Finding branch-decompositions of matroids, hypergraphs, and more

Given $n$ subspaces of a finite-dimensional vector space over a fixed finite field $\mathcal F$, we wish to find a "branch-decomposition" of these subspaces of width at most $k$, that is a subcubic tree $T$ with $n$ leaves mapped bijectively to the subspaces such that for every edge $e$ of $T$, the sum of subspaces associated with leaves in one component of $T-e$ and the sum of subspaces associated with leaves in the other component have the intersection of dimension at most $k$. This problem includes the problems of computing branch-width of $\mathcal F$-represented matroids, rank-width of graphs, branch-width of hypergraphs, and carving-width of graphs. We present a fixed-parameter algorithm to construct such a branch-decomposition of width at most $k$, if it exists, for input subspaces of a finite-dimensional vector space over $\mathcal F$. Our algorithm is analogous to the algorithm of Bodlaender and Kloks (1996) on tree-width of graphs. To extend their framework to branch-decompositions of vector spaces, we developed highly generic tools for branch-decompositions on vector spaces. The only known previous fixed-parameter algorithm for branch-width of $\mathcal F$-represented matroids was due to Hlin\v{e}n\'y and Oum (2008) that runs in time $O(n^3)$ where $n$ is the number of elements of the input $\mathcal F$-represented matroid. But their method is highly indirect. Their algorithm uses the non-trivial fact by Geelen et al. (2003) that the number of forbidden minors is finite and uses the algorithm of Hlin\v{e}n\'y (2005) on checking monadic second-order formulas on $\mathcal F$-represented matroids of small branch-width. Our result does not depend on such a fact and is completely self-contained, and yet matches their asymptotic running time for each fixed $k$.Comment: 73 pages, 10 figure

Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering

The problem of spurious programs is a longstanding challenge when training a semantic parser from weak supervision. To eliminate such programs that have wrong semantics but correct denotation, existing methods focus on exploiting similarities between examples based on domain-specific knowledge. In this paper, we propose a domain-agnostic filtering mechanism based on program execution results. Specifically, for each program obtained through the search process, we first construct a representation that captures the program's semantics as execution results under various inputs. Then, we run a majority vote on these representations to identify and filter out programs with significantly different semantics from the other programs. In particular, our method is orthogonal to the program search process so that it can easily augment any of the existing weakly supervised semantic parsing frameworks. Empirical evaluations on the Natural Language Visual Reasoning and WikiTableQuestions demonstrate that applying our method to the existing semantic parsers induces significantly improved performances.Comment: EMNLP 202

Distance-learning receptivity differences between American and Korean graduate students

The purposes of this study were to determine if differences exist in distance-learning receptivity and perceived technology usefulness between American and Korean graduate students as well as Individualists and Collectivists. Results indicated that the two groups differed in distance-learning receptivity and perceived technology usefulness. However, cultural value tendency did not influence either receptivity or usefulness. Recommendations based on this study: 1. Researchers who are interested in cross-cultural field of distance learning should find what potential factors influence the differences in the receptivity and perceived usefulness between American and Korean group. 2. Administrators and decision makers who want to implement or adopt distance learning for their employees or students need to understand that cultural value, at least individualism and collectivism, is not a significant factor in distance learning. Instead, they should understand the importance of prior experience because people feel that distance is better than they??ve ever thought possible once they experience. 3. In implementing distance learning, practitioners should consider interactive media more than non-interactive media. Distance learning is mostly dependent upon technology. Practitioners should consider that distance-learning technology should be developed in terms of perceived usefulness to users. 4. In respect to usefulness, advanced and contemporary technologies were perceived more useful than traditional technologies in distance learning. Therefore, practitioners should also consider advanced technology rather than traditional technology in distance learning. Recommendations for future research: 1. It is suggested that Hofstede??s other cultural value dimensions should be included in future studies. 2. Future researchers should consider other factors such as personal background, learning style, skill level, and motivation. 3. Future research is needed to extend the current findings and test their generalizability to other types of users, for example, undergraduate students or organization employees. 4. This study used American and Korean samples only. Other national cultures should be tested with various cultural dimensions in a future study

Bis[(2,2-dimethyl­propano­yloxy)meth­yl] {[2-(6-amino-9H-purin-9-yl)eth­oxy]meth­yl}phospho­nate–succinic acid (2/1)

