The Effect of Diplomacy on the Emergence of Food Security: Focusing on the diplomatic activities of Emperor Showa during the food crisis immediately after the World War II

This paper defines the postwar period from 1945 to the 1970s, when the policy term “food security” was not generally used, as the “embryonic stage of food security”, and considers the effect of diplomacy during that stage. The examination is intended to clarify the importance of imported food and critically analyze the effect of Emperor Showa’s diplomatic activities, with a focus on those activities during the food crisis immediately after the end of the war

The study about policy process of food self-sufficiency rates as a policy target in the Food, Agriculture and Rural Areas Basic Act

The Food, Agriculture and Rural Areas Basic Act was enacted in 1999 to replace the earlier Agriculture Basic Act. A food self-sufficiency rate was newly established as a policy objective in the Act. This paper examines in detail why food self-sufficiency rates became a policy target for policy development in the Food, Agriculture and Rural Areas Basic Act. In addition, the reason why the policy target of food self-sufficiency rates was implemented was explained from an academic perspective based on the power relationship of the three involved actors

A neural network-based direct adaptive fault tolerance flight control for control surface damage

AbstractIn order to enhance the reliability of flight control systems, a new neural network-based direct adaptive fault tolerance control was proposed for flight control system in the presence of control surface damage. Based on the accuracy approach of neural network, a fault parameter identification models were built to constitute hybrid compensator in order to ensure the strictly positive real of the failure flight control systems in the inner control loop. In the outer loop, a common direct adaptive controller was designed. The scheme was illustrated through simulations using an aircraft. The results show that an aircraft has also good dynamic performance in the control surface damage

Study on the Rough-set-based Clustering Algorithm for Sensor Networks

The traditional clustering algorithm is a very typical level routing algorithm in wireless sensor networks (WSN). On the basis of the classical LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm, this paper proposes an energy efficient clustering algorithm in WSN. Through the introduction of rough set, the new algorithm mainly introduces how to confirm an optimized strategy to choose the cluster head effectively by the simplified decision table. That is to say, by discrete normalized data preprocessing of attribute value, getting discretization decision table. Finally, the results from simulated experiments show that the clustering algorithm based on rough set theory can optimize the clustering algorithm in network data. That is to say, the rough-set-based clustering algorithm can effectively choose the cluster head, balance the energy of the nodes in the cluster and prolong the lifetime of sensor networks

Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data

Policymakers pay much attention to effectively increasing frequency of people’s cycling in the context of developing sustainable and green cities. Investigating associations of environmental characteristics and cycling behaviour could offer implications for changing urban infrastructure aiming at encouraging active travel. However, earlier examinations of associations between environmental characteristics and active travel behaviour are limited by low spatial granularity and coverage of traditional data. Crowdsourced geographic information offers an opportunity to determine the fine-grained travel patterns of people. Particularly, Strava Metro data offer a good opportunity for studies of recreational cycling behaviour as they can offer hourly, daily or annual cycling volumes with different purposes (commuting or recreational) in each street across a city. Therefore, in this study, we utilised Strava Metro data for investigating associations between environmental characteristics and recreational cycling behaviour at a large spatial scale (street level). In this study, we took account of population density, employment density, road length, road connectivity, proximity to public transit services, land use mix, proximity to green space, volume of motor vehicles and traffic accidents in an empirical investigation over Glasgow. Empirical results reveal that Strava cyclists are more likely to cycle for recreation on streets with short length, large connectivity or low volume of motor vehicles or on streets surrounded by residential land

Anti-tumor activity of polysaccharides extracted from Senecio scandens Buch, -Ham root on hepatocellular carcinoma

Purpose: To optimize the extraction conditions of polysaccharides from the root of Senecio scandens Buch,-Ham. (PRS) and evaluate its anti-tumor effect on hepatocellular carcinoma.Methods: Response surface methodology (RSM) applied with a Box-Behnken design (BBD, three levels and three factors) was employed to determine the effect of extraction time, number of extraction and ratio of water to raw material on the yield of PRS. The anti-tumor effect of PRS on A549, HL60, S180 and H22 cell lines was evaluated in vitro by 3-(4,5-dimethylthiazol-2-yl) -2,5-diphenyltetrazolium bromide (MTT) assay, while in vivo anti-tumor effect was evaluated in H22 tumor transplanted mice. Furthermore, expressions of proteins including caspase-3, caspase-9, Bcl-2 and Bax were determined by western blotting assay.Results: The established BBD model was highly significant and the optimal conditions were: extraction time, 3.06 h; number of extractions, 2; and ratio of water to raw material, 16.17 mL/g. PRS showed significant inhibitory effect on H22 cells (IC50 = 42.4 μg/mL), and significantly inhibited the growth of transplanted H22 tumors in mice at the doses of 20, 40 and 80 mg/kg (p < 0.05, p < 0.05 and p < 0.01, respectively). Treatment with PRS (20, 40 and 80 μg/mL) significantly up-regulated the expressions of Bax, caspase-3 and caspase-9 in H22 cells, whereas Bcl-2 protein was significantly down-regulated.Conclusion: The results suggest that PRS possesses significant anti-tumor activity on H22 cell line in vitro and in vivo, and the mechanism may be closely related to the induction of mitochondria-mediated apoptosis.Keywords: Senecio scandens, Polysaccharides, Hepatocellular carcinoma, Response surface methodology, Anti-tumor activity, Apoptosi

Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

Continual learning entails learning a sequence of tasks and balancing their knowledge appropriately. With limited access to old training samples, much of the current work in deep neural networks has focused on overcoming catastrophic forgetting of old tasks in gradient-based optimization. However, the normalization layers provide an exception, as they are updated interdependently by the gradient and statistics of currently observed training samples, which require specialized strategies to mitigate recency bias. In this work, we focus on the most popular Batch Normalization (BN) and provide an in-depth theoretical analysis of its sub-optimality in continual learning. Our analysis demonstrates the dilemma between balance and adaptation of BN statistics for incremental tasks, which potentially affects training stability and generalization. Targeting on these particular challenges, we propose Adaptive Balance of BN (AdaB$^2$N), which incorporates appropriately a Bayesian-based strategy to adapt task-wise contributions and a modified momentum to balance BN statistics, corresponding to the training and testing stages. By implementing BN in a continual learning fashion, our approach achieves significant performance gains across a wide range of benchmarks, particularly for the challenging yet realistic online scenarios (e.g., up to 7.68%, 6.86% and 4.26% on Split CIFAR-10, Split CIFAR-100 and Split Mini-ImageNet, respectively). Our code is available at https://github.com/lvyilin/AdaB2N.Comment: Accepted by NeurIPS 202