MWE as WSD: Solving Multiword Expression Identification with Word Sense Disambiguation

Recent approaches to word sense disambiguation (WSD) utilize encodings of the sense gloss (definition), in addition to the input context, to improve performance. In this work we demonstrate that this approach can be adapted for use in multiword expression (MWE) identification by training models which use gloss and context information to filter MWE candidates produced by a rule-based extraction pipeline. Our approach substantially improves precision, outperforming the state-of-the-art in MWE identification on the DiMSUM dataset by up to 1.9 F1 points and achieving competitive results on the PARSEME 1.1 English dataset. Our models also retain most of their WSD performance, showing that a single model can be used for both tasks. Finally, building on similar approaches using Bi-encoders for WSD, we introduce a novel Poly-encoder architecture which improves MWE identification performance

Language documentation in the aftermath of the 2015 Nepal earthquakes: A guide to two archives and a web exhibit

We describe two institutionally related archives and an online exhibit representing a set of Tibeto-Burman languages of Nepal. These archives and exhibit were built to house materials resulting from documentation of twelve Tibeto-Burman languages in the aftermath of the 2015 Nepal earthquakes. This account includes a detailed discussion of the different materials recorded, and how they were prepared for the collections. This account also provides a comparison of the two different types of archives, the different but complementary functions they serve, and a discussion of the role that online exhibits can play in the context of language documentation archives.National Foreign Language Resource Cente

WISCO oil field special waste landfill : final design report ; for Williams County, North Dakota Section 26 T. 154 N.R. 104 W

The increasing amount of special waste generated from drilling activity in western North Dakota has created the need for a local special waste landfill for the region. A quarter section of land has been selected for landfill use 20 miles west of Williston on ND 2, (sec.26, T. 154 N, R. 104 W.), Williams County. WISCO Oil Co. recognized this site as an appropriate destination to deposit the special waste. ND 2 dividing the site into Northern and Southern divisions leaves the smaller Northern division to be used for processing waste and maintenance buildings, while the larger 7 4-acre Southern division will contain the special waste landfill. The following report includes site analysis of geology, hydrogeology, hydrology, topography, soil characteristics, geomorphology, tectonic framework, and geotechnical hazards. The site investigation concludes that the site is suitable for the proposed landfill. The WISCO Oil special waste landfill\u27s design will cover a footprint of 109,000 square yards. By increasing the height the landfill potential volumes range from 2. 7 million to 4.5 million cubic yards based upon demand. Assuming an average daily deposit of 500 to 800 cubic yards of waste per day the landfill is expected to be in operation for 15 to 20 years. The site analysis and final design specifications are in compliance with North Dakota Century Code 33-22-07.1, as well as standards set by the North Dakota Department of Health Division of Waste Management

Mutant Study of Sinorhizobium meliloti Proline Utilization A (PutA)

The purpose of this project is to purify and characterize the reaction kinetics of mutant versions the enzyme Proline Utilization A (PutA) in Sinorhizobium meliloti. The enzyme catalyzes the first step in proline metabolism. It has two active sites. The first is proline dehydrogenase (PRODH) which converts proline to pyrroline-5-carboxylate (P5C). The second is P5C dehydrogenase (P5CDH) which converts P5C to glutamate. Although many bacterial organisms have PutA, there are still significant interspecies variations, resulting in an entire family of PutA enzymes. The main difference is the length of the amino acid sequence. This affects the protein’s structure or its shape, and the protein’s kinetics or how it behaves in reactions. In order to have a complete understanding of proline metabolism, all the variations of PutA must be characterized both structurally and kinetically. The version of PutA found in S. meliloti (SmPutA) has been categorized structurally but not kinetically. This project aims to fill this gap in our knowledge of proline metabolism and PutA from S. meliloti

Investigation of Post-Consumer Regrind Content in Polyethylene and Polypropylene for Consumer Packaging Applications

With the rise of plastics products in waste streams, both consumer products companies and consumers are looking for greener methods to produce the same products with less of a carbon footprint. One way of achieving these goals is to include recycled plastic into consumer goods. These recycled greener alternatives provide many of the same benefits of virgin plastic material. The goal of this project was to determine what, if any, differences are there between virgin resins and resins that contain post-consumer recycled content (PCR). Control and experimental resins were obtained and injection molded to create samples for analysis. Control resins were Ineos H05A-00 Polypropylene Homopolymer and Marlex 9012 High-Density Polyethylene. Experimental resins included Plastic Bank SDS clear polypropylene (Social Plastic), KWR-621 Post Consumer Recycled FDA Polypropylene Resin, and KW Post-Consumer Recycled Polyethylene Resins: KWR 102 BM High-Density Polyethylene and KWR 101 150 Natural High-Density Polyethylene. Samples underwent thermal testing by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) to determine key thermal transition and material degradation temperatures to compare each of the experimental materials to the virgin resins. Mechanical testing included tensile testing and Izod impact testing to determine the mechanical strength of each experimental materials to compare to the virgin resins. Melt flow was performed to determine the rheological properties of the virgin and post-consumer recycled (PCR) resins in the melt

