中国におけるCSR情報開示に関する研究

関西大

A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models

With the great success of graph embedding model on both academic and industry area, the robustness of graph embedding against adversarial attack inevitably becomes a central problem in graph learning domain. Regardless of the fruitful progress, most of the current works perform the attack in a white-box fashion: they need to access the model predictions and labels to construct their adversarial loss. However, the inaccessibility of model predictions in real systems makes the white-box attack impractical to real graph learning system. This paper promotes current frameworks in a more general and flexible sense -- we demand to attack various kinds of graph embedding model with black-box driven. To this end, we begin by investigating the theoretical connections between graph signal processing and graph embedding models in a principled way and formulate the graph embedding model as a general graph signal process with corresponding graph filter. As such, a generalized adversarial attacker: GF-Attack is constructed by the graph filter and feature matrix. Instead of accessing any knowledge of the target classifiers used in graph embedding, GF-Attack performs the attack only on the graph filter in a black-box attack fashion. To validate the generalization of GF-Attack, we construct the attacker on four popular graph embedding models. Extensive experimental results validate the effectiveness of our attacker on several benchmark datasets. Particularly by using our attack, even small graph perturbations like one-edge flip is able to consistently make a strong attack in performance to different graph embedding models.Comment: Accepted by the AAAI 202

Transfer Learning with Deep Recurrent Neural Networks for Remaining Useful Life Estimation

Prognostics, such as remaining useful life (RUL) prediction, is a crucial task in condition-based maintenance. A major challenge in data-driven prognostics is the difficulty of obtaining a sufficient number of samples of failure progression. However, for traditional machine learning methods and deep neural networks, enough training data is a prerequisite to train good prediction models. In this work, we proposed a transfer learning algorithm based on Bi-directional Long Short-Term Memory (BLSTM) recurrent neural networks for RUL estimation, in which the models can be first trained on different but related datasets and then fine-tuned by the target dataset. Extensive experimental results show that transfer learning can in general improve the prediction models on the dataset with a small number of samples. There is one exception that when transferring from multi-type operating conditions to single operating conditions, transfer learning led to a worse result

M gene reassortment in H9N2 influenza virus promotes early infection and replication: contribution to rising virus prevalence in chickens in China

Segment reassortment and base mutagenesis of influenza A viruses are the primary routes to the rapid evolution of high fitness virus genotypes. We recently described a predominant G57 genotype of avian H9N2 viruses that caused country-wide outbreaks in chickens in China during 2010-2013 which led to the zoonotic emergence of H7N9 viruses. One of the key features of the G57 genotype is the substitution of the earlier BJ/94-like M gene with the G1-like M gene of quail origin. We report here on the functional significance of the G1-like M gene in H9N2 viruses in conferring increased infection severity and infectivity in primary chicken embryonic fibroblasts and chickens. H9N2 virus housing the G1-like M gene, in place of BJ/94-like M gene, showed early surge in viral mRNA and vRNA transcription that were associated with enhanced viral protein production, and with early elevated release of progeny virus comprising largely spherical rather than filamentous virions. Importantly, H9N2 virus with G1-like M gene conferred extrapulmonary virus spread in chickens. Five highly represented signature amino acid residues (37A, 95K, 224N and 242N in M1 protein, and 21G in M2 protein) encoded by the prevalent G1-like M gene were demonstrated as prime contributors to enhanced infectivity. Therefore, the genetic evolution of M gene in H9N2 virus increases reproductive virus fitness, indicating its contribution to rising virus prevalence in chickens in China. Importance We recently described the circulation of a dominant genotype (G57) of H9N2 viruses in country-wide outbreaks in chickens in China, which was responsible through reassortment for the emergence of H7N9 viruses that cause severe human infections. A key feature of the G57 genotype H9N2 virus is the presence of quail origin G1-like M gene which had replaced the earlier BJ/94-like M gene. We found that H9N2 virus with G1-like M gene, but not BJ/94-like M gene, showed early surge in progeny virus production, more severe pathology and extrapulmonary virus spread in chickens. Five highly represented amino acid residues in M1 and M2 proteins derived from G1-like M gene were shown to mediate enhanced virus infectivity. These observations enhance what we currently know about the roles of reassortment and mutations on virus fitness and have implications for assessing the potential of variant influenza viruses that can cause rising prevalence in chickens

Effects of Physicochemical Properties and Microbial Communities of Fermented Soybean Products on the Formation of Biogenic Amines

