SU(3)SU(3) Topological Insulators in the Honeycomb Lattice

We investigate realizations of topological insulators with spin-1 bosons loaded in a honeycomb optical lattice and subjected to a $SU(3)$ spin-orbit coupling - a situation which can be realized experimentally using cold atomic gases. In this paper, we focus on the topological properties of the single-particle band structure, namely Chern numbers (lattice with periodic boundary conditions) and edge states (lattice with strip geometry). While $SU(2)$ spin-orbit couplings always lead to time-reversal symmetric Hubbard models, and thereby to topologically trivial band structures, suitable $SU(3)$ spin-orbit couplings can break time reversal symmetry and lead to topologically non-trivial bulk band structures and to edge states in the strip geometry. In addition, we show that one can trigger a series of topological transitions (i.e. integer changes of the Chern numbers) that are specific to the geometry of the honeycomb lattice by varying a single parameter in the Hamiltonian.Comment: 12 pages, 8 figure

Finding a New Safety Performance Function for Two-Way, Two-Lane Highways in Rural Areas

For over 30 years, crash prediction models (CPMs) have been created and analyzed, with the objective being to find the best way to predict where crashes will occur and how to prevent them in the future. This has recently become a popular discussion and reality since the release of the Highway Safety Manual (HSM) and its CPM in 2010. However, many are still hesitant to begin implementing these methods as the accuracy can vary. This is a study testing the original HSM's CPMs to state-specific calibrated CPMs, and new, independent CPMs to find the best model for rural, two-lane highways in Kansas. Almost 300 miles of highway geometric data were collected to create these new models using negative binomial regression. The most significant variables in each model were found to consistently be lane width and roadside hazard rating. These models were compared against CPMs calibrated to be used on the HSM using nine validation segments. A difficulty to overcome was the large amount of animal-related crashes, as they account for 58.9 percent of crashes on Kansas highways. Removing those from the equation showed a large improvement in accuracy compared to other models created

Object Stories Through Visual Prints

I have been fascinated by the shapes and textures of objects, how their properties not only capture beauty, but also tell stories of intent and use. My goal for this project was to investigate these objects, learn their stories, and convey that through letterpress and silkscreen printing. I include references to personal stories, advertisements and songs based on the objects, as well as the history of each object. The beginning prints focused mainly on precise research, highly designed compositions and learning the process of printing. As the project went on, I became looser in my interpretation of the project. The later prints show far more experimentation, in method of printing, how the object was referenced and the emotional capacity of the objects. In addition, my later prints respond to each other, discovering and building upon the connections between the shapes textures and stories. My last two prints Whisper and Scream are a response to what I had learned throughout the process, and are a reflection on the body of work I have completed.Â

Activation of Gαi3 triggers cell migration via regulation of GIV

During migration, cells must couple direction sensing to signal transduction and actin remodeling. We previously identified GIV/Girdin as a Gαi3 binding partner. We demonstrate that in mammalian cells Gαi3 controls the functions of GIV during cell migration. We find that Gαi3 preferentially localizes to the leading edge and that cells lacking Gαi3 fail to polarize or migrate. A conformational change induced by association of GIV with Gαi3 promotes Akt-mediated phosphorylation of GIV, resulting in its redistribution to the plasma membrane. Activation of Gαi3 serves as a molecular switch that triggers dissociation of Gβγ and GIV from the Gi3–GIV complex, thereby promoting cell migration by enhancing Akt signaling and actin remodeling. Gαi3–GIV coupling is essential for cell migration during wound healing, macrophage chemotaxis, and tumor cell migration, indicating that the Gαi3–GIV switch serves to link direction sensing from different families of chemotactic receptors to formation of the leading edge during cell migration

Multi-Objective Optimization and Network Routing with Near-Term Quantum Computers

Multi-objective optimization is a ubiquitous problem that arises naturally in many scientific and industrial areas. Network routing optimization with multi-objective performance demands falls into this problem class, and finding good quality solutions at large scales is generally challenging. In this work, we develop a scheme with which near-term quantum computers can be applied to solve multi-objective combinatorial optimization problems. We study the application of this scheme to the network routing problem in detail, by first mapping it to the multi-objective shortest path problem. Focusing on an implementation based on the quantum approximate optimization algorithm (QAOA) -- the go-to approach for tackling optimization problems on near-term quantum computers -- we examine the Pareto plot that results from the scheme, and qualitatively analyze its ability to produce Pareto-optimal solutions. We further provide theoretical and numerical scaling analyses of the resource requirements and performance of QAOA, and identify key challenges associated with this approach. Finally, through Amazon Braket we execute small-scale implementations of our scheme on the IonQ Harmony 11-qubit quantum computer

Improved limits on the weak, neutral, hadronic axial vector coupling constants from quasielastic scattering of polarized electrons.

