Are Fruit and Vegetable Prices Non-linear Stationary? Evidence from Smooth Transition Autoregressive Models

Over the last decade, there has been a growing interest in investigating agricultural commodity prices. We apply two more powerful smooth transition autoregressive models of the non-linear unit-root test - namely, the ESTAR model of Kapetanios et al. [Journal of Econometrics (2003)] and the LSTAR model of Leybourne, et a . [Journal of Time Series Analysis (1998)] - with a view to investigating non-linear stationarity for the retail prices of 8 major kinds of fruit and 18 major kinds of vegetable in Taiwan. The empirical evidence clearly finds that the Kapetanios et al. model provides solid, substantive evidence in favor of a non-linear mean-reverting adjustment for the individual price of 4 kinds of fruit and 5 kinds of vegetable. However, when we employ the Leybourne et al. model, we find that any such similar evidence of non-linear stationarity is considerably weaker. Finally, compared with the traditional linear unit root tests, it is important to note here that, all in all, the non-linear unit root tests do indeed provide much more evidence of the stationarity, albeit to varying degrees. This paper offers some policy implications.Smooth transition autoregressive model; Non-linear stationary; Fruit price; Vegetable price; Taiwan

Flow-based Intrinsic Curiosity Module

In this paper, we focus on a prediction-based novelty estimation strategy upon the deep reinforcement learning (DRL) framework, and present a flow-based intrinsic curiosity module (FICM) to exploit the prediction errors from optical flow estimation as exploration bonuses. We propose the concept of leveraging motion features captured between consecutive observations to evaluate the novelty of observations in an environment. FICM encourages a DRL agent to explore observations with unfamiliar motion features, and requires only two consecutive frames to obtain sufficient information when estimating the novelty. We evaluate our method and compare it with a number of existing methods on multiple benchmark environments, including Atari games, Super Mario Bros., and ViZDoom. We demonstrate that FICM is favorable to tasks or environments featuring moving objects, which allow FICM to utilize the motion features between consecutive observations. We further ablatively analyze the encoding efficiency of FICM, and discuss its applicable domains comprehensively.Comment: The SOLE copyright holder is IJCAI (International Joint Conferences on Artificial Intelligence), all rights reserved. The link is provided as follows: https://www.ijcai.org/Proceedings/2020/28

Gender and ethnicity differences manifested in chemistry achievement and self-regulated learning

The aim of this study is to examine whether gender and ethnicity differences are manifested in chemistry achievement and self-regulated learning among a matriculation programme students in Malaysia.The result of students’ midterm chemistry exam was used as the measure of chemistry achievement.The information of self-regulated learning was collected by using a survey questionnaire that was adapted from the Motivated Strategies and Learning Questionnaire (MSLQ). Random sampling method was utilized to select 358 students of Matriculation Science One-Year Programme.The results of gender differences showed that male students obtained significantly higher achievement in chemistry compared to female counterparts whereas there was no significant gender difference in self-regulated learning. The results of ethnicity differences confirmed that there was a significant difference in chemistry achievement between Malay and Chinese students, Malay and Indian students, respectively. In terms of self-regulated learning, however, a significant difference was found only between Malay and Indian students.The findings suggest that science instructors in higher education institutions utilize the MSLQ to get the information about students’ self-regulatory level and motivational level, design a “gender-based initiative” to address the lower science achievement of female students, and be ready to having learning resources and pedagogical practices available for a learning condition with diverse groups of different ethnicities

Microstructured Thin Film Nitinol for a Neurovascular Flow-Diverter

A cerebral aneurysm occurs as a result of a weakened blood vessel, which allows blood to flow into a sac or a ballooned section. Recent advancement shows that a new device, ‘flow-diverter’, can divert blood flow away from the aneurysm sac. People found that a flow-diverter based on thin film nitinol (TFN), works very effectively, however there are no studies proving the mechanical safety in irregular, curved blood vessels. Here, we study the mechanical behaviors and structural safety of a novel microstructured TFN membrane through the computational and experimental studies, which establish the fundamental aspects of stretching and bending mechanics of the structure. The result shows a hyper-elastic behavior of the TFN with a negligible strain change up to 180° in bending and over 500% in radial stretching, which is ideal in the use in neurovascular curved arteries. The simulation determines the optimal joint locations between the TFN and stent frame. In vitro experimental test qualitatively demonstrates the mechanical flexibility of the flow-diverter with multi-modal bending. In vivo micro X-ray and histopathology study demonstrate that the TFN can be conformally deployed in the curved blood vessel of a swine model without any significant complications or abnormalities

Transthyretin Stimulates Tumor Growth through Regulation of Tumor, Immune, and Endothelial Cells

Early detection of lung cancer offers an important opportunity to decrease mortality while it is still treatable and curable. Thirteen secretory proteins that are Stat3 downstream gene products were identified as a panel of biomarkers for lung cancer detection in human sera. This panel of biomarkers potentially differentiates different types of lung cancer for classification. Among them, the transthyretin (TTR) concentration was highly increased in human serum of lung cancer patients. TTR concentration was also induced in the serum, bronchoalveolar lavage fluid, alveolar type II epithelial cells, and alveolar myeloid cells of the CCSP-rtTA/(tetO)7-Stat3C lung tumor mouse model. Recombinant TTR stimulated lung tumor cell proliferation and growth, which were mediated by activation of mitogenic and oncogenic molecules. TTR possesses cytokine functions to stimulate myeloid cell differentiation, which are known to play roles in tumor environment. Further analyses showed that TTR treatment enhanced the reactive oxygen species production in myeloid cells and enabled them to become functional myeloid-derived suppressive cells. TTR demonstrated a great influence on a wide spectrum of endothelial cell functions to control tumor and immune cell migration and infiltration. TTR-treated endothelial cells suppressed T cell proliferation. Taken together, these 13 Stat3 downstream inducible secretory protein biomarkers potentially can be used for lung cancer diagnosis, classification, and as clinical targets for lung cancer personalized treatment if their expression levels are increased in a given lung cancer patient in the blood