Vegetation Effects on Fish Distribution in Impounded Salt Marshes

We compared the density and biomass of resident fish in vegetated and unvegetated flooded habitats of impounded salt marshes in the northern Indian River Lagoon (IRL) Estuary of east-central Florida. A 1-m2 throw trap was used to sample fish in randomly located, paired sample plots (n = 198 pairs) over 5 seasons in 7 impoundments. We collected a total of 15 fish taxa, and 88% of the fishes we identified from the samples belonged to three species: Cyprinodon variegatus (Sheepshead Minnow), Gambusia holbrooki (Eastern Mosquitofish), and Poecilia latipinna (Sailfin Molly). Vegetated habitat usually had higher density and biomass of fish. Mean fish density (and 95% confidence interval) for vegetated and unvegetated sites were 8.2 (6.7–9.9) and 2.0 (1.6–2.4) individuals m-2, respectively; mean biomass (and 95% confidence interval) for vegetated and unvegetated sites were 3.0 (2.5–3.7) and 1.1 (0.9–1.4) g m-2, respectively. We confirmed previous findings that impounded salt marshes of the northern IRL Estuary produce a high standing stock of resident fishes. Seasonal patterns of abundance were consistent with fish moving between vegetated and unvegetated habitat as water levels changed in the estuary. Differences in density, mean size, and species composition of resident fishes between vegetated and unvegetated habitats have important implications for movement of biomass and nutrients out of salt marsh by piscivores (e.g., wading birds and fishes) via a trophic relay

Workplace Stress: Implications for Employees and Organizations

Stressors are ubiquitous in today’s society, impacting the personal and professional lives of most people on a daily basis. In terms of stress in organizational settings, employees must deal with an array of workplace stressors, including: Role conflict or ambiguity; Task overload; Difficult relationships with co-workers or supervisor; Harsh environmental conditions; Lack of clear communication or direction; Insufficient resources needed to perform a job; Inadequate pay and benefits; Hostile work environment, including bullying or harassment; Job instability or uncertainty of the organization’s future. It is in the best interest of an organization to establish practices and programs to help reduce or eliminate stressors from the work environment. Employees who are able to perform their jobs with minimal stressors will demonstrate greater engagement, as well as productivity. This will enable an organization to sustain a high level of performance for achieving short and long-term objectives and overall success

A new family of non-local priors for chain event graph model selection

Chain Event Graphs (CEGs) are a rich and provenly useful class of graphical models. The class contains discrete Bayesian Networks as a special case and is able to depict directly the asymmetric context-specific statements in the model. But bespoke efficient algorithms now need to be developed to search the enormous CEG model space. In different contexts Bayes Factor scored search algorithm using non-local priors (NLPs) has recently proved very successful for searching other huge model spaces. Here we define and explore three different types of NLP that we customise to search CEG spaces. We demonstrate how one of these candidate NLPs provides a framework for search which is both robust and computationally efficient. It also avoids selecting an overfitting model as the standard conjugate methods sometimes do. We illustrate the efficacy of our methods with two examples. First we analyse a previously well-studied 5-year longitudinal study of childhood hospitalisation. The second much larger example selects between competing models of prisoners’ radicalisation in British prisons: because of its size an application beyond the scope of earlier Bayes Factor search algorithms

Isolation and characterisation of microcrystalline cellulose and cellulose nanocrystals from coffee husk and comparative study with rice husk

[EN] Cellulosic material from coffee husk has not been previously studied despite being a potential source of reinforcing agents for different applications. This material has been extracted and characterised from coffee husk, in parallel with previously studied rice husk. Samples have been analysed as to their ability to obtain cellulosic fibres and cellulose nanocrystals (CNC) by applying alkali and bleaching treatments and final sulphuric acid hydrolysis. Microstructural changes were analysed after treatments, and the size and aspect ratio of CNCs were determined. Crystallinity and thermal stability of both materials progressed in line with the enrichment in cellulosic compounds. The CNC aspect ratio was higher than 10, which confers good reinforcing properties. These were tested in thermoplastic starch films, whose elastic modulus increased by 186 and 121% when 1 wt% of CNCs from rice and coffee husks, respectively, was incorporated into the matrix. Coffee husk represents an interesting source of cellulosic reinforcing materials.The authors thank the Ministerio de Economia y Competitividad (Spain) for the financial support provided through Project AGL2016-76699-R. Authors also thank the Electron Microscopy Service of the UPV for their technical assistance.Collazo-Bigliardi, S.; Ortega-Toro, R.; Chiralt, A. (2018). Isolation and characterisation of microcrystalline cellulose and cellulose nanocrystals from coffee husk and comparative study with rice husk. Carbohydrate Polymers. 191:205-215. https://doi.org/10.1016/j.carbpol.2018.03.022S20521519

Automotive Cluster based on Raspberry Pi 3 B+

The automotive cluster is one of the most important devices in a car and is the interface between the car and the driver. However, the development of this Electronic Control Unit (ECU) used in the automotive industry is complex and expensive. The Raspberry Pi 3 is a lower cost board that can be used as an alternative board due to its versatility and ease of use. Therefore, the aim of the project is to develop an automotive cluster using the Raspberry Pi 3 as the main board, and be able to connect it to a CAN network. Buildroot was the main tool used in this project allowing to generate a customized Linux-based Operating System (OS). Furthermore, the project included the CAN-utils package and SocketCAN Application Programming Interface (API) to receive CAN messages, through a PiCAN2 module, and display the animation according to the message. Also, the interface was created using Qt5 IDE, so it was essential to add those Qt5 packages to the Raspberry Pi 3 as well. Finally, this project was configured to work with a baudrate of 100 Kbps. In conclusion, the proposed project is a practical choice for low cost hardware and free software automotive cluster, also it is user-friendly and interactive