2,4,6‐Trichlorophenol and phenol removal in methanogenic and partially‐aerated methanogenic conditions in a fluidized bed bioreactor

A fluidized bed bioreactor (FBBR) was operated for more than 575 days to remove 2,4,6‐trichlorophenol (TCP) and phenol (Phe) from a synthetic toxic wastewater containing 80 mg L^?1 of TCP and 20 mg L^?1 of Phe under two regimes: Methanogenic (M) and Partially‐Aerated Methanogenic (PAM). The mesophilic, laboratory‐scale FBBR consisted of a glass column (3 L capacity) loaded with 1 L of 1 mm diameter granular activated carbon colonized by an anaerobic consortium. Sucrose (1 g COD L^?1) was used as co‐substrate in the two conditions. The hydraulic residence time was kept constant at 1 day. Both conditions showed similar TCP and Phe removal (99.9 + %); nevertheless, in the Methanogenic regime, the accumulation of 4‐chlorophenol (4CP) up to 16 mg L^?1 and phenol up to 4 mg L^?1 was observed, whereas in PAM conditions 4CP and other intermediates were not detected. The specific methanogenic activity of biomass decreased from 1.01 ± 0.14 in M conditions to 0.19 ± 0.06 mmolCH₄ h^?1 gTKN^?1 in PAM conditions whereas the specific oxygen uptake rate increased from 0.039 ± 0.008 in M conditions to 0.054 ± 0.012 mmolO₂ h^?1 gTKN^?1, which suggested the co‐existence of both methanogenic archaea and aerobic bacteria in the undefined consortium. The advantage of the PAM condition over the M regime is that it provides for the thorough removal of less‐substituted chlorophenols produced by the reductive dehalogenation of TCP rather than the removal of the parent compound itself. Copyright © 2005 Society of Chemical Industry     

Close phenotypic and functional similarities between human and murine alphabeta T cells expressing invariant TCR alpha-chains

Several studies have demonstrated the existence of a murine NK1.1+ alphabeta T cell subset expressing V alpha14+ TCR alpha-chains with highly conserved invariant junctional sequences and able to secrete Th2 cytokines when exposed to CD1+ stimulator cells. In humans, alphabeta T cells carrying invariant V alpha24+ TCR alpha-chains highly homologous to those expressed by murine NK1.1 cells have been recently described. Here we show that these cells (referred to as V alpha24inv T cells) and murine NK1.1+ alphabeta T cells resemble each other in several ways. First, like their murine counterparts, T cells expressing high levels of V alpha24inv TCRs can be either CD4- CD8- double negative (DN) or CD4+, but they never express heterodimeric CD8 molecules. Second, most V alpha24inv T cells are brightly stained by NKRP1-specific mAb but not by mAb directed against other type II transmembrane proteins of the NK complex. Third, DN and particularly CD4+ V alpha24inv T cells are greatly enriched for IL-4 producers. The concomitant expression of highly conserved TCRs of a particular set of NK markers and of Th2 cytokines in human and murine alphabeta T cells suggests a coordinate acquisition of these phenotypic and functional properties. Furthermore, the relatively high frequency of human V alpha24inv T cells, which are presently shown to represent on average 1/500 PBL, and the high interindividual variations of the size of this cell subset under physiologic conditions go for a major role played by alphabeta T cells carrying invariant TCR in a large array of immune responses.     

Quantitative molecular monitoring of HIV-1 RNA during antiretroviral therapy

Plasma HIV-1 RNA testing was used to monitor 43 HIV-1 infected patients newly placed on antiretroviral therapy or whose therapy had been recently changed. A polymerase chain reaction kit was used to measure HIV-1 RNA in clinical samples or frozen plasma. The cutoff of this test was 200 RNA copies/ml. The first group (11 patients) was stable on long-term zidovudine monotherapy when switched to stavudine. The HIV-1 RNA of three patients who had a regular decline in CD4+ T cell count did not change despite this switch, with a mean follow-up of 630 days. The HIV-1 RNA copy numbers of eight patients whose CD4+ T cell counts were stable declined an average of 0.53 log10 between days 90 and 650. The second group (14 patients) was on long-term zidovudine monotherapy and had declining CD4+ T cell counts over the past 6 months. Lamivudine was added to this regimen on day 0. HIV-1 RNA copy number decreased rapidly within 30 d, reaching -0.86 log10 on day 90, and this effect was maintained thereafter, with a mean follow-up of 161 days. There was a concomitant mean gain of +33 CD4+ T cells on day 90. The third group (nine patients) had never received anti-retroviral therapy and was given zidovudine+didanosine. HIV-1 RNA copy number decreased in all cases but one, reaching -1.31 log10 on day 150. This decrease was transient in three cases. The last group (nine patients) had also not had previous anti-retroviral therapy and was given zidovudine + didanosine + lamivudine in combination. HIV-1 RNA copy numbers declined rapidly in all cases, to below the cutoff in eight cases within a mean period of 50.5 days. The CD4+ cell counts increased by 164 cells/microliter on day 14 and by 201 cells/microliter on day 180. The response to therapy of the total population of 43 patients varied according to cases. The relative changes in p24 antigen compared to HIV-1 RNA also differed between patients. Measurement of HIV-1 viremia appears to be a valuable tool in current practice for individualizing therapy.     

