The Image of God and Human Uniqueness: Challenges from the Biological and Information Sciences

The image of God is the doctrinal home of human uniqueness. Indeed, the Genesis text indicates that the image of God is decisively what separates human beings from the rest of creation and helps to define the human being as a special creature in the order of creation. Recent work in the biological and information sciences is eroding the centuries-old conviction that we are unique as creatures. How does this affect how we understand the image of God? Should we experience this loss of human uniqueness as damaging to the Christian faith? These questions are addressed by first calling attention to the various ways the image of God have been interpreted throughout Christian history. Employing the four views of the image of God—substantive, functional, relational and dynamic—I argue that this loss of human uniqueness need not threaten the image of God in each of these cases, but rather helps provide clarity to the doctrine itself

On Labor Market Histories

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Can trial quality be reliably assessed from published reports of cancer trials: evaluation of risk of bias assessments in systematic reviews

To evaluate the reliability of risk of bias assessments based on published trial reports, for determining trial inclusion in meta-analyses

Automated hippocampal segmentation in patients with epilepsy: Available free online

Hippocampal sclerosis, a common cause of refractory focal epilepsy, requires hippocampal volumetry for accurate diagnosis and surgical planning. Manual segmentation is time-consuming and subject to interrater/intrarater variability. Automated algorithms perform poorly in patients with temporal lobe epilepsy. We validate and make freely available online a novel automated method

Is Hot IT a False Economy? An Analysis of Server and Data Center Energy Efficiency as Temperatures Rise

As demand for digital services grows, there is need to improve efficiency and reduce the environmental impact of data centers. The largest energy consumer in any data center is the IT, followed by the systems dedicated to cooling. Aiming to improve efficiency, and driven by metrics like PUE, there is a trend towards running data centers hotter to reduce the cooling energy. There is little research investigating the effect this will have on the IT beyond failure rates. To ensure overall efficiency is improving, we must view the data center as a system of systems, taking a holistic view rather than focusing on individual sub-systems. In this paper we use industry standard benchmarks and a wind-tunnel to profile typical enterprise IT. We analyze the effect of environmental conditions on IT efficiency, showing minor increases in temperature or pressure impact the efficiency of servers. Using an idealized, simulated data center case study we show that the interaction between cooling systems, server behaviour and local climate are non-trivial and increasing temperatures has potential to worsen efficiency

Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States

Spatially explicit livestock disease models require demographic data for individual farms or premises. In the U.S., demographic data are only available aggregated at county or coarser scales, so disease models must rely on assumptions about how individual premises are distributed within counties. Here, we addressed the importance of realistic assumptions for this purpose. We compared modeling of foot and mouth disease (FMD) outbreaks using simple randomization of locations to premises configurations predicted by the Farm Location and Agricultural Production Simulator (FLAPS), which infers location based on features such as topography, land-cover, climate, and roads. We focused on three premises-level Susceptible-Exposed-Infectious-Removed models available from the literature, all using the same kernel approach but with different parameterizations and functional forms. By computing the basic reproductive number of the infection (R0) for both FLAPS and randomized configurations, we investigated how spatial locations and clustering of premises affects outbreak predictions. Further, we performed stochastic simulations to evaluate if identified differences were consistent for later stages of an outbreak. Using Ripley's K to quantify clustering, we found that FLAPS configurations were substantially more clustered at the scales relevant for the implemented models, leading to a higher frequency of nearby premises compared to randomized configurations. As a result, R0 was typically higher in FLAPS configurations, and the simulation study corroborated the pattern for later stages of outbreaks. Further, both R0 and simulations exhibited substantial spatial heterogeneity in terms of differences between configurations. Thus, using realistic assumptions when de-aggregating locations based on available data can have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD may invade the population. We conclude that methods such as FLAPS should be preferred over randomization approaches

Duplicated network meta-analysis in advanced prostate cancer: a case study and recommendations for change

Background: Research overlap and duplication is a recognised problem in the context of both pairwise and network systematic reviews and meta-analyses. As a case study, we carried out a scoping review to identify and examine duplicated network meta-analyses (NMAs) in a specific disease setting where several novel therapies have recently emerged: hormone-sensitive metastatic prostate cancer (mHSPC). Methods: MEDLINE and EMBASE were systematically searched, in January 2020, for indirect or mixed treatment comparisons or network meta-analyses of the systemic treatments docetaxel and abiraterone acetate in the mHSPC setting, with a time-to-event outcome reported on the hazard-ratio scale. Eligibility decisions were made, and data extraction performed, by two independent reviewers. Results: A total of 13 eligible reviews were identified, analysing between 3 and 8 randomised comparisons, and comprising between 1773 and 7844 individual patients. Although the included trials and treatments showed a high degree of overlap, we observed considerable variation between identified reviews in terms of review aims, eligibility criteria and included data, statistical methodology, reporting and inference. Furthermore, crucial methodological details and specific source data were often unclear. Conclusions and recommendations: Variation across duplicated NMAs, together with reporting inadequacies, may compromise identification of best-performing treatments. Particularly in fast-moving fields, review authors should be aware of all relevant studies, and of other reviews with potential for overlap or duplication. We recommend that review protocols be published in advance, with greater clarity regarding the specific aims or scope of the project, and that reports include information on how the work builds upon existing knowledge. Source data and results should be clearly and completely presented to allow unbiased interpretation

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

Most systematic reviews are retrospective and use aggregate data AD) from publications, meaning they can be unreliable, lag behind therapeutic developments and fail to influence ongoing or new trials. Commonly, the potential influence of unpublished or ongoing trials is overlooked when interpreting results, or determining the value of updating the meta-analysis or need to collect individual participant data (IPD). Therefore, we developed a Framework for Adaptive Metaanalysis (FAME) to determine prospectively the earliest opportunity for reliable AD meta-analysis. We illustrate FAME using two systematic reviews in men with metastatic (M1) and non-metastatic (M0)hormone-sensitive prostate cancer (HSPC)

The password is praise: content of feedback affects categorization of feedback sources.

PublishedJournal ArticleIn three experimental studies, we investigated the effect of the content of group-directed feedback on categorization of the feedback source as an ingroup or an outgroup member. In all studies, feedback valence (criticism vs. praise) and the attributional content of feedback (attributing outcomes to internal properties of the group vs. external circumstances) were experimentally manipulated. The results demonstrated that anonymous (Study 1) and ambiguous (Studies 2 and 3) sources of feedback are more likely to be seen as (typical) ingroup members when they provide praise rather than criticism. In addition, in all studies there was a significant interaction between valence and the attributional content of feedback, such that sources of praise were more likely to be seen as ingroup members when they attributed the group's success to internal (rather than external) causes, while the opposite was observed for critics. These effects were mediated by perceived group image threat. Implications for research on group-based feedback and social categorization are discussed

Role of Boron p-Electrons and Holes in Superconducting MgB2, and other Diborides: A Fully-Relaxed, Full-Potential Electronic Structure Study

We present the results of fully-relaxed, full-potential electronic structure calculations for the new superconductor MgB2, and BeB2, NaB2, and AlB2, using density-functional-based methods. Our results described in terms of (i) density of states (DOS), (ii) band-structure, and (iii) the DOS and the charge density around the Fermi energy EF, clearly show the importance of B p-band for superconductivity. In particular, we show that around EF, the charge density in MgB2, BeB2 and NaB2 is planar and is associated with the B plane. For BeB2 and NaB2, our results indicate qualitative similarities but significant quantitative differences in their electronic structure due to different lattice constants a and c.Comment: 4 pages, 4 figures, Submitted to Phys Rev. Lett. on March 6, 2001; resubmission on April 2