correlation. We prove the bootstrap is asymptotically valid without exploiting extreme value theory (standard in the literature) or recent Gaussian approximation theory. Finally, we extend Escanciano and Lobato’s (2009, Journal of Econometrics 151, 140–149) automatic maximum lag selection to our setting with an unbounded lag set that ensures a consistent white noise test, and find it works extremely well in controlled experiments.

Communication deviance (CD) reflects features of the content or manner of a person's speech that may confuse the listener and inhibit the establishment of a shared focus of attention. The construct was developed in the context of the study of familial risks for psychosis based on hypotheses regarding its effects during childhood. It is not known whether parental CD is associated with nonverbal parental behaviors that may be important in early development. This study explored the association between CD in a cohort of mothers (n = 287) at 32 weeks gestation and maternal sensitivity with infants at 29 weeks in a standard play procedure. Maternal CD predicted lower overall maternal sensitivity (B = –.385; p < .001), and the effect was somewhat greater for sensitivity to infant distress (B = –.514; p < .001) than for sensitivity to nondistress (B = –.311; p < .01). After controlling for maternal age, IQ and depression, and for socioeconomic deprivation, the associations with overall sensitivity and sensitivity to distress remained significant. The findings provide new pointers to intergenerational transmission of vulnerability involving processes implicated in both verbal and nonverbal parental behaviors.

The Participatory Model of Atonement (PMA) offers an alternative view of Christian salvation, drawing on Pauline theology. It conceives of sin as a contagion which can usually be escaped only by dying. By ‘participating’ in Christ's death, the believer can escape its effects without having to die. This notion of ‘participation’ is obscure. I consider a possible way of clarifying it using metaphysical ideas taken from Jonathan Edwards. ‘Participation’ might involve becoming similar to Christ through the action of the Holy Spirit, to such a degree that a person might be called identical (in some sense) with Christ.

We consider the relative performance of two common approaches to multiple imputation (MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a joint MVN distribution; and conditional MI, in which each variable is modeled conditionally on all the others. In order to use the multivariate normal distribution, implementations of joint MVN MI typically assume that categories of discrete variables are probabilistically constructed from continuous values. We use simulations to examine the implications of these assumptions. For each approach, we assess (1) the accuracy of the imputed values; and (2) the accuracy of coefficients and fitted values from a model fit to completed data sets. These simulations consider continuous, binary, ordinal, and unordered-categorical variables. One set of simulations uses multivariate normal data, and one set uses data from the 2008 American National Election Studies. We implement a less restrictive approach than is typical when evaluating methods using simulations in the missing data literature: in each case, missing values are generated by carefully following the conditions necessary for missingness to be “missing at random” (MAR). We find that in these situations conditional MI is more accurate than joint MVN MI whenever the data include categorical variables.