Context dependency of trait repeatability and its relevance for management and conservation of fish populations

Repeatability of behavioural and physiological traits is increasingly a focus for animal researchers, for which fish have become important models. Almost all of this work has been done in the context of evolutionary ecology, with few explicit attempts to apply repeatability and context dependency of trait variation toward understanding conservation-related issues. Here, we review work examining the degree to which repeatability of traits (such as boldness, swimming performance, metabolic rate and stress responsiveness) is context dependent. We review methods for quantifying repeatability (distinguishing between within-context and across-context repeatability) and confounding factors that may be especially problematic when attempting to measure repeatability in wild fish. Environmental factors such temperature, food availability, oxygen availability, hypercapnia, flow regime and pollutants all appear to alter trait repeatability in fishes. This suggests that anthropogenic environmental change could alter evolutionary trajectories by changing which individuals achieve the greatest fitness in a given set of conditions. Gaining a greater understanding of these effects will be crucial for our ability to forecast the effects of gradual environmental change, such as climate change and ocean acidification, the study of which is currently limited by our ability to examine trait changes over relatively short time scales. Also discussed are situations in which recent advances in technologies associated with electronic tags (biotelemetry and biologging) and respirometry will help to facilitate increased quantification of repeatability for physiological and integrative traits, which so far lag behind measures of repeatability of behavioural traits.

Genetic Diversity of Oilseed Rape Fields and Feral Populations in the Context of Coexistence with GM Crops

Despite growing concern about transgenes escaping from fields, few studies have analysed the genetic diversity of crops in an agroecosystem over several years. Accurate information about the dynamics and relationship of the genetic diversity of crops in an agroecosystem is essential for risk assessment and policies concerning the containment of genetically modified crops and their coexistence with crops grown by conventional practices. Here, we analysed the genetic diversity of oilseed rape plants from fields and feral populations over 4 years in an agricultural landscape of 41 km2. We used exact compatibility and maximum likelihood assignment methods to assign these plants to cultivars. Even pure lines and hybrid cultivar seed lots contained several genotypes. The cultivar diversity in fields reflected the conventional view of agroecosystems quite well: that is, there was a succession of cultivars, some grown for longer than others because of their good performance, some used for one year and then abandoned, and others gradually adopted. Three types of field emerged: fields sown with a single cultivar, fields sown with two cultivars, and unassigned fields (too many cultivars or unassigned plants to reliably assign the field). Field plant diversity was higher than expected, indicating the persistence of cultivars that were grown for only one year. The cultivar composition of feral populations was similar to that of field plants, with an increasing number of cultivars each year. By using genetic tools, we found a link between the cultivars of field plants in a particular year and the cultivars of feral population plants in the following year. Feral populations on road verges were more diverse than those on path verges. All of these findings are discussed in terms of their consequences in the context of coexistence with genetically modified crops.

Collaborative Management of Intermodal Mobility

Part 21: Mobility and Logistics

Strategic Context, Organizational Features and Network Performances: A Survey on Collaborative Networked Organizations of Italian SMEs

Part 15: Performance Management Frameworks

Adaptive Sampling with Mobile Sensor Networks

Mobile sensor networks have unique advantages compared with wireless sensor networks. The mobility enables mobile sensors to flexibly reconfigure themselves to meet sensing requirements. In this dissertation, an adaptive sampling method for mobile sensor networks is presented. Based on the consideration of sensing resource constraints, computing abilities, and onboard energy limitations, the adaptive sampling method follows a down sampling scheme, which could reduce the total number of measurements, and lower sampling cost. Compressive sensing is a recently developed down sampling method, using a small number of randomly distributed measurements for signal reconstruction. However, original signals cannot be reconstructed using condensed measurements, as addressed by Shannon Sampling Theory. Measurements have to be processed under a sparse domain, and convex optimization methods should be applied to reconstruct original signals. Restricted isometry property would guarantee signals can be recovered with little information loss. While compressive sensing could effectively lower sampling cost, signal reconstruction is still a great research challenge. Compressive sensing always collects random measurements, whose information amount cannot be determined in prior. If each measurement is optimized as the most informative measurement, the reconstruction performance can perform much better. Based on the above consideration, this dissertation is focusing on an adaptive sampling approach, which could find the most informative measurements in unknown environments and reconstruct original signals. With mobile sensors, measurements are collect sequentially, giving the chance to uniquely optimize each of them. When mobile sensors are about to collect a new measurement from the surrounding environments, existing information is shared among networked sensors so that each sensor would have a global view of the entire environment. Shared information is analyzed under Haar Wavelet domain, under which most nature signals appear sparse, to infer a model of the environments. The most informative measurements can be determined by optimizing model parameters. As a result, all the measurements collected by the mobile sensor network are the most informative measurements given existing information, and a perfect reconstruction would be expected. To present the adaptive sampling method, a series of research issues will be addressed, including measurement evaluation and collection, mobile network establishment, data fusion, sensor motion, signal reconstruction, etc. Two dimensional scalar field will be reconstructed using the method proposed. Both single mobile sensors and mobile sensor networks will be deployed in the environment, and reconstruction performance of both will be compared.In addition, a particular mobile sensor, a quadrotor UAV is developed, so that the adaptive sampling method can be used in three dimensional scenarios.

