Lake charr (Salvelinus namaycush) clotting response may act as a plasma biomarker of sea lamprey (Petromyzon marinus) parasitism: Implications for management and wound assessment

Sea lampreys (Petromyzon marinus) have decimated the Great Lakes fisheries over the past century, and their control is central to protecting native fish populations. Wounding data collected from host fish, including classifying wounds as Type A (penetrating the integument) or Type B (superficial), is an integral part of sea lamprey monitoring efforts and helps inform management decisions; however, wound assessment is subjective and error-prone. This study aimed to determine if protein biomarkers of parasitism could be quantified in host fish plasma to serve as a potential objective aide in current wound assessment practices. Male siscowet lake charr (Salvelinus namaycush) were parasitized in a lab setting for four days, after which the sea lamprey was removed, host blood was collected, and the wound Type recorded. A second blood sample was collected from host fish with Type A wounds 7 months later. The plasma proteome was quantified using iTRAQ, and the relative abundances of 169 proteins were compared between parasitized and non-parasitized control fish. Three functional classes of proteins were modified by sea lamprey parasitism: immune response, lipid transport, and blood coagulation. A major finding was evidence of a concerted anticoagulation response in fish with Type A wounds, including changes in protein components and regulators of fibrin clot formation, some of which did not fully recover within 7 months. A modified clotting assay yielded a smaller thrombin-induced fibrin clot from parasitized fish, supporting the proteomic results. Therefore, measuring blood clottability could improve sea lamprey damage estimates by providing a more objective and quantitative index of parasitism than is offered by wounding data alone.     

Evaluation of adult and offspring thiamine deficiency in salmonine species from Lake Ontario

Thiamine Deficiency Complex (TDC) is an ongoing problem impacting salmonine health in various waterbodies, including Lake Ontario. The prevalence of TDC has been variable and explanations for differences are limited. In the current study, thiamine concentrations were measured in eggs, liver tissue, and muscle tissue sampled from brown trout (Salmo trutta), Chinook salmon (Oncorhynchus tshawytscha), coho salmon (O. kisutch), lake trout (Salvelinus namaycush), and steelhead trout (O. mykiss) that were collected from Lake Ontario and its surrounding tributaries. The occurrence of TDC was measured for each species based on TDC-induced offspring mortality rates under laboratory conditions. TDC-induced offspring mortality was observed for all species except brown trout. For affected species, egg free thiamine (Th) was consistently low compared to lake trout collected from Lake Superior that are considered thiamine replete. In addition, species with the lowest percentages of Th in their eggs were the most susceptible to TDC, suggesting that limited thiamine reserves in the form of Th may cause TDC-induced offspring mortality. Lastly, our results show that egg thiamine concentrations have yearly variation and increased for all species throughout the study. Reasons for such variation are undetermined; but, if egg thiamine concentrations continue to increase, the impacts of TDC on these salmonine species may lessen. Future monitoring is needed for determining if thiamine concentrations are increasing and the potential impacts that may have on the entire Lake Ontario fishery.     

Research on Circular Area Search algorithm of multi-robot service based on SOA cloud platform

Considering autonomous mobile robots with a variety of specific functions as a kind of service, when there are many types and quantities of services and the density of regional services is large, proposing an algorithm of Circular Area Search (CAS) because of the problem of multi-robot service scheduling in various areas. Firstly, Django is used as the web framework to build the Service-Oriented Architecture (SOA) multi-robot service cloud platform, which is the basic platform for multi-service combination. Then, the service type, the latitude and longitude and the scoring parameters of the service are selected as the service search metrics to design the CAS algorithm that based on the existing service information registered in MySQL and the Gaode Map for screening optimal service, and then providing the service applicant with the best service. Finally, the service applicant applies for the self-driving tour service as an example to perform performance simulation test on the proposed CAS algorithm. The results show that the CAS algorithm of the multi-robot service cloud platform proposed in this paper is practical compared to the global search. And compared with the Greedy Algorithm experiment, the service search time is reduced about 58% compared with the Greedy Algorithm, which verifies the efficiency of CAS algorithm.     

Quantum computation based bundling optimization for combinatorial auction in freight service procurements

Combinatorial auction is a useful trade manner for transportation service procurements in e-marketplaces. To enhance the competition of combinatorial auction, a novel auction mechanism of two-round bidding with bundling optimization is proposed. As the recommended the auction mechanism, the shipper/auctioneer integrates the objects into several bundles based on the bidding results of first round auction. Then, carriers/bidders bid for the object bundles in second round. The bundling optimization is described as a multi-objective model with two criteria on price complementation and combination consistency. A Quantum Evolutionary Algorithm (QEA) with β-based rotation gate and the encoding scheme based on non-zero elements in complementary coefficient matrix is developed for the model solution. Comparing with a Contrast Genetic Algorithm, QEA can achieve better computational performances for small and middle size problems.     