In scattering polarized electrons (P1 = 44% by 9Be at an energy of 300 MeV at angles 115°⩽ϑ⩽145° a parity violating asymmetry of Acorr = (−3.5 ± 0.7 ± 0.2) × 10−6 was measured. After correction for finite electron polarization and background we deduce an experimental asymmetry of Acx = (−9.4 ± 1.8 ± 0.5) × 10−6. The quoted errors indicate the statistical and the systematic uncertainties, respectively. The asymmetry, which is dominated by the quasielastic cross section, is interpreted in terms of model-independent electron-nucleon coupling constants of the weak neutral current. The error limits in the sector of axial vector coupling constants have been improved by a factor of 3 over previous results. A model-dependent analysis for the Weinberg angle yields the result sin2θw = 0.221 ± 0.014 ± 0.004

A flow cytometry-based neutralization assay for simultaneous evaluation of blocking antibodies against SARS-CoV-2 variants

Vaccines against SARS-CoV-2 have alleviated infection rates, hospitalization and deaths associated with COVID-19. In order to monitor humoral immunity, several serology tests have been developed, but the recent emergence of variants of concern has revealed the need for assays that predict the neutralizing capacity of antibodies in a fast and adaptable manner. Sensitive and fast neutralization assays would allow a timely evaluation of immunity against emerging variants and support drug and vaccine discovery efforts. Here we describe a simple, fast, and cell-free multiplexed flow cytometry assay to interrogate the ability of antibodies to prevent the interaction of Angiotensin-converting enzyme 2 (ACE2) and the receptor binding domain (RBD) of the original Wuhan-1 SARS-CoV-2 strain and emerging variants simultaneously, as a surrogate neutralization assay. Using this method, we demonstrate that serum antibodies collected from representative individuals at different time-points during the pandemic present variable neutralizing activity against emerging variants, such as Omicron BA.1 and South African B.1.351. Importantly, antibodies present in samples collected during 2021, before the third dose of the vaccine was administered, do not confer complete neutralization against Omicron BA.1, as opposed to samples collected in 2022 which show significant neutralizing activity. The proposed approach has a comparable performance to other established surrogate methods such as cell-based assays using pseudotyped lentiviral particles expressing the spike of SARS-CoV-2, as demonstrated by the assessment of the blocking activity of therapeutic antibodies (i.e. Imdevimab) and serum samples. This method offers a scalable, cost effective and adaptable platform for the dynamic evaluation of antibody protection in affected populations against variants of SARS-CoV-2.Funding: This research was supported by the SPRI I+D COVID-19 fund (Basque Government, bG-COVID-19), BIOEF EITB Maratoia (BIO21/COV/037 to AP), the European Research Council (ERC) (ERC-2018-StG 804236-NEXTGEN-IO to AP), the Instituto de Salud Carlos iii (ISCiii, DTS21/00094 to AP and DTS20/00138 to MM-C), Ministerio de Ciencia, Innovación y Universidades (MICINN, PID2019-107956RA-I00 and TED2021-129433B-C21 to AP; PID2020-117116RB-I00 and RTC2019-007125-1 to MM-C) and the FERO Foundation to AP. Personal fellowships: EP-F (Juan de la Cierva-Formación, FJC2018-035449-I), ABo (AECC Bizkaia Scientific Foundation, PRDVZ19003BOSC), AG (Programa Bikaintek from the Basque Government, 48-AF-W1-2019-00012), AA-V (La Caixa Inphinit, LCF/BQ/DR20/11790022), BJ-L (Basque Government, PRE_2019_1_0320), ABl (AECC Bizkaia Scientific Foundation, PRDVZ21640DEBL), PV-B (Proyectos I +D+I, PRE2020-092342) and AP (Ramón y Cajal, RYC2018- 024183-I; and Ikerbasque Research Associate). Acknowledgments: The plasmids for the generation of pseudotyped lentiviral particles were kindly provided by Dr Jesse D. Bloom (Fred Hutchinson Cancer Research Center) and Dr Jean-Philippe Julien (The Hospital for Sick Children). HEK293T-ACE2 cells were kindly provided by Dr. June Ereño-Orbea (CIC bioGUNE) and Dr. Jean-Philippe Julien (The Hospital for Sick Children Research Institute, Toronto)

Computational Model Explains High Activity and Rapid Cycling of Rho GTPases within Protein Complexes

Formation of multiprotein complexes on cellular membranes is critically dependent on the cyclic activation of small GTPases. FRAP-based analyses demonstrate that within protein complexes, some small GTPases cycle nearly three orders of magnitude faster than they would spontaneously cycle in vitro. At the same time, experiments report concomitant excess of the activated, GTP-bound form of GTPases over their inactive form. Intuitively, high activity and rapid turnover are contradictory requirements. How the cells manage to maximize both remains poorly understood. Here, using GTPases of the Rab and Rho families as a prototype, we introduce a computational model of the GTPase cycle. We quantitatively investigate several plausible layouts of the cycling control module that consist of GEFs, GAPs, and GTPase effectors. We explain the existing experimental data and predict how the cycling of GTPases is controlled by the regulatory proteins in vivo. Our model explains distinct and separable roles that the activating GEFs and deactivating GAPs play in the GTPase cycling control. While the activity of GTPase is mainly defined by GEF, the turnover rate is a sole function of GAP. Maximization of the GTPase activity and turnover rate places conflicting requirements on the concentration of GAP. Therefore, to achieve a high activity and turnover rate at once, cells must carefully maintain concentrations of GEFs and GAPs within the optimal range. The values of these optimal concentrations indicate that efficient cycling can be achieved only within dense protein complexes typically assembled on the membrane surfaces. We show that the concentration requirement for GEF can be dramatically reduced by a GEF-activating GTPase effector that can also significantly boost the cycling efficiency. Interestingly, we find that the cycling regimes are only weakly dependent on the concentration of GTPase itself