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1. Universal route for the emergence of exceptional points in PT-symmetric metamaterials with unfolding spectral symmetries

   https://doi.org/10.1088/1367-2630/ac09c9  

   Fang, Yanghao; Kottos, Tsampikos; Thevamaran, Ramathasan (June 2021, New Journal of Physics)

   Abstract We introduce a class of parity-time symmetric elastodynamic metamaterials (Ed-MetaMater) whose Hermitian counterpart exhibits unfolding (fractal) spectral symmetries. Our study reveals a scale-free formation of exceptional points in those Ed-MetaMaters whose density is dictated by the fractal dimension of their Hermitian spectra. We demonstrate this scale-free EP-formation in a quasi-periodic Aubry-Harper Ed-MetaMater, a geometric H-tree-fractal Ed-MetaMater, and an aperiodic Fibonacci Ed-MetaMater—each having a specific fractal spectrum—using finite element models and establish a universal route for EP-formation via a coupled mode theory model with controllable fractal spectrum. This universality may enable the rational design of novel Ed-MetaMater for hypersensitive sensing and elastic wave control. 

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2. Situating Robots in the Emergency Department

   Taylor, A.; Matsumoto, S.; and Riek, L.D. (January 2020, AAAI Spring Symposium on Applied AI in Healthcare: Safety, Community, and the Environment)

   The emergency department (ED) is a safety-critical environ- ment in which mistakes can be deadly and providers are over- burdened. Well-designed and contextualized robots could be an asset in the ED by relieving providers of non-value added tasks and enabling them to spend more time on patient care. To support future work in this application domain, in this paper, we characterize ED staff workflow and patient experience, and identify key considerations for robots in the ED, including safety, physical and behavioral attributes, usability, and training. Then, we discuss the task representation and data needed to situate the robot in the ED, based on this do- main knowledge. To the best of our knowledge, this is the first work on robot design for the ED that explicitly takes task acu- ity into account. This is an exciting area of research and we hope our work inspires further exploration into this problem domain. 

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3. S-SOM v1.0: a structural self-organizing map algorithm for weather typing

   https://doi.org/10.5194/gmd-14-2097-2021  

   Doan, Quang-Van; Kusaka, Hiroyuki; Sato, Takuto; Chen, Fei (January 2021, Geoscientific Model Development)

   Abstract. This study proposes a novel structural self-organizingmap (S-SOM) algorithm for synoptic weather typing. A novel feature of theS-SOM compared with traditional SOMs is its ability to deal with input datawith spatial or temporal structures. In detail, the search scheme for thebest matching unit (BMU) in a S-SOM is built based on a structuralsimilarity (S-SIM) index rather than by using the traditional Euclideandistance (ED). S-SIM enables the BMU search to consider the correlation inspace between weather states, such as the locations of highs or lows, that is impossible when using ED. The S-SOM performance is evaluated by multipledemo simulations of clustering weather patterns over Japan using theERA-Interim sea-level pressure data. The results show the S-SOM'ssuperiority compared with a standard SOM with ED (or ED-SOM) in tworespects: clustering quality based on silhouette analysis and topologicalpreservation based on topological error. Better performance of S-SOM versusED is consistent with results from different tests and node-sizeconfigurations. S-SOM performs better than a SOM using the Pearsoncorrelation coefficient (or COR-SOM), though the difference is not as clear as it is compared to ED-SOM. 

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4. Coupling Monte Carlo, variational implicit solvation, and binary level-set for simulations of biomolecular binding

   Zhang, Z.; Ricci, C.; Fan, C.; Cheng, L.-T.; Li, B.; McCammon, J.A. (March 2021, Journal of chemical theory and computation)

   null (Ed.)

   We develop a hybrid approach that combines the Monte Carlo (MC)method, a variational implicit-solvent model (VISM), and a binary level-set method forthe simulation of biomolecular binding in an aqueous solvent. The solvation free energy for the biomolecular complex is estimated by minimizing the VISM free-energy functional of all possible solute−solvent interfaces that are used as dielectric boundaries. This functional consists of the solute volumetric, solute−solvent interfacial, solute−solvent van der Waals interaction, and electrostatic free energy. A technique of shifting the dielectric boundary is used to accurately predict the electrostatic part of the solvation free energy.Minimizing such a functional in each MC move is made possible by our new and fast binary level-set method. This method is based on the approximation of surface area by the convolution of an indicator function with a compactly supported kernel and is implemented by simple flips of numerical grid cells locally around the solute−solvent interface. We apply our approach to the p53-MDM2 system for which the two molecules are approximated by rigid bodies. Our efficient approach captures some of the poses before the final bound state. All atom molecular dynamics simulations with most of such poses quickly reach the final bound state.Our work is a new step toward realistic simulations of biomolecular interactions. With further improvement of coarse graining and MC sampling, and combined with other models, our hybrid approach can be used to study the free-energy landscape and kinetic pathways of ligand binding to proteins. 

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5. ELViM: Exploring Biomolecular Energy Landscapes through Multidimensional Visualization

   https://doi.org/10.1021/acs.jcim.4c00034  

   Viegas, Rafael Giordano; Martins, Ingrid_B S; Sanches, Murilo Nogueira; Oliveira_Junior, Antonio B; Camargo, Juliana_B de; Paulovich, Fernando V; Leite, Vitor_B P (April 2024, Journal of Chemical Information and Modeling)

   Molecular dynamics (MD) simulations provide a powerful means of exploring the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast data sets generated by MD simulations poses significant challenges. This article discusses the energy landscape visualization method (ELViM), a multidimensional reduction technique inspired by the energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply the ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, the ELViM provides intuitive visualizations, revealing structural correlations and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems. 

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