Hydration and properties of sodium sulfate activated slag

Interest in alkali-activated slag as a construction material is increasing, primarily due to its environmentally friendly nature. Although strong alkaline activators, such as sodium hydroxide and sodium silicate solution, are preferred for high strength, none of them exists naturally and their manufacturing process is quite energy intensive. Whilst sodium sulfate (NaSO ) can be obtained from natural resources, the early strength of NaSO activated slag is usually low. In this paper, the effects of slag fineness and NaSO dosage on strength, pH, hydration and microstructure were investigated and compared with those of a pure Portland cement (PC). Test results indicated that increasing the slag fineness is a more effective approach than increasing NaSO dosage for increasing both the early and long-term strength of NaSO activated slags. In addition, increasing the slag fineness can also increase the strength without increasing the pH of the hardened matrix, which is beneficial for immobilizing certain types of nuclear waste containing reactive metals and resins.© 2012 Elsevier Ltd. All rights reserved.

Are Alkyl Sulfate-Based Protic and Aprotic Ionic Liquids Stable with Water and Alcohols? A Thermodynamic Approach

The knowledge of the chemical stability as a function of the temperature of ionic liquids (ILs) in the presence of other molecules such as water is crucial prior to developing any no GO industrial application and process involving these novel materials. Fluid phase equilibria and density over a large range of temperature and composition can give basic information on IL purity and chemical stability. The IL scientific community requires accurate measurements accessed from reference data. In this work, the stability of different alkyl sulfate-based ILs in the presence of water and various alcohols (methanol, ethanol, 1-butanol, and 1-octanol) was investigated to understand their stability as a function of temperature up to 423.15 K over the hydrolysis and transesterification reactions, respectively. From this investigation, it was clear that methyl sulfate- and ethyl sulfate-based ILs are not stable in the presence of water, since hydrolysis of the methyl sulfate or ethyl sulfate anions to methanol or ethanol and hydrogenate anion is undoubtedly observed. Such observations could help to explain the differences observed for the physical properties published in the literature by various groups. Furthermore, it appears that a thermodynamic equilibrium process drives these hydrolysis reactions. In other words, these hydrolysis reactions are in fact reversible, providing the possibility to re-form the desired alkyl sulfate anions by a simple transesterification reaction between hydrogen sulfate-based ILs and the corresponding alcohol (methanol or ethanol). Additionally, butyl sulfate- and octyl sulfate-based ILs appear to follow this pattern but under more drastic conditions. In these systems, hydrolysis is observed in both cases after several months for temperatures up to 423 K in the presence of water. Therein, the partial miscibility of hydrogen sulfate-based ILs with long chain alcohols (1-butanol and 1-octanol) can help to explain the enhanced hydrolytic stability of the butyl sulfate- and octyl sulfate-based ILs compared with the methyl or ethyl sulfate systems. Additionally, rapid transesterification reactions are observed during liquid-liquid equilibrium studies as a function of temperature for binary systems of (hydrogen sulfate-based ionic liquids + 1-butanol) and of (hydrogen sulfate-based ionic liquids + 1-octanol). Finally, this atom-efficient catalyst-free transesterification reaction between hydrogen sulfate-based ILs and alcohol was then tested to provide a novel way to synthesize new ILs with various anion structures containing the alkyl sulfate group.

Impact of Metric Selection on Wireless DeAuthentication DoS Attack Performance

DeAuthentication Denial of Service attacks in Public Access WiFi operate by exploiting the lack of authentication of management frames in the 802.11 protocol. Detection of these attacks rely almost exclusively on the selection of appropriate thresholds. In this work the authors demonstrate that there are additional, previously unconsidered, metrics which also influence DoS detection performance. A method of systematically tuning these metrics to optimal values is proposed which ensures that parameter choices are repeatable and verifiable.

The Forgiving Graph: a distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.

