Charge transfer excitations, pair density waves, and superconductivity in moiré materials

Transition-metal dichalcogenide (TMD) bilayers are a new class of tunable moiré systems attracting interest as quantum simulators of strongly interacting electrons in two dimensions. In particular, recent theory predicts that the correlated insulator observed in WSe₂/WS₂ at half filling is a charge-transfer insulator similar to cuprates and, upon further hole doping, exhibits a transfer of charge from anionlike to cationlike orbitals at different locations in the moiré unit cell. In this work, we demonstrate that in this doped charge-transfer insulator, tightly bound charge-2e excitations can form to lower the total electrostatic repulsion. This composite excitation, which we dub a trimer, consists of a pair of holes bound to a charge-transfer exciton. When the bandwidth of doped holes is small, trimers crystallize into insulating pair density waves at a sequence of commensurate doping levels. When the bandwidth becomes comparable to the pair binding energy, itinerant holes and charge-2e trimers interact resonantly, leading to unconventional superconductivity similar to superfluidity in an ultracold Fermi gas near Feshbach resonance. Our theory is broadly applicable to strongly interacting charge-transfer insulators, such as WSe₂/WS₂ or TMD homobilayers under an applied electric field

Charge transfer excitations, pair density waves, and superconductivity in moiré materials

Transition-metal dichalcogenide (TMD) bilayers are a new class of tunable moiré systems attracting interest as quantum simulators of strongly interacting electrons in two dimensions. In particular, recent theory predicts that the correlated insulator observed in WSe₂/WS₂ at half filling is a charge-transfer insulator similar to cuprates and, upon further hole doping, exhibits a transfer of charge from anionlike to cationlike orbitals at different locations in the moiré unit cell. In this work, we demonstrate that in this doped charge-transfer insulator, tightly bound charge-2e excitations can form to lower the total electrostatic repulsion. This composite excitation, which we dub a trimer, consists of a pair of holes bound to a charge-transfer exciton. When the bandwidth of doped holes is small, trimers crystallize into insulating pair density waves at a sequence of commensurate doping levels. When the bandwidth becomes comparable to the pair binding energy, itinerant holes and charge-2e trimers interact resonantly, leading to unconventional superconductivity similar to superfluidity in an ultracold Fermi gas near Feshbach resonance. Our theory is broadly applicable to strongly interacting charge-transfer insulators, such as WSe₂/WS₂ or TMD homobilayers under an applied electric field

Confidence Intervals for the F1 Score: A Comparison of Four Methods

In Natural Language Processing (NLP), binary classification algorithms are often evaluated using the F1 score. Because the sample F1 score is an estimate of the population F1 score, it is not sufficient to report the sample F1 score without an indication of how accurate it is. Confidence intervals are an indication of how accurate the sample F1 score is. However, most studies either do not report them or report them using methods that demonstrate poor statistical properties. In the present study, I review current analytical methods (i.e., Clopper-Pearson method and Wald method) to construct confidence intervals for the population F1 score, propose two new analytical methods (i.e., Wilson direct method and Wilson indirect method) to do so, and compare these methods based on their coverage probabilities and interval lengths, as well as whether these methods suffer from overshoot and degeneracy. Theoretical results demonstrate that both proposed methods do not suffer from overshoot and degeneracy. Experimental results suggest that both proposed methods perform better, as compared to current methods, in terms of coverage probabilities and interval lengths. I illustrate both current and proposed methods on two suggestion mining tasks. I discuss the practical implications of these results, and suggest areas for future research.Comment: 12 pages, 2 figure

Multi-omics characterization of pancreatic neuroendocrine neoplasms

Pancreatic neuroendocrine neoplasms (PNENs) are biologically and clinically heterogeneous neoplasms in which pathogenic alterations are often indiscernible. Treatments for PNENs are insufficient in part due to lack of alternatives once current options are exhausted. Despite previous efforts to characterize PNENs at the molecular level, there remains a lack of molecular subgroups and molecular features with clinical utility for PNENs. In this work, I describe the identification and characterization of four molecularly distinct subgroups from primary PNEN specimens using whole-exome sequencing, RNA-sequencing and global proteome profiling. A Proliferative subgroup with molecular features of proliferating cells was associated with an inferior overall survival probability. A PDX1-high subgroup consisted of PNENs demonstrating genetic and transcriptomic indications of NRAS or HRAS activation. An Alpha cell-like subgroup, enriched in PNENs with deleterious MEN1 and DAXX mutations, bore transcriptomic similarity to pancreatic α-cells and harbored proteomic cues of dysregulated metabolism involving glutamine and arginine. Lastly, a Stromal/Mesenchymal subgroup exhibited increased expression and activation of the Hippo signaling pathway effectors YAP1 and WWTR1 that are of emerging interest as potentially actionable targets in other cancer types. Whole-genome and whole-transcriptome analysis of PNEN metastases identified novel molecular events likely contributing to pathogenesis, including one case presumably driven by MYCN amplification. In agreement with the findings in primary PNENs, four of the metastatic PNENs displayed a substantial Alpha cell-like subgroup signature and all harboured concurrent mutations in MEN1 and DAXX. Collectively, the identified subgroups present a potential stratification scheme that facilitates the identification of therapeutic vulnerabilities amidst PNEN heterogeneity to improve the effective management of PNENs

