Remote transfer of Gaussian quantum discord

Quantum discord quantifies quantum correlation between quantum systems, which has potential application in quantum information processing. In this paper, we propose a scheme realizing the remote transfer of Gaussian quantum discord, in which another quantum discordant state or an Einstein-Podolsky-Rosen entangled state serves as ancillary state. The calculation shows that two independent optical modes that without direct interaction become quantum correlated after the transfer. The output Gaussian quantum discord can be higher than the initial Gaussian quantum discord when optimal gain of the classical channel and the ancillary state are chosen. The physical reason for this result comes from the fact that the quantum discord of an asymmetric Gaussian quantum discordant state can be higher than that of a symmetric one. The presented scheme has potential application in quantum information network

Lamb wave defect detection and evaluation using a fully non-contact laser system

Traditional Lamb wave structural health monitoring (SHM)/nondestructive evaluation (NDE) system employs contact type transducers such as PZT, ultrasonic transducers, and optical fibers. In application, transducer attachment and maintenance can be time and labor consuming. In addition, the use of couplant and adhesives can introduce additional materials on structures, and the interface coupling is often not well understood. To overcome these limitations, we proposed a fully non-contact NDE system by employing pulsed laser (PL) for Lamb wave actuation and scanning laser Doppler vibrometer (SLDV) for Lamb wave sensing. The proposed system is implemented on aluminum plates. The PL Lamb wave excitation is calibrated, and the optimal parameters are obtained. Lamb wave modes are then characterized through 1D wavefield analysis. With the calibrated and characterized system, defect detection and evaluation are achieved on aluminum plates with simulated defects (surfaced-bonded quartz rod, and machine milled crack) through 1D and 2D inspection in both time-space and frequency-wavenumber domains

Monocular vision based navigation using image moments of polygonal features

This thesis presents a novel monocular-vision-based localization and mapping algorithm using moments of polygon features. The landmarks we use are polygonal regions instead of a dense set of feature points, which can significantly reduce the computational complexity of data association and produce a map that is geometrically and structurally more meaningful. Each region can be characterized using its depth and orientation with respect to the camera and an polygon detection and tracking algorithm is developed. The monocular vision Simultaneous Localization and Mapping (SLAM) problem is formulated as a filter problem to incorporate the image moments of the close regions or polygons tracked. The observability of the SLAM estimator is further improved by both the additional measurements with respect to the initial view location and the use of image moments. We analyze the performance of our SLAM algorithm with numerical simulations and experimental results. We also compared our results with ORB-SLAM to show the effectiveness of our algorithm in outdoor environments

ToMChallenges: A Principle-Guided Dataset and Diverse Evaluation Tasks for Exploring Theory of Mind

Theory of Mind (ToM), the capacity to comprehend the mental states of distinct individuals, is essential for numerous practical applications. With the development of large language models, there is a heated debate about whether they are able to perform ToM tasks. Previous studies have used different tasks and prompts to test the ToM on large language models and the results are inconsistent: some studies asserted these models are capable of exhibiting ToM, while others suggest the opposite. In this study, We present ToMChallenges, a dataset for comprehensively evaluating Theory of Mind based on Sally-Anne and Smarties tests. We created 30 variations of each test (e.g., changing the person's name, location, and items). For each variation, we test the model's understanding of different aspects: reality, belief, 1st order belief, and 2nd order belief. We adapt our data for various tasks by creating unique prompts tailored for each task category: Fill-in-the-Blank, Multiple Choice, True/False, Chain-of-Thought True/False, Question Answering, and Text Completion. If the model has a robust ToM, it should be able to achieve good performance for different prompts across different tests. We evaluated two GPT-3.5 models, text-davinci-003 and gpt-3.5-turbo-0301, with our datasets. Our results indicate that consistent performance in ToM tasks remains a challenge.Comment: work in progres

Examination of the influences of the industrial attributes on the entry mode selection: case studies of the Coca-Cola Company from U.S entering the Chinese beverage industry and the BT Group plc from U.K entering the Chinese telecommunication industry.

The study has the purpose of examining the influences of industrial attributes, such as market structure and industrial policies, on the choice of entry mode for MNEs. It adopts the case study approach with two firms entering China, one is the Coca-Cola Company from the U.S and the other is the BT Group plc from the U.K, which enable us to see how the market structure, competition conditions, entry barriers and policies of these two different industries can influent the entry mode selection of those two firms. Moreover this study will also see what challenges they are facing in their respective industries and how they respond to them. At the end, I’ll also talk about the future inward FDI in China and the direction of the future research in this topic. For the findings of this study, I find that higher level of competition leads to the entry mode with more control, i.e. firms in the monopolistic competition market are more likely to choose wholly owned subsidiaries and those in oligopoly market would prefer joint ventures. To what extent that foreign firms can invest in a certain industry is much depends on the regulatory policies of that industry. The entry and operation strategy can be restricted within a limited scope by the government tight central control. In terms of responding to challenges, firms need to deal with the natural resource scarcity with a sustainable strategy that benefits both the firm itself and the host country, and be aware the knowledge of the local market, trying to adapt the products and services to local customers and comply with the industrial policies. Furthermore, comparing to Dunning’s eclectic paradigm, the internalisation advantages are not necessity for FDI and can be split into two extent, including internalisation of management and internalisation of technology. The findings from the study of these two cases mostly answer to the research questions

Effect Of Type And Quantity Of Inherent Alkali Cations On Alkali-silica Reaction

In this study, the macroscopical expansion induced by alkali-silica reaction (ASR) and its corresponding ASR products are investigated using ordinary Portland cement (OPC) mortar specimens with a gradient of boosted alkalis. Experimental results show that the expansion increases with the concentration of inherent alkalis. Sodium-boosted samples expand approximately three times as much as potassium-boosted samples. ASR gels that are present in aggregate veins are calcium-free and amorphous; the atomic ratios of ASR gels are nearly independent of the type and quantity of alkali cations. Aggregate ASR gel exudation occurs in high (≥2.5 %) sodium cases and produces potential Na-shlykovite. Crystalline and amorphous calcium-containing ASR products are present in aggregate vicinities in either Na- or K-boosted samples. The higher hydrophilicity of Na-gel in aggregate veins accounts for the larger expansion. Boosted alkali cations are more effective in ASR products formation than in exposing solution. A new observation that NaOH exposure inhibits ASR in K-boosted samples (zero expansion) is reported

Effect of arabinogalactan protein complex content on emulsification performance of gum arabic

The emulsification properties of the standard (STD), matured (EM2 and EM10) and fractionated gum arabic samples via phase separation induced molecular fractionation were investigated to find out how the content of arabinogalactan protein (AGP) complex affects the resulting emulsion properties. Phase separation and the accompanying molecular fractionation were induced by mixing with different hydrocolloids including hyaluronan (HA), carboxymethyl cellulose (CMC), and maltodextrin (MD). Increase of AGP content from 11 to 28% resulted in the formation of emulsions with relatively smaller droplet sizes and better stability. Further increase in the AGP content to 41% resulted in the formation of emulsions with larger droplets. In spite of the larger droplets sizes, these emulsions were extremely stable. In addition, the emulsions prepared with GA higher AGP content better stability in the presence of ethanol. The results indicate that AGP content plays a vital role in emulsion stability and droplet size