A case report and statewide surveillance of "weak meat" condition of Alaska weathervane scallops, Patinopecten caurinus, linked to a recently identified pathogenic parasite, Merocystis kathae (Apicomplexa: Aggregatidae).

Weathervane scallop, Patinopecten caurinus, the largest scallop species in the world, is distributed from northern California, U.S.A., to the Bering Sea, and is only commercially harvested in Alaska. The fishery is considered well managed by the State of Alaska (U.S.A) Department of Fish and Game (ADF&G) and federal government, with many precautionary measures in place to avoid overharvest. There have been episodic declines in some management areas due to unknown causes. Fishermen also encounter scallops with abnormal adductor muscles, a condition colloquially termed "weak meat", characterized by the retention of muscle when shucked, an obvious darkened discoloration, and/or an abnormal texture making the product unacceptable for marketing. A similar syndrome in Atlantic sea scallops, Placopecten magellanicus, described as "gray meat", occurs in the eastern U.S. and Canada, and proposed causes include senescence, loss of bioenergetics due to chronic infestations, or a synergism of these factors. Recently a severe apicomplexan infection was found to cause a gray meat condition in Iceland scallops, Chlamys islandica, and the collapse of that stock. This parasite was subsequently detected in Atlantic sea scallops with the gray meat condition off the U.S. East Coast. Studies that followed identified the parasite as Merocystis kathae, previously described from the common whelk, Buccinum undatum, more than 100 years ago. In 2015 Bering Sea fishermen reported weak meat in their catch, so samples were submitted to ADF&G for diagnosis. Adductor muscles from all affected scallops had many large foci of an apicomplexan associated with necrosis, fibrosis, and muscular atrophy. Given the reduced quality, marketability, and possibly fitness of affected scallops, we performed a survey to estimate prevalence, intensity, and geographic distribution of this apicomplexan in Alaskan weathervane scallops. We sampled 180 scallops, from individual beds within each of the three major geographically broad scallop areas in Alaska. Overall prevalence was about 82%, ranging from 69 to 100% by district. Overall mean infection intensity, based on the number of parasite foci/section, was about 9 (range of 5-29, by location), with scallops from the Bering Sea and Southwest Kodiak being most severely infected. Molecular analyses confirmed that the Alaskan parasite is M. kathae, i.e., the same apicomplexan that caused the collapse of Icelandic scallops and a suspected cause for gray meat and mass mortality of Atlantic sea scallops in northeast North America.

A review of molecular modelling of electric double layer capacitors.

Electric double-layer capacitors are a family of electrochemical energy storage devices that offer a number of advantages, such as high power density and long cyclability. In recent years, research and development of electric double-layer capacitor technology has been growing rapidly, in response to the increasing demand for energy storage devices from emerging industries, such as hybrid and electric vehicles, renewable energy, and smart grid management. The past few years have witnessed a number of significant research breakthroughs in terms of novel electrodes, new electrolytes, and fabrication of devices, thanks to the discovery of innovative materials (e.g. graphene, carbide-derived carbon, and templated carbon) and the availability of advanced experimental and computational tools. However, some experimental observations could not be clearly understood and interpreted due to limitations of traditional theories, some of which were developed more than one hundred years ago. This has led to significant research efforts in computational simulation and modelling, aimed at developing new theories, or improving the existing ones to help interpret experimental results. This review article provides a summary of research progress in molecular modelling of the physical phenomena taking place in electric double-layer capacitors. An introduction to electric double-layer capacitors and their applications, alongside a brief description of electric double layer theories, is presented first. Second, molecular modelling of ion behaviours of various electrolytes interacting with electrodes under different conditions is reviewed. Finally, key conclusions and outlooks are given. Simulations on comparing electric double-layer structure at planar and porous electrode surfaces under equilibrium conditions have revealed significant structural differences between the two electrode types, and porous electrodes have been shown to store charge more efficiently. Accurate electrolyte and electrode models which account for polarisation effects are critical for future simulations which will consider more complex electrode geometries, particularly for the study of dynamics of electrolyte transport, where the exclusion of electrode polarisation leads to significant artefacts.