Performing GNSS Shadow Matching for User Equipment with Varied Carrying Positions

This publication describes apparatuses, methods, and techniques for performing Global Navigation Satellite System (GNSS) shadow matching for user equipment (e.g., smartphones) with varied carrying positions, such as in a user’s hand, pocket, purse, backpack, and so forth. To do so, the smartphone utilizes an Urban Canyon Positioning Algorithm to find line-of-sight (LOS) signals of satellites of the GNSS. Then, the Urban Canyon Positioning Algorithm estimates a signal-strength degradation of the LOS signals due to the carrying position, such as when the user puts their smartphone in their pocket. After estimating the signal-strength degradation of the LOS signals, the Urban Canyon Positioning Algorithm adjusts LOS signals and non-line-of-sight (NLOS) signals with the estimated signal-strength degradation of the LOS signals. Finally, the Urban Canyon Positioning Algorithm computes GNSS shadow matching by adjusting parameters (e.g., the median and the standard deviation) of the signal strength of all the signals (LOS and NLOS) received by the smartphone

Evolutionary Dynamics of Gig Economy Labor Strategies under Technology, Policy and Market Influence

The emergence of the modern gig economy introduces a new set of employment considerations for firms and laborers that include various trade-offs. With a game-theoretical approach, we examine the influences of technology, policy and markets on firm and worker preferences for gig labor. Theoretically, we present a new extension to the replicator equation and model oscillating dynamics in two-player asymmetric bi-matrix games with time-evolving environments, introducing concepts of the attractor arc, trapping zone and escape. We demonstrate how changing market conditions result in distinct evolutionary patterns for gig-labor preferences across high and low skill work-forces, which we explain through their differing sensitivities to market-driven consumer demand and financial incentives among other considerations. Informing tensions regarding the future of this new employment category, we present a novel payoff framework to analyze the role of technology on the growth of the gig economy. Finally, we explore regulatory implications within the gig economy, demonstrating how intervals of lenient and strict policy alter firm and worker sensitivities between gig and employee labor strategies

Incidence estimates for α\alpha-dimensional tubes and β\beta-dimensional balls in R2\mathbb{R}^2

We prove essentially sharp incidence estimates for a collection of $\delta$-tubes and $\delta$-balls in the plane, where the $\delta$-tubes satisfy an $\alpha$-dimensional spacing condition and the $\delta$-balls satisfy a $\beta$-dimensional spacing condition. Our approach combines a combinatorial argument for small $\alpha, \beta$ and a Fourier analytic argument for large $\alpha, \beta$.Comment: 18 pages, 8 figure

Customisable abstract representation layer for digital libraries

Includes bibliographical references (leaves 79-82).The user interface is a very important component in a piece of software as it is the layer which allows user interaction with the underlying functionality. Within the domain of digital libraries modification to the interface layer, to make it more appropriate for target users, requires substantial programming skill. This research studies the possibility of making a user customisable interface system by using HeI methodologies for user requirements identification and evaluation, as well as AJAX (Asynchronous JavaScript and XML) for design and development. The final prototype allows users to directly design pages by adding, deleting, dragging and dropping elements in a Web browser. The research ends with an expert evaluation of such a system where satisfactory results were shown

A Chemical and Enzymatic Approach to Study Site-Specific Sumoylation.

A variety of cellular pathways are regulated by protein modifications with ubiquitin-family proteins. SUMO, the Small Ubiquitin-like MOdifier, is covalently attached to lysine on target proteins via a cascade reaction catalyzed by E1, E2, and E3 enzymes. A major barrier to understanding the diverse regulatory roles of SUMO has been a lack of suitable methods to identify protein sumoylation sites. Here we developed a mass-spectrometry (MS) based approach combining chemical and enzymatic modifications to identify sumoylation sites. We applied this method to analyze the auto-sumoylation of the E1 enzyme in vitro and compared it to the GG-remnant method using Smt3-I96R as a substrate. We further examined the effect of smt3-I96R mutation in vivo and performed a proteome-wide analysis of protein sumoylation sites in Saccharomyces cerevisiae. To validate these findings, we confirmed several sumoylation sites of Aos1 and Uba2 in vivo. Together, these results demonstrate that our chemical and enzymatic method for identifying protein sumoylation sites provides a useful tool and that a combination of methods allows a detailed analysis of protein sumoylation sites