Braiding higher-order Majorana corner states through their spin degree of freedom

In this work, we study the spin texture of a class of higher-order topological superconductors (HOTSC) and show how it can be used to detect and braid Majorana corner modes (MCMs). This class of HOTSC is composed of two-dimensional topological insulators with s-wave superconductivity and in-plane magnetic fields, which offers advantages in experimental implementation. The spin polarization of the MCMs in this class is perpendicular with the applied magnetic field direction and is opposite on intrinsic orbitals, resulting in an overall ferrimagnetic spin texture. As a result, we find that the spin-selective Andreev reflection can be observed in a transverse instead of parallel direction to the applied magnetic field. Meanwhile, this spin texture leads to the gate-tunable $4\pi$ periodic $\phi_0$ Josephson current that performs qualitatively different behavior from the topologically trivial $\phi_0$-junction under rotating the in-plane magnetic field. Meanwhile, the existence of the MCMs in this class does not depend on the in-plane magnetic field direction. This gives rise to great advantage in constructing all electronically controlled Majorana network for braiding, which is confirmed through our numerical simulation. We thus provide a comprehensive scheme for probing non-Abelian statistics in this class of HOTSCs.Comment: 6 pages, 4 figure

Machine tool digital twin: Modelling methodology and applications

Cyber-Physical Machine Tools (CPMT) represent a new generation of complete Cyber-Physical Systems (CPS)-based machine tools that deeply integrate machine tool and machining processes with computation and networking. CPMT have a higher level of connectivity, intelligence and autonomy compared to current machine tools. Digital Twin is a critical component of any CPS. The core of a CPMT lies in the Machine Tool Digital Twin (MTDT). This paper presents the methodology for modelling the MTDT based on open, unified and platform-independent communication standards such as MTConnect and OPC UA. Two applications of the MTDT are developed to demonstrate the advantages and potential of the proposed approach. The first application is a Web-based machine tool condition monitoring application that allows users to monitor the real-time status as well as the 3D model of the machine tool through web browsers on mobile devices. The second application is an advanced Augmented Reality (AR)-assisted wearable Human-Machine Interface (HMI) that provides users with intuitive and enhanced visualization of the machining processes

Effects of dietary guava leaf aqueous extract supplementation on growth, antioxidant capacity, and non-specific immunity in mud crab <em>Scylla paramamosain</em>

Mud crab (*Scylla paramamosain*) fed five different diets with varying concentrations of guava leaf aqueous extract (0 mg·kg^--1^, 80 mg·kg^--1^, 160 mg·kg^--1^, 320 mg·kg^--1^, and 640 mg·kg^--1^) for 30 days. Mud crabs in the 320 mg·kg^--1^ guava-leaf extract groups outperformed the control group in terms of survival rates (SR), weight gain rates (WGR), and specific growth rates (SGR). When compared to the control group, mud crabs in the 320 mg·kg^--1^ guava-leaf extract groups had significantly higher levels of lipase (LPS), pepsin, lysozyme (LZM), superoxide dismutase (SOD), acid phosphatase (ACP), and glutathione (GSH) (*P \< 0.05*). The amylase (AMS) activity was significantly decreased in all experimental groups (*P \< 0.05*). Malondialdehyde (MDA) content in the hepatopancreas of mud crabs in the 160 mg·kg^--1^, 320 mg·kg^--1^, and 640 mg·kg^--1^ guava-leaf extract groups were significantly reduced compared to the control group (*P \< 0.05*). Additionally, real-time PCR results illustrated that the expression levels of *GPx3*, *CAT*, and *JNK* were all considerably increased in the 80 mg·kg^--1^ guava-leaf extract groups compared to the control group (*P \< 0.05*). In the 160 mg·kg^--1^, 320 mg·kg^--1^, and 320 mg·kg^--1^ guava-leaf extract groups, the expression levels of *SOD* genes were considerably greater than the control (*P \< 0.05*), which was consistent with the level of SOD activity. *GST* and *P53* gene expression levels were significantly up-regulated in the 80 mg·kg^--1^, 160 mg·kg^--1^, 320 mg·kg^--1^, and 640 mg·kg^--1^ guava-leaf extract groups compared to the control group (*P \< 0.05*). Overall, the addition of 160 mg·kg^--1^-320 mg·kg^--1^ guava-leaf extract to the feed of *Scylla paramamosain* promoted growth, enhanced the activities of digestive and antioxidant enzymes, and strengthened immunity

Deterministic topological quantum gates for Majorana qubits without ancillary modes

