中国西北少数民族地域における貧困動態と貧困削減について

Tohoku University冬木勝仁課

Poverty Dynamics and Poverty Reduction in Ethnic-minority Areas of Northwest China

令和元年度博士論文要

Calibrated deep attention model for 3D pose estimation in the wild

Three-dimensional human pose estimation is a key technology in many computer vision tasks. Regressing a 3D pose from 2D images is a challenging task, especially for applications in natural scenes. Recovering the 3D pose from a monocular image is an ill-posed problem itself; moreover, most of the existing datasets have been captured in a laboratory environment, which means that the model trained by them cannot generalize well to in-the-wild data. In this work, we improve the 3D pose estimation performance by introducing the attention mechanism and a calibration network. The attention model will capture the channel-wise dependence, so as to enhance the depth analysis ability of the model. The multi-scale pose calibration network adaptively learns body structure and motion characteristics, and will therefore rectify the estimation results. We tested our model on the Human 3.6M dataset for quantitive evaluation, and the experimental results show the proposed methods with higher accuracy. In order to test the generalization capability for in-the-wild applications, we also report the qualitative results on the natural scene Leeds Sports Pose dataset; the visualization results show that the estimated results are more reasonable than the baseline model

Preparation of quinoa bran dietary fiber-based zinc complex and investigation of its antioxidant capacity in vitro

In order to improve the economic utilization of quinoa bran and develop a safe and highly available zinc ion biological supplement. In this study, a four-factor, three-level response surface optimization of quinoa bran soluble dietary fiber (SDF) complexation of zinc was studied. The effect used four factors on the chelation rate was investigated: (A) mass ratio of SDF to ZnSO4.7H2O, (B) chelation temperature, (C) chelation time, and (D) pH. Based on the results of the single-factor test, the four-factor three-level response surface method was used to optimize the reaction conditions. The optimal reaction conditions were observed as mentioned here: the mass ratio of quinoa bran SDF to ZnSO4.7H2O was 1, the reaction temperature was 65°C, the reaction time was 120 min, and the pH of the reaction system was 8.0. The average chelation rate was 25.18%, and zinc content is 465.2 μg/g under optimal conditions. The hydration method rendered a fluffy quinoa bran SDF structure. The intramolecular functional groups were less stable which made the formation of the lone pairs of electrons feasible to complex with the added divalent zinc ions to form a quinoa bran soluble dietary fiber-zinc complex [SDF-Zn(II)]. The SDF-Zn(II) chelate had higher 2,2-diphenylpicrylhydrazyl (DPPH), ABTS+, hydroxyl radical scavenging ability, and total antioxidant capacity. Therefore, metal ion chelation in dietary fiber is of biological importance

Regress 3D human pose from 2D skeleton with kinematics knowledge

3D human pose estimation is a hot topic in the field of computer vision. It provides data support for tasks such as pose recognition, human tracking and action recognition. Therefore, it is widely applied in the fields of advanced human-computer interaction, intelligent monitoring and so on. Estimating 3D human pose from a single 2D image is an ill-posed problem and is likely to cause low prediction accuracy, due to the problems of self-occlusion and depth ambiguity. This paper developed two types of human kinematics to improve the estimation accuracy. First, taking the 2D human body skeleton sequence obtained by the 2D human body pose detector as input, a temporal convolutional network is proposed to develop the movement periodicity in temporal domain. Second, geometrical prior knowledge is introduced into the model to constrain the estimated pose to fit the general kinematics knowledge. The experiments are tested on Human3.6M and MPII (Max Planck Institut Informatik) Human Pose (MPI-INF-3DHP) datasets, and the proposed model shows better generalization ability compared with the baseline and the state-of-the-art models

Changing Pastoralism and Pastoral Livelihoods Under Climate Change in Northwestern China

The livelihood of pastoralists is strongly influenced and partially determined by regulatory grazing limitations and global climate change. It was assumed that the challenges associated with the latter factor would invariably obligate and motivate herders to practice sustainable animal husbandry. However, the former factor also incentivizing adaptive changes in the agricultural practices of herders and pastoralists as well. The present study investigated changes in the management practices that rural pastoralists have made to ensure the sustainable maintenance of their livelihood in the face of strict public policy and climate risks. Surveys were conducted in two pastoral counties of northwestern China in a region subjected to frequent annual drought events and low wintertime temperatures. This region has already undergone numerous institutional changes within the last few decades. The results of the field research indicated that farmers in both counties have modified their livelihood patterns and nomadic practices in response to regulatory and climate change. Five new adaptive livelihood patterns were identified among the agricultural workers in the study area. The novel adaptive farming practices assumed by herders were intended to cope with the tension between the requirement for environmental protection and the need for socioeconomic development. The specificity of this research helps clarify how local communities change their livelihood patterns in response to ecosystem degradation and policy modifications resulting from climate change, and enrich the understanding of the actions for dealing with climate change under the individual perspective

Integrated metabolite profiling and transcriptome analysis unraveling mechanism of RC catabolism in Paenarthrobacter ilicis CR5301

Steviol glycosides are ideal sweeteners that are widely used in food, medicine, and cosmetics. Rebaudioside C (RC) is considered to be the third most abundant steviol glycoside, which has a bitter aftertaste that limits its application. Hydrolysis of RC to generate other bioactive steviol glycosides is an effective way to promote its additional utilization. In our previous study, a bacterium Paenarthrobacter ilicis CR5301 was isolated and identified for hydrolyzing RC with high efficiency. Herein, the expression profiles of P. ilicis CR5301 in the deletion and presence of RC were investigated by RNA-seq. The RC metabolites were identified by high-performance liquid chromatography and ultra-performance liquid chromatography-triple-time of flight mass spectrometry. Novel results were discovered in four aspects of research. First, the identification of metabolites revealed that four metabolites, namely, dulcoside A, dulcoside B, dulcoside A1, and steviol, were produced during RC metabolism. Second, RNA-seq analyses unraveled that 105 genes of P. ilicis CR5301 were significantly differentially expressed, and 7 pathways were significantly enriched. Third, independent RT-qPCR verified the accuracy and reliability of the RNA-seq results. Finally, a complete catabolic model of RC in P. ilicis CR5301 was proposed, and key genes were indicated in the RC catabolic metabolism by combining them with literature and sequence alignments. This study comprehensively unraveled the genes and pathways of RC catabolism in P. ilicis CR5301 at the transcriptional and metabolic levels. It provided new insights and evidence for understanding the mechanism of RC catabolism in bacteria. Key candidate genes may potentially contribute to the RC hydrolysis and preparation of other functional steviol glycosides in the future