Requirement-oriented risk management for incremental software development

In incremental software development (ISD) functionalities are delivered incrementally and requirements keep on evolving across iterations. The requirements evolution involves the addition of new dependencies and conflicts among functional and non-functional requirements along with changes in priorities and dependency weights. This, in turn, demands refactoring the order of development of system components to minimize the impact of these changes. Neglecting the non-functional constraints in the software development process exposes it to risks that may accumulate across several iterations. In this research work, we propose a risk management framework for ISD processes that provides an estimate of risk exposure for the project when functional features are frozen while ignoring the associations with non-functional requirements. Our framework proposes suitable risk reduction strategies that work in tandem with the risk assessment module. We also provide a tool interface for our risk management framework.

     

A single pass algorithm for clustering evolving data streams based on swarm intelligence

Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics, and an offline phase that generates the clusters by using the summary data. In this article we propose a data stream clustering method based on a multi-agent system that uses a decentralized bottom-up self-organizing strategy to group similar data points. Data points are associated with agents and deployed onto a 2D space, to work simultaneously by applying a heuristic strategy based on a bio-inspired model, known as flocking model. Agents move onto the space for a fixed time and, when they encounter other agents into a predefined visibility range, they can decide to form a flock if they are similar. Flocks can join to form swarms of similar groups. This strategy allows to merge the two phases of density-based approaches and thus to avoid the computing demanding offline cluster computation, since a swarm represents a cluster. Experimental results show that the bio-inspired approach can obtain very good results on real and synthetic data sets.     

Landscape-aware location-privacy protection in location-based services

Mobile network providers have developed a variety of location-based services (LBSs), such as friend-finder, point of interest services, emergency rescue and many other safety and security services. The protection of location-privacy has consequently become a key aspect to the success of LBSs, since users consider their own physical location and movements highly privacy-sensitive, and demand for solutions able to protect such an information in a variety of environments. The idea behind location-privacy protection is that the individual should be able to set the level at which the location information is released to avoid undesired exploitation by a potential attacker: one of the approaches to this problem is given by the application of spatial obfuscation techniques, actuated by a trusted agent, and consisting in artificial perturbations of the location information collected by sensing technologies, before its disclosure to third parties. In many situations, however, landscape/map information can help a third party to perform Bayesian inference over spatially obfuscated data and to refine the user’s location estimate up to a violation of the original user’s location-privacy requirements. The goal of this paper is to provide a map-dependent obfuscation procedure that enables the release of the maximum possible user’s location information, that does not lead to a violation of the original user’s location-privacy requirements, even when refined through map-based inference.     

Self-adaptive utility-based web session management

In the Internet, where millions of users are a click away from your site, being able to dynamically classify the workload in real time, and predict its short term behavior, is crucial for proper self-management and business efficiency. As workloads vary significantly according to current time of day, season, promotions and linking, it becomes impractical for some ecommerce sites to keep over-dimensioned infrastructures to accommodate the whole load. When server resources are exceeded, session-based admission control systems allow maintaining a high throughput in terms of properly finished sessions and QoS for a limited number of sessions; however, by denying access to excess users, the website looses potential customers.In the present study we describe the architecture of AUGURES, a system that learns to predict Web user’s intentions for visiting the site as well its resource usage. Predictions are made from information known at the time of their first request and later from navigational clicks. For this purpose we use machine learning techniques and Markov-chain models. The system uses these predictions to automatically shape QoS for the most profitable sessions, predict short-term resource needs, and dynamically provision servers according to the expected revenue and the cost to serve it. We test the AUGURES prototype on access logs from a high-traffic, online travel agency, obtaining promising results.     

Real time identification of discrete event systems using Petri nets

The paper defines the identification problem for Discrete Event Systems (DES) as the problem of inferring a Petri Net () model using the observation of the events and the available output vectors, that correspond to the markings of the measurable places. Two cases are studied considering different levels of the system knowledge. In the first case the place and transition sets are assumed known. Hence, an integer linear programming problem is defined in order to determine a modelling the DES. In the second case the transition and place sets are assumed unknown and only an upper bound of the number of places is given. Hence, the identification problem is solved by an identification algorithm that observes in real time the occurred events and the corresponding output vectors. The integer linear programming problem is defined at each observation so that the can be recursively identified. Some results and examples characterize the identified systems and show the flexibility and simplicity of the proposed technique. Moreover, an application to the synthesis of supervisory control of systems via monitor places is proposed.     

Recommendation of RILEM Technical Committee 250-CSM: Test method for Textile Reinforced Mortar to substrate bond characterization

Textile Reinforced Mortar (TRM), also known as Fabric Reinforced Mortar or Fabric Reinforced Cementitious Matrix, composites are an emerging technology for the external repair and strengthening of existing structures. For most applications, the effectiveness of the TRM reinforcement relies on its bond performance. This recommendation identifies the best practice to characterize the bond behaviour of TRM. A shear bond test method is proposed to determine the peak axial stress (associated with the maximum load that can be transferred from the structural member to the externally bonded TRM reinforcement), the stress–slip relationship and the failure mode that controls the TRM-to-substrate load transfer capacity. Guidelines on specimen manufacturing, experimental setup, test execution, and determination of test results are provided.