TRMM Version 7 Near-Realtime Data Products

The TRMM data system has been providing near-realtime data products to the community since late 1999. While the TRMM project never had near-realtime production requirements, the science and applications communities had a great interest in receiving TRMM data as quickly as possible. As a result these NRT data are provided under a best-effort scenario but with the objective of having the swath data products available within three hours of data collection 90% of the time. In July of 2011 the Joint Precipitation Measurement Missions Science Team (JPST) authorized the reprocessing of TRMM mission data using the new version 7 algorithms. The reprocessing of the 14+ years of the mission was concluded within 30 days. Version 7 algorithms had substantial changes in the data product file formats both for data and metadata. In addition, the algorithms themselves had major modifications and improvements. The general approach to versioning up the NRT is to wait for the regular production algorithms to have run for a while and shake out any issues that might arise from the new version before updating the NRT products. Because of the substantial changes in data/metadata formats as well as the algorithm improvements themselves, the update of NRT to V7 followed an even more conservative path than usual. This was done to ensure that applications agencies and other users of the TRMM NRT would not be faces with short-timeframes for conversion to the new format. This paper will describe the process by which the TRMM NRT was updated to V7 and the V7 data products themselves

The Image 1994: Soaring To The Top

Rowan College of New Jersey yearbook for the Class of 1994; 184 pages. Contents: Soaring to the Top p. 4, Seniors p. 17, Graduation p. 93, Faculty and Administration p. 98, Athletics p. 113, Organizations p. 150, Yearbook Staff p. 174.https://rdw.rowan.edu/yearbooks/1037/thumbnail.jp

The shift from sterling to the dollar 1965-76: evidence from Australia and New Zealand

The management of foreign exchange reserves has recently attracted attention from both policy-makers and historians. Historical research has focussed on the nineteenth century and the interwar period, with less attention to the strategies of smaller countries in the final transition from sterling to the dollar in the post-1945 period. This article examines the evolution of reserve currency policy from the perspective of Australia and New Zealand in the 1960s and early 1970s. As in the 1930s, economic uncertainty and a shift in global economic power prompted changes in reserves strategy. Patterns of trade and debt and falling confidence in British economic policy prompted a move away from sterling, but the timing and extent of this transition were affected by the fragility of the sterling exchange rate, lack of alternative assets, and continued dependence on the London capital market. The choices for Australia and New Zealand were thus constrained, but they were able to leverage their position as holders of sterling to engage in agreements that provided an exchange rate guarantee for their sterling holdings and continued access to the London capital market. This mitigated the effect of the final global transition from sterling to the dollar while protecting their interests

Interleukin-23 is critical for full-blown expression of a non-autoimmune destructive arthritis and regulates interleukin-17A and RORγt in γδ T cells

Introduction: Interleukin (IL)-23 is essential for the development of various experimental autoimmune models. However, the role of IL-23 in non-autoimmune experimental arthritis remains unclear. Here, we examined the role of IL-23 in the non-autoimmune antigen-induced arthritis (AIA) model. In addition, the regulatory potential of IL-23 in IL-17A and retinoic acid-related orphan receptor gamma t (RORγt) expression in CD4+and TCRγδ+T cells was evaluated systemically as well as at the site of inflammation.Methods: Antigen-induced arthritis was induced in wild-type, IL-23p19-deficient and IL-17 Receptor A - knockout mice. At differe

Modular architecture providing convergent and ubiquitous intelligent connectivity for networks beyond 2030

The transition of the networks to support forthcoming beyond 5G (B5G) and 6G services introduces a number of important architectural challenges that force an evolution of existing operational frameworks. Current networks have introduced technical paradigms such as network virtualization, programmability and slicing, being a trend known as network softwarization. Forthcoming B5G and 6G services imposing stringent requirements will motivate a new radical change, augmenting those paradigms with the idea of smartness, pursuing an overall optimization on the usage of network and compute resources in a zero-trust environment. This paper presents a modular architecture under the concept of Convergent and UBiquitous Intelligent Connectivity (CUBIC), conceived to facilitate the aforementioned transition. CUBIC intends to investigate and innovate on the usage, combination and development of novel technologies to accompany the migration of existing networks towards Convergent and Ubiquitous Intelligent Connectivity (CUBIC) solutions, leveraging Artificial Intelligence (AI) mechanisms and Machine Learning (ML) tools in a totally secure environment

Molecularly defined circuitry reveals input-output segregation in deep layers of the medial entorhinal cortex

SummaryDeep layers of the medial entorhinal cortex are considered to relay signals from the hippocampus to other brain structures, but pathways for routing of signals to and from the deep layers are not well established. Delineating these pathways is important for a circuit level understanding of spatial cognition and memory. We find that neurons in layers 5a and 5b have distinct molecular identities, defined by the transcription factors Etv1 and Ctip2, and divergent targets, with extensive intratelencephalic projections originating in layer 5a, but not 5b. This segregation of outputs is mirrored by the organization of glutamatergic input from stellate cells in layer 2 and from the hippocampus, with both preferentially targeting layer 5b over 5a. Our results suggest a molecular and anatomical organization of input-output computations in deep layers of the MEC, reveal precise translaminar microcircuitry, and identify molecularly defined pathways for spatial signals to influence computation in deep layers