Changes of Rice Sodium Content due to Sodium Exclusion and Transpiration under Salinity

The relationship between sodium contents of tops and transpiration rates was studied in two rice varieties with different sodium exclusion rates in roots; Kala-Rata1-24(KR1;low exclusion rate) and IR28 (high exclusion rate). Seedlings at 7th leaf stage grown in culture solution were subjected to saline water(100mM sodium chloride) and transpired for 12 hours. Various transpiration rates were obtained under different humidity, light intensity and temperature conditions. Transpiration stream concentration factor of Na+ (TSCFNa+), which denotes the sodium exclusion rate in the root, decreased with increase in the transpiration rate under different humidity and light intensity conditions. On the other hand, TSCFNa+ was lower in KR1 than in IR28 under different temperature conditions. There were no different in the sodium exclusion rates at high transpiration rates. Sodium contents of tops initially increased with the transpiration rates but afterwards decreased with the transpiration rates. Sodium contents of tops were higher in KR1 than in IR28 at low transpiration rates under high humidity and low light intensity conditions, but it was higher in IR28 under low temperature conditions. There were no varietal differences in the sodium contents of tops at high transpiration rates. These results indicated that the varietal differences in sodium exclusion rates were detectable at low transpiration rates and affected the sodium contents of tops, but there were no differences in the sodium contents of tops at high transpiration rates.イネでは、ナトリウム（Na)含有率が高いほど光合成速度、苗の生存率および相対生長速度が低下することから、塩ストレス下における体内Na含有率の品種間差異に着目した研究が進められてきた。しかし、塩ストレスに対する体内Na含有率の品種による反応は、研究によって異なる。Makiharaらは、幼苗期にNa含有率が異なるとされる品種を成熟まで栽培したところ、Na含有率に大きな差異を見出さなかった。また、Makiharaらの研究でNa含有率が低かった品種が、森田らの研究では高かった。イネは、根においてナトリウムイオン（Na+）を分離排除する能力をもし、その程度は品種によって異なる。この能力は体内に入り込む水のNa+濃度に影響を与えるのが、体内に取り込まれるNa+の質は、流れる水の総量に影響される。すなわち、イネのNa含有率は、蒸散量と蒸散流に含まれるNa+濃度によって決まり、後者は根におけるNa+排除率によって変わる。蒸散と排除率はいずれも環境条件によって変わると考えられ、それによって体内Na含有率も変わるであろう。したがって、研究によってNa含有率の反応が異なるのは、両者の相互作用によると考えられえる。しかし、蒸散量とNa+排除率の変化が体内Na含有率にどのように影響を与えるのかは知られていないので、本研究で調べた

Cross-View Gait Recognition Using View-Dependent Discriminative Analysis

Abstrac

Wearable Sensor-Based Gait Analysis for Age and Gender Estimation

Wearable sensor-based systems and devices have been expanded in different application domains, especially in the healthcare arena. Automatic age and gender estimation has several important applications. Gait has been demonstrated as a profound motion cue for various applications. A gait-based age and gender estimation challenge was launched in the 12th IAPR International Conference on Biometrics (ICB), 2019. In this competition, 18 teams initially registered from 14 countries. The goal of this challenge was to find some smart approaches to deal with age and gender estimation from sensor-based gait data. For this purpose, we employed a large wearable sensor-based gait dataset, which has 745 subjects (357 females and 388 males), from 2 to 78 years old in the training dataset; and 58 subjects (19 females and 39 males) in the test dataset. It has several walking patterns. The gait data sequences were collected from three IMUZ sensors, which were placed on waist-belt or at the top of a backpack. There were 67 solutions from ten teams—for age and gender estimation. This paper extensively analyzes the methods and achieved-results from various approaches. Based on analysis, we found that deep learning-based solutions lead the competitions compared with conventional handcrafted methods. We found that the best result achieved 24.23% prediction error for gender estimation, and 5.39 mean absolute error for age estimation by employing angle embedded gait dynamic image and temporal convolution network

Growth and yield responses of upland NERICAs to variable water management under field conditions

This study aimed to investigate the possible causes for inconsistent performances of upland New Rice for Africa (NERICA) varieties in uplands and lowlands, while identifying important determinants in grain yield under deficient soil moisture. We compared the growth and yield of NERICA 1 and NERICA 5 to those of Yumenohatamochi, a Japanese upland variety, and Hinohikari, a Japanese lowland variety, subjected to different water management regimes (continually flooded, supplementary irrigation, and non-irrigation). Under conditions of deficient soil moisture, panicle number per square meter, spikelet number per panicle, and 1000-grain weight of NERICAs decreased, whereas the panicle number of the Japanese varieties experienced little change. In contrast, the grain filling ratio was unaffected by water management, irrespective of variety. The primary source of yield reduction under low soil water conditions was a decrease in spikelet number per panicle, and water stress intensity was the primary factor for the degree of this reduction. Variation in the abortion of secondary rachis-branches caused differences between NERICAs in their spikelet number response to soil moisture deficiency. The inconsistency in NERICA performance across uplands vs. lowlands can be partially attributed to variation in yield response to low soil water conditions. Moreover, water stress intensity and the presence of a water gradient along the vertical soil profile may combine to affect the fluctuation in NERICA performance under upland conditions

Multi-view Discriminant Analysis with Tensor Representation and Its Application to Cross-view Gait Recognition

Abstract-This paper describes a method of discriminant analysis for cross-view recognition with a relatively small number of training samples. Since appearance of a recognition target (e.g., face, gait, gesture, and action) is in general drastically changes as an observation view changes, we introduce multiple view-specific projection matrices and consider to project a recognition target from a certain view by a corresponding view-specific projection matrix into a common discriminant subspace. Moreover, conventional vectorized representation of an originally higher-order tensor object (e.g., a spatio-temporal image in gait recognition) often suffers from the curse of dimensionality dilemma, we therefore encapsulate the multiple view-specific projection matrices in a framework of discriminant analysis with tensor representation, which enables us to overcome the curse of dimensionality dilemma. Experiments of cross-view gait recognition with two publicly available gait databases show the effectiveness of the proposed method in case where a training sample size is small