The study was carried out to evaluate the contents of common biogenic amines, microbial community diversity and physicochemical indicators of seven samples of fermented liquid soybean products and seven samples of fermented solid soybean products. The results showed that the total amount of biogenic amines in defatted soy sauce, steamed fish soy sauce and oyster reduced salt soy sauce were all higher than 8 000 mg/L and significantly higher than those in the other samples (P < 0.05). The pH and Kjeldahl nitrogen contents of the samples were negatively correlated with the total content of biogenic amines, while water activity (factor loading 0.413), total acid content (factor loading 0.399) and salinity (factor loading 0.330) had a greater positive effect on the production of biogenic amines. Pseudomonas spp. and Bacillus spp. were positively and negatively correlated with the content of biogenic amines, respectively. The results of the study provide a theoretical basis for the development of relevant standards

Bird Flight Resistance Analysis and Planning Strategies in Urban Regeneration Areas: A Case Study of a Certain Area in Shenzhen, China

At present, the sharp decline in urban biodiversity worldwide is severe. Conducting biological perspective analysis and proposing space construction solutions during urban regeneration can greatly alleviate the contradiction between urban construction and biodiversity conservation. In this study, birds were taken as biological representatives, and a certain area in Shenzhen with strong conservation needs was used as an example. Based on a thorough analysis of bird status, the minimum resistance model was applied to establish a resistance surface describing the real flight movement of the indicator species and to construct a bird conservation pattern from the flight process of birds. The results show that: (1) bird flight resistance is the lowest in the southern green space and northern woodland around the reservoir in the research region, and the resistance is higher in the central part, but the path of least resistance therein has the potential to become a corridor. (2) From the perspective of the community structure of green space vegetation, the sparse woodland and shrubland in the research region have low resistance and high richness, which are the most ideal green space forms for birds; from the perspective of architecture, bird flight resistance shows a negative correlation with building height and a positive correlation with building density. The final urban regeneration design plan is thus derived, and the validity of the method is verified based on the biodiversity index. This study reveals the possibility of applying bird flight resistance analysis based on the minimum resistance model to small and medium-scale urban regeneration areas, and also provides insight into the correlation between flight resistance and spatial design elements, which can assist decision-makers, planners and developers in spatial design and planning from a biological standpoint

Ecological Restoration Strategies for the Topography of Loess Plateau Based on Adaptive Ecological Sensitivity Evaluation: A Case Study in Lanzhou, China

Existing studies related to ecological sensitivity evaluation are comparatively mature; however, few approaches are concerned with distinctive topographical conditions that enable response to specific environmental restoration requirements. In this paper, an adaptive ecological sensitivity evaluation framework is established according to a representative plateau topography (i.e., the Loess Plateau region) via a case study of Gaolan County, China. Through the process of factor selection, index system construction, formula adaption, factor weight determination by analytic hierarchy process (AHP) as well as the support of RS and GIS technology, the ecological sensitivity of the research region has been evaluated and analyzed in combination with land use types and typical gully problems. The results show that high sensitivity areas account for 11.16 percent of the total area in the research region and a tendency for fragmentation in spatial distribution. Forest lands with steep slopes in gullies&rsquo; upstream have the highest ecological sensitivity, the proportion of forest and garden land dominated by trees in the highest sensitivity area is around 80 percent. Evidence-based ecological restoration strategies are proposed in terms of the topography of Loess Plateau. This study shows possibilities to adapt existing sensitivity evaluation model for medium-scaled specific topography problems and provides useful clues as a basis for knowledge acquisition that can feed into spatial design, planning and restoration processes

Ecological Restoration Strategies for the Topography of Loess Plateau Based on Adaptive Ecological Sensitivity Evaluation: A Case Study in Lanzhou, China

Existing studies related to ecological sensitivity evaluation are comparatively mature; however, few approaches are concerned with distinctive topographical conditions that enable response to specific environmental restoration requirements. In this paper, an adaptive ecological sensitivity evaluation framework is established according to a representative plateau topography (i.e., the Loess Plateau region) via a case study of Gaolan County, China. Through the process of factor selection, index system construction, formula adaption, factor weight determination by analytic hierarchy process (AHP) as well as the support of RS and GIS technology, the ecological sensitivity of the research region has been evaluated and analyzed in combination with land use types and typical gully problems. The results show that high sensitivity areas account for 11.16 percent of the total area in the research region and a tendency for fragmentation in spatial distribution. Forest lands with steep slopes in gullies’ upstream have the highest ecological sensitivity, the proportion of forest and garden land dominated by trees in the highest sensitivity area is around 80 percent. Evidence-based ecological restoration strategies are proposed in terms of the topography of Loess Plateau. This study shows possibilities to adapt existing sensitivity evaluation model for medium-scaled specific topography problems and provides useful clues as a basis for knowledge acquisition that can feed into spatial design, planning and restoration processes