Energy Monitoring & Management System (EMMS)

The Energy Monitoring and Management System (EMMS) is developing an electrical power meter to help make electricity more available in energy impoverished regions of the world. The meter fills a unique niche for energy tracking and regulation within micro-grid systems. The EMMS project has partners in Burkina Faso and Zimbabwe: Open Door Development (ODD), the Institut Missiologique du Sahel (IMS), and the Theological College of Zimbabwe (TCZ). Ties are also maintained on a regular basis with IEEE Smart Village for potential future widespread system implementation. Recent work on the EMMS meter has been focused on resolving the last few remaining bugs, establishing a robust communication system, and developing a centralized server-based interface which aids with meter configuration and administration. The team has also begun several future developments which include datalogging and remote access features.https://mosaic.messiah.edu/engr2021/1004/thumbnail.jp

Energy Monitoring and Management System

The Energy Monitoring and Management System facilitates access to electric power in regions with limited energy by increasing energy conservation and education. The solution consists of a meter which allocates a configurable daily energy limit per facility, and a display that provides practical information to the user including reporting how much energy they have used and how much they have left before their power is automatically cut off until the next day. The current version of the system has successfully been installed in multiple facilities in Burkina Faso and Zimbabwe, however software errors are preventing the system from meeting client specifications. To remedy this issue, our team has performed various updates to the software of the meters in preparation in order to distribute a software update to our client. A testing procedure has been implemented to verify functional operation. Mechanical performance issues were also reported about the installed meters. Hardware revisions and design updates have been implemented to resolve the issues. This presentation will detail the steps made to debug module programming and revise hardware design.https://mosaic.messiah.edu/engr2020/1006/thumbnail.jp

PluginPlay: Enabling exascale scientific software one module at a time

For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy’s Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks. This in turn requires a tremendous amount of resources and development time, resources that cannot reasonably be afforded by every computational science project. It thus becomes imperative that computational science transition to a more sustainable paradigm. Key to such a paradigm is modular software. While the importance of modular software is widely recognized, what is perhaps not so widely appreciated is the effort still required to leverage modular software in a sustainable manner. The present manuscript introduces PluginPlay, https://github.com/NWChemEx-Project/PluginPlay, an inversion-of-control framework designed to facilitate developing, maintaining, and sustaining modular scientific software packages. This manuscript focuses on the design aspects of PluginPlay and how they specifically influence the performance of the resulting package. Although, PluginPlay serves as the framework for the NWChemEx package, PluginPlay is not tied to NWChemEx or even computational chemistry. We thus anticipate PluginPlay to prove to be a generally useful tool for a number of computational science packages looking to transition to the exascale.This article is published as Richard, Ryan M., Kristopher Keipert, Jonathan Waldrop, Murat Keçeli, David Williams-Young, Raymond Bair, Jeffery Boschen et al. "PluginPlay: Enabling exascale scientific software one module at a time." The Journal of Chemical Physics 158, no. 18 (2023). DOI: 10.1063/5.0147903. Copyright 2023 AIP Publishing. Posted with permission. DOE Contract Number(s): AC02-07CH11358, 17-SC-20-S

PluginPlay: Enabling exascale scientific software one module at a time

For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy's Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks. This in turn requires a tremendous amount of resources and development time, resources that cannot reasonably be afforded by every computational science project. It thus becomes imperative that computational science transition to a more sustainable paradigm. Key to such a paradigm is modular software. While the importance of modular software is widely recognized, what is perhaps not so widely appreciated is the effort still required to leverage modular software in a sustainable manner. The present manuscript introduces PluginPlay, https://github.com/NWChemEx-Project/PluginPlay, an inversion-of-control framework designed to facilitate developing, maintaining, and sustaining modular scientific software packages. This manuscript focuses on the design aspects of PluginPlay and how they specifically influence the performance of the resulting package. Although, PluginPlay serves as the framework for the NWChemEx package, PluginPlay is not tied to NWChemEx or even computational chemistry. We thus anticipate PluginPlay to prove to be a generally useful tool for a number of computational science packages looking to transition to the exascale

Multigene Profiling of Circulating Tumor Cells (CTCs) for Prognostic Assessment in Treatment-Naïve Metastatic Hormone-Sensitive Prostate Cancer (mHSPC)

The substantial biological heterogeneity of metastatic prostate cancer has hindered the development of personalized therapeutic approaches. Therefore, it is difficult to predict the course of metastatic hormone-sensitive prostate cancer (mHSPC), with some men remaining on first-line androgen deprivation therapy (ADT) for several years while others progress more rapidly. Improving our ability to risk-stratify patients would allow for the optimization of systemic therapies and support the development of stratified prospective clinical trials focused on patients likely to have the greatest potential benefit. Here, we applied a liquid biopsy approach to identify clinically relevant, blood-based prognostic biomarkers in patients with mHSPC. Gene expression indicating the presence of CTCs was greater in CHAARTED high-volume (HV) patients (52% CTChigh) than in low-volume (LV) patients (23% CTChigh; * p = 0.03). HV disease (p = 0.005, q = 0.033) and CTC presence at baseline prior to treatment initiation (p = 0.008, q = 0.033) were found to be independently associated with the risk of nonresponse at 7 months. The pooled gene expression from CTCs of pre-ADT samples found AR, DSG2, KLK3, MDK, and PCA3 as genes predictive of nonresponse. These observations support the utility of liquid biomarker approaches to identify patients with poor initial response. This approach could facilitate more precise treatment intensification in the highest risk patients