Pathfinding in Games

Commercial games can be an excellent testbed to artificial intelligence (AI) research, being a middle ground between synthetic, highly abstracted academic benchmarks, and more intricate problems from real life. Among the many AI techniques and problems relevant to games, such as learning, planning, and natural language processing, pathfinding stands out as one of the most common applications of AI research to games. In this document we survey recent work in pathfinding in games. Then we identify some challenges and potential directions for future work. This chapter summarizes the discussions held in the pathfinding workgroup

Documenting Bronze Age Akrotiri on Thera using laser scanning, image-based modelling and geophysical prospection

The excavated architecture of the exceptional prehistoric site of Akrotiri on the Greek island of Thera/Santorini is endangered by gradual decay, damage due to accidents, and seismic shocks, being located on an active volcano in an earthquake-prone area. Therefore, in 2013 and 2014 a digital documentation project has been conducted with support of the National Geographic Society in order to generate a detailed digital model of Akrotiri’s architecture using terrestrial laser scanning and image-based modeling. Additionally, non-invasive geophysical prospection has been tested in order to investigate its potential to explore and map yet buried archaeological remains. This article describes the project and the generated results

SILS MRAT: A Multi-Agent Decision-Support System for Shipboard Integration of Logistics Systems

This report describes work performed by CDM Technologies Inc. on subcontract to ManTech Advanced Systems International, Inc. (Fairmont, West Virginia), and under sponsorship of the Office of Naval Research (ONR). The principal aim of the SILS (Shipboard Integration of Logistics Systems) project is to provide a decision-support capability for Navy ships that integrates shipboard logistical and tactical systems within a near real-time, automated, computer-based shipboard readiness and situation awareness facility. Specifically, SILS is intended to provide the captain of a ship and his staff with an accurate evaluation of the current condition of the ship, based on the ability of all of its equipment, services and personnel to perform their intended functions. The SILS software system consists of two main subsystems, namely: the SILS IE (Interface Engine) subsystem for information interchange with heterogeneous external applications, developed by ManTech Advanced Systems International; and, the SILS MRAT (Mission Readiness Analysis Toolkit) subsystem for intelligent decision-support with collaborative software agents, developed by CDM Technologies. This report is focused specifically on the technical aspects of the SILS MRAT subsystem. The automated reasoning capabilities of SILS MRAT are supported by a knowledge management architecture that is based on information-centric principles. Such an architecture utilizes a virtual model of the real world problem situation, consisting of data objects with characteristics and a rich set of relationships. Commonly referred to as an ontology, this internal information model provides a common vocabulary and context for software agents with reasoning capabilities. The concurrent need for incremental capability increases implies a steadily increasing data load from diverse operational (dynamic) and historical (static) data sources, ranging from free text messages and Web content to highly structured data contained in consolidated operational data stores, Data Warehouses, and Data Marts. In order to provide useful high-level capabilities the architecture is required to support the transformation of these data flows into information and knowledge relevant to the concerns and operational context of individual shipboard users. Accordingly, the system must be capable of not only storing data but also the relationships and higher level concepts that place the data into context. For this reason, to manage an increasing number of relationships and concepts over time, the SILS MRAT subsystem was designed to employ a formalized ontological framework. There were four additional considerations in the selection of the overall SILS architecture. First, utility to support a useful level of automated information management (i.e., the ability to collaboratively analyze data, monitor dynamic operational context, formulate warnings and alerts, and generate recommendations). Second, flexibility to accommodate contributions from multiple team members that may employ differing technologies and implementation paradigms. Third, scalability to allow a progressive increase in the breadth and diversity of the data sources, the volume of data processed, the number of validated components, and the intelligence of the tools (i.e., agents). Fourth, adaptability to facilitate the tailoring of the information management capabilities to different data sources and existing data environments. The current SILS architecture addresses these desirable characteristics by partitioning the system into a lower-level data collection and integration layer, a higher-level information management layer (SILS MRAT), and a translation facility that is capable of mapping the data schema of the lower layer to the information representation (i.e., ontology) of the upper layer (SILS IE). The higher-level information management layer provides a collaborative, distributed communication facility that supports the development of semi-autonomous modules of capability referred to as agents. The agents employ the formalized ontology supported by the communication facility to collaborate with each other and the human users in a meaningful manner

The Design and Methodology of the Ohio COVID-19 Survey

Background: Governments worldwide are balancing contrasting needs to curtail the toll that coronavirus disease 2019 (COVID-19) takes on lives and health care systems and to preserve their economies. To support decisions, data that simultaneously measure the health status of the population and the economic impact of COVID-19 mitigation strategies are needed. In the United States, prior to the onset of COVID-19, surveys or tracking systems usually focused on public health or economic indicators, but not both. However, tracking public health and economic measures together allow policy makers and epidemiologists to understand how policy and program decisions are associated. The Ohio COVID-19 Survey (OCS) attempts to track both measures in Ohio as one of the first statewide population surveys on COVID-19. To achieve this there are several methodological challenges which need to be overcome. Methods: The OCS utilizes a representative panel offering both cross-sectional and longitudinal analyses. It targets 700 to 1000 respondents per week for a total of 12 600 to 18 000 respondents over an 18-week period. Leveraging a sample of 24 000 adult Ohioans developed from a statewide population health survey conducted in fall 2019, the OCS produces weekly economic and health measures that can be compared to baseline measures obtained before the COVID-19 pandemic began. Results: The OCS was able to quickly launch and achieve high participation (45.2%) and retention across waves. Conclusion: The OCS demonstrates how it is possible to leverage an existing health-based survey in Ohio to generate a panel which can be used to quickly track fast-breaking health issues like COVID-19

Global transformations and “Cosmopolitical” Social Science

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Energy and Electron Transfer Dynamics within a Series of Perylene Diimide/Cyclophane Systems.

