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Every year new safety features and regulations are employed within the process industry to reduce risks associated with operations. Despite these advancements chemical plants remain hazardous places, and the role of the engineer will always involve risk mitigation through real time decision making. Results from a previous study by Kongsvik et al., 2015 indicated that there were three types of decisions in major chemical plants: strategic decisions, operational decisions, and instantaneous decisions. The study showed the importance for improving upon engineers’ operational and instantaneous choices when tasked with quick solutions in the workforce. In this research study, we dive deeper to understand how senior chemical engineering students’ prioritize components of decision making such as budget, productivity, relationships, safety, and time, and how this prioritization may change as a result of participation in a digital immersive training environment called Contents Under Pressure. More specifically, we seek to address the following two research questions: (1) How do senior chemical engineering students prioritize safety in comparison to criteria such as budget, personal relationships, plant productivity, and time in a process safety context, and (2) How does senior chemical engineering students’ prioritization of decision making criteria (budget, personal relationships, plant productivity, safety, and time) change after exposure to a virtual process safety decision making environment? As part of this study, 187 senior chemical engineering students from three separate institutions completed a pre- and post-reflection survey around their engagement with Contents Under Pressure and asked them to rank their prioritizations of budget, productivity, relationships, safety, and time. Data was analyzed using descriptive statistics, and Friedman and Wilcoxon-sign-rank post hoc analyses were completed to determine any statistical differences between the rankings of decision making factors before and after engagement with Contents Under Pressure. Simulating process safety decision making with interactive educational supports may increase students’ understanding of genuine workplace environments and factors that contribute to process safety, without the real world hazards that result from poor decision making. By understanding how students prioritize these factors, chemical engineering curricula can be adapted to focus on the areas of process safety decision making where students need the largest improvement, thereby better preparing them to enter the engineering workforce. 

Today’s STEM classrooms have expanded the domain of computer science education from a basic two-toned terminal screen to now include helpful Integrated Development Environments(IDE) (BlueJ, Eclipse), block-based programming (MIT Scratch, Greenfoot), and even physical computing with embedded systems (Arduino, LEGO Mindstorm). But no matter which environment a student starts programming in, all students will eventually need help in finding and fixing bugs in their code. While the helpful IDE’s have debugger tools built in (breakpoints for pausing your program, ways to view/modify variable values, and "stepping" through code execution), in many of the other programming environments, students are limited to using print statements to try and "see" what is happening inside their program. Most students who learn to write code for Arduino microcontrollers will start within the Arduino IDE, but the official Arduino IDE does not currently provide any debugging tools. Instead, a student would have to move on to a professional IDE such as Atmel Studio or acquire a hardware debugger in order to add breakpoints or view their program’s variables. But each of these options has a steep learning curve, additional costs, and can require complex configurations. Based on research of student debugging practices[3, 7] and our own classroom observations, we have developed an Arduino software library, called Arduino Debugger, which provides some of these debugging tools (ex. breakpoints) while staying within the official Arduino IDE. This work continues a previous library, (redacted), which focused on features specific to e-textiles development boards. The Arduino Debugger library has been modified to support not only e-textile boards (Lilypad, Adafruit Circuit Playground) but most AVR and ARM based Arduino boards.We are also in the process of testing a set of Debugging Code Templates to see how they might increase student adoption of debugging tools. 

The e-textile landscape has enabled creators to combine textile materiality with electronic capability. However, the tools that e-textile creators use have been adapted from traditional textile or hardware tools. This puts creators at a disadvantage, as e-textile projects present new and unique challenges that currently can only be addressed using a non-specialized toolset. This paper introduces the first iteration of a wearable e-textile debugging tool to assist novice engineers in problem solving e-textile circuitry errors. These errors are often only detected after the project is fully built and are resolved only by disassembling the circuit. Our tool actively monitors the continuity of the conductive thread as the user stitches, which enables the user to identify and correct circuitry errors as they create their project. 

IceCube alert events are neutrinos with a moderate-to-high probability of having astrophysical origin. In this study, we analyze 11 yr of IceCube data and investigate 122 alert events and a selection of high-energy tracks detected between 2009 and the end of 2021. This high-energy event selection (alert events + high-energy tracks) has an average probability of ≥0.5 of being of astrophysical origin. We search for additional continuous and transient neutrino emission within the high-energy events’ error regions. We find no evidence for significant continuous neutrino emission from any of the alert event directions. The only locally significant neutrino emission is the transient emission associated with the blazar TXS 0506+056, with a local significance of 3σ, which confirms previous IceCube studies. When correcting for 122 test positions, the globalp-value is 0.156 and compatible with the background hypothesis. We constrain the total continuous flux emitted from all 122 test positions at 100 TeV to be below 1.2 × 10⁻¹⁵(TeV cm²s)⁻¹at 90% confidence assuming anE⁻²spectrum. This corresponds to 4.5% of IceCube’s astrophysical diffuse flux. Overall, we find no indication that alert events in general are linked to lower-energetic continuous or transient neutrino emission.