Prediction of Benthic Impact for Salmon Net-Pens Based on the Balance of Benthic Oxygen Supply and Demand

The ratio between oxygen supply and oxygen demand was examined as a predictor of benthic response to organic enrichment caused by salmon net-pen aquaculture. Oxygen supply to the benthos was calculated based on Fickian diffusion and near-bottom flow velocities. A strong linear correlation was found between measured carbon sedimentation rates and rates of benthic metabolism. This relationship allowed an estimation of oxygen demand based on sedimentation rates. Comparison of several production sites in Maine (USA) coastal waters showed that for sites where oxygen demand exceeded supply benthic impacts were high and for sites where oxygen supply exceeded demand benthic impacts were low. These findings were summarized in the form of a predictive model that should be useful in siting salmon production facilities

Sensitivity analysis of optimal routes, departure times and speeds for fuel-efficient truck journeys

Embedded within the vehicle "routing" problem of determining the order in which customers are served, is the route choice problem of which sequence of roads to use between a pair of pick-up/drop-off locations, and this latter is the focus of the paper. When the objective is something other than travel time, such as fuel consumption, an additional control dimension is that of speed, and in a time-varying context the question of optimal speed determination is no longer a local one, due to potential downstream interactions. This also brings in the possibility to adjust departure times. Recently this problem, of joint route, departure time and speed determination for fuel minimization in a time-varying network, was shown to be efficiently solvable using a Space-Time Extended Network (STEN). In the present paper, we explore the sensitivity of the optimal solutions produced to: i) the fidelity of the within-day traffic information; ii) the currency of between-day traffic information in comparison with historical mean conditions; iii) the availability of historical information on variability for risk-averse routing; and iv) competition from other equally-optimal or near equally-optimal solutions. We set out the methods by which each of these tests may be achieved by adaptation of the underlying STEN, taking care to ensure a consistent reference basis, and describe the potential real-life relevance of each test. The results of illustrative numerical experiments are reported from interfacing the methods with real-time data accessed through the Google Maps API

Cladorhiza corona sp. nov. (Porifera : Demospongiae : Cladorhizidae) from the Aleutian Islands (Alaska)

A new species of Cladorhizidac, front the Aleutian Islands is described and compared with all known species of Cladorhizza worldwide. Cladorhiza corona sp. now has a unique growth form with two planes of differently shaped appendages. Appendages are Inserted directly at the stalk; a spherical or conical body at the stalk is lacking. It is the only species reported where different spicule types occur in three morphologically different areas of the sponge. The spiculation of the basal plate is characterized by the occurrence of short, thick anisoxcas and the lack of anisochelae. Anisochelac arc found in the stalk and the basal appendages only. Flattened sigmancistras and (sub-)tylostyles are restricted to the crown. The arrangement of spicules is different in the basal plate, the stalk with the basal appendages, and in the distal append ages. The dimensions and combination of spicule types separate C. corona sp. nov. from all known members of the genus

Optimization of route choice, speeds and stops in time-varying networks for fuel-efficient truck journeys

A method is presented for the real-time optimal control of the journey of a truck, travelling between a pair of pick-up/drop-off locations in a time-varying traffic network, in order to reduce fuel consumption. The method, when applied during the journey, encapsulates the choice of route, choice of speeds on the links, and choice of stop locations/durations; when applied pre-trip, it additionally incorporates choice of departure time. The problem is formulated by using a modified form of space-time extended network, in such a way that a shortest path in this network corresponds to an optimal choice of not only route, stops and (when relevant) departure time, but also of speeds. A series of simple illustrative examples are presented to illustrate the formulation. Finally, the method is applied to a realistic-size case study

Effective mobilities in pseudomorphic Si/SiGe/Si p-channel metal-oxide-semiconductor field-effect transistors with thin silicon capping layers

The room-temperature effective mobilities of pseudomorphic Si/Si0.64Ge0.36/Si p-metal-oxidesemiconductor field effect transistors are reported. The peak mobility in the buried SiGe channel increases with silicon cap thickness. It is argued that SiO2/Si interface roughness is a major source of scattering in these devices, which is attenuated for thicker silicon caps. It is also suggested that segregated Ge in the silicon cap interferes with the oxidation process, leading to increased SiO2/Si interface roughness in the case of thin silicon caps

Report of the ICES\NAFO Joint Working Group on Deep-water Ecology (WGDEC), 11–15 March 2013, Floedevigen, Norway.

On 11 February 2013, the joint ICES/NAFO WGDEC, chaired by Francis Neat (UK) and attended by ten members met at the Institute for Marine Research in Floedevi-gen, Norway to consider the terms of reference (ToR) listed in Section 2. WGDEC was requested to update all records of deep-water vulnerable marine eco-systems (VMEs) in the North Atlantic. New data from a range of sources including multibeam echosounder surveys, fisheries surveys, habitat modelling and seabed imagery surveys was provided. For several areas across the North Atlantic, WGDEC makes recommendations for areas to be closed to bottom fisheries for the purposes of conservation of VMEs

An Enhanced Predictive Cruise Control System Design with Data-Driven Traffic Prediction

