Coring, profiling, and trenching: Archaeological field strategies for investigating the Pleistocene-Holocene-Anthropocene continuum

Archaeologists have long emphasized the importance of large-scale excavations and multi-year or even decades-long projects at a single site or site complex. Here, we highlight archaeological field strategies, termed coring, profiling, and trenching (CPT), that rely on relatively small-scale excavations or the collection of new samples from intact deposits in previously excavated trenches (aka test units or pits). Examples from multiple sites in Africa, Asia, and North America demonstrate that CPT is highly effective for obtaining high-resolution archaeobiological and geoarchaeological samples (e.g., faunal and botanical remains, sediments) and artefacts from areas that have seen limited or no archaeological research, little systematic application of archaeological science methods, or research only on a relatively narrow time period or geographic scale. Designed to complement large-scale excavations at single sites, CPT is ideal for multi-scalar research that works in tandem with remote sensing techniques, providing samples for detailed laboratory analyses and offering a bridge between surface surveys and large-scale excavation. Given the threats facing archaeological sites around the world from climate change and human development, as well as financial, training and infrastructure constraints, and concerns from many Indigenous communities about large excavations, we argue that CPT is an important method for addressing 21st century human-environmental research questions

Myocardial Fat Imaging

The presence of intramyocardial fat may form a substrate for arrhythmias, and fibrofatty infiltration of the myocardium has been shown to be associated with sudden death. Therefore, noninvasive detection could have high prognostic value. Fat-water–separated imaging in the heart by MRI is a sensitive means of detecting intramyocardial fat and characterizing fibrofatty infiltration. It is also useful in characterizing fatty tumors and delineating epicardial and/or pericardial fat. Multi-echo methods for fat and water separation provide a sensitive means of detecting small concentrations of fat with positive contrast and have a number of advantages over conventional chemical-shift fat suppression. Furthermore, fat and water–separated imaging is useful in resolving artifacts that may arise due to the presence of fat. Examples of fat-water–separated imaging of the heart are presented for patients with ischemic and nonischemic cardiomyopathies, as well as general tissue classification

Beliefs about bad people are volatile

People form moral impressions rapidly, effortlessly and from a remarkably young age1,2,3,4,5. Putatively \u2018bad\u2019 agents command more attention and are identified more quickly and accurately than benign or friendly agents5,6,7,8,9,10,11,12. Such vigilance is adaptive, but can also be costly in environments where people sometimes make mistakes, because incorrectly attributing bad character to good people damages existing relationships and discourages forming new relationships13,14,15,16. The ability to accurately infer the moral character of others is critical for healthy social functioning, but the computational processes that support this ability are not well understood. Here, we show that moral inference is explained by an asymmetric Bayesian updating mechanism in which beliefs about the morality of bad agents are more uncertain (and therefore more volatile) than beliefs about the morality of good agents. This asymmetry seems to be a property of learning about immoral agents in general, as we also find greater uncertainty for beliefs about the non-moral traits of bad agents. Our model and data reveal a cognitive mechanism that permits flexible updating of beliefs about potentially threatening others, a mechanism that could facilitate forgiveness when initial bad impressions turn out to be inaccurate. Our findings suggest that negative moral impressions destabilize beliefs about others, promoting cognitive flexibility in the service of cooperative but cautious behaviour

RNA motif search with data-driven element ordering

BACKGROUND: In this paper, we study the problem of RNA motif search in long genomic sequences. This approach uses a combination of sequence and structure constraints to uncover new distant homologs of known functional RNAs. The problem is NP-hard and is traditionally solved by backtracking algorithms. RESULTS: We have designed a new algorithm for RNA motif search and implemented a new motif search tool RNArobo. The tool enhances the RNAbob descriptor language, allowing insertions in helices, which enables better characterization of ribozymes and aptamers. A typical RNA motif consists of multiple elements and the running time of the algorithm is highly dependent on their ordering. By approaching the element ordering problem in a principled way, we demonstrate more than 100-fold speedup of the search for complex motifs compared to previously published tools. CONCLUSIONS: We have developed a new method for RNA motif search that allows for a significant speedup of the search of complex motifs that include pseudoknots. Such speed improvements are crucial at a time when the rate of DNA sequencing outpaces growth in computing. RNArobo is available at http://compbio.fmph.uniba.sk/rnarobo. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1074-x) contains supplementary material, which is available to authorized users

Efficacy of Visual Surveys for White-Nose Syndrome at Bat Hibernacula

White-Nose Syndrome (WNS) is an epizootic disease in hibernating bats caused by the fungus Pseudogymnoascus destructans. Surveillance for P. destructans at bat hibernacula consists primarily of visual surveys of bats, collection of potentially infected bats, and submission of these bats for laboratory testing. Cryptic infections (bats that are infected but display no visual signs of fungus) could lead to the mischaracterization of the infection status of a site and the inadvertent spread of P. destructans. We determined the efficacy of visual detection of P. destructans by examining visual signs and molecular detection of P. destructans on 928 bats of six species at 27 sites during surveys conducted from January through March in 2012-2014 in the southeastern USA on the leading edge of the disease invasion. Cryptic infections were widespread with 77% of bats that tested positive by qPCR showing no visible signs of infection. The probability of exhibiting visual signs of infection increased with sampling date and pathogen load, the latter of which was substantially higher in three species (Myotis lucifugus, M. septentrionalis, and Perimyotis subflavus). In addition, M. lucifugus was more likely to show visual signs of infection than other species given the same pathogen load. Nearly all infections were cryptic in three species (Eptesicus fuscus, M. grisescens, and M. sodalis), which had much lower fungal loads. The presence of M. lucifugus or M. septentrionalis at a site increased the probability that P. destructans was visually detected on bats. Our results suggest that cryptic infections of P. destructans are common in all bat species, and visible infections rarely occur in some species. However, due to very high infection prevalence and loads in some species, we estimate that visual surveys examining at least 17 individuals of M. lucifugus and M. septentrionalis, or 29 individuals of P. subflavus are still effective to determine whether a site has bats infected with P. destructans. In addition, because the probability of visually detecting the fungus was higher later in winter, surveys should be done as close to the end of the hibernation period as possible