Digital Music Notation Data Model and Prototype Delivery System

The UVa Library requests $161,175 in outright funds from NEH to collaborate with the University of Paderborn in Detmold, Germany, to produce a Music Encoding Initiative (MEI) demonstration project and to engage in dissemination efforts that will establish MEI as the predominant academic encoding standard for music notation. The demonstration project will include basic software for transforming material into MEI, a searchable archive of representative MEI-encoded data, and a prototype delivery system for items in the archive. This will allow the scholarly community to overcome the limitations of today's printed editions by extending the potential of digital editions, implementing new methodological techniques for music research, and facilitating collaboration between musicologists

Digital Music Notation Data Model and Prototype Delivery System

The U.Va. Library requests $44,164 in outright funds from NEH to collaborate with the University of Paderborn in Detmold, Germany, in conducting two workshops, one to be held in summer 2009 and one in spring 2010, which will promote an international collaboration to create a music notation data model and prototype delivery system. We intend to engage a select group of international scholars and technologists with a broad range of expertise in discussing the features and functions required in a scholarly XML music notation model, critically evaluate the existing data models, discuss optimum solutions for achieving the desired features, and plan for future implementation of the solutions. Our long-term plans include applying for further grant funding to continue to develop this project after this basic collaboration is complete

Regulatory Changes in Power Systems Explored with Explainable Artificial Intelligence

A stable supply of electrical energy is essential for the functioning of our society. Therefore, the electrical power grid's operation and energy and balancing markets are subject to strict regulations. As the external technical, economic, or social influences on the power grid change, these regulations must also be constantly adapted. However, whether these regulatory changes lead to the intended results is not easy to assess. Could eXplainable Artificial Intelligence (XAI) models distinguish regulatory settings and support the understanding of the effects of these changes? In this article, we explore two examples of regulatory changes in the German energy markets for bulk electricity and for reserve power. We explore the splitting of the German-Austrian bidding zone and changes in the pricing schemes of the German balancing energy market. We find that boosted tree models and feedforward neural networks before and after a regulatory change differ in their respective parametrizations. Using Shapley additive explanations, we reveal model differences, e.g. in terms of feature importances, and identify key features of these distinct models. With this study, we demonstrate how XAI can be applied to investigate system changes in power systems.Comment: 7 pages, 3 figure

Smart Charging of Electric Vehicles with Cloud-based Optimization and a Lightweight User Interface – A Real-World Application in the Energy Lab 2.0: Poster

Smart Charging (SC) of Electric Vehicles (EVs) integrates them into the power system to support grid stability by power management. Large-scale adoption of SC requires a high level of EV user acceptance. Therefore, it is imperative to make the underlying charging scheme tangible for the user. We propose a web app for the user to start, adjust and monitor the charging process via a User Interface (UI). We outline the integration of this web app into an Internet of Things (IoT) architecture to establish communication with the charging station. Two scenarios demonstrate the operation of the system. Future field studies on SC should involve the EV user due to individual preferences and responses to incentive schemes. Therefore, we propose the Smart Charging Wizard with a customizable UI and optimization module for future research and collaborative development

Energy Hub Gas: A Modular Setup for the Evaluation of Local Flexibility and Renewable Energy Carriers Provision

The ambitious targets for the reduction of green-house gas (GHG) emissions force the enhanced integration and installation of Renewable Energy Sources (RESs). Furthermore, the increased reliance of multiple sectors on electrical energy additionally challenges the electricity grid with high volatility from the demand side. In order to keep the transmission system operation stable and secure, the present approach adds local flexibility into the distribution system using the modular Energy Hub Gas (EHG) concept. For this concept, two different test cases are configured and evaluated. The two configured EHGs demonstrate the ability to provide flexibility and adaptability by reducing the difference between maximal and minimal load in the surrounding grid infrastructure by 30% in certain time periods. Furthermore, the average energy exchange is reduced by 8%. Therefore, by relieving the grid infrastructure in the local surrounding, the additional potential of RES is enabled and curtailment of existing ones can be reduced

Expression of submaxillary gland androgen-regulated protein 3A (SMR3A) in adenoid cystic carcinoma of the head and neck

Background: Adenoid cystic carcinoma of the head and neck (ACC) is a rare tumor entity which originates from the salivary glands. The prognosis remains poor, as the tumor tends to exhibit perineural invasion and frequently develops distant metastases. The submaxillary gland androgen-regulated protein 3A (SMR3A) belongs to a gene family producing opiorphin homologs and is physiologically secreted by salivary glands. Expression of SMR3A has been identified as an unfavorable risk factor in survival of patients with squamous cell carcinoma in the head and neck, but its value as a prognostic biomarker for ACC has not been addressed. Materials and Methods: Tissue sections from primary ACC (n=86) and healthy glandular tissue as reference, were stained by immunohistochemistry. SMR3A expression levels were correlated with clinical and pathological features, including overall survival. Results: All patients had undergone surgery and 67 received adjuvant radiotherapy. The median disease-free survival (DFS) was 37 months and the median overall survival (OS) was 75 months. Prominent SMR3A expression in tumor cells was found in 24 of 86 patients (27,9%), and was inversely correlated with a male gender (p=0.009). There was no significant correlation between SMR3A expression and DFS, metastasis-free survival or OS. Conclusion: Our data demonstrate for the first time decreased levels of SMR3A in ACC compared to normal glandular tissue. These data suggest a context-dependent regulation of SMR3A expression in the pathogenesis of distinct subtypes of head and neck tumors, and support the assumption that detection of SMR3A expression serves as a surrogate for aberrant differentiation into mucosal- or glandular-like cells in ACC and head and neck squamous cell carcinoma

Energy Hub Gas : A Multi-Domain System Modelling and Co-Simulation Approach

Coping with the complexity of future energy grids and the rising challenges of the energy transition to more renewable energy sources (RES), an Energy Hub Gas (EHG) concept appears to be a promising approach. This concept combines various technical components to a sector-coupling system network to support the electricity grid with ancillary and balancing services to cope with the fluctuating generation by RES and to provide (renewable) energy carriers. Additionally, the EHG serves as regional gateway and as a converter for large, centralized RES-feed-in and aggregation/distribution hub of local RES-feed-in. For combining several separate models from different domains to an EHG system model, a co-simulation approach is used with high regard on flexibility concerning the modelling aspects as well as high modularity to easily adapt the concept to further use cases. As main results presented in the paper, the coherence of the extended EHG system model and its usability for implementation in co-simulation can be shown in first simulations