The predictive cruise control (PCC) is a promising method to optimize energy consumption of vehicles, especially the heavy-duty vehicles (HDV). Due to the limited sensing range and computational capabilities available on-board, the conventional PCC system can only obtain a sub-optimal speed trajectory based on a shorter prediction horizon. The recently emerging information and communication technologies such as vehicular communication, cloud computing, and Internet of Things provide huge potentials to improve the traditional PCC system. In this paper, we propose a general framework for the enhanced cloud-based PCC system which integrates a data-driven traffic predictive model and the instantaneous control algorithms. Specifically, we introduce a novel multi-view CNN deep learning algorithm to predict traffic situation based on the historical and real-time traffic data collected from fields, and the time-varying adaptive model predictive control (MPC) to calculate the instantaneous optimal speed profile with the aim of minimizing energy consumption. We verified our approach via simulations in which the impact of various traffic condition on the PCC-enabled HDV has been fully evaluated

Computation of Equilibrium Distributions of Markov Traffic-Assignment Models

Markov traffic-assignment models explicitly represent the day-to-day evolving interaction between traffic congestion and drivers' information acquisition and choice processes. Such models can, in principle, be used to investigate traffic flows in stochastic equilibrium, yielding estimates of the equilibrium mean and covariance matrix of link or route traffic flows. However, in general these equilibrium moments cannot be written down in closed form. While Monte Carlo simulations of the assignment process may be used to produce “empirical” estimates, this approach can be extremely computationally expensive if reliable results (relatively free of Monte Carlo error) are to be obtained. In this paper an alternative method of computing the equilibrium distribution is proposed, applicable to the class of Markov models with linear exponential learning filters. Based on asymptotic results, this equilibrium distribution may be approximated by a Gaussian process, meaning that the problem reduces to determining the first two multivariate moments in equilibrium. The first of these moments, the mean flow vector, may be estimated by a conventional traffic-assignment model. The second, the flow covariance matrix, is estimated through various linear approximations, yielding an explicit expression. The proposed approximations are seen to operate well in a number of illustrative examples. The robustness of the approximations (in terms of network input data) is discussed, and shown to be connected with the “volatility” of the traffic assignment process

SARS-CoV-2 positivity in asymptomatic-screened dental patients

Enhanced community surveillance is a key pillar of the public health response to COVID-19. Asymptomatic carriage of SARS-CoV-2 is a potentially significant source of transmission, yet remains relatively poorly understood. Disruption of dental services continues with significantly reduced capacity. Ongoing precautions include pre- and/or at appointment COVID-19 symptom screening and use of enhanced personal protective equipment (PPE). This study aimed to investigate SARS-CoV-2 infection in dental patients to inform community surveillance and improve understanding of risks in the dental setting. Thirty-one dental care centres across Scotland invited asymptomatic screened patients over 5-years-old to participate. Following verbal consent and completion of sociodemographic and symptom history questionnaire, trained dental teams took a combined oropharyngeal and nasal swab sample using standardised VTM-containing testkits. Samples were processed by the Lighthouse Lab and patients informed of their results by SMS/e-mail with appropriate self-isolation guidance in the event of a positive test. All positive cases were successfully followed up by the national contact tracing program. Over a 13-week period (from 3August to 31October2020) n=4,032 patients, largely representative of the population, were tested. Of these n=22 (0.5%; 95%CI 0.5%, 0.8%) tested positive for SARS-CoV-2. The positivity rate increased over the period, commensurate with uptick in community prevalence identified across all national testing monitoring data streams. To the best of our knowledge this is the first report of a COVID-19 testing survey in asymptomatic-screened patients presenting in a dental setting. The positivity rate in this patient group reflects the underlying prevalence in community at the time. These data are a salient reminder, particularly when community infection levels are rising, of the importance of appropriate ongoing Infection Prevention Control and PPE vigilance, which is relevant as healthcare team fatigue increases as the pandemic continues. Dental settings are a valuable location for public health surveillance

Widespread forest vertebrate extinctions induced by a mega hydroelectric dam in lowland Amazonia

Mega hydropower projects in tropical forests pose a major emergent threat to terrestrial and freshwater biodiversity worldwide. Despite the unprecedented number of existing, underconstruction and planned hydroelectric dams in lowland tropical forests, long-term effects on biodiversity have yet to be evaluated. We examine how medium and large-bodied assemblages of terrestrial and arboreal vertebrates (including 35 mammal, bird and tortoise species) responded to the drastic 26-year post-isolation history of archipelagic alteration in landscape structure and habitat quality in a major hydroelectric reservoir of Central Amazonia. The Balbina Hydroelectric Dam inundated 3,129 km2 of primary forests, simultaneously isolating 3,546 land-bridge islands. We conducted intensive biodiversity surveys at 37 of those islands and three adjacent continuous forests using a combination of four survey techniques, and detected strong forest habitat area effects in explaining patterns of vertebrate extinction. Beyond clear area effects, edge-mediated surface fire disturbance was the most important additional driver of species loss, particularly in islands smaller than 10 ha. Based on species-area models, we predict that only 0.7% of all islands now harbor a species-rich vertebrate assemblage consisting of ≥80% of all species. We highlight the colossal erosion in vertebrate diversity driven by a man-made dam and show that the biodiversity impacts of mega dams in lowland tropical forest regions have been severely overlooked. The geopolitical strategy to deploy many more large hydropower infrastructure projects in regions like lowland Amazonia should be urgently reassessed, and we strongly advise that long-term biodiversity impacts should be explicitly included in pre-approval environmental impact assessments