Community Based Fisheries Management (CBFM) in Sunamganj district of Bangladesh: the nature of cooperation and conflicts

There are altogether 411 haors comprising an area of about 8000 square kilometer, covering 25% of entire region dispersed in the districts of Sunamgonj, Sylhet, Moulvibazar, Hobigonj, Netrokona and Kishoreganj. Sunamganj district is particularly known as a district of haors and baors where a large number of people depend on fishing for their livelihood. Some people are basically fishermen and fish all the year round. Community Based Fisheries Management (CBFM) project has been initiated in this area to develop fishery sector as well as for the development of the inland fishermen of haor area. Healthy cooperation among the beneficiaries of the project is very much present and some NGOs are found working actively there to help the fishermen for the sound implementation of the project. But the influentials of different villages around create troubles and conflicts intentionally in the project area because of which fishermen cannot fish smoothly and the implementation of the project is getting hampered. Therefore, a kind of consensus needs to be reached among the inhabitants of the haor area and a powerful association of the fishermen should be established so that fishing may be undertaken in the beel without having any troubles and conflicts. In this article the conflicts and cooperation that are in existence in the implementation process of CBFM project in the haor areas of Sunamgonj district have been discussed. Some suggestions have been offered in the paper to overcome the existing conflicts impeding the smooth implementation of CBFM project in the fishery sector of haor area under Sunamganj district.

Conditional Moment Closure for Turbulent Premixed Flames

The conditional moment closure (CMC) method has been successfully applied to various non-premixed combustion systems in the past, but its application to premixed flames is not fully tested and validated. The main difficulty is associated with the modeling of conditional scalar dissipation rate of the conditioning scalar, the progress variable. A simple algebraic model for the conditional dissipation rate is validated using DNS results of a V-flame. This model along with the standard k- turbulence modeling is used in computations of stoichiometric pilot stabilized Bunsen flames using the RANS-CMC method. A first-order closure is used for the conditional mean reaction rate. The computed non reacting and reacting scalars are in reasonable agreement with the experimental measurements and are consistent with earlier computations using flamelets and transported PDF methods. Sensitivity to chemical kinetic mechanism is also assessed. The results suggest that the CMC may be applied across the regimes of premixed combustion.

Kernel conditional quantile estimation via reduction revisited

Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among other domains. In this paper, we show how to estimate these conditional quantile functions within a Bayes risk minimization framework using a Gaussian process prior. The resulting non-parametric probabilistic model is easy to implement and allows non-crossing quantile functions to be enforced. Moreover, it can directly be used in combination with tools and extensions of standard Gaussian Processes such as principled hyperparameter estimation, sparsification, and quantile regression with input-dependent noise rates. No existing approach enjoys all of these desirable properties. Experiments on benchmark datasets show that our method is competitive with state-of-the-art approaches. © 2009 IEEE.

Using sub-word-level information for confidence estimation with conditional random field models

The task of word-level confidence estimation (CE) for automatic speech recognition (ASR) systems stands to benefit from the combination of suitably defined input features from multiple information sources. However, the information sources of interest may not necessarily operate at the same level of granularity as the underlying ASR system. The research described here builds on previous work on confidence estimation for ASR systems using features extracted from word-level recognition lattices, by incorporating information at the sub-word level. Furthermore, the use of Conditional Random Fields (CRFs) with hidden states is investigated as a technique to combine information for word-level CE. Performance improvements are shown using the sub-word-level information in linear-chain CRFs with appropriately engineered feature functions, as well as when applying the hidden-state CRF model at the word level.

Computations of turbulent lean premixed combustion using conditional moment closure

Conditional Moment Closure (CMC) is a suitable method for predicting scalars such as carbon monoxide with slow chemical time scales in turbulent combustion. Although this method has been successfully applied to non-premixed combustion, its application to lean premixed combustion is rare. In this study the CMC method is used to compute piloted lean premixed combustion in a distributed combustion regime. The conditional scalar dissipation rate of the conditioning scalar, the progress variable, is closed using an algebraic model and turbulence is modelled using the standard k-e{open} model. The conditional mean reaction rate is closed using a first order CMC closure with the GRI-3.0 chemical mechanism to represent the chemical kinetics of methane oxidation. The PDF of the progress variable is obtained using a presumed shape with the Beta function. The computed results are compared with the experimental measurements and earlier computations using the transported PDF approach. The results show reasonable agreement with the experimental measurements and are consistent with the transported PDF computations. When the compounded effects of shear-turbulence and flame are strong, second order closures may be required for the CMC. © 2013 Copyright Taylor and Francis Group, LLC.

Cooperation of Mtmr8 with PI3K Regulates Actin Filament Modeling and Muscle Development in Zebrafish

Background: It has been shown that mutations in at least four myotubularin family genes (MTM1, MTMR1, 2 and 13) are causative for human neuromuscular disorders. However, the pathway and regulative mechanism remain unknown. Methodology/Principal Findings: Here, we reported a new role for Mtmr8 in neuromuscular development of zebrafish. Firstly, we cloned and characterized zebrafish Mtmr8, and revealed the expression pattern predominantly in the eye field and somites during early somitogenesis. Using morpholino knockdown, then, we observed that loss-of-function of Mtmr8 led to defects in somitogenesis. Subsequently, the possible underlying mechanism and signal pathway were examined. We first checked the Akt phosphorylation, and observed an increase of Akt phosphorylation in the morphant embryos. Furthermore, we studied the PH/G domain function within Mtmr8. Although the PH/G domain deletion by itself did not result in embryonic defect, addition of PI3K inhibitor LY294002 did give a defective phenotype in the PH/G deletion morphants, indicating that the PH/G domain was essential for Mtmr8's function. Moreover, we investigated the cooperation of Mtmr8 with PI3K in actin filament modeling and muscle development, and found that both Mtmr8-MO1 and Mtmr8-MO2+LY294002 led to the disorganization of the actin cytoskeleton. In addition, we revealed a possible participation of Mtmr8 in the Hedgehog pathway, and cell transplantation experiments showed that Mtmr8 worked in a non-cell autonomous manner in actin modeling. Conclusion/Significance: The above data indicate that a conserved functional cooperation of Mtmr8 with PI3K regulates actin filament modeling and muscle development in zebrafish, and reveal a possible participation of Mtmr8 in the Hedgehog pathway. Therefore, this work provides a new clue to study the physiological function of MTM family members.

Promotion of cooperation in the form C0C1D classified by 'degree grads' in a scale-free network

In this paper, we revisit the issue of the public goods game (PGG) on a heterogeneous graph. By introducing a new effective topology parameter, 'degree grads' phi, we clearly classify the agents into three kinds, namely, C-0, C-1, and D. The mechanism for the heterogeneous topology promoting cooperation is discussed in detail from the perspective of C0C1D, which reflects the fact that the unreasoning imitation behaviour of C-1 agents, who are 'cheated' by the well-paid C-0 agents inhabiting special positions, stabilizes the formation of the cooperation community. The analytical and simulation results for certain parameters are found to coincide well with each other. The C0C1D case provides a picture of the actual behaviours in real society and thus is potentially of interest.