Effect of ultrasonic wave on latex production and quality of rubber tree

The effects of ultrasonic wave on tapping surface of ‘PR107’ rubber tree were studied. Daily production and cumulative production of latex were measured to estimate the effects of ultrasonic wave on latex production. The solid substance content, dry rubber content and mechanical stability of latex were determined to study the effects of ultrasonic wave on latex quality. Results showed that ultrasonic wave could increase both daily and cumulative production of latex and maintain latex basic quality. The daily production of latex was increased and appeared two peaks both in the ultrasound-treated rubber tree and the one with no treatment. The first peak appeared on the fifth day, and the latex production by ultrasound was 212.34 ml and the control was 141.75 ml The second peak appeared with the production 266.59 ml on the seventeenth day by ultrasound, while the control appeared on the thirteenth day with production of 193.5 ml. The latex cumulative production of ultrasound-treated trees was 209.56 ml higher than that of control in one month. There was little change in solid substance content and dry rubber content between different ultrasonic time. The best mechanical stability of latex was obtained by ultrasound-treating the rubber tree for 4-6 min. it was proved that the ultrasound was helpful in improving the latex production and quality. The application of ultrasonic wave on rubber tree is novel, and its mechanism is worth further research.

Growing Self Organizing Map with an Imposed Binary Search Tree for Discovering Temporal Input Patterns

In this paper the Binary Search Tree Imposed Growing Self Organizing Map (BSTGSOM) is presented as an extended version of the Growing Self Organizing Map (GSOM), which has proven advantages in knowledge discovery applications. A Binary Search Tree imposed on the GSOM is mainly used to investigate the dynamic perspectives of the GSOM based on the inputs and these generated temporal patterns are stored to further analyze the behavior of the GSOM based on the input sequence. Also, the performance advantages are discussed and compared with that of the original GSOM.

Female body condition affects foetal growth in a capital breeding mysticete

1.Sex allocation theory has received considerable attention, yet the mechanism(s) by which mothers skew offspring sex ratios remain unknown. In birds, females are the heterogametic sex, which potentially gives them control of whether gametes will be male or female. How females might control the sex of the gamete is unclear, but one possibility is that variation in steroid hormones may mediate this process. 2.We experimentally altered circulating levels of corticosterone in female Gouldian finches (Erythrura gouldiae), a species that demonstrates both extreme stress responses and extreme offspring sex ratio biases when breeding with a low-quality (genetically incompatible) partner. 3.During egg production, individual females received both corticosterone and metyrapone (a corticosterone-synthesis inhibitor) implants, in random order, to induce both high and low levels of circulating stress hormones (within physiological limits). 4.We found that females with elevated corticosterone levels produced male-biased sex ratios, but when the same females were treated with metyrapone they produced female-biased offspring sex ratios. 5.These stress responses are adaptive because females constrained to breeding with low-quality males can substantially increase their fitness by overproducing sons. Changes in maternal corticosterone levels during stressful situations, such as the quality of a breeding partner, may provide an endocrine mechanism that can be exploited for strategic sex allocation.

An effective deferentially private data releasing algorithm for decision tree

Differential privacy is a strong definition for protecting individual privacy in data releasing and mining. However, it is a rigid definition introducing a large amount of noise to the original dataset, which significantly decreases the quality of data mining results. Recently, how to design a suitable data releasing algorithm for data mining purpose is a hot research area. In this paper, we propose a differential private data releasing algorithm for decision tree construction. The proposed algorithm provides a non-interactive data releasing method through which miner can obtain the complete dataset for data mining purpose. With a given privacy budget, the proposed algorithm generalizes the original dataset, and then specializes it in a differential privacy constrain to construct decision trees. As the designed novel scheme selection operation can fully utilize the allocated privacy budget, the data set released by the proposed algorithm can yield better decision tree models than other method. Experimental results demonstrate that the proposed algorithm outperforms existing methods for private decision tree construction.

Empirical investigation of decision tree ensembles for monitoring cardiac complications of diabetes

Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of patients. In order to monitor clinical complications of diabetes using wearable sensors, a small set of features have to be identified and effective algorithms for their processing need to be investigated. This article focuses on detecting and monitoring cardiac autonomic neuropathy (CAN) in diabetes patients. The authors investigate and compare the effectiveness of classifiers based on the following decision trees: ADTree, J48, NBTree, RandomTree, REPTree, and SimpleCart. The authors perform a thorough study comparing these decision trees as well as several decision tree ensembles created by applying the following ensemble methods: AdaBoost, Bagging, Dagging, Decorate, Grading, MultiBoost, Stacking, and two multi-level combinations of AdaBoost and MultiBoost with Bagging for the processing of data from diabetes patients for pervasive health monitoring of CAN. This paper concentrates on the particular task of applying decision tree ensembles for the detection and monitoring of cardiac autonomic neuropathy using these features. Experimental outcomes presented here show that the authors' application of the decision tree ensembles for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the results obtained previously in the literature.

Factors affecting breeding success in Peregrine Falcons (Falco peregrinus macropus) across Victoria 1991 - 2012

Peregrine Falcon’s lifetime reproductive outputs are influenced more by the quality of the nest site than by the environmental landscape in which they live. The installation of a nest boxes significantly improves breeding outcomes. Uniquely, Victorian Peregrines use novel (non-cliff) nest sites and disperse considerably shorter distances to adopt these sites.