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1. Noncrossing partitions of an annulus

   https://doi.org/10.5070/C65165023  

   Brestensky, Laura G; Reading, Nathan (March 2025, Combinatorial Theory)

   The noncrossing partition poset associated to a Coxeter group W and Coxeter element c is the interval [1,c]_T in the absolute order on W. We construct a new model of noncrossing partititions for W of classical affine type, using planar diagrams (affine types A tilde and C tilde in this paper and affine types D tilde and B tilde in the sequel). The model in type A tilde consists of noncrossing partitions of an annulus. In type C tilde, the model consists of symmetric noncrossing partitions of an annulus or noncrossing partitions of a disk with two orbifold points. Following the lead of McCammond and Sulway, we complete [1,c]_T to a lattice by factoring the translations in [1,c]_T, but the combinatorics of the planar diagrams leads us to make different choices about how to factor. 

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2. Data-Driven Forgetting and Discount Factors for Vehicle Speed Forecasting in Ecological Adaptive Cruise Control

   https://doi.org/10.1115/1.4052272  

   Hyeon, Eunjeong; Kim, Youngki; Ersal, Tulga; Stefanopoulou, Anna (January 2022, Journal of Dynamic Systems, Measurement, and Control)

   Abstract This paper investigates temporal correlations in human driving behavior using real-world driving to improve speed forecasting accuracy. These correlations can point to a measurement weighting function with two parameters: a forgetting factor for past speed measurements that the vehicle itself drove with, and a discount factor for the speeds of vehicles ahead based on information from vehicle-to-vehicle communication. The developed weighting approach is applied to a vehicle speed predictor using polynomial regression, a prediction method well-known in the literature. The performance of the developed approach is then assessed in both real-world and simulated traffic scenarios for accuracy and robustness. The new weighting method is applied to an ecological adaptive cruise control system, and its influence is analyzed on the prediction accuracy and the performance of the ecological adaptive cruise control in an electric vehicle powertrain model. The results show that the new prediction method improves energy saving from the eco-driving by up to 4.7% compared to a baseline least-square-based polynomial regression. This is a 10% improvement over the constant speed/acceleration model, a conventional speed predictor. 

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3. A search for top-squark pair production, in final states containing a top quark, a charm quark and missing transverse momentum, using the 139 fb−1 of pp collision data collected by the ATLAS detector

   https://doi.org/10.1007/JHEP07(2024)250  

   Aad, G; Abbott, B; Abeling, K; Abicht, N J; Abidi, S H; Aboulhorma, A; Abramowicz, H; Abreu, H; Abulaiti, Y; Acharya, B S; et al (July 2024, Journal of High Energy Physics)

   A<sc>bstract</sc> This paper presents a search for top-squark pair production in final states with a top quark, a charm quark and missing transverse momentum. The data were collected with the ATLAS detector during LHC Run 2 and correspond to an integrated luminosity of 139 fb⁻¹of proton-proton collisions at a centre-of-mass energy of$$ \sqrt{s} $$ $\sqrt{s}$= 13 TeV. The analysis is motivated by an extended Minimal Supersymmetric Standard Model featuring a non-minimal flavour violation in the second- and third-generation squark sector. The top squark in this model has two possible decay modes, either$$ {\tilde{t}}_1\to c{\overset{\sim }{\chi}}_1^0 $$ ${\tilde{t}}_1\to c{\tilde{\chi }}_1^0$or$$ {\tilde{t}}_1\to t{\overset{\sim }{\chi}}_1^0 $$ ${\tilde{t}}_1\to t{\tilde{\chi }}_1^0$, where the$$ {\overset{\sim }{\chi}}_1^0 $$ ${\tilde{\chi }}_1^0$is undetected. The analysis is optimised assuming that both of the decay modes are equally probable, leading to the most likely final state of$$ tc+{E}_T^{\textrm{miss}} $$ $\mathrm{tc}+E_T^{\text{miss}}$. Good agreement is found between the Standard Model expectation and the data in the search regions. Exclusion limits at 95% CL are obtained in the$$ m\left({\tilde{t}}_1\right) $$ $m\left({\tilde{t}}_1\right)$vs.$$ m\left({\overset{\sim }{\chi}}_1^0\right) $$ $m\left({\tilde{\chi }}_1^0\right)$plane and, in addition, limits on the branching ratio of the$$ {\tilde{t}}_1\to t{\overset{\sim }{\chi}}_1^0 $$ ${\tilde{t}}_1\to t{\tilde{\chi }}_1^0$decay as a function ofm($$ {\tilde{t}}_1 $$ ${\tilde{t}}_1$) are also produced. Top-squark masses of up to 800 GeV are excluded for scenarios with light neutralinos, and top-squark masses up to 600 GeV are excluded in scenarios where the neutralino and the top squark are almost mass degenerate. 

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4. Review of Root-Mean-Square Error Calculation Methods for Large Deployable Mesh Reflectors

   https://doi.org/10.1155/2022/5352146  

   Yuan, Sichen (August 2022, International Journal of Aerospace Engineering)

   Ghenaiet, Adel (Ed.)

   In the design of a large deployable mesh reflector, high surface accuracy is one of ultimate goals since it directly determines overall performance of the reflector. Therefore, evaluation of surface accuracy is needed in many cases of design and analysis of large deployable mesh reflectors. The surface accuracy is usually specified as root-mean-square error, which measures deviation of a mesh geometry from a desired working surface. In this paper, methods of root-mean-square error calculation for large deployable mesh reflectors are reviewed. Concept of reflector gain, which describes reflector performance, and its relationship with the root-mean-square error is presented. Approaches to prediction or estimation of root-mean-square error in preliminary design of a large deployable mesh reflector are shown. Three methods of root-mean-square error calculation for large deployable mesh reflectors, namely, the nodal deviation root-mean-square error, the best-fit surface root-mean-square error, and the direct root-mean-square error, are presented. Concept of effective region is introduced. An adjusted calculation of root-mean-square error is suggested when the concept of effective region is involved. Finally, these reviewed methods of root-mean-square error calculation are applied to surface accuracy evaluation of a two-facet mesh geometry, a center-feed mesh reflector, and an offset-feed mesh reflector for demonstration and comparison. 

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5. STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

   https://doi.org/10.1609/aaai.v35i6.16615  

   Nikos Kargas, Cheng Qian (January 2021, The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21))

   Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to predict the evolution of epidemic trends for many regions simultaneously. We construct a 3-way spatio-temporal tensor (location, attribute, time) of case counts and propose a nonnegative tensor factorization with latent epidemiological model regularization named STELAR. Unlike standard tensor factorization methods which cannot predict slabs ahead, STELAR enables long-term prediction by incorporating latent temporal regularization through a system of discrete time difference equations of a widely adopted epidemiological model. We use latent instead of location/attribute-level epidemiological dynamics to capture common epidemic profile sub-types and improve collaborative learning and prediction. We conduct experiments using both county- and state level COVID-19 data and show that our model can identify interesting latent patterns of the epidemic. Finally, we evaluate the predictive ability of our method and show superior performance compared to the baselines, achieving up to 21% lower root mean square error and 25% lower mean absolute error for county-level prediction. 

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