A study on damage caused to crustacean and finfish larvae during collection of Penaeus monodon (Fab.) postlarvae in the estuaries of Barguna, Bangladesh

A year round investigation in the estuaries of Barguna district revealed that for each Penaeus monodon postlarvae (PL), about 37 larvae of other shrimp species, 12 finfishes and 10 macrozooplankters are destroyed during the process of shrimp seed collection. Although abundance of P. monodon PL was not recorded throughout the year, a significant number of other shrimp spp., fin fishes including macrozooplankters are being damaged by the shrimp seed collectors. This indiscriminate destruction of aquatic organisms during P. monodon PL collection is serious threat to aquatic biodiversity

Outlier detection in 2 × 2 crossover design using Bayesian framework

We consider the problem of outlier detection method in 2×2 crossover design via Bayesian framework. We study the problem of outlier detection in bivariate data fitted using generalized linear model in Bayesian framework used by Nawama. We adapt their work into a 2×2 crossover design. In Bayesian framework, we assume that the random subject effect and the errors to be generated from normal distributions. However, the outlying subjects come from normal distribution with different variance. Due to the complexity of the resulting joint posterior distribution, we obtain the information on the posterior distribution from samples by using Markov Chain Monte Carlo sampling. We use two real data sets to illustrate the implementation of the method

Growth, immunity and ammonia excretion of albino and normal Apostichopus japonicus (Selenka) feeding with various experimental diets

An experiment was conducted to evaluate the effects of six experimental diets on growth performance, ammonia excretion and immunity of albino and normal Apostichopus japonicus. A factorial design was used, the factors being type of diets (six levels) and colour of A. japonicus (two levels). A total of 30 randomly selected albino A. japonicus were housed in each (60 × 50 × 30 cm3) of 18 blue plastic aquaria to form six groups in triplicate, and the same set-up was used for the normal A. japonicus. Each group of animals was fed with one of the six experimental diets. Apparent dry matter digestibility (ADMD) and apparent crude protein digestibility (ACPD) were analysed using acid-insoluble ash (AIA) content method. At the end of the experiment, all A. japonicus were harvested and weighed to calculate growth parameters. After weighing, six individuals from each aquarium were randomly sampled for immune indices. Results indicated that all growth parameters of A. japonicus increased with decreasing nutrient content in their diets (p < .01), whereas an opposite result was observed in case of the ammonia-nitrogen production by A. japonicus. Normal A. japonicus grew better (p < .01) and produced lower (p < .01) quantity of ammonia nitrogen compared to the albino A. japonicus. Immunity particularly superoxide dismutase and lysozyme activities was higher (p < .05) in normal compared to albino A. japonicus. Considering all measured variables, D1 (diet containing crude protein, crude lipid, carbohydrate and crude ash 51.8, 8.7, 231.3, 708.2 g/kg, respectively) was the best diet among all experimental diets. More research is still needed to optimize nutrients in the diet of A. japonicus, as this study does not provide information about critical threshold level of nutrients in diets. Until then, diet D1 can be recommended for A. japonicus aquaculture

Von Neumann equations with time-dependent Hamiltonians and supersymmetric quantum mechanics

Starting with a time-independent Hamiltonian $h$ and an appropriately chosen solution of the von Neumann equation $i\dot\rho(t)=[ h,\rho(t)]$ we construct its binary-Darboux partner $h_1(t)$ and an exact scattering solution of $i\dot\rho_1(t)=[h_1(t),\rho_1(t)]$ where $h_1(t)$ is time-dependent and not isospectral to $h$. The method is analogous to supersymmetric quantum mechanics but is based on a different version of a Darboux transformation. We illustrate the technique by the example where $h$ corresponds to a 1-D harmonic oscillator. The resulting $h_1(t)$ represents a scattering of a soliton-like pulse on a three-level system.Comment: revtex, 3 eps file

Existence of superposition solutions for pulse propagation in nonlinear resonant media

Existence of self-similar, superposed pulse-train solutions of the nonlinear, coupled Maxwell-Schr\"odinger equations, with the frequencies controlled by the oscillator strengths of the transitions, is established. Some of these excitations are specific to the resonant media, with energy levels in the configurations of $\Lambda$ and $N$ and arise because of the interference effects of cnoidal waves, as evidenced from some recently discovered identities involving the Jacobian elliptic functions. Interestingly, these excitations also admit a dual interpretation as single pulse-trains, with widely different amplitudes, which can lead to substantially different field intensities and population densities in different atomic levels.Comment: 11 Pages, 6 Figures, presentation changed and 3 figures adde

Breathlessness in COPD: linking symptom clusters with brain activity

Rationale: Current models of breathlessness often fail to explain disparities between patients' experiences of breathlessness and objective measures of lung function. While a mechanistic understanding of this discordance has thus far remained elusive, factors such as mood, attention and expectation have all been implicated as important modulators of breathlessness. Therefore, we have developed a model to better understand the relationships between these factors using unsupervised machine learning techniques. Subsequently we examined how expectation-related brain activity differed between these symptom-defined clusters of participants. Methods: A cohort of 91 participants with mild-to-moderate chronic obstructive pulmonary disease (COPD) underwent functional brain imaging, self-report questionnaires and clinical measures of respiratory function. Unsupervised machine learning techniques of exploratory factor analysis and hierarchical cluster modelling were used to model brain-behaviour-breathlessness links. Results: We successfully stratified participants across four key factors corresponding to mood, symptom burden and two capability measures. Two key groups resulted from this stratification, corresponding to high and low symptom burden. Compared to the high symptom load group, the low symptom burden group demonstrated significantly greater brain activity within the anterior insula, a key region thought to be involved in monitoring internal bodily sensations (interoception). Conclusions: This is the largest functional neuroimaging study of COPD to date and is the first to provide a clear model linking brain, behaviour and breathlessness expectation. Furthermore, it was possible to stratify participants into groups, which then revealed differences in brain activity patterns. Together, these findings highlight the value of multi-modal models of breathlessness in identifying behavioural phenotypes, and for advancing understanding of differences in breathlessness burden

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types