The Effect of the Disorder on the Longitudinal Resistance of a Graphene p-n Junction in Quantum Hall Regime

The longitudinal resistances of a six-terminal graphene p-n junction under a perpendicular magnetic field are investigated. Because of the chirality of the Hall edge states, the longitudinal resistances on top and bottom edges of the graphene ribbon are not equal. In the presence of suitable disorder, the top-edge and bottom-edge resistances well show the plateau structures in the both unipolar and bipolar regimes and the plateau values are determined by the Landau filling factors only. These plateau structures are in excellent agreement with the recent experiment. For the unipolar junction, the resistance plateaus emerge in the absence of impurity and they are destroyed by strong disorder. But for the bipolar junction, the resistances are very large without the plateau structures in the clean junction. The disorder can strongly reduce the resistances and leads the formation of the resistance plateaus, due to the mixture of the Hall edge states in virtue of the disorder. In addition, the size effect of the junction on the resistances is studied and some extra resistance plateaus are found in the long graphene junction case. This is explained by the fact that only part of the edge states participate in the full mixing.Comment: 7 pages, 5 figure

Learning Rays via Deep Neural Network in a Ray-based IPDG Method for High-Frequency Helmholtz Equations in Inhomogeneous Media

We develop a deep learning approach to extract ray directions at discrete locations by analyzing highly oscillatory wave fields. A deep neural network is trained on a set of local plane-wave fields to predict ray directions at discrete locations. The resulting deep neural network is then applied to a reduced-frequency Helmholtz solution to extract the directions, which are further incorporated into a ray-based interior-penalty discontinuous Galerkin (IPDG) method to solve the Helmholtz equations at higher frequencies. In this way, we observe no apparent pollution effects in the resulting Helmholtz solutions in inhomogeneous media. Our 2D and 3D numerical results show that the proposed scheme is very efficient and yields highly accurate solutions.Comment: 30 page

AI chatbots not yet ready for clinical use

As large language models (LLMs) expand and become more advanced, so do the natural language processing capabilities of conversational AI, or “chatbots”. OpenAI's recent release, ChatGPT, uses a transformer-based model to enable human-like text generation and question-answering on general domain knowledge, while a healthcare-specific Large Language Model (LLM) such as GatorTron has focused on the real-world healthcare domain knowledge. As LLMs advance to achieve near human-level performances on medical question and answering benchmarks, it is probable that Conversational AI will soon be developed for use in healthcare. In this article we discuss the potential and compare the performance of two different approaches to generative pretrained transformers—ChatGPT, the most widely used general conversational LLM, and Foresight, a GPT (generative pretrained transformer) based model focused on modelling patients and disorders. The comparison is conducted on the task of forecasting relevant diagnoses based on clinical vignettes. We also discuss important considerations and limitations of transformer-based chatbots for clinical use

Bis[(1S*,2S*)-trans-1,2-bis­(diphenyl­phosphin­oxy)cyclo­hexa­ne]chlorido­ruthenium(II) trifluoro­methane­sulfonate dichloro­methane disolvate

The crystal structure of a racemic mixture of the title ruthenium(II) complex, [RuCl(C30H30O2P2)2]CF3SO3·2CH2Cl2, reveals that the coordination geometry about the coordinatively unsaturated metal centre is approximately trigonal-pyramidal, with the chlorine atom occupying one of the equatorial positions. The axial Ru—P bonds are longer than the equatorial Ru—P bonds and there is an acute P—Ru—P angle

SCRIBBLE is required for pregnancy-induced alveologenesis in the adult mammary gland

The cell polarity protein SCRIB is a critical regulator of polarization, cell migration and tumourigenesis. Whereas SCRIB is known to regulate early stages of mouse mammary gland development, its function in the adult gland is not known. Using an inducible RNAi mouse model for downregulating SCRIB expression, we report an unexpected role for SCRIB as a positive regulator of cell proliferation during pregnancy associated mammary alveologenesis. SCRIB was required in the epithelial cell compartment of the mammary gland. Lack of SCRIB attenuated prolactin-induced activation of the JAK2/STAT5 signaling pathway. In addition, loss of SCRIB resulted in the downregulation of PRLR at cell surface and accumulation in intracellular structures that express markers of the Golgi apparatus and the recycling endosome. Unlike its role in virgin gland as a negative regulator cell proliferation, SCRIB is a positive regulator of mammary epithelial cell proliferation during pregnancy