Giant Gating Tunability of Optical Refractive Index in Transition Metal Dichalcogenide Monolayers

We report that the refractive index of transition metal dichacolgenide (TMDC) monolayers, such as MoS2, WS2, and WSe2, can be substantially tuned by > 60% in the imaginary part and > 20% in the real part around exciton resonances using CMOS-compatible electrical gating. This giant tunablility is rooted in the dominance of excitonic effects in the refractive index of the monolayers and the strong susceptibility of the excitons to the influence of injected charge carriers. The tunability mainly results from the effects of injected charge carriers to broaden the spectral width of excitonic interband transitions and to facilitate the interconversion of neutral and charged excitons. The other effects of the injected charge carriers, such as renormalizing bandgap and changing exciton binding energy, only play negligible roles. We also demonstrate that the atomically thin monolayers, when combined with photonic structures, can enable the efficiencies of optical absorption (reflection) tuned from 40% (60%) to 80% (20%) due to the giant tunability of refractive index. This work may pave the way towards the development of field-effect photonics in which the optical functionality can be controlled with CMOS circuits

APICom: Automatic API Completion via Prompt Learning and Adversarial Training-based Data Augmentation

Based on developer needs and usage scenarios, API (Application Programming Interface) recommendation is the process of assisting developers in finding the required API among numerous candidate APIs. Previous studies mainly modeled API recommendation as the recommendation task, which can recommend multiple candidate APIs for the given query, and developers may not yet be able to find what they need. Motivated by the neural machine translation research domain, we can model this problem as the generation task, which aims to directly generate the required API for the developer query. After our preliminary investigation, we find the performance of this intuitive approach is not promising. The reason is that there exists an error when generating the prefixes of the API. However, developers may know certain API prefix information during actual development in most cases. Therefore, we model this problem as the automatic completion task and propose a novel approach APICom based on prompt learning, which can generate API related to the query according to the prompts (i.e., API prefix information). Moreover, the effectiveness of APICom highly depends on the quality of the training dataset. In this study, we further design a novel gradient-based adversarial training method {\atpart} for data augmentation, which can improve the normalized stability when generating adversarial examples. To evaluate the effectiveness of APICom, we consider a corpus of 33k developer queries and corresponding APIs. Compared with the state-of-the-art baselines, our experimental results show that APICom can outperform all baselines by at least 40.02\%, 13.20\%, and 16.31\% in terms of the performance measures EM@1, MRR, and MAP. Finally, our ablation studies confirm the effectiveness of our component setting (such as our designed adversarial training method, our used pre-trained model, and prompt learning) in APICom.Comment: accepted in Internetware 202

Toward Automatic Task Design: A Progress Report

A central challenge in human computation is in understanding how to design task environments that effectively attract participants and coordinate the problem solving process. In this paper, we consider a common problem that requesters face on Amazon Mechanical Turk: how should a task be designed so as to induce good output from workers? In posting a task, a requester decides how to break down the task into unit tasks, how much to pay for each unit task, and how many workers to assign to a unit task. These design decisions affect the rate at which workers complete unit tasks, as well as the quality of the work that results. Using image labeling as an example task, we consider the problem of designing the task to maximize the number of quality tags received within given time and budget constraints. We consider two different measures of work quality, and construct models for predicting the rate and quality of work based on observations of output to various designs. Preliminary results show that simple models can accurately predict the quality of output per unit task, but are less accurate in predicting the rate at which unit tasks complete. At a fixed rate of pay, our models generate different designs depending on the quality metric, and optimized designs obtain significantly more quality tags than baseline comparisons.Engineering and Applied Science

Polysaccharide from Fuzi (FPS) Prevents Hypercholesterolemia in Rats

<p>Abstract</p> <p>Background and aim</p> <p>Polysaccharide from fuzi (FPS), a Chinese herbal medicine extract, has been demonstrated to exert lipid lowering affects. In this study we examined potential mechanisms underlying this affect, specifically alterations in expression of the LDL-receptor (LDL-R), 3-hydroxy-3-methyl glutaryl (HMG)-CoA reductase and cytochrome P450 7α-1 (CYP7α-1), using a rat model of hypercholesterolemia.</p> <p>Methods and results</p> <p>Male rats were fed either a normal or high cholesterol (HC) diet for two-weeks. Half of the rats on the HC diet were orally gavaged with FPS (224 mg/kg, 448 mg/kg or 896 mg/kg diet) daily. Serum lipid levels were quantified at end of the study period as were liver levels of LDL-R protein and mRNA expression of CYP7α-1 and HMG-CoA. Serum cholesterol and LDL-C concentrations were significantly elevated from control in HC rats, but not in those treated with FPS (P < 0.05). LDL-R expression was significantly decreased in the HC group compared to control (P < 0.05), but significantly increased in the FPS group (P < 0.05). HMG-CoA mRNA levels were significantly increased in the HC group compared both other groups (P < 0.05), while CYP7α-1 expression was significantly higher in the FPS group compared to both other groups (P < 0.05).</p> <p>Conclusion</p> <p>These findings suggest that the cholesterol lowering effect of FPS in hypercholesteremic rats is caused at least in part by increased hepatic LDL-R and CYP7α-1 expression and decreased HMG-CoA expression. Further study is needed to determine precisely where and how FPS exerts these effects. FPS offers potential as a therapeutic agent for the treatment of hypercholesterolemia.</p