Induced spawning and larval rearing of the sea cucumber Holothuria nobilis

Sea cucumber Holothuria nobilis is an economically important species for livelihoods in many countries. However, an increase in demand for this species has led to the depletion of wild stocks. The introduction of this species in aquaculture is necessary to reduce fishing pressure. This study was taken to establish breeding and larval rearing techniques for the development of H. nobilis aquaculture. The broodstock collected from the wild were induced to spawn by using thermal stimulation and the combination of thermal and algal stimulation methods. The larvae obtained from induced spawning were reared using different diets (mixed microalgae and mixed microalgae with artificial feeds) at different stocking densities (300, 600, and 1000 larvae/l). Thermal stimulation is the best method of inducing spawning to H. nobilis yielding up to 1,300,000 fertilized eggs. The highest survival rate (27.5%) of doliolaria larvae was achieved using a mixed microalgae diet. The highest survival rate of doliolaria larvae (41.5 %), growth, and development were in the stocking density of 600 larvae/l

Remote sensing and GIS-based analysis of cave development in the Suoimuoi Catchment (Son La - NW Vietnam)

Integration of remotely sensed imagery with ground surveys is a promising method in cave development studies. In this research a methodology was set up in which a variety of remote sensing and GIS techniques support cave analysis in the tropical karst area of the Suoimuoi catchment, NW Vietnam. In order to extract the maximum information from different remotely sensed data, the hue invariant IHS transformation was applied to integrate Landsat multispectral channels with the high resolution Landsat 7 ETM panchromatic channel. The resulting fused image was used, after enhancement, to visually and digitally extract lineaments. Aerial photos evaluated the extracted lineaments. Based on lineament density indices a fracture zone favorable for cave development is defined. The distance between caves and faults was investigated as well as the correspondence between the cave occurrence and the fracture zone

Rare K decays in a model of quark and lepton masses

An extension of a model of neutrino masses to the quark sector provides an interesting link between these two sectors. A parameter which is important to describe neutrino oscillations and masses is found to be a crucial one appearing in various ``penguin'' operators, in particular the so-called Z penguin. This parameter is severely constrained by the rare decay process $K_{L} \to \mu^{+} \mu^{-}$. This in turn has interesting implications on the decay rates of other rare processes such as $K_{L} \to \mu e$, etc..., as well as on the masses of the neutrinos and the masses of the vector-like quarks and leptons which appear in our model.Comment: 34 pages, 10 figures, corrected some typos in the introductio

Activity recognition and abnormality detection with the switching hidden semi-Markov model

This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environment. In dealing with ADL, we argue that it is beneficial to exploit both the inherent hierarchical organization of the activities and their typical duration. To this end, we introduce the Switching Hidden Semi-Markov Model (S-HSMM), a two-layered extension of the hidden semi-Markov model (HSMM) for the modeling task. Activities are modeled in the S-HSMM in two ways: the bottom layer represents atomic activities and their duration using HSMMs; the top layer represents a sequence of high-level activities where each high-level activity is made of a sequence of atomic activities. We consider two methods for modeling duration: the classic explicit duration model using multinomial distribution, and the novel use of the discrete Coxian distribution. In addition, we propose an effective scheme to detect abnormality without the need for training on abnormal data. Experimental results show that the S-HSMM performs better than existing models including the flat HSMM and the hierarchical hidden Markov model in both classification and abnormality detection tasks, alleviating the need for presegmented training data. Furthermore, our discrete Coxian duration model yields better computation time and generalization error than the classic explicit duration model

Human behavior recognition with generic exponential family duration modeling in the hidden semi-Markov model

The ability to learn and recognize human activities of daily living (ADLs) is important in building pervasive and smart environments. In this paper, we tackle this problem using the hidden semi-Markov model. We discuss the state-of-the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. Inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic Bayesian network (DBN). We investigate both discrete and continuous distributions from the exponential family (Poisson and Inverse Gaussian respectively) for the problem of learning and recognizing ADLs. A full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new Coxian are also presented. Our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.<br /

Study of cavernous underground conduits in Nam La (Northwest Vietnam) by an integrative approach

This paper presents the result of an investigation of underground conduits, which connect the swallow holes and the resurgence of a blind river in the tropical, highly karstified limestone Nam La catchment in the NW of Vietnam. The Nam La River disappears underground in several swallow holes near the outlet of the catchment. In the rainy season this results in flooding upstream of the sinkholes. A hypothesis is that the Nam La River resurges at a large cavern spring 4.5 km east of the catchment outlet. A multi-thematic study of the possible connections between the swallow holes and the resurgence was carried out to investigate the geological structure, tectonics, cave structure analysis and discharge time series. The existence of the underground conduits was also tested and proven by tracer experiments. On the basis of a lineament analysis the location of the underground conduits were predicted. A remote sensing derived lineament-length density map was used to track routes from the swallow holes to the resurgence, having the shortest length but highest lineament density. This resulted in a plan-view prediction of underground conduits that matches with the cave and fault development. The functioning of the conduits was further explained by analysing flooding records of a nearby doline, which turns out to act as a temporary storage reservoir mitigating flooding of the catchment outlet area