Hybrid Power System Intelligent Operation and Protection Involving Distributed Architectures and Pulsed Loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Inclusion in an age of mobility

Learning with mobiles in UK universities is not new and is not novel. It is, in fact, at least 10 years old, well-documented and comparable to activity in universities elsewhere in Western Europe, America and Asia Pacific. Continued and dramatic changes in the ownership, access and expectations of mobiles amongst university students and equally across UK society have suddenly propelled learning with mobiles to centre-stage as a feasible proposition but, it is now argued, only if students can bring-your-own-device. This has already catalysed discussion about authority, agency and control within university settings but the equally significant and profound implications for the inclusion agenda have not been articulated. This paper begins that process. A theoretical framework for social inclusion in this context is considered, identified and discussed. The paper reviews the progress and problems of the substantial and unique programme of mobile learning across UK higher education since 2000 in relation to its stance on inclusion, where this is apparent. These are all well-documented in academic and official sources; the paper does however also draw on the author's involvement in many of the events and initiatives. The paper raises however significant questions about this programme's meaning and direction in a world where now there is more, better, cheaper, faster, newer but different digital technology in the hands of students, potential students and everyone else than there is routinely in the educational institutions themselves. This digital technology, mobile technology, now allows learners to create, own, transform, discuss, discard, share, store and broadcast ideas, opinions, images and information, and to create and transform identities and communities. The paper argues that this epistemological revolution may mean that universities and colleges are no longer credible and authoritative gatekeepers to knowledge and its technologies and so the meaning and relevance of inclusion are much less clear. The paper proposes a new stance on inclusion.

Distributed optimization and games over networks: a system theoretical perspective

Several decision and control tasks involve networks of cyber-physical systems that need to be coordinated and controlled according to a fully-distributed paradigm involving only local communications without any central unit. This thesis focuses on distributed optimization and games over networks from a system theoretical perspective. In the addressed frameworks, we consider agents communicating only with neighbors and running distributed algorithms with optimization-oriented goals. The distinctive feature of this thesis is to interpret these algorithms as dynamical systems and, thus, to resort to powerful system theoretical tools for both their analysis and design. We first address the so-called consensus optimization setup. In this context, we provide an original system theoretical analysis of the well-known Gradient Tracking algorithm in the general case of nonconvex objective functions. Then, inspired by this method, we provide and study a series of extensions to improve the performance and to deal with more challenging settings like, e.g., the derivative-free framework or the online one. Subsequently, we tackle the recently emerged framework named distributed aggregative optimization. For this setup, we develop and analyze novel schemes to handle (i) online instances of the problem, (ii) ``personalized'' optimization frameworks, and (iii) feedback optimization settings. Finally, we adopt a system theoretical approach to address aggregative games over networks both in the presence or absence of linear coupling constraints among the decision variables of the players. In this context, we design and inspect novel fully-distributed algorithms, based on tracking mechanisms, that outperform state-of-the-art methods in finding the Nash equilibrium of the game.

Distributed ledger technologies between anonymity and transparency: AML/CFT regulation of cryptocurrency ecosystems in the EU

The advent of Bitcoin suggested a disintermediated economy in which Internet users can take part directly. The conceptual disruption brought about by this Internet of Money (IoM) mirrors the cross-industry impacts of blockchain and distributed ledger technologies (DLTs). While related instances of non-centralisation thwart regulatory efforts to establish accountability, in the financial domain further challenges arise from the presence in the IoM of two seemingly opposing traits: anonymity and transparency. Indeed, DLTs are often described as architecturally transparent, but the perceived level of anonymity of cryptocurrency transfers fuels fears of illicit exploitation. This is a primary concern for the framework to prevent money laundering and the financing of terrorism and proliferation (AML/CFT/CPF), and a top priority both globally and at the EU level. Nevertheless, the anonymous and transparent features of the IoM are far from clear-cut, and the same is true for its levels of disintermediation and non-centralisation. Almost fifteen years after the first Bitcoin transaction, the IoM today comprises a diverse set of socio-technical ecosystems. Building on an analysis of their phenomenology, this dissertation shows how there is more to their traits of anonymity and transparency than it may seem, and how these features range across a spectrum of combinations and degrees. In this context, trade-offs can be evaluated by referring to techno-legal benchmarks, established through socio-technical assessments grounded on teleological interpretation. Against this backdrop, this work provides framework-level recommendations for the EU to respond to the twofold nature of the IoM legitimately and effectively. The methodology cherishes the mutual interaction between regulation and technology when drafting regulation whose compliance can be eased by design. This approach mitigates the risk of overfitting in a fast-changing environment, while acknowledging specificities in compliance with the risk-based approach that sits at the core of the AML/CFT/CPF regime.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.

