Do commercial fishers aggregate around marine reserves? Evidence from Big Creek Marine Ecological Reserve, central California

Marine reserves have been widely touted as a promising strategy for managing fisheries and protecting marine biodiversity. However, their establishment can involve substantial social conflict and may not produce the anticipated biological and economic benefits. A crucial factor associated with the success of marine reserves for enhancing fisheries and protecting biodiversity is the spatial distribution of fishing activity. Fishers may be attracted to the perimeter of a reserve in expectation of spillover of adult fishes. This concentration of effort can reduce spillover of fish to the surrounding fishery and has major implications for the effectiveness of reserves in achieving ecological and socioeconomic goals. We examined the spatial distribution of fishing activity relative to California's Big Creek Marine Ecological Reserve and found no aggregation near the reserve. We discuss the factors driving the spatial distribution of fishing activity relative to the reserve and the relevance of that distribution to the performance and evaluation of marine reserves.

Ecological criteria for evaluating candidate sites for marine reserves

Several schemes have been developed to help select the locations of marine reserves. All of them combine social, economic, and biological criteria, and few offer any guidance as to how to prioritize among the criteria identified. This can imply that the relative weights given to different criteria are unimportant. Where two sites are of equal value ecologically; then socioeconomic criteria should dominate the choice of which should be protected. However, in many cases, socioeconomic criteria are given equal or greater weight than ecological considerations in the choice of sites. This can lead to selection of reserves with little biological value that fail to meet many of the desired objectives. To avoid such a possibility, we develop a series of criteria that allow preliminary evaluation of candidate sites according to their relative biological values in advance of the application of socioeconomic criteria. We include criteria that,. while not strictly biological, have a strong influence on the species present or ecological processes. Out scheme enables sites to be assessed according to their biodiversity, the processes which underpin that diversity, and the processes that support fisheries and provide a spectrum of other services important to people. Criteria that capture biodiversity values include biogeographic representation, habitat representation and heterogeneity, and presence of species or populations of special interest (e.g., threatened species). Criteria that capture sustainability of biodiversity and fishery values include the size of reserves necessary to protect viable habitats, presence of exploitable species, vulnerable life stages, connectivity among reserves, links among ecosystems, and provision of ecosystem services to people. Criteria measuring human and natural threats enable candidate sites to be eliminated from consideration if risks are too great, but also help prioritize among sites where threats can be mitigated by protection. While our criteria can be applied to the design of reserve networks, they also enable choice of single reserves to be made in the context of the attributes of existing protected areas. The overall goal of our scheme is to promote the development of reserve networks that will maintain biodiversity and ecosystem functioning at large scales. The values of eco-system goods and services for people ultimately depend on meeting this objective.

Improving quality-of-service in wireless sensor networks by mitigating “Hidden-Node Collisions”

Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.

H-NAMe: specifying, implementing and testing a hidden-node avoidance mechanism for wireless sensor networks

The hidden-node problem has been shown to be a major source of Quality-of-Service (QoS) degradation in Wireless Sensor Networks (WSNs) due to factors such as the limited communication range of sensor nodes, link asymmetry and the characteristics of the physical environment. In wireless contention-based Medium Access Control protocols, if two nodes that are not visible to each other transmit to a third node that is visible to the formers, there will be a collision – usually called hidden-node or blind collision. This problem greatly affects network throughput, energy-efficiency and message transfer delays, which might be particularly dramatic in large-scale WSNs. This technical report tackles the hidden-node problem in WSNs and proposes HNAMe, a simple yet efficient distributed mechanism to overcome it. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes and then scales to multiple clusters via a cluster grouping strategy that guarantees no transmission interference between overlapping clusters. We also show that the H-NAMe mechanism can be easily applied to the IEEE 802.15.4/ZigBee protocols with only minor add-ons and ensuring backward compatibility with the standard specifications. We demonstrate the feasibility of H-NAMe via an experimental test-bed, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. We believe that the results in this technical report will be quite useful in efficiently enabling IEEE 802.15.4/ZigBee as a WSN protocol.

Diversity in Teams: Source of Conflict or Source of Creativity? Investigating Hidden Mental Models

The workforce in organizations today is becoming increasingly diverse. Consequently the role of diversity management is heavily discussed with respect to the question how diversity influences the productivity of a group. Empirical studies show that on one hand there is a potential for increasing productivity but on the other hand it might be as well that conflicts arise due to the heterogeneity of the group. Usually according empirical studies are based on interviews, questionnaires and/or observations. These methods imply that answers are highly selective and filtered. In order to make the invisible visible, to have access to mental models of team members the paper will present an empirical study on the self-understanding of groups based on an innovative research method, called “mind-scripting”.