Unsupervised foveal vision neural architecture with top-down attention.

Deep learning architectures are an extremely powerful tool for recognizing and classifying images. However, they require supervised learning and normally work on vectors of the size of image pixels and produce the best results when trained on millions of object images. To help mitigate these issues, we propose an end-to-end architecture that fuses bottom-up saliency and top-down attention with an object recognition module to focus on relevant data and learn important features that can later be fine-tuned for a specific task, employing only unsupervised learning. In addition, by utilizing a virtual fovea that focuses on relevant portions of the data, the training speed can be greatly improved. We test the performance of the proposed Gamma saliency technique on the Toronto and CAT 2000 databases, and the foveated vision in the large Street View House Numbers (SVHN) database. The results with foveated vision show that Gamma saliency performs at the same level as the best alternative algorithms while being computationally faster. The results in SVHN show that our unsupervised cognitive architecture is comparable to fully supervised methods and that saliency also improves CNN performance if desired. Finally, we develop and test a top-down attention mechanism based on the Gamma saliency applied to the top layer of CNNs to facilitate scene understanding in multi-object cluttered images. We show that the extra information from top-down saliency is capable of speeding up the extraction of digits in the cluttered multidigit MNIST data set, corroborating the important role of top down attention.

Uptake and degradation of Orange II by zinc aluminum layered double oxides.

In this work ZnAl-layered double oxide composites (LDO) were developed to remove organic dyes in wastewater by adsorption and photocatalysis. Various LDO composites were synthesized by adjusting synthetic parameters including the molar ratio of Zn to Al, and calcination temperature. LDO adsorption and photocatalytic properties for decomposition of organic dyes were also investigated. Orange II sodium salt (OrgII), an azo dye and water contaminant, was chosen as the model to investigate the properties of LDOs compared with commercial ZnO, TiO2 (P25) and ZnO-LDH. The adsorption and photocatalytic performance results showed that LDO composites significantly enhanced adsorption-photocatalytic performance for OrgII degradation. LDO at the Zn/Al molar ratio of 2 (2)LDO has the best adsorption capacity (800.8 mg/g of OrgII for (2)LDO), and improved photocatalytic activity (74.3% of OrgII decomposition for (2)LDO). It is believed that the better adsorption properties of LDO are due to the adsorption and intercalation of dyes in the interlayer during LDO's rehydration process. ZnO/ZnAl-rehydrated layered double hydroxide composites (ZnO-rLDH) after rehydration of LDOs in aqueous solution was also obtained. After restoration in water, the structure and morphology of ZnO-rLDHs were characterized by XRD, FTIR, SEM/TEM, N2 adsorption/desorption and UV-vis-DRS. Finally, the relations between the structural features of the ZnO-rLDH composites and the adsorption properties and photocatalytic activity of LDO was studied.

Capacitance of Nanoporous Carbon-Based Supercapacitors Is a Trade-Off between the Concentration and the Separability of the Ions.

Nanoporous carbon-based supercapacitors store electricity through adsorption of ions from the electrolyte at the surface of the electrodes. Room temperature ionic liquids, which show the largest ion concentrations among organic liquid electrolytes, should in principle yield larger capacitances. Here, we show by using electrochemical measurements that the capacitance is not significantly affected when switching from a pure ionic liquid to a conventional organic electrolyte using the same ionic species. By performing additional molecular dynamics simulations, we interpret this result as an increasing difficulty of separating ions of opposite charges when they are more concentrated, that is, in the absence of a solvent that screens the Coulombic interactions. The charging mechanism consistently changes with ion concentration, switching from counterion adsorption in the diluted organic electrolyte to ion exchange in the pure ionic liquid. Contrarily to the capacitance, in-pore diffusion coefficients largely depend on the composition, with a noticeable slowing of the dynamics in the pure ionic liquid.