Storm power outage prediction modeling

The purpose of this study is to investigate the extent to which librarians in Nigeria engaged in professional development workshops during the COVID-19 era. The study adopted a survey method using an online questionnaire. Factors such as saving money, the free nature of workshops, eliminating travel risk, in the comfort of the home, and providing an opportunity for all were mentioned as the benefits of participating in online workshops using Zoom. Buying data bundle, lack of computer/Android phone/smartphone, ignorance or lack of awareness of up-coming workshops, lack of time, power outage, nonchalant attitude towards technology, and network failures were identified as challenges of participation. The Zoom platform can be adopted for organizing workshops and meetings, and for teaching and learning in the post COVID-19 era.

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Using Mobile Edge-Computing Sensors to Avoid Power Outage Impacts on the Economy

2020 IEEE Green Technologies Conference(GreenTech) ◽

10.1109/greentech46478.2020.9289743 ◽

2020 ◽

Author(s):

John L. Lauletta ◽

Rachana Shukthija Dassari ◽

Yilmaz Sozer ◽

Jose Alexis De Abreu-Garcia

Keyword(s):

Edge Computing ◽

Mobile Edge Computing ◽

Power Outage

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Proteomics of Primary Uveal Melanoma: Insights into Metastasis and Protein Biomarkers

Cancers ◽

10.3390/cancers13143520 ◽

2021 ◽

Vol 13 (14) ◽

pp. 3520

Author(s):

Geeng-Fu Jang ◽

Jack S. Crabb ◽

Bo Hu ◽

Belinda Willard ◽

Helen Kalirai ◽

...

Keyword(s):

Immune System ◽

Uveal Melanoma ◽

Immune Therapy ◽

Protein Biomarkers ◽

Prediction Modeling ◽

Liver Histopathology ◽

Discriminatory Accuracy ◽

Melanoma Metastases ◽

Study Support ◽

Mascot Search Engine

Uveal melanoma metastases are lethal and remain incurable. A quantitative proteomic analysis of 53 metastasizing and 47 non-metastasizing primary uveal melanoma (pUM) was pursued for insights into UM metastasis and protein biomarkers. The metastatic status of the pUM specimens was defined based on clinical data, survival histories, prognostic analyses, and liver histopathology. LC MS/MS iTRAQ technology, the Mascot search engine, and the UniProt human database were used to identify and quantify pUM proteins relative to the normal choroid excised from UM donor eyes. The determined proteomes of all 100 tumors were very similar, encompassing a total of 3935 pUM proteins. Proteins differentially expressed (DE) between metastasizing and non-metastasizing pUM (n = 402) were employed in bioinformatic analyses that predicted significant differences in the immune system between metastasizing and non-metastasizing pUM. The immune proteins (n = 778) identified in this study support the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as possible candidates for immune therapy checkpoint blockade. Prediction modeling identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy, supporting the potential for protein-based prognostic methods for detecting UM metastasis.

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Pressure Prediction Modeling and Validation for Lithium-Ion Pouch Cells in Buffered Module Assemblies

Journal of Energy Storage ◽

10.1016/j.est.2021.102517 ◽

2021 ◽

Vol 40 ◽

pp. 102517

Author(s):

Severin Hahn ◽

Sebastian Theil ◽

Jan Kroggel ◽

Kai Peter Birke

Keyword(s):

Lithium Ion ◽

Prediction Modeling

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Assessing the Energy Resilience of Office Buildings: Development and Testing of a Simplified Metric for Real Estate Stakeholders

Buildings ◽

10.3390/buildings11030096 ◽

2021 ◽

Vol 11 (3) ◽

pp. 96

Author(s):

Paul Mathew ◽

Lino Sanchez ◽

Sang Hoon Lee ◽

Travis Walter

Keyword(s):

Regression Models ◽

Health And Safety ◽

Office Buildings ◽

Extreme Weather Events ◽

Economic Losses ◽

Power Outage ◽

Continuity Of Operations ◽

Quasi Monte Carlo ◽

Building Characteristics ◽

The Impact

Increasing concern over higher frequency extreme weather events is driving a push towards a more resilient built environment. In recent years there has been growing interest in understanding how to evaluate, measure, and improve building energy resilience, i.e., the ability of a building to provide energy-related services in the event of a local or regional power outage. In addition to human health and safety, many stakeholders are keenly interested in the ability of a building to allow continuity of operations and minimize business disruption. Office buildings are subject to significant economic losses when building operations are disrupted due to a power outage. We propose “occupant hours lost” (OHL) as a means to measure the business productivity lost as the result of a power outage in office buildings. OHL is determined based on indoor conditions in each space for each hour during a power outage, and then aggregated spatially and temporally to determine the whole building OHL. We used quasi-Monte Carlo parametric energy simulations to demonstrate how the OHL metric varies due to different building characteristics across different climate zones and seasons. The simulation dataset was then used to develop simple regression models for assessing the impact of ten key building characteristics on OHL. The most impactful were window-to-wall ratio and window characteristics. The regression models show promise as a simple means to assess and screen for resilience using basic building characteristics, especially for non-critical facilities where it may not be viable to conduct detailed engineering analysis.

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