Observation of vacancy-induced suppression of electronic cooling in defected graphene

Previous studies of electron-phonon interaction in impure graphene have found that static disorder can give rise to an enhancement of electronic cooling. We investigate the effect of dynamic disorder and observe over an order of magnitude suppression of electronic cooling compared with clean graphene. The effect is stronger in graphene with more vacancies, confirming its vacancy-induced nature. The dependence of the coupling constant on the phonon temperature implies its link to the dynamics of disorder. Our study highlights the effect of disorder on electron-phonon interaction in graphene. In addition, the suppression of electronic cooling holds great promise for improving the performance of graphene-based bolometer and photo-detector devices.Comment: 13 pages, 4 figure

Creating And Maintaining Instructor/Student Connection Between Class Meetings: The Use Of Eyejot-A Video Messaging Technology

Eyejot, a free video email service, makes it possible to create, send, and receive video messages over the Internet. By adding the warmth of face-to-face interaction to the traditional email message, Eyejot creates a more interactive form of communication that engages today’s tech-savvy students. This paper shares our experience using Eyejot to strengthen rapport and engagement between instructor and student outside the traditional classroom setting. We describe how Eyejot works and offer tips for incorporating Eyejot into course design. Student feedback offers anecdotal evidence indicating a high level of satisfaction that Eyejot brings to the teaching-learning experience

Spatially dispersive circular photogalvanic effect in a Weyl semimetal

Weyl semimetals are gapless topological states of matter with broken inversion and/or time reversal symmetry, which can support unconventional responses to externally applied electrical, optical and magnetic fields. Here we report a new photogalvanic effect in type-II WSMs, MoTe2 and Mo0.9W0.1Te2, which are observed to support a circulating photocurrent when illuminated by circularly polarized light at normal incidence. This effect occurs exclusively in the inversion broken phase, where crucially we find that it is associated with a spatially varying beam profile via a new dispersive contribution to the circular photogalvanic effect (s-CPGE). The response functions derived for s-CPGE reveal the microscopic mechanism of this photocurrent, which are controlled by terms that are allowed in the absence of inversion symmetry, along with asymmetric carrier excitation and relaxation. By evaluating this response for a minimal model of a Weyl semimetal, we obtain the frequency dependent scaling behavior of this form of photocurrent. These results demonstrate opportunities for controlling photoresponse by patterning optical fields to store, manipulate and transmit information over a wide spectral range

Descope of the ALIA mission

The present work reports on a feasibility study commissioned by the Chinese Academy of Sciences of China to explore various possible mission options to detect gravitational waves in space alternative to that of the eLISA/LISA mission concept. Based on the relative merits assigned to science and technological viability, a few representative mission options descoped from the ALIA mission are considered. A semi-analytic Monte Carlo simulation is carried out to understand the cosmic black hole merger histories starting from intermediate mass black holes at high redshift as well as the possible scientific merits of the mission options considered in probing the light seed black holes and their coevolution with galaxies in early Universe. The study indicates that, by choosing the armlength of the interferometer to be three million kilometers and shifting the sensitivity floor to around one-hundredth Hz, together with a very moderate improvement on the position noise budget, there are certain mission options capable of exploring light seed, intermediate mass black hole binaries at high redshift that are not readily accessible to eLISA/LISA, and yet the technological requirements seem to within reach in the next few decades for China

Nonlinear Optical Responses in Type-II Weyl Semimetals

Weyl semimetals are gapless topological states of matter with broken inversion and/or time reversal symmetry. In this thesis, we will firstly discuss the observation of a novel photogalvanic effect in type-II Weyl semimetals including Td-MoTe2 Mo0.9W0.1Te2 and Mo0.3W0.7Te2. A circulating photocurrent is obtained under the illumination of normally incident light with circular polarization and the circulating current direction is opposite with different light helicity. Through temperature induced phase transition of MoTe2, this effect is further confirmed to exclusively occur in the Weyl phase. Since this CPGE current is controlled by the spatially varying beam profile, we define the effect as a spatially dispersive circular photogalvanic effect (sCPGE) and current amplitude is proven to be proportional to the beam gradient. By performing frequency-dependent measurements on the Weyl phase, we observe a sign reversal of sCPGE current at high energy excitation and low energy excitation. Our theoretical derivation shows that sCPGE is controlled by a unique symmetry selection rule related to asymmetric carrier excitation and relaxation, explaining the difference between Weyl phase and trivial phase as well as frequency dependent properties. Photoinduced anomalous Hall effect (AHE) is also observed in type-II Weyl semimetals. Longitudinal CPGE current is obtained under normally incident light while applying transverse bias, and the current magnitude is observed to be proportional to the bias voltage. Comparing the AHE conductivity in the 1T\u27 phase and the Td phase of MoT2,e photoinduced AHE is found to be much more significant in Weyl phase. This effect can be understood by symmetry arguments and is described by a Fermi surface modulation under the external electric field; meanwhile, the difference between two phases is evaluated. This model further predicts that under low energy excitation, Weyl points can be partially muted with tilted Fermi level, which provides a promising method to probe the band topology and Weyl nodes as well as encode more degree of freedom in device applications. Our studies on sCPGE and photoinduced AHE in type-II Weyl semimetals provide a new idea of probing and controlling nonlinear optical responses of topological semimetals and will potentially promote the applications of those new material systems