The title compound, C20H32N5O8P·0.5C4H6O4, is composed of two 9-{2-[bis­(pivaloyloxymeth­oxy)phosphinylmeth­oxy]eth­yl}adenine, commonly known as adefovir dipivoxil (AD), mol­ecules linked to the carb­oxy­lic acid groups of succinic acid (SA). The asymmetric unit contains one mol­ecule of AD and half a mol­ecule of SA, which sits on an inversion center. Both adenine units in the two AD mol­ecules make AD–SA N—H⋯O and SA–AD O—H⋯N hydrogen bonds to SA. In addition, the inter­molecular AD–AD N—H⋯O—P hydrogen bond serves to stabilize the cocrystal. There is also a π–π stacking inter­action [inter­planar spacing 3.34 (19) Å] between adjacent inversion-related adenine groups

TC- E 5003, a protein methyltransferase 1 inhibitor, activates the PKA- dependent thermogenic pathway in primary murine and human subcutaneous adipocytes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162696/2/feb213900_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162696/1/feb213900.pd

Topological Structure of Dense Hadronic Matter

We present a summary of work done on dense hadronic matter, based on the Skyrme model, which provides a unified approach to high density, valid in the large $N_c$ limit. In our picture, dense hadronic matter is described by the {\em classical} soliton configuration with minimum energy for the given baryon number density. By incorporating the meson fluctuations on such ground state we obtain an effective Lagrangian for meson dynamics in a dense medium. Our starting point has been the Skyrme model defined in terms of pions, thereafter we have extended and improved the model by incorporating other degrees of freedom such as dilaton, kaons and vector mesons.Comment: 13 pages, 8 figures, Talk given at the KIAS-APCTP Symposium in Astro-Hadron Physics "Compact Stars: Quest for New States of Dense Matter", November 10-14, 2003, Seoul, Korea, published by World Scientific. Based on talk by B.-Y. Par

Model-Free Reconstruction of Capacity Degradation Trajectory of Lithium-Ion Batteries Using Early Cycle Data

Early degradation prediction of lithium-ion batteries is crucial for ensuring safety and preventing unexpected failure in manufacturing and diagnostic processes. Long-term capacity trajectory predictions can fail due to cumulative errors and noise. To address this issue, this study proposes a data-centric method that uses early single-cycle data to predict the capacity degradation trajectory of lithium-ion cells. The method involves predicting a few knots at specific retention levels using a deep learning-based model and interpolating them to reconstruct the trajectory. Two approaches are used to identify the retention levels of two to four knots: uniformly dividing the retention up to the end of life and finding optimal locations using Bayesian optimization. The proposed model is validated with experimental data from 169 cells using five-fold cross-validation. The results show that mean absolute percentage errors in trajectory prediction are less than 1.60% for all cases of knots. By predicting only the cycle numbers of at least two knots based on early single-cycle charge and discharge data, the model can directly estimate the overall capacity degradation trajectory. Further experiments suggest using three-cycle input data to achieve robust and efficient predictions, even in the presence of noise. The method is then applied to predict various shapes of capacity degradation patterns using additional experimental data from 82 cells. The study demonstrates that collecting only the cycle information of a few knots during model training and a few early cycle data points for predictions is sufficient for predicting capacity degradation. This can help establish appropriate warranties or replacement cycles in battery manufacturing and diagnosis processes

Effects of the energy spread of secondary electrons in a dc-biased single-surface multipactor

The effects of the energy spread of secondary electrons are theoretically investigated for a dc-biased single-surface multipactor. In our previous publication [S. G. Jeon et al., Phys. Plasmas 16, 073101 (2009)], we obtained the conditions for the phase lock of an electron bunch, assuming zero velocity spread of the secondary electrons. In this work, we extended our previous theory to derive a quadratic map, by which the stability and bifurcation of the electron bunch can be systematically investigated. For the study of the energy spread of the secondary electrons, a randomized term was added to this map. The modified map then showed significant smearing-out of the bifurcated branches. The theoretical results were verified by particle-in-cell simulations, which showed good agreement in wide parameter ranges for both cases of monoenergetic and energy-spread secondary electrons.open4

Implicit Kernel Attention

\textit{Attention} computes the dependency between representations, and it encourages the model to focus on the important selective features. Attention-based models, such as Transformers and graph attention networks (GAT) are widely utilized for sequential data and graph-structured data. This paper suggests a new interpretation and generalized structure of the attention in Transformer and GAT. For the attention in Transformer and GAT, we derive that the attention is a product of two parts: 1) the RBF kernel to measure the similarity of two instances and 2) the exponential of $L^{2}$ norm to compute the importance of individual instances. From this decomposition, we generalize the attention in three ways. First, we propose implicit kernel attention with an implicit kernel function, instead of manual kernel selection. Second, we generalize $L^{2}$ norm as the $L^{p}$ norm. Third, we extend our attention to structured multi-head attention. Our generalized attention shows better performance on classification, translation, and regression tasks