Coastal fishing for blue swimming crab (Portunus pelagicus) is economically important in Indonesia. Baited traps to capture crabs are increasing in use due to their low operational costs and high catch quality. However, the transition to using baited traps has been hindered by their low capture efficiency that leads many fishers to continue using gillnets that cause greater environmental impacts than traps. To catalyze a transition to trap fishing, improvements in the efficiency of traps are needed. Five different trap designs were tested in the laboratory to quantify the effects of trap entrance color and cover mesh size on blue swimming crab capture efficiency and size selectivity. Three trap designs were also tested in field trials in Banten Bay, Indonesia, and were compared to commercial trap designs with a dark-green entrance color and 25-mm cover mesh size. Entrance color affected fishing efficiency, and cover mesh size affected size selectivity. In laboratory and field trials, traps with yellow entrances attracted more crabs than traps with dark-green or red entrances. In laboratory trials, cover mesh size affected escapement rates of undersized crabs, with larger mesh sizes (75 mm) allowing smaller crabs (carapace width < 100 mm) to escape. Our findings suggest that catch rates of blue swimming crabs in traps can be significantly increased by using yellow entrances, and catches of undersized swimming crabs can be reduced by using > 75 mm mesh sizes. This would improve the economic performance and sustainability of trap fishing.
Hydraulic, overcoring and LVDT stress measurements have been conducted for characterizing the in situ stress state at the spent nuclear fuel repository at Olkiluoto site, located in Western Finland. The effect of foliation on the stress measurement data was investigated. The analysis of the hydraulic data conducted in foliated rock types shows that the hydraulically-induced fracture propagates along a foliation plane rather than developing along the true maximum horizontal stress direction as dictated by the theory of hydraulic fracturing. An integration of the stress measurement data considered to be reliable was conducted for establishing the most likely stress field and confidence intervals for the large (site) and small scales. At the depth of the planned repository, the stress magnitudes obtained for the two scales were found to be similar, thus concluding that the confidence in the derived stresses is high. The mean magnitudes of the major, intermediate and minor principal stresses are 22, 18, and 11 MPa, respectively. The estimated orientation of the major principal stress (WNW-ESE) agrees with the regional stress state.
The diverse socio-economic and geographical situation of Nepal contributes to the complexity of community development. In such varied contexts, holistic community development faces many challenges, addressing cross-cutting issues like health and education, which may be viewed differently by men and women, as well as different castes, ethnicities, economic status, political associations and religions. The community's well-being must be the central focus of every development intervention, yet there is no one opinion that reflects the diversity of opinions within every community. How can community development practitioners listen to all viewpoints and find an accepted method to achieve grassroots development in such a complex environment, when they themselves come from diverse backgrounds and education, and bring their own attitudes and opinions? The central focus of this study was to investigate the reflective practices of community development at the grassroots level of rural Nepal. The study investigates the practices and perceptions of community development practitioners and their reflexivity regarding their life experiences and efforts to adequately relate to diverse communities. For this, critical reflective inquiry has been used. Practitioners with extensive experiences were chosen as research participants for that purpose. The life experience of both authors and the practitioners is interpreted through the lens of actor perspective on community development. Additionally, we consider how the insider and outsider perspectives of development practitioners may influence their work. Three key elements with the potential to directly interference the process of community development in rural Nepal were explored: local people as subjective forms of beneficiary; community development practitioners as mediators of interventions; and development policies as a roadmap of community inclusion. The dynamic involvement of these three elements is crucial to reach goals envisioned by community development interventions, yet often the practitioners are ignored. The paper concludes that the success of such interventions rests upon the active and reflective intercourse of this triangulation.
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basins. The hyperspectral data consists of 36 bands in the wavelength range of 508–878 nm and the water quality parameters to be predicted are temperature, conductivity, turbidity, Secchi depth, blue-green algae, chlorophyll-a, total phosphorus, acidity and dissolved oxygen. The objective of this investigation was to study the behaviour of different types of neural networks with this kind of data. Study is a survey of the operation of neural networks on this problem, which can be used as a basis for the design of a more comprehensive study. The neural network types examined were multilayer perceptron and 1-, 2- and 3-dimensional convolutional neural networks with the effect of scaling the hyperspectral data with standard or min-max -scaler recorded. We also investigated investigated how the prediction of individual water quality parameter depends on whether the neural network model is done solely with respect to this one parameter or with several parameters predicted simultaneously with the same model. The results of the correspondence between the predicted and measured water quality parameters were presented with normalized root mean square error, Pearson correlation coefficient and coefficient of determination. The best models were obtained the 2-dimensional convolutional neural networks with standard scaling made separately for each parameter. The parameters showing good predictability were conductivity, turbidity, Secchi-depth, blue-green algae, chlorophyll-a and total phosphorus, for which the coefficient of determination was at least 0.96 (apart from Secchi-depth even 0.98).
Nowadays, many buildings are equipped with various energy sources. The challenge is how to efficiently utilize their energy production. This includes decreasing the share and costs of external energy—usually electrical energy delivered from the grid. The following study presents a qualitative approach with a combined control to solve the problem. The approach is demonstrated using a simulated residential building equipped with a hybrid energy system: a thermal energy storage combined with an electrical heater, a geothermal heat pump and a solar thermal collector. Consequently, the share of renewable energy was increased and, conversely, costs of the external energy from grid decreased by 12.2%. The results were based on a qualitative approach and the algorithm which predicts the need of energy of the building over the next 6 h with the aid of weather forecasting. This approach included a storage tank of 300 L. The energy costs can be further decreased 7.7% by increasing thermal storage capacity and modifying the control algorithm. In all cases, the indoor conditions were kept at a comfortable level. However, if the room temperature is temporarily allowed to slightly drop a few degrees during the heating season, the energy costs were further reduced.
