Study on Long-term Mechanism for Government to Encourage Enterprises on Low-carbon Development——Analysis based on Enterprises’ Capacity Variance and Task Difficulty

AbstractBased on reference to Lazear and Rosen (1981) rank-order tournaments mechanism model, this essay introduces the two variables, namely capacity variance and task difficulty, to establish a long-term mechanism model for the government to encourage enterprises for low-carbon development. It is included through model analysis that, the optimal effort level during enterprises’ low-carbon development is directly proportional to bonus difference (L-l) set by the government, and inversely proportional to task difficulty, capacity variance and “performance” appraisal error. When enterprises’ capacities are identical, their optimal effort level will be the highest and equal. Besides, the government should take task difficulty and capacity into comprehensive consideration to set reasonable bonus difference. If task difficulty is relatively large, the government should enlarge bonus difference; if task difficulty is small, the government should correspondingly shorten bonus difference

DYNAMIC LINKAGES BETWEEN PRICES AND IMPORTS FOR JAPANESE FROZEN TUNA

VAR models have been used to describe the dynamic relationships among market price, Japanese harvest, import-from-Taiwan, and import-from-Korea for frozen Big-Eye tuna and Yellow-Fin tuna markets in Japan. It is found that tuna imports from South Korea exert more significant effects on Japan market prices than import-from-Taiwan.Demand and Price Analysis, International Relations/Trade,

Low magnetic field reversal of electric polarization in a Y-type hexaferrite

Magnetoelectric multiferroics in which ferroelectricity and magnetism coexist have attracted extensive attention because they provide great opportunities for the mutual control of electric polarization by magnetic fields and magnetization by electric fields. From a practical point view, the main challenge in this field is to find proper multiferroic materials with a high operating temperature and great magnetoelectric sensitivity. Here we report on the magnetically tunable ferroelectricity and the giant magnetoelectric sensitivity up to 250 K in a Y-type hexaferrite, BaSrCoZnFe11AlO22. Not only the magnitude but also the sign of electric polarization can be effectively controlled by applying low magnetic fields (a few hundreds of Oe) that modifies the spiral magnetic structures. The magnetically induced ferroelectricity is stabilized even in zero magnetic field. Decayless reproducible flipping of electric polarization by oscillating low magnetic fields is shown. The maximum linear magnetoelectric coefficient reaches a high value of ~ 3.0\times10^3 ps/m at 200 K.Comment: 9 pages, 5 figures, a couple of errors are correcte

Electrical Control of Magnetization in Charge-ordered Multiferroic LuFe2O4

LuFe2O4 exhibits multiferroicity due to charge order on a frustrated triangular lattice. We find that the magnetization of LuFe2O4 in the multiferroic state can be electrically controlled by applying voltage pulses. Depending on with or without magnetic fields, the magnetization can be electrically switched up or down. We have excluded thermal heating effect and attributed this electrical control of magnetization to an intrinsic magnetoelectric coupling in response to the electrical breakdown of charge ordering. Our findings open up a new route toward electrical control of magnetization.Comment: 14 pages, 5 figure

Team I2R-VI-FF Technical Report on EPIC-KITCHENS VISOR Hand Object Segmentation Challenge 2023

In this report, we present our approach to the EPIC-KITCHENS VISOR Hand Object Segmentation Challenge, which focuses on the estimation of the relation between the hands and the objects given a single frame as input. The EPIC-KITCHENS VISOR dataset provides pixel-wise annotations and serves as a benchmark for hand and active object segmentation in egocentric video. Our approach combines the baseline method, i.e., Point-based Rendering (PointRend) and the Segment Anything Model (SAM), aiming to enhance the accuracy of hand and object segmentation outcomes, while also minimizing instances of missed detection. We leverage accurate hand segmentation maps obtained from the baseline method to extract more precise hand and in-contact object segments. We utilize the class-agnostic segmentation provided by SAM and apply specific hand-crafted constraints to enhance the results. In cases where the baseline model misses the detection of hands or objects, we re-train an object detector on the training set to enhance the detection accuracy. The detected hand and in-contact object bounding boxes are then used as prompts to extract their respective segments from the output of SAM. By effectively combining the strengths of existing methods and applying our refinements, our submission achieved the 1st place in terms of evaluation criteria in the VISOR HOS Challenge

Metal Amidoboranes and Their Derivatives for Hydrogen Storage

As potential hydrogen storage mediums, ammonia borane and its derivatives have been paid an increasing attention owing to their higher hydrogen capacities and facile dehydrogenation properties under moderate conditions. In this chapter, we presented extensive studies on thermodynamic tailoring of dehydrogenation of metal amidoboranes, metal borohydride-ammonia borane complexes, and metal amidoborane ammoniates as well as their derivatives, with special focus on the syntheses, crystal structures, and dehydrogenation properties. Finally, future perspective was given toward the practical applications