Lattice dynamics and correlated atomic motion from the atomic pair distribution function

The mean-square relative displacements (MSRD) of atomic pair motions in crystals are studied as a function of pair distance and temperature using the atomic pair distribution function (PDF). The effects of the lattice vibrations on the PDF peak widths are modelled using both a multi-parameter Born von-Karman (BvK) force model and a single-parameter Debye model. These results are compared to experimentally determined PDFs. We find that the near-neighbor atomic motions are strongly correlated, and that the extent of this correlation depends both on the interatomic interactions and crystal structure. These results suggest that proper account of the lattice vibrational effects on the PDF peak width is important in extracting information on static disorder in a disordered system such as an alloy. Good agreement is obtained between the BvK model calculations of PDF peak widths and the experimentally determined peak widths. The Debye model successfully explains the average, though not detailed, natures of the MSRD of atomic pair motion with just one parameter. Also the temperature dependence of the Debye model largely agrees with the BvK model predictions. Therefore, the Debye model provides a simple description of the effects of lattice vibrations on the PDF peak widths.Comment: 9 pages, 11 figure

Does resuscitation status affect decision making in a deteriorating patient? Results from a randomised vignette study

Aims and objectives: The aim of this paper is to determine the influence of do not attempt cardiopulmonary resuscitation (DNACPR) orders and the Universal Form of Treatment Options (‘UFTO’: an alternative approach that contextualizes the resuscitation decision within an overall treatment plan) on nurses' decision making about a deteriorating patient. Methods: An online survey with a developing case scenario across three timeframes was used on 231 nurses from 10 National Health Service Trusts. Nurses were randomised into three groups: DNACPR, the UFTO and no-form. Statements were pooled into four subcategories: Increasing Monitoring, Escalating Concern, Initiating Treatments and Comfort Measures. Results: Reported decisions were different across the three groups. Nurses in the DNACPR group agreed or strongly agreed to initiate fewer intense nursing interventions than the UFTO and no-form groups (P < 0.001) overall and across subcategories of Increase Monitoring, Escalate Concern and Initiate Treatments (all P < 0.001). There was no difference between the UFTO and no-form groups overall (P = 0.795) or in the subcategories. No difference in Comfort Measures were observed (P = 0.201) between the three groups. Conclusion: The presence of a DNACPR order appears to influence nurse decision making in a deteriorating patient vignette. Differences were not observed in the UFTO and no-form group. The UFTO may improve the way nurses modulate their behaviours towards critically ill patients with DNACPR status. More hospitals should consider adopting an approach where the resuscitation decisions are contextualised within overall goals of care

Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements

Peak positions and shapes in neutron pair correlation functions from powders of highly anisotropic crystals

The effect of the powder average on the peak shapes and positions in neutron pair distribution functions of polycrystalline materials is examined. It is shown that for highly anisotropic crystals, the powder average leads to shifts in peak positions and to non-Gaussian peak shapes. The peak shifts can be as large as several percent of the lattice spacing

Legal Uncertainty A Selective Deterrent

I show that legal uncertainty, i.e., uncertainty about the legality of a specific action, has positive welfare effects. Legal uncertainty works as a screening device provided that the threshold of legality is uncertain. The uncertainty discourages controversial actions, while it encourages socially beneficial actions. Legal uncertainty is a selective deterrent, because the uncertainty changes the probability of being convicted in opposite directions. Hence, in designing optimal rules there is no reason to avoid legal uncertainty at all costs. For example, the positive effect of legal uncertainty influences the balance between per-se rules and rules of reason in competition law

A Classifier-based approach to identify genetic similarities between diseases

Motivation: Genome-wide association studies are commonly used to identify possible associations between genetic variations and diseases. These studies mainly focus on identifying individual single nucleotide polymorphisms (SNPs) potentially linked with one disease of interest. In this work, we introduce a novel methodology that identifies similarities between diseases using information from a large number of SNPs. We separate the diseases for which we have individual genotype data into one reference disease and several query diseases. We train a classifier that distinguishes between individuals that have the reference disease and a set of control individuals. This classifier is then used to classify the individuals that have the query diseases. We can then rank query diseases according to the average classification of the individuals in each disease set, and identify which of the query diseases are more similar to the reference disease. We repeat these classification and comparison steps so that each disease is used once as reference disease

Priority for the Worse Off and the Social Cost of Carbon

The social cost of carbon (SCC) is a monetary measure of the harms from carbon emission. Specifically, it is the reduction in current consumption that produces a loss in social welfare equivalent to that caused by the emission of a ton of CO2. The standard approach is to calculate the SCC using a discounted-utilitarian social welfare function (SWF)—one that simply adds up the well-being numbers (utilities) of individuals, as discounted by a weighting factor that decreases with time. The discounted-utilitarian SWF has been criticized both for ignoring the distribution of well-being, and for including an arbitrary preference for earlier generations. Here, we use a prioritarian SWF, with no time-discount factor, to calculate the SCC in the integrated assessment model RICE. Prioritarianism is a well-developed concept in ethics and theoretical welfare economics, but has been, thus far, little used in climate scholarship. The core idea is to give greater weight to well-being changes affecting worse off individuals. We find substantial differences between the discounted-utilitarian and non-discounted prioritarian SCC