Valuing a Natura 2000 network site to inform land use options using a discrete choice experiment: An illustration from the Basque Country

One of the main problems that public institutions face in the management of protected areas, such as the European Natura 2000 network, is determining how to design and implement sustainable management plans that account for the wide range of marketed and non-marketed benefits they provide to society. This paper presents an application of a stated preference valuation approach aimed at evaluating the social preferences of the population of the Basque Country, Spain, for the key attributes of a regional Natura 2000 network site. According to our results, individuals’ willingness-to-pay (WTP) is higher for attributes associated with non-use values (native tree species and biodiversity conservation) than for attributes associated with use values (agricultural development and commercial forestry). The paper concludes that management policies related to Natura 2000 network sites should account for both for the importance of non-use values and the heterogeneity of the population's preferences in order to minimize potential land use conflicts.

The development of the South Carolina Coastal Information Network and portal site: Bringing training opportunities and educational resources to coastal community officials and the public

The South Carolina Coastal Information Network (SCCIN) emerged as a result of a number of coastal outreach institutions working in partnership to enhance coordination of the coastal community outreach efforts in South Carolina. This organized effort, led by the S.C. Sea Grant Consortium and its Extension Program, includes partners from federal and state agencies, regional government agencies, and private organizations seeking to coordinate and/or jointly deliver outreach programs that target coastal community constituents. The Network was officially formed in 2006 with the original intention of fostering intra-and inter- agency communication, coordination, and cooperation. Network partners include the S.C. Sea Grant Consortium, S.C. Department of Health and Environmental Control – Office of Ocean and Coastal Resource Management and Bureau of Water, S.C. Department of Natural Resources – ACE Basin National Estuarine Research Reserve, North Inlet-Winyah Bay National Estuarine Research Reserve, Clemson University Cooperative Extension Service and Carolina Clear, Berkeley-Charleston-Dorchester Council of Governments, Waccamaw Regional Council of Governments, Urban Land Institute of South Carolina, S.C. Department of Archives and History, the National Oceanic and Atmospheric Administration – Coastal Services Center and Hollings Marine Laboratory, Michaux Conservancy, Ashley-Cooper Stormwater Education Consortium, the Coastal Waccamaw Stormwater Education Consortium, the S.C. Chapter of the U.S. Green Building Council, and the Lowcountry Council of Governments. (PDF contains 3 pages)

Entrepreneurship in the University of the Basque Country (UPV/EHU)

Currently entrepreneurship is a basic pillar in the socioeconomic area of any country since it contributes to attain the government objectives of job creation and boost of dynamism and competitiveness of the business network. These aspects are even more crucial nowadays due to the global economic crisis. This paper attempts to provide some new insights about the scientific field entrepreneurship in the Basque Country analyzing some aspects related to the entrepreneurial activity, the profile of the entrepreneur and the characteristics of the entrepreneurial businesses. It also aims to provide empirical evidence that proves the good features of the spin-offs and TBF groups as job creators, technology transferors to the society and important actors in the growth and development of the economies for both the business network and its surrounding society. To this aim, a descriptive study has been performed of the firms belonging to the Zitek Program of Bizkaia Campus of the University of the Basque Country (UPV/EHU).

Linking elements of the Integrated Ocean Observing System (IOOS) with the planned National Water Quality Monitoring Network. Proceedings from the NOAA-Supported workshop 19-21 September 2005

The National Oceanic and Atmospheric Administration (NOAA), in cooperation with the New Jersey Marine Sciences Consortium (NJMSC), hosted a workshop at Rutgers University on 19-21 September 2005 to explore ways to link the U.S. Integrated Ocean Observing System (IOOS) to the emerging infrastructure of the National Water Quality Monitoring Network (NWQMN). Participating partners included the Mid-Atlantic Coastal Ocean Observing Regional Association, U.S. Geological Survey, Rutgers University Coastal Ocean Observing Laboratory, and the New Jersey Sea Grant College. The workshop was designed to highlight the importance of ecological and human health linkages in the movement of materials, nutrients, organisms and contaminants along the Delaware Bay watershed-estuary-coastal waters gradient (hereinafter, the “Delaware Bay Ecosystem [DBE]”), and to address specific water quality issues in the mid-Atlantic region, especially the area comprising the Delaware River drainage and near-shore waters. Attendees included federal, state and municipal officials, coastal managers, members of academic and research institutions, and industry representatives. The primary goal of the effort was to identify key management issues and related scientific questions that could be addressed by a comprehensive IOOS-NWQMN infrastructure (US Commission on Ocean Policy 2004; U.S. Ocean Action Plan 2004). At a minimum, cooperative efforts among the three federal agencies (NOAA, USGS and EPA) involved in water quality monitoring were required. Further and recommended by the U.S. Commission on Ocean Policy, outreach to states, regional organizations, and tribes was necessary to develop an efficient system of data gathering, quality assurance and quality control protocols, product development, and information dissemination.

