Suppression of stimulated Raman scattering by angularly incoherent light, towards a laser system of incoherence in all dimensions of time, space, and angle

Laser-plasma instability (LPI) is one of the main obstacles in laser-driven inertial confinement fusion (ICF) for achieving predictable and reproducible fusion at high gain. For the first time we have proved analytically and confirmed with three-dimensional particle-in-cell simulations that angular incoherence has additional and much stronger suppression of the instability growth rate than the well-known temporal incoherence and spatial incoherence usually used in ICF studies. For the model used in our calculations, the maximum field ratio between the stimulated Raman scattering and the driving pulses drops from 0.2 for the Laguerre-Gaussian pulse with a single non-zero topological charge to 0.05 for the super light spring with an angular momentum spread and random relative phases. In particular, angular incoherence does not introduce extra undesirable hot electrons. This opens a novel way to suppress LPI with the light of an angular momentum spread and paves the way towards a low LPI laser system with a super light spring of incoherence in all dimensions of time, space, and angle

Heterostructure of ferromagnetic and ferroelectric materials with magneto-optic and electro-optic effects

A heterostructure of multiferroics or magnetoelectrics (ME) was disclosed. The film has both ferromagnetic and ferroelectric properties, as well as magneto-optic (MO) and electro-optic (EO) properties. Oxide buffer layers were employed to allow grown a cracking-free heterostructure a solution coating method

A Rare Case of a Primary Cardiac Tumor Presenting as Fatal Ventricular Tachycardia

Primary cardiac tumors are extremely uncommon. Here, we report the case of a patient with a primary left ventricular interstitial tumor presenting with hemodynamically unstable ventricular tachycardia. In response to hemodynamically unstable ventricular tachycardia, an implantable cardioverter-defibrillator was inserted. One month after defibrillator implantation, the patient developed episodes of high ventricular tachycardia that could not be effectively terminated by catheter radiofrequency ablation, thus further confirming that the ventricular tachycardia was induced by the left ventricular interstitial tumor. The patient is doing well on medical therapy to date

Lost at starting line : predicting maladaptation of university freshmen based on educational big data

The transition from secondary education to higher education could be challenging for most freshmen. For students who fail to adjust to university life smoothly, their status may worsen if the university cannot offer timely and proper guidance. Helping students adapt to university life is a long-term goal for any academic institution. Therefore, understanding the nature of the maladaptation phenomenon and the early prediction of “at-risk” students are crucial tasks that urgently need to be tackled effectively. This article aims to analyze the relevant factors that affect the maladaptation phenomenon and predict this phenomenon in advance. We develop a prediction framework (MAladaptive STudEnt pRediction, MASTER) for the early prediction of students with maladaptation. First, our framework uses the SMOTE (Synthetic Minority Oversampling Technique) algorithm to solve the data label imbalance issue. Moreover, a novel ensemble algorithm, priority forest, is proposed for outputting ranks instead of binary results, which enables us to perform proactive interventions in a prioritized manner where limited education resources are available. Experimental results on real-world education datasets demonstrate that the MASTER framework outperforms other state-of-art methods. © 2022 The Authors. Journal of the Association for Information Science and Technology published by Wiley Periodicals LLC on behalf of Association for Information Science and Technology

Experimental Study of Closed System in the Chlorine Dioxide-Iodide-Sulfuric Acid Reaction by UV-Vis Spectrophotometric Method

The mole ratio r(r = [I−]0/[ClO2]0) has great influence on ClO2-I−-H2SO4 closed reaction system. By changing the initiate concentration of potassium iodide, the curve of absorbance along with the reaction time was obtained at 350 nm and 297 nm for triiodide ion, and 460 nm for iodine. The changing point of the absorbance curve's shape locates at r = 6.00. For the reaction of ClO2-I− in the absence of H2SO4, the curve of absorbance along with the reaction time can be obtained at 350 nm for triiodide ion, 460 nm for iodine. The mole ratio r is equal to 1.00 is the changing point of the curve's shape no matter at which wavelength to determine the reaction. For the reaction of ClO2-I−-H+ in different pH buffer solution, the curve of absorbance along with the reaction time was recorded at 460 nm for iodine. When r is greater than 1.00, the transition point of the curve's shape locates at pH 2.0, which is also the point of producing chlorite or chloride for chlorine dioxide at different pH. When r is less than 1.00, the transition point locates at pH 7.0

Educational anomaly analytics : features, methods, and challenges

Anomalies in education affect the personal careers of students and universities' retention rates. Understanding the laws behind educational anomalies promotes the development of individual students and improves the overall quality of education. However, the inaccessibility of educational data hinders the development of the field. Previous research in this field used questionnaires, which are time- and cost-consuming and hardly applicable to large-scale student cohorts. With the popularity of educational management systems and the rise of online education during the prevalence of COVID-19, a large amount of educational data is available online and offline, providing an unprecedented opportunity to explore educational anomalies from a data-driven perspective. As an emerging field, educational anomaly analytics rapidly attracts scholars from a variety of fields, including education, psychology, sociology, and computer science. This paper intends to provide a comprehensive review of data-driven analytics of educational anomalies from a methodological standpoint. We focus on the following five types of research that received the most attention: course failure prediction, dropout prediction, mental health problems detection, prediction of difficulty in graduation, and prediction of difficulty in employment. Then, we discuss the challenges of current related research. This study aims to provide references for educational policymaking while promoting the development of educational anomaly analytics as a growing field. Copyright © 2022 Guo, Bai, Tian, Firmin and Xia