Letter from Richard M. Kovacevich, Group Executive with Citibank, to Geraldine Ferraro

Congratulatory letter from Richard M. Kovacevich, Citibank Executive, to Geraldine Ferraro. Includes data entry sheet.https://ir.lawnet.fordham.edu/vice_presidential_campaign_correspondence_1984_new_york/1264/thumbnail.jp

American Society for Parenteral and Enteral Nutrition Guidelines for the Selection and Care of Central Venous Access Devices for Adult Home Parenteral Nutrition Administration

This document represents the American Society for Parenteral and Enteral Nutrition (ASPEN) clinical guidelines to describe best practices in the selection and care of central venous access devices (CVADs) for the infusion of home parenteral nutrition (HPN) admixtures in adult patients. The guidelines targeted adults >18 years of age in which the intervention or exposure had to include HPN that was administered via a CVAD. Case studies, non‐English studies, or studies of CVAD no longer available in the United States were excluded. In total, 564 abstract citations, 350 from Medline and 214 from PubMed/non‐MEDLINE databases, were scanned for relevance. Of the 564 citations, 13 studies addressed at least 1 of the 6 guideline‐related questions, and none of the studies were prospective and randomized. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria were used to adjust the evidence grade based on assessment of the quality of study design and execution. Recommendations for the CVAD type, composition, or number of lumens to minimize infectious or mechanical complications are based on a limited number of studies and expert opinion of the authors, all very experienced in home infusion therapy. No studies were found that compared best solutions for routine flushing of lumens (eg, heparin versus saline) or for maintaining catheters in situ while treating CVAD mechanical or infectious complications. It is clear that studies to answer these questions are very limited, and further research is needed. These clinical guidelines were approved by the ASPEN Board of Directors.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147811/1/jpen1455_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147811/2/jpen1455.pd

Association of Parenteral Nutrition Catheter Sepsis with Urinary Tract Infections

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141954/1/jpen0639.pd

Clinical Rounds With Nutrition Support Services

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68406/2/10.1177_011542659400900273.pd

Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization

Ethanol‐Lock Therapy for the Prevention of Central Venous Access Device Infections in Pediatric Patients With Intestinal Failure

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141158/1/jpen0067.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141158/2/jpen0067-sup-0001.pd

Searches for Neutrinos from Gamma-Ray Bursts Using the IceCube Neutrino Observatory

Gamma-ray bursts (GRBs) are considered as promising sources of ultra-high-energy cosmic rays (UHECRs) due to their large power output. Observing a neutrino flux from GRBs would offer evidence that GRBs are hadronic accelerators of UHECRs. Previous IceCube analyses, which primarily focused on neutrinos arriving in temporal coincidence with the prompt gamma-rays, found no significant neutrino excess. The four analyses presented in this paper extend the region of interest to 14 days before and after the prompt phase, including generic extended time windows and targeted precursor searches. GRBs were selected between 2011 May and 2018 October to align with the data set of candidate muon-neutrino events observed by IceCube. No evidence of correlation between neutrino events and GRBs was found in these analyses. Limits are set to constrain the contribution of the cosmic GRB population to the diffuse astrophysical neutrino flux observed by IceCube. Prompt neutrino emission from GRBs is limited to ≲1% of the observed diffuse neutrino flux, and emission on timescales up to 104 s is constrained to 24% of the total diffuse flux.Peer Reviewe

Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube

The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstruction tasks. Many of these applications have been adopted from other domains. However, data in the field of physics are unique in the context of machine learning, insofar as their generation process and the laws and symmetries they abide by are usually well understood. Most commonly used deep learning architectures fail at utilizing this available information. In contrast, more traditional likelihood-based methods are capable of exploiting domain knowledge, but they are often limited by computational complexity. In this contribution, a hybrid approach is presented that utilizes generative neural networks to approximate the likelihood, which may then be used in a traditional maximum-likelihood setting. Domain knowledge, such as invariances and detector characteristics, can easily be incorporated in this approach. The hybrid approach is illustrated by the example of event reconstruction in IceCube