The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

Informal gold mining and mercury pollution in Brazil

The Amazon region has been responsible for a major share of Brazilian gold production in recent years. The region has witnessed a sizable gold rush comparable only to the California gold rush last century. The gold rush has spawned a powerful informal mining sector and has attracted many people - some who have come to the region in search of wealth and some who were already there but were displaced from other, unsuccessful economicactivities. What these people encounter at the mining sites are dreadful living and working conditions. Gold mining also causes substantial environmental problems, which may persist whether gold deposits do or not. The author discusses the environmental effects of gold mining in the region, focusing on mercury pollution. Mercury, an important input in gold extraction, is being discharged into the atmosphere and the rivers at alarming rates. The environmental costs of the present extraction, is being discharged into the atmosphere and the rivers at alarming rates. The environmental costs of the present extraction technology will be faced primarily by future generations, because of natural chemical processes. Although removing the mercury already discharged from the Amazonian environment may be an enormous task, at least future discharges should be curtailed through the use of appropriate technology, environmental education, and a combination of command and control measures and market-based incentives. The author describes the gold extraction process and the extent of mercury use and contamination. He analyzes key elements of the environmental problem, especially the informal miner and the fish economy. Finally, he suggests a combination of command and control regulations and market-based incentives adapted to the informal gold mining economic environment. He emphasizes the need for an education campaign about the perils of using mercury and the availability of more appropriate, and inexpensive, alternative extraction technologies.Mining&Extractive Industry (Non-Energy),Montreal Protocol,Water and Industry,Coastal and Marine Resources,Primary Metals

Multi-site Event Discrimination in Large Liquid Scintillation Detectors

Simulation studies have been carried out to explore the ability to discriminate between single-site and multi-site energy depositions in large scale liquid scintillation detectors. A robust approach has been found that is predicted to lead to a significant statistical separation for a large variety of event classes, providing a powerful tool to discriminate against backgrounds and break important degeneracies in signal extraction. This has particularly relevant implications for liquid scintillator searches for neutrinoless double beta decay ($0\nu\beta\beta$) from $^{130}$Te and $^{136}$Xe, where it is possible for a true $0\nu\beta\beta$ signal to be distinguished from most radioactive backgrounds (including those from cosmogenic production) as well as unknown gamma lines from the target isotope.Comment: 20 pages, 10 figure

Another Look at Confidence Intervals: Proposal for a More Relevant and Transparent Approach

The behaviors of various confidence/credible interval constructions are explored, particularly in the region of low statistics where methods diverge most. We highlight a number of challenges, such as the treatment of nuisance parameters, and common misconceptions associated with such constructions. An informal survey of the literature suggests that confidence intervals are not always defined in relevant ways and are too often misinterpreted and/or misapplied. This can lead to seemingly paradoxical behaviours and flawed comparisons regarding the relevance of experimental results. We therefore conclude that there is a need for a more pragmatic strategy which recognizes that, while it is critical to objectively convey the information content of the data, there is also a strong desire to derive bounds on models and a natural instinct to interpret things this way. Accordingly, we attempt to put aside philosophical biases in favor of a practical view to propose a more transparent and self-consistent approach that better addresses these issues.Comment: 23 pages, 11 figure

From text to interaction: The digital advance directive method for advance directives

Advance directives allow people to specify individual treatment preferences in case of decision-making incapacity involving decisions of utmost importance. There are many tools that provide information on the topic, digital forms for structured data input, or platforms that support data storage and availability. Yet, there is no tool supporting the innermost process of an advance directive: decision making itself. To address this issue, we developed a visual-interactive, semi-quantitative method for generating digital advance directives (DiADs) that harnesses the potential of digitalization in healthcare. In this article, we describe the DiAD method and its app lined with the exemplary narrative of user Mr S. linking the theory to an exemplary use case. The DiAD method is intended to lower barriers and increase comfort in creating an advance directive by shifting the focus from heavily text-based processes to visual representation and interaction, that is, from text to reflection. Keywords: Advance directive; data model; data representation; digital healthcare; visual-interactive application

The Advance Care Compass- A New Mechanics for Digitally Transforming Advance Directives

Advance directives allow people to declare their treatment preferences for a potential future state of incompetency. Covid-19, with its high numbers of quickly deteriorating patients requiring intensive care, has acutely demonstrated how helpful it would be for clinicians to have reliable, readily available, up-to-date information at hand to be able to act in accordance with what the individual patient would have wanted. Yet for the past few decades advance directives have fallen short of their potential, for various reasons. At worst, advance directives are perceived as unwieldy legal documents that put excessive demands on patients without providing useful guidance for better care. Recent efforts such as advance care planning have tried to remedy some of these shortcomings but have so far met with limited success. We suggest a new concept-the Advance Care Compass-that harnesses the potential of digitalization in healthcare to overcome many of difficulties encountered so far