Report of 2009 Bottlenose Dolphin (Tursiops truncatus) Life History Workshop: expanding network capabilities

The Virginia Aquarium & Marine Science Center Foundation’s Stranding Response Program (VAQS) was awarded a grant in 2008 to conduct life history analysis on over 10 years of Tursiops truncatus teeth and gonad samples from stranded animals in Virginia. A major part of this collaborative grant included a workshop involving life historians from Hubbs-Sea World Research Institute (HSWRI), NOS, Texas A & M University (TAMU), and University of North Carolina Wilmington (UNCW). The workshop was held at the NOAA Center for Coastal Environmental Health & Biomolecular Research in Charleston, SC on 7-9 July 2009. The workshop convened to 1) address current practices among the groups conducting life history analysis, 2) decide on protocols to follow for the collaborative Prescott grant between VAQS and HSWRI, 3) demonstrate tissue preparation techniques and discuss shortcuts and pitfalls, 4) demonstrate data collection from prepared testes, ovaries, and teeth, and 5) discuss data analysis and prepare an outline and timeline for a future manuscript. The workshop concluded with discussions concerning the current collaborative Tursiops Life History Prescott grant award and the beginnings of a collaborative Prescott proposal with members of the Alliance of Marine Mammal Parks and Aquariums to further clarify reproductive analyses. This technical memorandum serves as a record of this workshop.

State estimation over a communication network: Measurement or estimate communication?

In this paper we consider the problem of state estimation over a communication network. Using estimation quality as a metric, two communication schemes are studied and compared. In scheme one, each sensor node communicates its measurement data to the remote estimator, while in scheme two, each sensor node communicates its local state estimate to the remote estimator. We show that with perfect communication link, if the sensor has unlimited computation capability, the two schemes produce the same estimate at the estimator, and if the sensor has limited computation capability, scheme one is always better than scheme two. On the other hand, when data packet drops occur over the communication link, we show that if the sensor has unlimited computation capability, scheme two always outperforms scheme one, and if the sensor has limited computation capability, we show that in general there exists a critical packet arrival rate, above which scheme one outperforms scheme two. Simulations are provided to demonstrate the two schemes under various circumstances. © South China University of Technology and Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg 2010.

Improving bilingual higher education: Training university professors in content and language integrated learning

With increasing international mobility, higher education must cater to the varying linguistic and cultural needs of students. Successful delivery of courses through English as the vehicular language is essential to encourage international enrollment. However, this cannot be achieved without preparing university professors in the many intricacies delivering their subjects in English may pose. This paper aims to: share preliminary data concerning Content and Language Integrated Learning (CLIL) at Laureate Network Universities worldwide as few studies have been conducted at the tertiary level, reflect upon data regarding student and teacher satisfaction with CLIL at the Universidad Europea de Madrid (UEM), and to propose improvements in English-taught subjects.

The function of the self-attention network

This commentary links Humphrey and Sui’s proposed Self-attention Network (SAN) to the memory advantage associated with self-relevant information (i.e., the self-reference effect). Articulating this link elucidates the functional quality of the SAN in ensuring that information of potential importance to self is not lost. This adaptive system for self-processing mirrors the cognitive response to threat stimuli, which also elicit attentional biases and produce characteristically enhanced, episodic representations in memory. Understanding the link between the SAN and memory is key to comprehending more broadly the operation of the self in cognition.

Using Warp to Control Network Contention in Mermera

Parallel computing on a network of workstations can saturate the communication network, leading to excessive message delays and consequently poor application performance. We examine empirically the consequences of integrating a flow control protocol, called Warp control [Par93], into Mermera, a software shared memory system that supports parallel computing on distributed systems [HS93]. For an asynchronous iterative program that solves a system of linear equations, our measurements show that Warp succeeds in stabilizing the network's behavior even under high levels of contention. As a result, the application achieves a higher effective communication throughput, and a reduced completion time. In some cases, however, Warp control does not achieve the performance attainable by fixed size buffering when using a statically optimal buffer size. Our use of Warp to regulate the allocation of network bandwidth emphasizes the possibility for integrating it with the allocation of other resources, such as CPU cycles and disk bandwidth, so as to optimize overall system throughput, and enable fully-shared execution of parallel programs.

On the Convergence of Statistical Techniques for Inferring Network Traffic Demands

Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study strategies to improve the convergence of a powerful statistical technique based on an Expectation-Maximization iterative algorithm. First we analyze modeling approaches to generating starting points. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we study the convergence characteristics of our EM algorithm and compare it against a recently proposed Weighted Least Squares approach.

How Well Can TCP Infer Network State?

The Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. We ask a fundamental question: What is the basic predictive power of TCP of network state, including wireless error conditions? The goal is to improve or readily exploit this predictive power to enable TCP (or variants) to perform well in generalized network settings. To that end, we use Maximum Likelihood Ratio tests to evaluate TCP as a detector/estimator. We quantify how well network state can be estimated, given network response such as distributions of packet delays or TCP throughput that are conditioned on the type of packet loss. Using our model-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient detector can be built; distributions of network loads can provide effective means for estimating packet loss type; and packet delay is a better signal of network state than short-term throughput. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect estimation.