Infrastructures and productivity: an updated survey

The relationship between infrastructures and productivity has been the subject of an ongoing debate during the last two decades. The available empirical evidence is inconclusive and its interpretation is complicated by econometric problems that have not been fully solved. This paper surveys the relevant literature, focusing on studies that estimate aggregate production functions or growth regressions, and extracts some tentative conclusions. On the whole, my reading of the evidence is that there are sufficient indications that public infrastructure investment contributes significantly to productivity growth, at least for countries where a saturation point has not been reached. The returns to such investment are probably quite high in early stages, when infrastructures are scarce and basic networks have not been completed, but fall sharply thereafter. Hence, appropriate infrastructure provision is probably a key input for development policy, even if it does not hold the key to rapid productivity growth in advanced countries where transportation and communications needs are already adequately served.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Coevolutionary networks: a novel approach to understanding the relationships of humans with the infectious agents

Human organism is interpenetrated by the world of microorganisms, from the conception until the death. This interpenetration involves different levels of interactions between the partners including trophic exchanges, bi-directional cell signaling and gene activation, besides genetic and epigenetic phenomena, and tends towards mutual adaptation and coevolution. Since these processes are critical for the survival of individuals and species, they rely on the existence of a complex organization of adaptive systems aiming at two apparently conflicting purposes: the maintenance of the internal coherence of each partner, and a mutually advantageous coexistence and progressive adaptation between them. Humans possess three adaptive systems: the nervous, the endocrine and the immune system, each internally organized into subsystems functionally connected by intraconnections, to maintain the internal coherence of the system. The three adaptive systems aim at the maintenance of the internal coherence of the organism and are functionally linked by interconnections, in such way that what happens to one is immediately sensed by the others. The different communities of infectious agents that live within the organism are also organized into functional networks. The members of each community are linked by intraconnections, represented by the mutual trophic, metabolic and other influences, while the different infectious communities affect each other through interconnections. Furthermore, by means of its adaptive systems, the organism influences and is influenced by the microbial communities through the existence of transconnections. It is proposed that these highly complex and dynamic networks, involving gene exchange and epigenetic phenomena, represent major coevolutionary forces for humans and microorganisms.

Association between social relationships and survival of Swiss octogenarians. A five-year prospective, population-based study.

BACKGROUND AND AIMS: Data from the literature reveal the contrasting influences of family members and friends on the survival of old adults. On one hand, numerous studies have reported a positive association between social relationships and survival. On the other, ties with children may be associated with an increased risk of disability, whereas ties with friends or other relatives tend to improve survival. A five-year prospective, population-based study of 295 Swiss octogenarians tested the hypothesis that having a spouse, siblings or close friends, and regular contacts with relatives or friends are associated with longer survival, even at a very old age. METHODS: Data were collected through individual interviews, and a Cox regression model was applied to assess the effects of kinship and friendship networks on survival, after adjusting for socio-demographic and health-related variables. RESULTS: Our analyses indicate that the presence of a spouse in the household is not significantly related to survival, whereas the presence of siblings at baseline improves the oldest old's chances of surviving five years later. Moreover, the existence of close friends is a central component in the patterns of social relationships of oldest adults, and one which is significantly associated with survival. Overall, the protective effect of social relationships on survival is more related to the quality of those relationships (close friends) than to the frequency of relationships (regular contacts). CONCLUSIONS: We hypothesize that the existence of siblings or close friends may beneficially affect survival, due to the potential influence on the attitudes of octogenarians regarding health practices and adaptive strategies.

Spiritual Kinship, Political Mobilization and Social Cooperation: a Swiss Alpine valley in the Eighteenth and Nineteenth Centuries

In this chapter I will present some observations and results about Ritual Kinship and political mobilization of popular groups in an Alpine valley: the Val de Bagnes, in the Swiss canton of Valais, - a mountain valley, well known today thanks to the tourist station of Verbier - where we can rely on excellent sources about local families. This region presents a particular political situation, because the 11 major villages of the valley form only one commune, which includes the whole valley.¦There are two major reasons to choose the Val de Bagnes for our inquiry on kinship and social networks in a rural society:¦A. The existence of sharp political and social conflicts during the 18th and the 19th centuries;¦B. The existence of almost systematic genealogical data between 1700 and 1900. (Casanova, Gard, Perrenoud 2005-08)¦The 18th century was characterized by the struggle of an important part of the community of Bagnes against the feudal lord, the abbot of St-Maurice. The culminating point was a local upheaval in 1745 in Le Châble, during which the abbot was forced to sign several documents in accordance with the wishes of the rebels (Guzzi-Heeb 2007). In the 19th century feudal lordship was abolished, but now the struggle confronted a liberal-radical faction and the conservative majority in the commune.¦The starting point of my presentation focuses on this question: which role did spiritual kinship play in the political mobilization of popular groups and in the organization of competing factions? This question allows us to shed light on some utilizations and meanings of spiritual kinship in the local society. Was spiritual kinship a significant instrument for economic cooperation? Or was it a channel for privileged social contacts and transactions?

