Rumor Clarification, Digital Platform, and Stock Movement

Stock return is influenced by information release, dissemination, and acceptance. Rumor clarification is supposed to reduce asymmetric information and abnormal stock return. In this research, we extracted 4134 rumor-clarification pairs from 687,429 postings in social media, and quantified the language used in these messages, along with online firm behaviors, to study the effect of clarifications on stock returns. Our findings include (1) the digitalized rumor clarification messages affect the abnormal returns of the relevant stocks; (2) Such influence can be quantified and measured by the emotion polarity of rumor clarification; (3) Firm’s online clarification behaviors may have no influence on abnormal returns except for the total response number of rumor clarification for a listed company. In particular, investors prefer to trust the clarifications from the companies with frequent online interactive engagements

Anticancer drug synergy prediction in understudied tissues using transfer learning

ocaa212Objective: Drug combination screening has advantages in identifying cancer treatment options with higher efficacy without degradation in terms of safety. A key challenge is that the accumulated number of observations in in-vitro drug responses varies greatly among different cancer types, where some tissues are more understudied than the others. Thus, we aim to develop a drug synergy prediction model for understudied tissues as a way of overcoming data scarcity problems. Materials and Methods: We collected a comprehensive set of genetic, molecular, phenotypic features for cancer cell lines. We developed a drug synergy prediction model based on multitask deep neural networks to integrate multimodal input and multiple output. We also utilized transfer learning from data-rich tissues to data-poor tissues. Results: We showed improved accuracy in predicting synergy in both data-rich tissues and understudied tissues. In data-rich tissue, the prediction model accuracy was 0.9577 AUROC for binarized classification task and 174.3 mean squared error for regression task. We observed that an adequate transfer learning strategy significantly increases accuracy in the understudied tissues. Conclusions: Our synergy prediction model can be used to rank synergistic drug combinations in understudied tissues and thus help to prioritize future in-vitro experiments. Code is available at https://github.com/yejinjkim/synergy-transfer.Peer reviewe

Oxygen dissociation on the C3N monolayer: A first-principles study

The oxygen dissociation and the oxidized structure on the pristine C3N monolayer in exposure to air are the inevitably critical issues for the C3N engineering and surface functionalization yet have not been revealed in detail. Using the first-principles calculations, we have systematically investigated the possible O2 adsorption sites, various O2 dissociation pathways and the oxidized structures. It is demonstrated that the pristine C3N monolayer shows more O2 physisorption sites and exhibits stronger O2 adsorption than the pristine graphene. Among various dissociation pathways, the most preferable one is a two-step process involving an intermediate state with the chemisorbed O2 and the barrier is lower than that on the pristine graphene, indicating that the pristine C3N monolayer is more susceptible to oxidation than the pristine graphene. Furthermore, we found that the most stable oxidized structure is not produced by the most preferable dissociation pathway but generated from a direct dissociation process. These results can be generalized into a wide range of temperatures and pressures using ab initio atomistic thermodynamics. Our findings deepen the understanding of the chemical stability of 2D crystalline carbon nitrides under ambient conditions, and could provide insights into the tailoring of the surface chemical structures via doping and oxidation.Comment: 23 pages,8 figure

Observation of spin polarons in a frustrated moir\'e Hubbard system

The electron's kinetic energy plays a pivotal role in magnetism. While virtual electron hopping promotes antiferromagnetism in an insulator, the real process usually favors ferromagnetism. But in kinetically frustrated systems, such as hole doped triangular lattice Mott insulators, real hopping has been shown to favor antiferromagnetism. Kinetic frustration has also been predicted to induce a new quasiparticle -- a bound state of the doped hole and a spin flip called a spin polaron -- at intermediate magnetic fields, which could form an unusual metallic state. However, the direct experimental observation of spin polarons has remained elusive. Here we report the observation of spin polarons in triangular lattice MoTe2/WSe2 moir\'e bilayers by the reflective magnetic circular dichroism measurements. We identify a spin polaron phase at lattice filling factor between 0.8-1 and magnetic field between 2-4 T; it is separated from the fully spin polarized phase by a metamagnetic transition. We determine that the spin polaron is a spin-3/2 particle and its binding energy is commensurate to the kinetic hopping energy. Our results open the door for exploring spin polaron pseudogap metals, spin polaron pairing and other new phenomena in triangular lattice moir\'e materials

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training

Emergence of ferromagnetism at the onset of moir\'e Kondo breakdown

The interaction of a lattice of localized magnetic moments with a sea of conduction electrons in Kondo lattice models induces rich quantum phases of matter, such as Fermi liquids with heavily renormalized electronic quasiparticles, quantum critical non-Fermi liquid metals and unconventional superconductors, among others. The recent demonstration of moir\'e Kondo lattices has opened the door to investigate the Kondo problem with continuously tunable parameters. Although a heavy Fermi liquid phase has been identified in moir\'e Kondo lattices, the magnetic phases and Kondo breakdown transitions remain unexplored. Here we report a density-tuned Kondo destruction in AB-stacked MoTe2/WSe2 moir\'e bilayers by combining magneto transport and optical studies. As the itinerant carrier density decreases, the Kondo temperature decreases. At a critical density, we observe a heavy Fermi liquid to insulator transition, and a nearly concomitant emergence of ferromagnetic order. The observation is consistent with the scenario of a ferromagnetic Anderson insulator and suppression of the Kondo screening effect. Our results pave the path for inducing other exotic quantum phase transitions in moir\'e Kondo lattices

Determination of the spin axis in quantum spin Hall insulator monolayer WTe2

Evidence for the quantum spin Hall (QSH) effect has been reported in several experimental systems in the form of approximately quantized edge conductance. However, the most fundamental feature of the QSH effect, spin-momentum locking in the edge channels, has never been demonstrated experimentally. Here, we report clear evidence for spin-momentum locking in the edge channels of monolayer WTe2, thought to be a two-dimensional topological insulator (2D TI). We observe that the edge conductance is controlled by the component of an applied magnetic field perpendicular to a particular axis, which we identify as the spin axis. The axis is the same for all edges, situated in the mirror plane perpendicular to the tungsten chains at 40$\pm$2{\deg} to the layer normal, implying that the spin-orbit coupling is inherited from the bulk band structure. We show that this finding is consistent with theory if the band-edge orbitals are taken to have like parity. We conclude that this parity assignment is correct and that both edge states and bulk bands in monolayer WTe2 share the same simple spin structure. Combined with other known features of the edge states this establishes spin-momentum locking, and therefore that monolayer WTe2 is truly a natural 2D TI