The Didache and Traditioned Innovation: Shaping Christian Community in the First Century and the Twenty-First Century

Church leaders, both lay and clergy, shape Christian community. Among their central tasks are: building communal identity, nurturing Christian practices, and developing faithful structures. When it comes to understanding the approach of the earliest Christian communities to these tasks, the Didache might well be the most important text most twenty-first century church leaders have never read. The Didache innovated on tradition, shaping the second generation of Christians to meet the crises and challenges of a changing world.

Most likely composed in the second half of the first century, the Didache served as a training manual for gentile converts to Christianity, preparing them for life in Christian community. This brief document, roughly one third the length of Mark’s gospel, developed within early Jewish-Christian communities. It soon found wide usage throughout the Mediterranean region, and its influence endured throughout the patristic and into the medieval period.

The Didache outlines emerging Christian practices that were rooted in both Jewish tradition and early Jesus material, yet were reaching forward in innovative ways. The Didache adopts historical teachings and practices and then adapts them for an evolving context. In this respect, the writers of the Didache, as well as the community shaped by its message, exemplify the pattern of thinking described by Greg Jones as “traditioned innovation.”

The Didache invites reflection on the shape and content of Christian community and Christian leadership in the twenty-first century. As churches and church leaders engage a rapidly changing world, the Didache is an unlikely and yet important conversation partner from two millennia ago. A quick read through its pages – a task accomplished in less than half an hour – brings the reader face to face with a brand of Christianity both very familiar and strikingly dissimilar to modern Christianity. Such dissonance challenges current assumptions about the church and creates a space in which to re-imagine our situation in light of this ancient Christian tradition. The Didache provides a window through which we might re-examine current conceptualizations of Christian life, liturgy, and leadership.

This thesis begins with an exploration of the form and function of the Didache and an examination of a number of important background issues for the informed study of the Didache. The central chapters of this thesis exegete and explore select passages in each of the three primary sections of the Didache – the Two Ways (Didache 1-6), the liturgical section (Didache 7-10), and the church order (Didache 11-15). In each instance, the composers of the Didache reach back into a cherished and life-giving aspect of the community’s heritage and shape it anew into a fresh and faithful approach to living the Christian life in a drastically different context.

The thesis concludes with three suggestions of how the Didache may provide a resource for the way the Church in the present thinks about training disciples, shaping community, and developing leadership structures. These conversation starters offer beginning points for a richer, fuller discussion of traditioned innovation in our current church context. The Didache provides a source of wisdom from our spiritual forebears that modern Christian leaders would do well not to ignore. With a look through the first century window of the Didache, twenty-first century Christians can discover fresh insights for shaping Christian community in the present.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

Distribution of HPV genotypes in cervical intraepithelial lesions and cervical cancer in Tanzanian women.

BACKGROUND: Infection with human papillomavirus (HPV) is associated with uterine cervical intraepithelial neoplasia (CIN) and invasive cancers (ICC). Approximately 80% of ICC cases are diagnosed in under-developed countries. Vaccine development relies on knowledge of HPV genotypes characteristic of LSIL, HSIL and cancer; however, these genotypes remain poorly characterized in many African countries. To contribute to the characterization of HPV genotypes in Northeastern Tanzania, we recruited 215 women from the Reproductive Health Clinic at Kilimanjaro Christian Medical Centre. Cervical scrapes and biopsies were obtained for cytology and HPV DNA detection. RESULTS: 79 out of 215 (36.7%) enrolled participants tested positive for HPV DNA, with a large proportion being multiple infections (74%). The prevalence of HPV infection increased with lesion grade (14% in controls, 67% in CIN1 cases and 88% in CIN2-3). Among ICC cases, 89% had detectable HPV. Overall, 31 HPV genotypes were detected; the three most common HPV genotypes among ICC were HPV16, 35 and 45. In addition to these genotypes, co-infection with HPV18, 31, 33, 52, 58, 68 and 82 was found in 91% of ICC. Among women with CIN2-3, HPV53, 58 and 84/83 were the most common. HPV35, 45, 53/58/59 were the most common among CIN1 cases. CONCLUSIONS: In women with no evidence of cytological abnormalities, the most prevalent genotypes were HPV58 with HPV16, 35, 52, 66 and 73 occurring equally. Although numerical constraints limit inference, findings that 91% of ICC harbor only a small number of HPV genotypes suggests that prevention efforts including vaccine development or adjuvant screening should focus on these genotypes.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Witnessing Crisis in Contemporary and Golden Age Spain

In this volume, experts on the Spanish Golden Age from the United Kingdom, Ireland, and the United States offer analyses of contemporary works that have been influenced by the classics from the sixteenth and seventeenth centuries.