Artificial photosynthetic systems for solar energy conversion exploit both covalent and supramolecular chemistry to produce favorable arrangements of light-harvesting and redox-active chromophores in space. An understanding of the interplay between key processes for photosynthesis, namely light-harvesting, energy transfer, and photoinduced charge separation and the design of novel, self-assembling components capable of these processes are imperative for the realization of multifunctional integrated systems. We report our investigations on the potential of extended tetracationic cyclophane/perylene diimide systems as components for artificial photosynthetic applications. We show how the selection of appropriate heterocycles, as extending units, allows for tuning of the electron accumulation and photophysical properties of the extended tetracationic cyclophanes. Spectroscopic techniques confirm energy transfer between the extended tetracationic cyclophanes and perylene diimide is ultrafast and quantitative, while the heterocycle specifically influences the energy transfer related parameters and the acceptor excited state.S.T.J.R. thanks the Cambridge Home and European Scholarship Scheme and the Robert Gardiner memorial scholarship. S.T.J.R., A.F. and O.A.S. thank the ERC starting investigator grant ASPiRe (project no. 240629) and the EPSRC (reference no. EP/G060649/1). Femtosecond and nanosecond spectroscopy (R.M.Y.), EPR spectroscopy (M.D.K.) and phosphorescence spectroscopy (Y.W.) were supported as part of the ANSER Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under award no. DE-SC0001059. J.F.S., J.J.H., N.H., N.A.V. and E.D.J. acknowledge the Joint Center of Excellence in Integrated Nano-Systems (JCIN) between KACST and Northwestern University (Project 34-946) for their continued financial support. E.J.D. acknowledges NSF and Ryan fellowships. A.H. and W.M.N. thank the COST Action CM1005 “Supramolecular Chemistry in Water” and the DFG (grant NA-686/5) for financial support.This is the author accepted manuscript. The final version is available from the American Chemical Society via http://dx.doi.org/10.1021/jacs.5b1032

A Checklist for Medication Compliance and Persistence Studies Using Retrospective Databases

The increasing number of retrospective database studies related to medication compliance and persistence (C&P), and the inherent variability within each, has created a need for improvement in the quality and consistency of medication C&P research. This article stems from the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) efforts to develop a checklist of items that should be either included, or at least considered, when a retrospective database analysis of medication compliance or persistence is undertaken. This consensus document outlines a systematic approach to designing or reviewing retrospective database studies of medication C&P. Included in this article are discussions on data sources, measures of C&P, results reporting, and even conflict of interests. If followed, this checklist should improve the consistency and quality of C&P analyses, which in turn will help providers and payers understand the impact of C&P on health outcomes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75562/1/j.1524-4733.2006.00139.x.pd

Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages

This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments

Discrimination of SARS-CoV-2 Infections From Other Viral Respiratory Infections by Scent Detection Dogs

Background: Testing of possibly infected individuals remains cornerstone of containing the spread of SARS-CoV-2. Detection dogs could contribute to mass screening. Previous research demonstrated canines' ability to detect SARS-CoV-2-infections but has not investigated if dogs can differentiate between COVID-19 and other virus infections. Methods: Twelve dogs were trained to detect SARS-CoV-2 positive samples. Three test scenarios were performed to evaluate their ability to discriminate SARS-CoV-2-infections from viral infections of a different aetiology. Naso- and oropharyngeal swab samples from individuals and samples from cell culture both infected with one of 15 viruses that may cause COVID-19-like symptoms were presented as distractors in a randomised, double-blind study. Dogs were either trained with SARS-CoV-2 positive saliva samples (test scenario I and II) or with supernatant from cell cultures (test scenario III). Results: When using swab samples from individuals infected with viruses other than SARS-CoV-2 as distractors (test scenario I), dogs detected swab samples from SARS-CoV-2-infected individuals with a mean diagnostic sensitivity of 73.8% (95% CI: 66.0–81.7%) and a specificity of 95.1% (95% CI: 92.6–97.7%). In test scenario II and III cell culture supernatant from cells infected with SARS-CoV-2, cells infected with other coronaviruses and non-infected cells were presented. Dogs achieved mean diagnostic sensitivities of 61.2% (95% CI: 50.7–71.6%, test scenario II) and 75.8% (95% CI: 53.0–98.5%, test scenario III), respectively. The diagnostic specificities were 90.9% (95% CI: 87.3–94.6%, test scenario II) and 90.2% (95% CI: 81.1–99.4%, test scenario III), respectively. Conclusion: In all three test scenarios the mean specificities were above 90% which indicates that dogs can distinguish SARS-CoV-2-infections from other viral infections. However, compared to earlier studies our scent dogs achieved lower diagnostic sensitivities. To deploy COVID-19 detection dogs as a reliable screening method it is therefore mandatory to include a variety of samples from different viral respiratory tract infections in dog training to ensure a successful discrimination process.Peer Reviewe