Interaction of combined chloride and sulfate ingression in concrete

Chloride is the most severe form of deterioration experienced by concrete and one of the principal sources of chlorides is sea water. However, the presence of sulfates in seawater will influence the movement of chloride ions and vice versa. This interaction is not well understood and current codes of practice provide no guidelines for such dual exposure.
An investigation to monitor combined effect of the ingress of chlorides and sulfates during a realistic 12 month wetting and drying exposure regime to simulate conditions in which multiple mode transport mechanisms are active was conducted on a variety of binders (PC, PFA and GGBS). Penetration was evaluated using water and acid soluble chloride profiles and sulfate profiles.
It was found that the nature of the exposure provided multiple modes of transport within the concrete, thus creating a complex pattern of distribution of ions. The presence of sulfates decreased the penetration of chlorides in the PC system at all ages relative to a chloride only control. The matrices containing PFA and GGBS also showed an initial decrease in chloride penetration. However, after six months the presence of sulfates then increased chloride penetration.

Man-in-the-Middle Attack Test-bed Investigating Cyber-security Vulnerabilities in Smart Grid SCADA Systems

The increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in the Smart Grid has exposed them to a wide range of cyber-security issues, and there are a multitude of potential access points for cyber attackers. This paper presents a SCADA-specific cyber-security test-bed which contains SCADA software and communication infrastructure. This test-bed is used to investigate an Address Resolution Protocol (ARP) spoofing based man-in-the-middle attack. Finally, the paper proposes a future work plan which focuses on applying intrusion detection and prevention technology to address cyber-security issues in SCADA systems.

The Forgiving Graph:A distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions,without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been - in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most - log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degreewould have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network. © Springer-Verlag 2012.

A pilot study of a family focused, psychosocial intervention with war-exposed youth at risk of attack and abduction in north-eastern Democratic Republic of Congo

Rural communities in the Haut-Uele Province of northern Democratic Republic of Congo live in constant danger of attack and/or abduction by units of the Lord's Resistance Army operating in the region. This pilot study sought to develop and evaluate a community-participative psychosocial intervention involving life skills and relaxation training and Mobile Cinema screenings with this war-affected population living under current threat. 159 war-affected children and young people (aged 7-18) from the villages of Kiliwa and Li-May in north-eastern DR Congo took part in this study. In total, 22% of participants had been abduction previously while 73% had a family member abducted. Symptoms of post-traumatic stress reactions, internalising problems, conduct problems and pro-social behaviour were assessed by blinded interviewers at pre- and post-intervention and at 3-month follow-up. Participants were randomised (with an accompanying caregiver) to 8 sessions of a group-based, community-participative, psychosocial intervention (n=79) carried out by supervised local, lay facilitators or a wait-list control group (n=80). Average seminar attendance rates were high: 88% for participants and 84% for caregivers. Drop-out was low: 97% of participants were assessed at post-intervention and 88% at 3 month follow-up. At post-test, participants reported significantly fewer symptoms of post-traumatic stress reactions compared to controls (Cohen's d=0.40). At 3 month follow up, large improvements in internalising symptoms and moderate improvements in pro-social scores were reported, with caregivers noting a moderate to large decline in conduct problems among the young people. Trial Registration clinicalTrials.gov, Identifier: NCT01542398.

PRECYSE: Cyber-attack Detection and Response for Industrial Control Systems

In this short paper, we present an integrated approach to detecting and mitigating cyber-attacks to modern interconnected industrial control systems. One of the primary goals of this approach is that it is cost effective, and thus whenever possible it builds on open-source security technologies and open standards, which are complemented with novel security solutions that address the specific challenges of securing critical infrastructures.

The effect of probe interval estimation on attack detection performance of a WLAN independent intrusion detection system

A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.

Mechanism of effluent attack on Portland cement and alkali activated mortars

The alkali activation of waste products has become a widespread topic of research, mainly due to environmental benefits. Portland cement and alkali-activated mortar samples were prepared to compare their resistance to silage effluent which contains lactic acid. The mechanism of attack on each sample has also been investigated.

Neural Network Based Attack on a Masked Implementation of AES

Masked implementations of cryptographic algorithms are often used in commercial embedded cryptographic devices to increase their resistance to side channel attacks. In this work we show how neural networks can be used to both identify the mask value, and to subsequently identify the secret key value with a single attack trace with high probability. We propose the use of a pre-processing step using principal component analysis (PCA) to significantly increase the success of the attack. We have developed a classifier that can correctly identify the mask for each trace, hence removing the security provided by that mask and reducing the attack to being equivalent to an attack against an unprotected implementation. The attack is performed on the freely available differential power analysis (DPA) contest data set to allow our work to be easily reproducible. We show that neural networks allow for a robust and efficient classification in the context of side-channel attacks.