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

Adaption of Courses and Learning Environment to the User Context in dotLRN

The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time

Airline Consolidation and the Distribution of Traffic between Primary and Secondary Hubs

Several airline consolidation events have recently been completed both in Europe and in the United States. The model we develop considers two airlines operating hub-and-spoke networks, using different hubs to connect the same spoke airports. We assume the airlines to be vertically differentiated, which allows us to distinguish between primary and secondary hubs. We conclude that this differentiation in air services becomes more accentuated after consolidation, with an increased number of flights being channeled through the primary hub. However, congestion can act as a brake on the concentration of flight frequency in the primary hub following consolidation. Our empirical application involves an analysis of Delta s network following its merger with Northwest. We find evidence consistent with an increase in the importance of Delta s primary hubs at the expense of its secondary airports. We also find some evidence suggesting that the carrier chooses to divert traffic away from those hub airports that were more prone to delays prior to the merger, in particular New York s JFK airport. Keywords: primary hub; secondary hub; airport congestion; airline consolidation; airline networks JEL Classi fication Numbers: D43; L13; L40; L93; R4

The hotel industry and its importance in the technical and economic development of a region : the Lake Geneva case (1852-1914)

The historiography dedicated to tourism has emphasised how some socio-economic evolutions such as urbanisation, mechanisation of transport or the advent of leisure time in society have supported pleasure trips and therefore the development of the hotel industry. On the contrary, the research has too often neglected or at least minimised the impact of the hotel sector on a region's development. This contribution seeks to fill this gap by analysing the Geneva Lake region, one of the most important birthplaces of the European tourism. In this space not much touched by the first industrial revolution, the hotel business has in fact played the role of an economic motor, stimulating investment and employment. This dynamism provoked a domino effect on several other sectors of the economy (industry, bulding sector, banking). To please their customers, the hoteliers have not only given impulses on housing modernisation, but also to the revitalisation of transport, energy and communication networks. The necessity to remain on the state-of-the-art of technical issues, with the concern of competitiveness, has called forth an acceleration of the technology transfer and stimulated the constitution of technical know-how.

Information security and the enforcement of secrecy : the practical application of quantum key distribution

There is no doubt about the necessity of protecting digital communication: Citizens are entrusting their most confidential and sensitive data to digital processing and communication, and so do governments, corporations, and armed forces. Digital communication networks are also an integral component of many critical infrastructures we are seriously depending on in our daily lives. Transportation services, financial services, energy grids, food production and distribution networks are only a few examples of such infrastructures. Protecting digital communication means protecting confidentiality and integrity by encrypting and authenticating its contents. But most digital communication is not secure today. Nevertheless, some of the most ardent problems could be solved with a more stringent use of current cryptographic technologies. Quite surprisingly, a new cryptographic primitive emerges from the ap-plication of quantum mechanics to information and communication theory: Quantum Key Distribution. QKD is difficult to understand, it is complex, technically challenging, and costly-yet it enables two parties to share a secret key for use in any subsequent cryptographic task, with an unprecedented long-term security. It is disputed, whether technically and economically fea-sible applications can be found. Our vision is, that despite technical difficulty and inherent limitations, Quantum Key Distribution has a great potential and fits well with other cryptographic primitives, enabling the development of highly secure new applications and services. In this thesis we take a structured approach to analyze the practical applicability of QKD and display several use cases of different complexity, for which it can be a technology of choice, either because of its unique forward security features, or because of its practicability.

Legitimacy and Accountability of Independent Regulatory Agencies: A Critical Review

This article reviews the literature that deals with the problem of legitimizing regulatory governance, with a special attention to the question of the accountability of independent regulatory agencies. The discussion begins with the presentation of the traditional arguments concerning the democratic deficit of the regulatory state. The positive evaluation of regulatory performance by citizens is presented as an alternative source of legitimacy. It follows the discussion of the existing approaches to make agencies accountable, so as to ensure the procedural legitimacy of regulatory governance. Some insights concerning new forms of accountability are offered in the last section, namely with reference to the establishment and ongoing consolidation of formal and informal networks of regulators.

Synchronizability of EEG-Based Functional Networks in Early Alzheimer's Disease.

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.