Origami Club - A Gateway Into the Art of Self Expression

The Nebraska Honors Program\u27s Origami Club is an engaging platform for 3rd-5th graders that uses the fascinating Japanese art of origami to create a rich, interactive learning environment. Under the guidance of experienced instructors Minjae Song and Noah Rachwitz, and supplemented with YouTube tutorials, the club facilitates a captivating journey from simple projects to complex designs, skillfully developing each student\u27s creativity, teamwork, and problem-solving capabilities. Each session is planned meticulously to ensure an immersive experience, starting with anticipation-building project reveals and culminating in the production of personal origami masterpieces. As a hands-on club, students are encouraged to question, explore, assist their peers, and reflect on their learning, instilling a sense of camaraderie, service, and an understanding of the process of continuous learning. Carefully designed to integrate practical application of origami skills, the curriculum features activities like paper airplane contests, crane making, modular box construction, and ninja star crafting. Regular feedback and recommended adjustments ensure the learning experience is continuously optimized for each student\u27s growth. The final lesson, centered on creating ninja stars, underscores the importance of quality work, patience, and precision in crafting items of potential use in life, thereby imparting valuable life skills. In essence, the Origami Club transcends the boundaries of traditional learning experiences by not only teaching the art of paper folding, but also equipping students with a range of interpersonal and practical skills, nurturing them for challenges within and outside the classroom

Graph-based 3D Collision-distance Estimation Network with Probabilistic Graph Rewiring

We aim to solve the problem of data-driven collision-distance estimation given 3-dimensional (3D) geometries. Conventional algorithms suffer from low accuracy due to their reliance on limited representations, such as point clouds. In contrast, our previous graph-based model, GraphDistNet, achieves high accuracy using edge information but incurs higher message-passing costs with growing graph size, limiting its applicability to 3D geometries. To overcome these challenges, we propose GDN-R, a novel 3D graph-based estimation network.GDN-R employs a layer-wise probabilistic graph-rewiring algorithm leveraging the differentiable Gumbel-top-K relaxation. Our method accurately infers minimum distances through iterative graph rewiring and updating relevant embeddings. The probabilistic rewiring enables fast and robust embedding with respect to unforeseen categories of geometries. Through 41,412 random benchmark tasks with 150 pairs of 3D objects, we show GDN-R outperforms state-of-the-art baseline methods in terms of accuracy and generalizability. We also show that the proposed rewiring improves the update performance reducing the size of the estimation model. We finally show its batch prediction and auto-differentiation capabilities for trajectory optimization in both simulated and real-world scenarios.Comment: 7 pages, 6 figure

Bundling Among Rivals: A Case of Pharmaceutical Cocktails

We empirically analyze the welfare effects of cross-firm bundling in the pharmaceutical industry. Physicians often treat patients with "cocktail" regimens that combine two or more drugs. Firms cannot price discriminate because each drug is produced by a different firm and a physician creates the bundle in her office from the component drugs. We show that a less competitive equilibrium arises with cocktail products because firms can internalize partially the externality their pricing decisions impose on competitors. The incremental profits from creating a bundle are sometimes as large as the incremental profits from a merger of the same two firms.

SGGNet2^2: Speech-Scene Graph Grounding Network for Speech-guided Navigation

The spoken language serves as an accessible and efficient interface, enabling non-experts and disabled users to interact with complex assistant robots. However, accurately grounding language utterances gives a significant challenge due to the acoustic variability in speakers' voices and environmental noise. In this work, we propose a novel speech-scene graph grounding network (SGGNet$^2$) that robustly grounds spoken utterances by leveraging the acoustic similarity between correctly recognized and misrecognized words obtained from automatic speech recognition (ASR) systems. To incorporate the acoustic similarity, we extend our previous grounding model, the scene-graph-based grounding network (SGGNet), with the ASR model from NVIDIA NeMo. We accomplish this by feeding the latent vector of speech pronunciations into the BERT-based grounding network within SGGNet. We evaluate the effectiveness of using latent vectors of speech commands in grounding through qualitative and quantitative studies. We also demonstrate the capability of SGGNet$^2$ in a speech-based navigation task using a real quadruped robot, RBQ-3, from Rainbow Robotics.Comment: 7 pages, 6 figures, Paper accepted for the Special Session at the 2023 International Symposium on Robot and Human Interactive Communication (RO-MAN), [Dohyun Kim, Yeseung Kim, Jaehwi Jang, and Minjae Song] contributed equally to this wor

