New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009This study proposes new developmental stages for Callithrix jacchus, usingK-Means algorithm and an artificial neural network–self-organising maps (SOM) as computational tools, based on weight and age. Eight developmental stages are proposed: infantI ,IIandIII ,Juvenile I and II ,Subadult ,Young adult and Older adult. This classification is consistent with the first appearance of several behavioural and physiological characteristics and thus may have generality indefining critical developmental periods. It also reveals differences in male and female development and establishes stage for the onset of the final adult life cycle. This classification is also important to understanding the biology of the ontogenetic development of common marmosets, providing new insights for the management and care of captive animals and improving age estimate indicators when specimens are captured in long term monitoring of free ranging group

Início da função gonadal no sagui comum (Callithrix jacchus): diferenças entre gêneros

Os primatas não humanos, como Callithrix jacchus vêm sendo utilizados com maior frequência em pesquisa biomédica e, recentemente, nosso laboratório propôs uma nova classificação para monitorar com mais detalhes as modificações comportamentais e hormonais relacionadas ao desenvolvimento. O presente trabalho monitorou os níveis de hormônios gonadais de 4 machos e 6 fêmeas de C. jacchus durante as fases juvenil I e II e subadulta (dos 5 aos 15 meses). Os resultados apontaram que os níveis de progesterona nas fêmeas e andrógenas nos machos foram estatisticamente mais elevados nos estágios juvenil II e subadulto, respectivamente, em relação ao estágio juvenil I. Estes achados indicam que, de acordo com a nova classificação, foi possível observar que o funcionamento gonadal se instala mais cedo nas fêmea

Application of Self-Organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection

Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology. Recently, network intrusion detection has been one of the most important technologies in network security detection. The accuracy of network intrusion detection has reached higher accuracy so far. However, these methods have very low efficiency in network intrusion detection, even the most popular SOM neural network method. In this paper, an efficient and fast network intrusion detection method was proposed. Firstly, the fundamental of the two different methods are introduced respectively. Then, the self-organizing feature map neural network based on K-means clustering (KSOM) algorithms was presented to improve the efficiency of network intrusion detection. Finally, the NSL-KDD is used as network intrusion data set to demonstrate that the KSOM method can significantly reduce the number of clustering iteration than SOM method without substantially affecting the clustering results and the accuracy is much higher than K-Means method. The Experimental results show that our method can relatively improve the accuracy of network intrusion and significantly reduce the number of clustering iteration

Natural and Experimental Evidence Drives Marmosets for Research on Psychiatric Disorders Related to Stress

Knowledge of the behavioral ecology of marmosets carried out in their natural habitat associated with the advent of a non-invasive technique for measuring steroid hormones in feces has made a significant contribution to understanding their social relationships and sexual strategies. These studies showed that they are mainly monogamous, live in relatively stable social groups according to a social hierarchy in which females compete and males cooperate, and form social bonds similar to humans, which makes this species a potential animal model to study disorders related to social stress. In addition, laboratory studies observed the expression of behaviors similar to those in nature and deepened the descriptions of their social and reproductive strategies. They also characterized their responses to the challenge using behavioral, cognitive, physiological, and genetic approaches that were sexually dimorphic and influenced by age and social context. These findings, added to some advantages which indicate good adaptation to captivity and the benefits of the birth of twins, small size, and life cycle in comparison to primates of the Old World, led to their use as animal models for validating psychiatric diseases such as major depression. Juvenile marmosets have recently been used to develop a depression model and to test a psychedelic brew called Ayahuasca from the Amazon rainforest as an alternative treatment for major depression, for which positive results have been found which encourage further studies in adolescents. Therefore, we will review the experimental evidence obtained so far and discuss the extension of the marmoset as an animal model for depression

Solar Energy Validation for Strategic Investment Planning via Comparative Data Mining Methods: An Expanded Example within the Cities of Turkey

Energy supply together with the data management is one of the key challenges of our century. Specifically, to decrease the climate change effects as energy requirement increases day by day poses a serious dilemma. It can be adequately reconciled with innovative data management in (renewable) energy technologies. The new environmental-friendly planning methods and investments that are discussed by researchers, governments, NGOs, and companies will give the basic and most important variables in shaping the future. We use modern data mining methods (SOM and K-Means) and official governmental statistics for clustering cities according to their consumption similarities, the level of welfare, and growth rate and compare them with their potential of renewable resources with the help of Rapid Miner 5.1 and MATLAB software. The data mining was chosen to make the possible secret relations visible within the variables that can be unpredictable at first sight. Here, we aim to see the success level of the chosen algorithms in validation process simultaneously with the utilized software. Additionally, we aim to improve innovative approach for decision-makers and stakeholders about which renewable resource is the most suitable for an exact region by taking care of different variables at the same time