H-NAMe: a hidden-node avoidance mechanism for wireless sensor networks

The hidden-node problem has been shown to be a major source of Quality-of-Service (QoS) degradation in Wireless Sensor Networks (WSNs) due to factors such as the limited communication range of sensor nodes, link asymmetry and the characteristics of the physical environment. In wireless contention-based Medium Access Control protocols, if two nodes that are not visible to each other transmit to a third node that is visible to the formers, there will be a collision – usually called hidden-node or blind collision. This problem greatly affects network throughput, energy-efficiency and message transfer delays, which might be particularly dramatic in large-scale WSNs. This paper tackles the hiddennode problem in WSNs and proposes H-NAMe, a simple yet efficient distributed mechanism to overcome it. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes and then scales to multiple clusters via a cluster grouping strategy that guarantees no transmission interference between overlapping clusters. We also show that the H-NAMe mechanism can be easily applied to the IEEE 802.15.4/ZigBee protocols with only minor add-ons and ensuring backward compatibility with the standard specifications. We demonstrate the feasibility of H-NAMe via an experimental test-bed, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. We believe that the results in this paper will be quite useful in efficiently enabling IEEE 802.15.4/ZigBee as a WSN protocol

Collision-free prioritized medium access in the presence of hidden nodes without relying on out-of-band signaling

Consider the problem of sharing a wireless channel between a set of computer nodes. Hidden nodes exist and there is no base station. Each computer node hosts a set of sporadic message streams where a message stream releases messages with real-time deadlines. We propose a collision-free wireless medium access control (MAC) protocol which implements staticpriority scheduling. The MAC protocol allows multiple masters and is fully distributed. It neither relies on synchronized clocks nor out-of-band signaling; it is an adaptation to a wireless channel of the dominance protocol used in the CAN bus. But unlike that protocol, our protocol does not require a node having the ability to receive an incoming bit from the channel while transmitting to the channel. Our protocol has the key feature of not only being prioritized and collision-free but also dealing successfully with hidden nodes. This key feature enables schedulability analysis of sporadic message streams in multihop networks.

Collision-free prioritized medium access control in wireless networks with hidden nodes

We propose a collision-free medium access control (MAC) protocol, which implements static-priority scheduling and works in the presence of hidden nodes. The MAC protocol allows multiple masters and is fully distributed; it is an adaptation to a wireless channel of the dominance protocol used in the CAN bus. But unlike that protocol, our protocol does not require a node having the ability to sense the channel while transmitting to the channel. Our protocol is collision-free even in the presence of hidden nodes and it achieves this without synchronized clocks or out-of-band busy tones. In addition, the protocol is designed to ensure that many non-interfering nodes can transmit in parallel and it functions for both broadcast and unicast transmissions.

Are there hidden scalars in LHC Higgs results?

The Higgs boson recently discovered at the Large Hadron Collider has shown to have couplings to the remaining particles well within what is predicted by the Standard Model. The search for other new heavy scalar states has so far revealed to be fruitless, imposing constraints on the existence of new scalar particles. However, it is still possible that any existing heavy scalars would preferentially decay to final states involving the light Higgs boson thus evading the current LHC bounds on heavy scalar states. Moreover, decays of the heavy scalars could increase the number of light Higgs bosons being produced. Since the number of light Higgs bosons decaying to Standard Model particles is within the predicted range, this could mean that part of the light Higgs bosons could have their origin in heavy scalar decays. This situation would occur if the light Higgs couplings to Standard Model particles were reduced by a concomitant amount. Using a very simple extension of the SM - the two-Higgs doublet model we show that in fact we could already be observing the effect of the heavy scalar states even if all results related to the Higgs are in excellent agreement with the Standard Model predictions.

Integration in MASCEM of the Joint Dispatch of Energy and Reserves Provided by Generation and Demand Resources

The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

The hidden value behind capital structure decisions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.

Small mammal abundances in isolated and non-isolated primary forest reserves near Manaus, Brazil

Abundances of msmall terrestrial mammals were estimated in 10 and 100-ha, isolated and non-isolated primary forest reserves near, Manaus, Brazil between October 1983 and March 1984. The smalt mammal abundance pattern In a 10 ha reserve isolated fan appoximately three years differed significantly from that in othen reserves, primarily due to higher capture rates of Marmosa cinerea, Rhipidomys mastacalis, and Onyzomys paricola in the isolated reserve. Viet type and re-invasion potential may be important factors the small mammal communities in forest patches. Variation the small mammal community among othen reserves was pnimanlty due to variatton In the abundances of Proechimys and 0. capito. At least pant of this vantation was attributable to temporal efects, but variation due to reserve effects also was suggested. Small mammals were much more abundant in the reserves during the present study than in 1982.

Finding the hidden influencers

This thesis is a first step in the search for the characteristics of funders, and the underlying motivation that drives them to participate in crowdfunding. The purpose of the study is to identify demographics and psychographics that influence a funder’s willingness to financially support a crowdfunding project (WFS). Crowdfunding, crowdsourcing and donation literature are combined to create a conceptual model in which age, gender, altruism and income, together with several control variables, are expected to have an influence on a funder’s WFS. Primary data collection was conducted using a survey, and a dataset of 175 potential crowdfunders was created. The data is analysed using a multiple regression and provided several interesting results. First of all, age and gender have a significant effect on WFS, males and young adults until the age of 30 have a higher intention to give money to crowdfunding projects. Second, altruism is significantly positively related to WFS, meaning that the funders do not just care about the potential rewards they could receive, but also about the benefits that they create for the entrepreneur and the people affected by the crowdfunding project. Third, the moderation effect of income was found to be insignificant in this model. It shows that income does not affect the strength of the relationship between the age, gender and altruism, and WFS. This study provides important theoretical contributions by, to the best of my knowledge, being the first study to quantitatively investigate the characteristics of funders and using the funder as the unit of analysis. Moreover, the study provides important insights for entrepreneurs who wish to target the crowd better in order to attract and retain more funders, thereby increasing the chance of success of their project.

An integrated system for human action recognition from video using hidden Markov model

In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.