Testing and Developing DIY Masks

ME450 Capstone Design and Manufacturing Experience: Fall 2020The purpose of this design project is to develop a DIY mask to combat the shortage of N95 respirators and medical masks in low resource settings. In the preliminary stages of the project, meetings with stakeholders, mostly in the form of experts in the area of study, were conducted. Research was also done on literature in the area, which led to the development of engineering specifications. The mask should have a low cost of fewer than 2 cedis or 0.34 USD. The mask should be made in less than 30 minutes with fewer than 12 steps of instructions. The mask should filter over 50% of particles over 50 nm in size. The mask should fit well to the face and minimize airflow around the edge with a fit factor greater than or equal to 2. The mask should also be comfortable to wear with average scores greater than 4 on a 6 point Likert scale. Finally, the mask should sustain a long lifespan, supporting over 20 uses with a decontamination cycle in between each use. Using a combination of design heuristics and a morphological matrix, several designs were brainstormed to meet the project requirements. These designs were then filtered using a decision matrix, resulting in the three best designs. Engineering analyses were then developed to further evaluate the mask designs and answer some key design drivers. The first and simplest test was the Mask Fabrication Test, which simply recorded the time it took to create the masks. The test indicated that the three designs had a comparable fabrication time. The next substantial test that was conducted was the Mask Fit Test, which measured airflow around the masks. From this test, various factors of the best performing masks were determined. To help ensure the mask was comfortable, several steps were taken. First, a Comfort Priority Survey was conducted, which helped provide context for the results of the Mask Comfort Test. Then, prototypes of the three mask designs were tried on and rated for various aspects of comfort by people close to team members. From these tests, the nylon design was chosen as the final design, with a few modifications. The final design uses three layers of material -cotton, silk, and nylon- to filter out particles. The nylon layer also acts as the ear straps for comfortability. Wires are sewn inside the top and bottom of the mask to improve fit, and pleats are sewn on the side for flexibility. One final comfort test was conducted with the design, which verified the requirement. The low-cost requirement was verified through calculations, and the “uses available materials requirement” was verified from research. The “is easy to create” requirement was verified with a use test. To verify the lifetime and filtration efficiency requirements, a Mask Filtration Efficiency Test was performed. However, due to a lack of testing time, no conclusive results were obtained from the test, and the lifetime and filtration efficiency requirements were left unverified. An inability to test also left the fit requirement unverified. By the end of the project, a design and instructions on creating the design were created. This design has been verified to fulfill 4 out of 7 requirements. The filtration efficiency, lifetime, and fit requirements all require further testing for verification.Caroline Soyars, U-M Mechanical Engineeringhttp://deepblue.lib.umich.edu/bitstream/2027.42/164436/1/Testing_and_Developing_DIY_Masks.pd

Functional connectivity modules in recurrent neural networks: function, origin and dynamics

Understanding the ubiquitous phenomenon of neural synchronization across species and organizational levels is crucial for decoding brain function. Despite its prevalence, the specific functional role, origin, and dynamical implication of modular structures in correlation-based networks remains ambiguous. Using recurrent neural networks trained on systems neuroscience tasks, this study investigates these important characteristics of modularity in correlation networks. We demonstrate that modules are functionally coherent units that contribute to specialized information processing. We show that modules form spontaneously from asymmetries in the sign and weight of projections from the input layer to the recurrent layer. Moreover, we show that modules define connections with similar roles in governing system behavior and dynamics. Collectively, our findings clarify the function, formation, and operational significance of functional connectivity modules, offering insights into cortical function and laying the groundwork for further studies on brain function, development, and dynamics

Asynchronous Video Interviews and Artificial Intelligence: A Multi-Study Exploration

Asynchronous video interviews (AVIs) provide scalable, low-cost opportunities for matching interviewees and organizations. However, the implications of a shift from synchronous interviews aren’t fully understood, especially when design choices such as AI evaluations are employed. To better understand the impact of AVIs, we undertook an exploratory qualitative study in addition to an experiment. The first study involves 100 qualitative responses and exploratory quantitative tests on the relationships between coded values and demographic and trait variables of the respondents. Our second study tests the impact of AI feedback using a large online AVI service while accounting for various disadvantaged groups that could experience discrimination in their AVI interactions. We developed 5 propositions regarding the interaction of interviewee traits and AVI design. Additionally, we did not find support that AI feedback increases the performance of interviewees, though we identify several traits that lead to high AI scores and human-rater performance

Demystifying generative AI: A talent professional’s guide to using a new tool.

Humans’ use of tools is nothing new. For centuries, people have been using tools and technology to increase their performance. However, the speed at which technology is changing the tools we have access to is accelerating. Artificial intelligence (AI) has quickly emerged as a new and powerful technology, and generative AI like ChatGPT and Dall-E have made AI widely accessible - and adopted - by millions of people. However, for users and non-users alike it still remains unclear what generative AI is and how this new technology fits into a practitioner’s toolkit. Like most tools, generative AI can be used in ways that are more and less effective, and the consequences of using a tool incorrectly may be steep (after all, you might not use a hammer to dig a hole). With a clear understanding of what generative AI is, how these new tools apply this technology, and how they might fit into a talent professional’s arsenal, users can understand how to confidently and competently use generative AI applications in their organization. This interactive session will dispel the mystique around generative AI and address some misconceptions about AI-powered interactive platforms. Participants will gain an understanding of what generative AI is, how to incorporate emerging AI tools into the work process, and learn how asking the right questions can help find the right balance between professional expertise, others’ viewpoints, and AI-powered insights. Humans’ use of tools is nothing new, but the tools that AI is powering are a bit novel. This session will help cut through the hype and determine the best way to maximize the benefits and minimize the downsides of using generative AI to attract, retain, and maximize talent in an organization