Jewish Paideia in the Hellenistic Diaspora: Discussing Education, Shaping Identity.

While the integral role of paideia in Greek, Roman, and early Christian history has been widely recognized, the place of paideia in Jewish thought and the resultant influence on late antique Christianity, and thus on Western education as a whole, has been largely neglected. This study examines the theories of ideal Jewish education from three contemporaneous, but unique Diaspora Jews—Philo of Alexandria, the pseudonymous author of the Wisdom of Solomon, and Paul of Tarsus—particularly in light of the role of the Greek Septuagint translations. The purpose is not to locate a unified concept of Jewish Hellenistic paideia, but to allow the views of each author to stand on their own. The diverse educational theories all developed out of a complex amalgam of Jewish and Greco-Roman influences, brought together and reimagined thanks to the Septuagint and the consistent use of paideia as a translation for the Hebrew musar. The translators of the ancient Hebrew scriptures handed down to future generations a textbook and a teacher, a lens through which later Jewish thinkers could merge and morph ancestral traditions with contemporary Platonic and Stoic philosophy in the creation of new and innovative paideutic concepts. With their textbook in hand, these authors would deploy their ideal notions of paideia as a means of contemplating on and shaping the self and Jewish identity. Paideia, then, becomes the mechanism by which the most highly valued constituents of Jewish ethics and culture are formed and employed. The diverse developments in Jewish education explored reveal the varied dynamics both within the Jewish community and between the Jews and the wider cultural world. Paideia became the perfect surrogate, a common, universal good which could touch on every facet determinative in the construction of the self.PhDNear Eastern StudiesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133300/1/jasonzur_1.pd

Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

Global scientific collaborations, such as ATLAS, continue to push the network requirements envelope. Data movement in this collaboration is routinely including the regular exchange of petabytes of datasets between the collection and analysis facilities in the coming years. These requirements place a high emphasis on networks functioning at peak efficiency and availability; the lack thereof could mean critical delays in the overall scientific progress of distributed data-intensive experiments like ATLAS. Network operations staff routinely must deal with problems deep in the infrastructure; this may be as benign as replacing a failing piece of equipment, or as complex as dealing with a multi-domain path that is experiencing data loss. In either case, it is crucial that effective monitoring and performance analysis tools are available to ease the burden of management. We will report on our experiences deploying and using the perfSONAR-PS Performance Toolkit at ATLAS sites in the United States. This software creates a dedicated monitoring server, capable of collecting and performing a wide range of passive and active network measurements. Each independent instance is managed locally, but able to federate on a global scale; enabling a full view of the network infrastructure that spans domain boundaries. This information, available through web service interfaces, can easily be retrieved to create customized applications. The US ATLAS collaboration has developed a centralized “dashboard” offering network administrators, users, and decision makers the ability to see the performance of the network at a glance. The dashboard framework includes the ability to notify users (alarm) when problems are found, thus allowing rapid response to potential problems and making perfSONAR-PS crucial to the operation of our distributed computing infrastructure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98635/1/1742-6596_396_4_042038.pd

Great Plains Network - Kansas State University Agronomy Application Deep Dive

In May 2019, staff members from the Engagement and Performance Operations Center (EPOC) and members of the Great Plains Network (GPN) attending their Annual Meeting meeting met with researchers at Kansas State University (KSU) for the purpose of an Application Deep Dive training session. The goal of this training session was to help characterize the requirements for an agronomy application, to enable cyberinfrastructure support staff to better understand the needs of the researchers they support, and to offer training to GPN members to be able to conduct these on their own. Material for this event includes both the written documentation from the agronomy application at KSU, details about the infrastructure setup at KSU, and also a writeup of the discussion that took place in person on May 20, 2019. EPOC, GPN, and KSU recorded a set of action items for this use case, continuing the ongoing support and collaboration. These are a reflection of the case study report, and in person discussion

Instantiating a Global Network Measurement Framework

perfSONAR is a web services-based infrastructure for collecting and publishing network performance monitoring. A primary goal of perfSONAR is making it easier to solve end-to-end performance problems on paths crossing several networks. It contains a set of services delivering performance measurements in a federated environment. These services act as an intermediate layer, between the performance measurement tools and the diagnostic or visualization applications. This layer is aimed at making and exchanging performance measurements across multiple networks and multiple user communities, using well-defined protocols. This paper summarizes the key perfSONAR components, and describes how they are deployed by the US-LHC community to monitor the networks distributing LHC data from CERN. All monitoring data described herein is publicly available, and we hope the availability of this data via a standard schema will inspire others to contribute to the effort by building network data analysis applications that use perfSONAR

PerfSONAR: A Service Oriented Architecture for Multi-domain Network Monitoring

Abstract. In the area of network monitoring a lot of tools are already available to measure a variety of metrics. However, these tools are often limited to a single administrative domain so that no established methodology for the monitoring of network connections spanning over multiple domains currently exists. In addition, these tools only monitor the network from a technical point of view without providing meaningful network performance indicators for different user groups. These indicators should be derived from the measured basic metrics. In this paper a Service Oriented Architecture is presented which is able to perform multi-domain measurements without being limited to specific kinds of metrics. A Service Oriented Architecture has been chosen as it allows for increased flexibility and scalability in comparison to traditional software engineering techniques. The resulting measurement framework will be applied for measurement

Systematic Evaluation of Candidate Blood Markers for Detecting Ovarian Cancer

Epithelial ovarian cancer is a significant cause of mortality both in the United States and worldwide, due largely to the high proportion of cases that present at a late stage, when survival is extremely poor. Early detection of epithelial ovarian cancer, and of the serous subtype in particular, is a promising strategy for saving lives. The low prevalence of ovarian cancer makes the development of an adequately sensitive and specific test based on blood markers very challenging. We evaluated the performance of a set of candidate blood markers and combinations of these markers in detecting serous ovarian cancer.We selected 14 candidate blood markers of serous ovarian cancer for which assays were available to measure their levels in serum or plasma, based on our analysis of global gene expression data and on literature searches. We evaluated the performance of these candidate markers individually and in combination by measuring them in overlapping sets of serum (or plasma) samples from women with clinically detectable ovarian cancer and women without ovarian cancer. Based on sensitivity at high specificity, we determined that 4 of the 14 candidate markers--MUC16, WFDC2, MSLN and MMP7--warrant further evaluation in precious serum specimens collected months to years prior to clinical diagnosis to assess their utility in early detection. We also reported differences in the performance of these candidate blood markers across histological types of epithelial ovarian cancer.By systematically analyzing the performance of candidate blood markers of ovarian cancer in distinguishing women with clinically apparent ovarian cancer from women without ovarian cancer, we identified a set of serum markers with adequate performance to warrant testing for their ability to identify ovarian cancer months to years prior to clinical diagnosis. We argued for the importance of sensitivity at high specificity and of magnitude of difference in marker levels between cases and controls as performance metrics and demonstrated the importance of stratifying analyses by histological type of ovarian cancer. Also, we discussed the limitations of studies (like this one) that use samples obtained from symptomatic women to assess potential utility in detection of disease months to years prior to clinical detection