6G enabled IoV scenarios with distributed intelligence mechanisms

The Internet of Vehicles (IoV) paradigm has emerged in recent times, where with the support of technologies like the Internet of Things and V2X , Vehicular Users (VUs) can access different services through internet connectivity. With the support of 6G technology, the IoV paradigm will evolve further and converge into a fully connected and intelligent vehicular system. However, this brings new challenges over dynamic and resource-constrained vehicular systems, and advanced solutions are demanded. This dissertation analyzes the future 6G enabled IoV systems demands, corresponding challenges, and provides various solutions to address them. The vehicular services and application requests demands proper data processing solutions with the support of distributed computing environments such as Vehicular Edge Computing (VEC). While analyzing the performance of VEC systems it is important to take into account the limited resources, coverage, and vehicular mobility into account. Recently, Non terrestrial Networks (NTN) have gained huge popularity for boosting the coverage and capacity of terrestrial wireless networks. Integrating such NTN facilities into the terrestrial VEC system can address the above mentioned challenges. Additionally, such integrated Terrestrial and Non-terrestrial networks (T-NTN) can also be considered to provide advanced intelligent solutions with the support of the edge intelligence paradigm. In this dissertation, we proposed an edge computing-enabled joint T-NTN-based vehicular system architecture to serve VUs. Next, we analyze the terrestrial VEC systems performance for VUs data processing problems and propose solutions to improve the performance in terms of latency and energy costs. Next, we extend the scenario toward the joint T-NTN system and address the problem of distributed data processing through ML-based solutions. We also proposed advanced distributed learning frameworks with the support of a joint T-NTN framework with edge computing facilities. In the end, proper conclusive remarks and several future directions are provided for the proposed solutions.

Understanding Red Blood Cell Parameters In The Context Of The Frailty Phenotype: Interpretations Of The Fibra (frailty In Brazilian Seniors) Study.

Frailty and anemia in the elderly appear to share a common pathophysiology associated with chronic inflammatory processes. This study uses an analytical, cross-sectional, population-based methodology to investigate the probable relationships between frailty, red blood cell parameters and inflammatory markers in 255 community-dwelling elders aged 65 years or older. The frailty phenotype was assessed by non-intentional weight loss, fatigue, low grip strength, low energy expenditure and reduced gait speed. Blood sample analyses were performed to determine hemoglobin level, hematocrit and reticulocyte count, as well as the inflammatory variables IL-6, IL-1ra and hsCRP. In the first multivariate analysis (model I), considering only the erythroid parameters, Hb concentration was a significant variable for both general frailty status and weight loss: a 1.0g/dL drop in serum Hb concentration represented a 2.02-fold increase (CI 1.12-3.63) in an individual's chance of being frail. In the second analysis (model II), which also included inflammatory cytokine levels, hsCRP was independently selected as a significant variable. Each additional year of age represented a 1.21-fold increase in the chance of being frail, and each 1-unit increase in serum hsCRP represented a 3.64-fold increase in the chance of having the frailty phenotype. In model II reticulocyte counts were associated with weight loss and reduced metabolic expenditure criteria. Our findings suggest that reduced Hb concentration, reduced RetAbs count and elevated serum hsCRP levels should be considered components of frailty, which in turn is correlated with sarcopenia, as evidenced by weight loss.

[strategies For Integration Of Health Care Practices And Sanitary Surveillance In The Context Of The Implementation Of Rede Cegonha - A Brazilian Mother And Infant Health Care Network].

Mother and infant mortality has been the scope of analysis throughout the history of public health in Brazil and various strategies to tackle the issue have been proposed to date. The Ministry of Health has been working on this and the Rede Cegonha strategy is the most recent policy in this context. Given the principle of comprehensive health care and the structure of the Unified Health System in care networks, it is necessary to ensure the integration of health care practices, among which are the sanitary surveillance actions (SSA). Considering that the integration of health care practices and SSA can contribute to reduce mother and infant mortality rates, this article is a result of qualitative research that analyzed the integration of these actions in four cities in the State of São Paulo/Brazil: Campinas, Indaiatuba, Jaguariúna and Santa Bárbara D'Oeste. The research was conducted through interviews with SSA and maternal health managers, and the data were evaluated using thematic analysis. The results converge with other studies, identifying the isolation of health care practices and SSA. The insertion of SSA in collectively-managed areas appears to be a potential strategy for health planning and implementation of actions in the context under scrutiny.

Saude coletiva e aptdão fisica de escolares de segundo grau : estudo a partis do Colegio Tecnico Industrial - UNESP, Bauru

Universidade Estadual de Campinas . Faculdade de Educação Física

Projeto Sol Morumbi - Paulinia : as lembranças da infancia e adolescencia pelos caminhos da Educação Fisica

Universidade Estadual de Campinas . Faculdade de Educação Fisica