Virginia Mason Bainbridge Island Medical Center

A core computational challenge in the analysis of mass spectrometry data is the de novo sequencing problem, in which the generating amino acid sequence is inferred directly from an observed fragmentation spectrum without the use of a sequence database. Recently, deep learning models have made substantial advances in de novo sequencing by learning from massive datasets of high-confidence labeled mass spectra. However, these methods are designed primarily for data-dependent acquisition experiments. Over the past decade, the field of mass spectrometry has been moving toward using data-independent acquisition (DIA) protocols for the analysis of complex proteomic samples owing to their superior specificity and reproducibility. Hence, we present a de novo sequencing model called Cascadia, which uses a transformer architecture to handle the more complex data generated by DIA protocols. In comparisons with existing approaches for de novo sequencing of DIA data, Cascadia achieves substantially improved performance across a range of instruments and experimental protocols.

Historically, safety and efficacy assessment of medical devices began and has continued as standards under the International Organization for Standardization (ISO) rather than under regulatory agency guidelines applied to developing other biomedical product classes. These parallel and unequal pathways have led to multiple and substantive differences in methods and endpoints to determine adverse biological responses among therapeutic classes. Toxicologic pathologists with medical device experience consider standardized nomenclature and diagnostic criteria for medical devices and device-containing combination products as a critical unmet need for nonclinical pathology evaluations. The International Harmonization of Nomenclature and Diagnostic Criteria for Lesions (INHAND) initiative has established globally accepted terminology for proliferative and nonproliferative lesions in various laboratory animal species. Experienced pathologists have identified that some existing INHAND terms for rodents and particularly nonrodents are already used or can be modified for use in medical device studies, but new terms for diagnostic features unique to medical device studies are needed to close gaps in existing INHAND nomenclature. The best approach to establishing appropriate INHAND terms for medical devices (and by extension, device-containing combination products) will be to develop and implement suitable terminology (modified and new, as warranted) to address unmet needs for this distinctive therapeutic class.

The City of Bainbridge Island (COBI) applied for and received technical assistance from the Energy Transitions Initiative Partnership Program (ETIPP) in part to achieve their goal of 100% renewable electricity generation by 2040, five years ahead of the Washington State goal. Their second goal of increasing energy resilience is discussed in this report. Pacific Northwest National Laboratory (PNNL) completed the technical analysis aspects of the project, supported by the community partner Spark Northwest and the program administrator, the National Renewable Energy Laboratory (NREL). PNNL worked with the Community Lead and stakeholders to ensure selection of hazards and energy infrastructure of highest priority and integration of existing expertise into the analysis. We have also worked to align analysis with current activities conducted by Puget Sound Energy (PSE), and other efforts within the Bainbridge Island community around resilience. This report, conducted under the ETIPP project in partnership with COBI, aims to build on this existing knowledge base with a specific energy focus, to identify hazards and threats to critical energy infrastructure, summarize the risk, and identify and analyze remaining resilience gaps.

Abstract This Scientific and Technical Report (STR) provides in-depth fundamentals and guidelines regarding Computational Fluid Dynamics (CFD) simulations of Water Resources Recovery Facilities (WRRFs) unit processes (e.g. headworks, aerobic and anaerobic biological reactors, settling tanks, disinfection). Each unit process is described with respect to: Literature review and process descriptionRelevant CFD concepts and modelling approachCase studiesFuture research needs CFD Modelling for Wastewater Treatment Processes also opens the discussion on two fundamental topics: experimental validation of CFD simulations, and the complementarity between CFD and Chemical Reaction Engineering approaches. This book is intended for undergraduate and graduate students majoring in fields related to wastewater treatment and/or fluid mechanics, as well as researchers and engineers who conduct research and practices in modelling such unit processes. Water resource recovery modelling is not just about lab-scale processes. Now and in the future it is about improving our understanding of (and designing better) full-scale facilities!

Computational fluid dynamics (CFD) modelling in the wastewater treatment (WWT) field is continuing to grow and be used to solve increasingly complex problems. However, the future of CFD models and their value to the wastewater field are a function of their proper application and knowledge of their limits. As has been established for other types of wastewater modelling (i.e. biokinetic models), it is timely to define a good modelling practice (GMP) for wastewater CFD applications. An International Water Association (IWA) working group has been formed to investigate a variety of issues and challenges related to CFD modelling in water and WWT. This paper summarizes the recommendations for GMP of the IWA working group on CFD. The paper provides an overview of GMP and, though it is written for the wastewater application, is based on general CFD procedures. A forthcoming companion paper to provide specific details on modelling of individual wastewater components forms the next step of the working group.

Climate change threatens tropical coastal communities and ecosystems. Governments, resource managers, and communities recognize the value of assessing the social and ecological impacts of climate change, but there is little consensus on the most effective framework to support vulnerability and adaptation assessments. The framework presented in this research is based on a gap analysis developed from the recommendations of climate and adaptation experts. The article highlights social and ecological factors that affect vulnerability to climate change; adaptive capacity and adaptation options informing policy and conservation management decisions; and a methodology including criteria to assess current and future vulnerability to climate change. The framework is intended for conservation practitioners working in developing countries, small island nations, and traditional communities. It identifies core components that assess climate change impacts on coastal communities and environments at the local scale, and supports the identification of locally relevant adaptation strategies. Although the literature supporting vulnerability adaptation assessments is extensive, little emphasis has been placed on the systematic validation of these tools. To address this, we validate the framework using the Delphi technique, a group facilitation technique used to achieve convergence of expert opinion, and address gaps in previous vulnerability assessments.