Research Progress of Respiratory Disease and Idiopathic Pulmonary Fibrosis Based on Artificial Intelligence

Machine Learning (ML) is an algorithm based on big data, which learns patterns from the previously observed data through classifying, predicting, and optimizing to accomplish specific tasks. In recent years, there has been rapid development in the field of ML in medicine, including lung imaging analysis, intensive medical monitoring, mechanical ventilation, and there is need for intubation etiology prediction evaluation, pulmonary function evaluation and prediction, obstructive sleep apnea, such as biological information monitoring and so on. ML can have good performance and is a great potential tool, especially in the imaging diagnosis of interstitial lung disease. Idiopathic pulmonary fibrosis (IPF) is a major problem in the treatment of respiratory diseases, due to the abnormal proliferation of fibroblasts, leading to lung tissue destruction. The diagnosis mainly depends on the early detection of imaging and early treatment, which can effectively prolong the life of patients. If the computer can be used to assist the examination results related to the effects of fibrosis, a timely diagnosis of such diseases will be of great value to both doctors and patients. We also previously proposed a machine learning algorithm model that can play a good clinical guiding role in early imaging prediction of idiopathic pulmonary fibrosis. At present, AI and machine learning have great potential and ability to transform many aspects of respiratory medicine and are the focus and hotspot of research. AI needs to become an invisible, seamless, and impartial auxiliary tool to help patients and doctors make better decisions in an efficient, effective, and acceptable way. The purpose of this paper is to review the current application of machine learning in various aspects of respiratory diseases, with the hope to provide some help and guidance for clinicians when applying algorithm models

Second-Generation Sequencing with Deep Reinforcement Learning for Lung Infection Detection

Recently, deep reinforcement learning, associated with medical big data generated and collected from medical Internet of Things, is prospective for computer-aided diagnosis and therapy. In this paper, we focus on the application value of the second-generation sequencing technology in the diagnosis and treatment of pulmonary infectious diseases with the aid of the deep reinforcement learning. Specifically, the rapid, comprehensive, and accurate identification of pathogens is a prerequisite for clinicians to choose timely and targeted treatment. Thus, in this work, we present representative deep reinforcement learning methods that are potential to identify pathogens for lung infection treatment. After that, current status of pathogenic diagnosis of pulmonary infectious diseases and their main characteristics are summarized. Furthermore, we analyze the common types of second-generation sequencing technology, which can be used to diagnose lung infection as well. Finally, we point out the challenges and possible future research directions in integrating deep reinforcement learning with second-generation sequencing technology to diagnose and treat lung infection, which is prospective to accelerate the evolution of smart healthcare with medical Internet of Things and big data

Formation and Characterization of β-Lactoglobulin and Gum Arabic Complexes: the Role of pH

Protein–polysaccharide complexes have received increasing attention as delivery systems to improve the stability and bioavailability of multiple bioactive compounds. However, deep and comprehensive understanding of the interactions between proteins and polysaccharides is still required for enhancing their loading efficiency and facilitating targeted delivery. In this study, we fabricated a type of protein–polysaccharide complexes using food-grade materials of β-lactoglobulin (β-Lg) and gum arabic (GA). The formation and characteristics of β-Lg–GA complexes were investigated by determining the influence of pH and other factors on their turbidity, zeta-potential, particle size and rheology. Results demonstrated that the β-Lg and GA suspension experienced four regimes including co-soluble polymers, soluble complexes, insoluble complexes and co-soluble polymers when the pH ranged from 1.2 to 7 and that β-Lg–GA complexes formed in large quantities at pH 4.2. An increased ratio of β-Lg in the mixtures was found to promote the formation of β-Lg and GA complexes, and the optimal β-Lg/GA ratio was found to be 2:1. The electrostatic interactions between the NH3+ group in β-Lg and the COO− group in GA were confirmed to be the main driving forces for the formation of β-Lg/GA complexes. The formed structure also resulted in enhanced thermal stability and viscosity. These findings provide critical implications for the application of β-lactoglobulin and gum arabic complexes in food research and industry