Public-Private Partnerships in the Water Sector

Abstract

Types of partnerships between public and private companies in water and sewage services are evaluated on the basis of the economic efficiency of the scheme for each partner. Modeling of public-private partnerships involves the formulation of a contract prototype, which determines the roles, functions, and responsibilities as well as the allocation of costs and revenues for each partner. Alternative water management scenarios are used to identify the investments required for meeting the projected demand for water and sewage services. Investment and operational costs as well as revenues from water and sewage services are estimated according to the allocation defined in the contract prototype. The economic efficiency of the scheme is assessed through a cost benefit analysis for each partner. The evaluation of different water management scenarios indicates that, for the Cyclades Islands, Greece, there is a substantial water market where several forms of partnerships could be attractive for both the public and the private sectors. Such partnerships include, among others, lease purchase, temporary privatization, built operate transfer (BOT), and built own operate transfer (BOOT). These forms of public-private partnerships could also be successful in similar regions where significant improvements and expansion of the infrastructure is required while access to the required funds and expertise is restricted for small public water companies.     

Improving the performance of passive network monitoring applications with memory locality enhancements

Passive network monitoring is the basis for a multitude of systems that support the robust, efficient, and secure operation of modern computer networks. Emerging network monitoring applications are more demanding in terms of memory and CPU resources due to the increasingly complex analysis operations that are performed on the inspected traffic. At the same time, as the traffic throughput in modern network links increases, the CPU time that can be devoted for processing each network packet decreases. This leads to a growing demand for more efficient passive network monitoring systems in which runtime performance becomes a critical issue.In this paper we present locality buffering, a novel approach for improving the runtime performance of a large class of CPU and memory intensive passive monitoring applications, such as intrusion detection systems, traffic characterization applications, and NetFlow export probes. Using locality buffering, captured packets are being reordered by clustering packets with the same port number before they are delivered to the monitoring application. This results in improved code and data locality, and consequently, in an overall increase in the packet processing throughput and decrease in the packet loss rate. We have implemented locality buffering within the widely used libpcap packet capturing library, which allows existing monitoring applications to transparently benefit from the reordered packet stream without modifications. Our experimental evaluation shows that locality buffering improves significantly the performance of popular applications, such as the Snort IDS, which exhibits a 21% increase in the packet processing throughput and is able to handle 67% higher traffic rates without dropping any packets.     

Maintaining Privacy on a Line

Consider a situation where people have to choose among a sequence of n linearly ordered positions to perform some task requiring a certain amount of privacy. Which position should one choose so as to maximize one’s privacy, i.e., minimize the chances that one of your neighboring positions becomes occupied by a later arrival? In this paper, we attempt to answer this question under a variety of models for the behavior of the later arrivals. Our results suggest that for the most part one should probably choose one of the extreme positions (with some interesting exceptions). We also suggest a number of variations on the problem that lead to many open problems.     

Gene Discovery in Gelsemium Highlights Conserved Gene Clusters in Monoterpene Indole Alkaloid Biosynthesis

Genome mining is a routine technique in microbes for discovering biosynthetic pathways. In plants, however, genomic information is not commonly used to identify novel biosynthesis genes. Here, we present the genome of the medicinal plant and oxindole monoterpene indole alkaloid (MIA) producer Gelsemium sempervirens (Gelsemiaceae). A gene cluster from Catharanthus roseus, which is utilized at least six enzymatic steps downstream from the last common intermediate shared between the two plant alkaloid types, is found in G. sempervirens, although the corresponding enzymes act on entirely different substrates. This study provides insights into the common genomic context of MIA pathways and is an important milestone in the further elucidation of the Gelsemium oxindole alkaloid pathway.     

Reconstructing experiences with iScale

We present iScale, a survey tool for the retrospective elicitation of longitudinal user experience data. iScale aims to minimize retrospection bias and employs graphing to impose a process during the reconstruction of one's experiences. Two versions, the constructive and the value-account iScale, were motivated by two distinct theories on how people reconstruct emotional experiences from memory. These two versions were tested in two separate studies. Study 1 aimed at providing qualitative insight into the use of iScale and compared its performance to that of free-hand graphing. Study 2 compared the two versions of iScale to free recall, a control condition that does not impose structure on the reconstruction process. Overall, iScale resulted in an increase in the amount, the richness, and the test–retest consistency of recalled information as compared to free recall. These results provide support for the viability of retrospective techniques as a cost-effective alternative to longitudinal studies.     

Numerical simulation of particulate processes for control and estimation by spectral methods

Results of application of pseudospectral methods, also known as spectral collocation methods, to practical particulate processes including growth, nucleation, aggregation, and breakage are presented. For growth‐dominated processes, a considerable reduction in model dimension can be achieved; for pure aggregation and breakage they form a viable option. To handle problems that include aggregation, breakage, and growth phenomena simultaneously, we introduce a hybrid algorithm combining the advantages of spectral methods and cell average or fixed pivot methods for aggregation and breakage. Results are shown for analytical examples as well as real processes taken from the fields of granulation and crystallization. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2309–2319, 2012     

Climate change: the views of forestry students in a Greek university

The trend to global warming is one of the most important problems of our time. This paper reports the findings of self‐management questionnaires, in regard to views held on the issue of climate change by the students of the Department of Forestry and Management of the Environment and Natural Resources of the Democritus University of Thrace.     

A study on natural clinoptilolite for CO2/N2 gas separation

Based on its low cost and low water adsorption capacity, compared to synthetic zeolites (A-type, X-type and Y-type), natural, untreated clinoptilolite was examined as a potential adsorbent for a separation process targeting on removal of CO₂ from flue gas. Taking into consideration typical flue gas composition and temperature, adsorptive properties of binary CO₂/N₂ mixtures were tested in the temperature range of 268 to 403 K and compared with literature data. The results showed that CO₂ concentration, total pressure, and temperature strongly affect selectivity and working capacity, restricting the conditions under which the material could be used as an efficient adsorbent.