The realization of quantum gates in topological quantum computation still confronts significant challenges in both fundamental and practical aspects. Here, we propose a deterministic and fully topologically protected measurement-based scheme to realize the issue of implementing Clifford quantum gates on the Majorana qubits. Our scheme is based on rigorous proof that the single-qubit gate can be performed by leveraging the neighboring Majorana qubit but not disturbing its carried quantum information, eliminating the need for ancillary Majorana zero modes (MZMs) in topological quantum computing. Benefiting from the ancilla-free construction, we show the minimum measurement sequences with four steps to achieve two-qubit Clifford gates by constructing their geometric visualization. To avoid the uncertainty of the measurement-only strategy, we propose manipulating the MZMs in their parameter space to correct the undesired measurement outcomes while maintaining complete topological protection, as demonstrated in a concrete Majorana platform. Our scheme identifies the minimal operations of measurement-based topological and deterministic Clifford gates and offers an ancilla-free design of topological quantum computation.Comment: 5 pages, 3 figures and appendi

N evolution and physiochemical structure changes in chars during co-pyrolysis: Effects of abundance of glucose in fiberboard

© 2020 by the authors. The simple incineration of wood-based panels (WBPs) waste generates a significant amount of NOx, which has led to urgency in developing a new method for treating the N-containing biomass residues. This work aims to examine the N evolution and physiochemical structural changes during the co-pyrolysis of fiberboard and glucose, where the percentage of glucose in the feedstock was varied from 0% to 70%. It was found that N retention in chars was monotonically increased with increasing use of glucose, achieving ~60% N fixation when the glucose accounted for 70% in the mixture. Pyrrole-N (N-5) and Pyridine-N (N-6) were preferentially formed at high ratios of glucose to fiberboard. While the relevant importance of volatile–char interactions to N retention and transformation could be observed, the volatile–volatile reactions from the two feedstocks played a vital role in the increase in abundance of glucose. With the introduction of glucose, the porous structure and porosity in chars from the co-pyrolysis were dramatically altered, whereas the devolatilization of glucose tended to generate larger pores than the fiberboard. The insignificant changes in carbon structure of all chars revealed by Raman spectroscopy would practically allow us to apply the monosaccharides to the WBPs for regulating N evolution without concerns about its side effects for char carbon structures

Early Prediction of Alzheimers Disease Leveraging Symptom Occurrences from Longitudinal Electronic Health Records of US Military Veterans

Early prediction of Alzheimer's disease (AD) is crucial for timely intervention and treatment. This study aims to use machine learning approaches to analyze longitudinal electronic health records (EHRs) of patients with AD and identify signs and symptoms that can predict AD onset earlier. We used a case-control design with longitudinal EHRs from the U.S. Department of Veterans Affairs Veterans Health Administration (VHA) from 2004 to 2021. Cases were VHA patients with AD diagnosed after 1/1/2016 based on ICD-10-CM codes, matched 1:9 with controls by age, sex and clinical utilization with replacement. We used a panel of AD-related keywords and their occurrences over time in a patient's longitudinal EHRs as predictors for AD prediction with four machine learning models. We performed subgroup analyses by age, sex, and race/ethnicity, and validated the model in a hold-out and "unseen" VHA stations group. Model discrimination, calibration, and other relevant metrics were reported for predictions up to ten years before ICD-based diagnosis. The study population included 16,701 cases and 39,097 matched controls. The average number of AD-related keywords (e.g., "concentration", "speaking") per year increased rapidly for cases as diagnosis approached, from around 10 to over 40, while remaining flat at 10 for controls. The best model achieved high discriminative accuracy (ROCAUC 0.997) for predictions using data from at least ten years before ICD-based diagnoses. The model was well-calibrated (Hosmer-Lemeshow goodness-of-fit p-value = 0.99) and consistent across subgroups of age, sex and race/ethnicity, except for patients younger than 65 (ROCAUC 0.746). Machine learning models using AD-related keywords identified from EHR notes can predict future AD diagnoses, suggesting its potential use for identifying AD risk using EHR notes, offering an affordable way for early screening on large population.Comment: 24 page

Antes del pensar : las aventuras del "ergo" desde Descartes hasta Heidegger

Desde Descartes hasta Husserl se desarrolla una figura de fundamentación filosófica que a partir del pensar autointuyente quiere alcanzar el ser mediante alguna conexión reflexiva o lógica, que en mi enunciado se simboliza con el "ergo". ¿Cómo lia de concebirse la conexión entre pensar y ser? Puede alcanzarse el ser cuando el punto de partida es el pensamiento? La forma de ver esa conexión es el hilo conductor de la filosofia moderna, y podría decirse que la modernidad filosófica acaba cuando se devuelve al ser la soberanía sobre el pensar (ontologización del neokantismo, reconducción de la fenomenología hacia el mundo de la vida). El punto decisivo en esta inflexión es la ontologia fundamental de Martin Heidegger. El camino que le precede está jalonado por Descartes, el idealismo alemán y la fenomenología