Honeycomb oxide heterostructure: a new platform for Kitaev quantum spin liquid

Kitaev quantum spin liquid, massively quantum entangled states, is so scarce in nature that searching for new candidate systems remains a great challenge. Honeycomb heterostructure could be a promising route to realize and utilize such an exotic quantum phase by providing additional controllability of Hamiltonian and device compatibility, respectively. Here, we provide epitaxial honeycomb oxide thin film Na3Co2SbO6, a candidate of Kitaev quantum spin liquid proposed recently. We found a spin glass and antiferromagnetic ground states depending on Na stoichiometry, signifying not only the importance of Na vacancy control but also strong frustration in Na3Co2SbO6. Despite its classical ground state, the field-dependent magnetic susceptibility shows remarkable scaling collapse with a single critical exponent, which can be interpreted as evidence of quantum criticality. Its electronic ground state and derived spin Hamiltonian from spectroscopies are consistent with the predicted Kitaev model. Our work provides a unique route to the realization and utilization of Kitaev quantum spin liquid

A Dynamic Analysis of Cooperative Research in the Semiconductor Industry

The paper has two objectives. The first is to construct a dynamic model of research joint ventures (RJVs) in which firms competing in the product market cooperate in investing to improve generic manufacturing technology. The second objective is to analyze cooperative research led by SEMATECH in the semiconductor industry using the dynamic model. The estimation consists of two stages. In the first stage, consumer demand is estimated using product level data, and state variables are constructed to reflect a technological advance and an evolution of firms' competitiveness in the product market. In the second stage, research expenditure level and firms' value functions are computed for every combination of the state variables as solutions to the dynamic model. I also compute firms' research expenditures for competitive research by making firms unilaterally invest in research. The results show that in RJVs firms' research expenditures go down to one fifth of what they would spend in competitive research. Lower research expenditure results in higher net profits in RJVs, although variable profits are similar in all regimes. RJVs are also more likely to generate higher consumer surplus than competitive research. This is because, while consumers benefit from more frequent introductions of higher quality products in competitive research, they occasionally pay higher prices than they do in RJVs for the same quality products. The net effect is that consumers are hurt more by higher price in competitive research than by less frequent introductions of new products in RJVs. Firms also make different research decisions for the same changes in the product market conditions, depending on whether they cooperate or compete in researchResearch Joint Venture, Dynamic Model of Oligopoly Market, Product Innovation

Estimating Platform Market Power in Two-Sided Markets with an Application to Magazine Advertising”. The Bradley Policy Research Center Financial Research and Policy Working Paper No. FR

Abstract In this paper I estimate platform markups in two-sided markets using structural models of platform demand. My models and estimation procedure are applicable to general two-sided market settings where agents on each side care about the presence of agents on the other side and platforms set two membership prices to maximize the sum of pro…ts. Using data on TV magazines in Germany I show that the magazines typically set copy prices below marginal costs and earn pro…ts from selling advertising pages. I also show that mergers are much less anticompetitive than in one-sided markets and could even be welfare enhancing

Do media consumers really dislike advertising? An empirical assessment of the role of advertising in print media markets

This paper uses data on German consumer magazines observed between 1992 and 2004 to analyze the extent to which consumers (dis-)like advertising. We estimate logit demand models separately for the six most important magazine segments in terms of circulation. We find little evidence for readers disliking advertising. On the contrary, we show that readers in many magazine segments appreciate advertising. Readers of Women's magazines, Business and politics magazines as well as Car magazines -- market segments where advertisements are relatively more informative -- appreciate advertising while advertising is nuisance to readers of Adult magazines, a segment where advertisements are particularly uninformative. Demand for interior design magazines is not well identified. Our logit demand estimates are confirmed by logit demand models with random coefficients and by magazine-specific monopoly demand models.Two-sided markets Advertising Mean Group Estimation Random coefficients model Media markets Nuisance