Biogeography in deep time - What do phylogenetics, geology, and paleoclimate tell us about early platyrrhine evolution?

Molecular data have converged on a consensus about the genus-level phylogeny of extant platyrrhine monkeys, but for most extinct taxa and certainly for those older than the Pleistocene we must rely upon morphological evidence from fossils. This raises the question as to how well anatomical data mirror molecular phylogenies and how best to deal with discrepancies between the molecular and morphological data as we seek to extend our phylogenies to the placement of fossil taxa. Here I present parsimony-based phylogenetic analyses of extant and fossil platyrrhines based on an anatomical dataset of 399 dental characters and osteological features of the cranium and postcranium. I sample 16 extant taxa (one from each platyrrhine genus) and 20 extinct taxa of platyrrhines. The tree structure is constrained with a "molecular scaffold" of extant species as implemented in maximum parsimony using PAUP with the molecular-based 'backbone' approach. The data set encompasses most of the known extinct species of platyrrhines, ranging in age from latest Oligocene (∼26 Ma) to the Recent. The tree is rooted with extant catarrhines, and Late Eocene and Early Oligocene African anthropoids. Among the more interesting patterns to emerge are: (1) known early platyrrhines from the Late Oligocene through Early Miocene (26-16.5Ma) represent only stem platyrrhine taxa; (2) representatives of the three living platyrrhine families first occur between 15.7 Ma and 13.5 Ma; and (3) recently extinct primates from the Greater Antilles (Cuba, Jamaica, Hispaniola) are sister to the clade of extant platyrrhines and may have diverged in the Early Miocene. It is probable that the crown platyrrhine clade did not originate before about 20-24 Ma, a conclusion consistent with the phylogenetic analysis of fossil taxa presented here and with recent molecular clock estimates. The following biogeographic scenario is consistent with the phylogenetic findings and climatic and geologic evidence: Tropical South America has been a center for platyrrhine diversification since platyrrhines arrived on the continent in the middle Cenozoic. Platyrrhines dispersed from tropical South America to Patagonia at ∼25-24 Ma via a "Paraná Portal" through eastern South America across a retreating Paranense Sea. Phylogenetic bracketing suggests Antillean primates arrived via a sweepstakes route or island chain from northern South America in the Early Miocene, not via a proposed land bridge or island chain (GAARlandia) in the Early Oligocene (∼34 Ma). Patagonian and Antillean platyrrhines went extinct without leaving living descendants, the former at the end of the Early Miocene and the latter within the past six thousand years. Molecular evidence suggests crown platyrrhines arrived in Central America by crossing an intermittent connection through the Isthmus of Panama at or after 3.5Ma. Any more ancient Central American primates, should they be discovered, are unlikely to have given rise to the extant Central American taxa in situ.

Modeling non-harmonic behavior of materials from experimental inelastic neutron scattering and thermal expansion measurements

Based on thermodynamic principles, we derive expressions quantifying the non-harmonic vibrational behavior of materials, which are rigorous yet easily evaluated from experimentally available data for the thermal expansion coefficient and the phonon density of states. These experimentally- derived quantities are valuable to benchmark first-principles theoretical predictions of harmonic and non-harmonic thermal behaviors using perturbation theory, ab initio molecular-dynamics, or Monte-Carlo simulations. We illustrate this analysis by computing the harmonic, dilational, and anharmonic contributions to the entropy, internal energy, and free energy of elemental aluminum and the ordered compound FeSi over a wide range of temperature. Results agree well with previous data in the literature and provide an efficient approach to estimate anharmonic effects in materials.