Modeling trade-offs among ecosystem services in agricultural production systems

Although agricultural ecosystems can provide humans with a wide set of benefits agricultural production system management is mainly driven by food production. As a consequence, a need to ensure food security globally has been accompanied by a significant decline in the state of ecosystems. In order to reduce negative trade-offs and identify potential synergies it is necessary to improve our understanding of the relationships between various ecosystem services (ES) as well as the impacts of farm management on ES provision. We present a spatially explicit application that captures and quantifies ES trade-offs in the crop systems of Llanada Alavesa in the Basque Country. Our analysis presents a quantitative assessment of selected ES including crop yield, water supply and quality, climate regulation and air quality. The study is conducted using semantic meta-modeling, a technique that enables flexible integration of models to overcome the service-by-service modeling approach applied traditionally in ES assessment.     

A generalized method for the inherent energy performance modeling of machine tools

Machine tools (MTs), as the key equipment of manufacturing systems, have enormous quantities and consume a great amount of energy. However, the diversity of both machines and their energy consumption properties make it difficult to transfer the energy-saving knowledge and services among different MT. To facilitate the initialization configuration of energy-saving services, the inherent energy performance (IEP) is investigated to describe the differences in energy consumption among MTs, and a generalized method for modeling the IEP of MT and its electrical subsystems is proposed. Three key enablers, including generalized experimental design rules, automatic coding, and data processing algorithms, are presented and integrated into a supporting system to reduce the modeling efforts and knowledge requirements. Case studies of an offline manufacturing scenario and an Internet of Things (IoT)-enabled manufacturing scenario were carried out to verify the effectiveness and convenience of the proposed method. The results show that the proposed method can provide essential modeling support for large-scale energy-saving service configurations and energy-efficient MT development.     

Sustainability of ride-hailing services in China’s mobility market: A simulation model of socio-technical system transition

As a symbol of sharing economy, ride-hailing services have spread to Asia, where various forms of services have been established according to the existing socio-technical regimes, including legal, policy, and environmental concerns. China, in particular, has accepted ride-hailing services by revising existing institutions. This study analyzes China’s acceptance of ride-hailing services in the socio-technical system context set up for legacy services. Simulation modeling, combined with transition theory and an agent-based model, is used to analyze the data. This study calculates consumer disutility based on mobility market share, reflecting consumer preference, and predicts the sustainability of ride-hailing services. The simulation results conclude that legalization and socio-technical context are of importance for sustainable mobility.     

Liner services network design and fleet deployment with empty container repositioning

Transportation demand of shipping container fluctuates due to the seasonality of international trade, thus, every 3–6 months, the liner company has to alter its current liner shipping service network, redeploy ships and design cargo routes with the objective of minimizing the total cost. To solve the problem, the paper presents a mixed integer linear program model. The proposed model incorporates several relevant constraints, such as weekly frequency, the transshipment of cargo between two or more service routes, and transport time. Extensive numerical experiments based on realistic date of Asia–Europe–Oceania shipping operations show that the proposed model can solve real-case problems efficiently by CPLEX. The results demonstrate that the model can reduce ship’s capacity consumption and raise ships’ capacity utilization.     

Resource allocation for multi-class services in multipath networks

In multipath networks, multiple paths are available for each pair of source and destination and can be used to carry data packets parallelly. It has been recognized that using multipath could promote the transmission reliability and fault tolerance, and improve the performance of increasingly bandwidth-hungry multi-media applications. In this paper we propose the resource allocation model for multi-class services in multipath networks with the objective of utility maximization, which is an intrinsically difficult problem of nonconvex optimization. We firstly analyze the model for only elastic services and obtain the optimal rate allocation for them. Then we also discuss the model for inelastic services with nonconcave (sigmoidal or discontinuous) utilities which share common links with elastic ones, and obtain some sufficient conditions under which the global optimum for both elastic and inelastic services can be obtained. For the nonconvex optimization problem, we present a heuristic algorithm using Particle Swarm Optimization (PSO), which can lead to improved solutions over existing approaches. Finally, some numerical examples are given to verify the results obtained.     

Designing the framework of technological entrepreneurship ecosystem: A grounded theory approach in the context of Iran

The ecosystem approach, as a comprehensive way of understanding multi-aspect environments, has recently gained so much attention in entrepreneurship and innovation studies. The application of this approach has led to the introduction of the currently available ecosystem frameworks that are dealing with some issues such as infirm structure and heterogeneity of components. In this research, by adopting the grounded theory approach in the context of Iran, we defined a novel and comprehensive framework for the technological entrepreneurship ecosystem (TEE). Twenty-six in-depth and semi-structured interviews have been conducted and analysed through a modified grounded theory procedure. Seventy-four secondary sources were added to the study to expand the breadth of our analysis and reach a stronger saturation. The concluded framework comprised of four interconnected layers representing environmental conditions, entity domains, functional realms, and tech-entrepreneurial agents. In addition, we identified some general principles and rules as important underlying aspects of this framework. The inferred components and structure of this novel framework not only could enable us to design the relations between the ecosystem components, but also prompt and support further research on each dimension of the ecosystem.