Shear Strength and Durability Testing of Adhesive Bonds in Cross-Laminated Timber

The paper addresses the quality of the interface and edge bonded joints in layers of cross-laminated timber (CLT) panels. The shear performance was studied to assess the suitability of two different adhesives, Polyurethane (PUR) and Phenol-Resorcinol-Formaldehyde (PRF), and to determine the optimum clamping pressure. Since there is no established testing procedure to determine the shear strength of the surface bonds between layers in a CLT panel, block shear tests of specimens in two different configurations were carried out, and further shear tests of edge bonded specimen in two configurations were performed. Delamination tests were performed on samples which were subjected to accelerated aging to assess the durability of bonds in severe environmental conditions. Both tested adhesives produced boards with shear strength values within the edge bonding requirements of prEN 16351 for all manufacturing pressures. While the PUR specimens had higher shear strength values, the PRF specimens demonstrated superior durability characteristics in the delamination tests. It seems that the test protocol introduced in this study for crosslam bonded specimens, cut from a CLT panel, and placed in the shearing tool horizontally, accurately reflects the shearing strength of glue lines in CLT.

The BRUTUS Automatic Cryptanalytic Framework: Testing CAESAR Authenticated Encryption Candidates for Weaknesses

This report summarizes our results from security analysis covering all 57 competitions for authenticated encryption: security, applicability, and robustness (CAESAR) first-round candidates and over 210 implementations. We have manually identified security issues with three candidates, two of which are more serious, and these ciphers have been withdrawn from the competition. We have developed a testing framework, BRUTUS, to facilitate automatic detection of simple security lapses and susceptible statistical structures across all ciphers. From this testing, we have security usage notes on four submissions and statistical notes on a further four. We highlight that some of the CAESAR algorithms pose an elevated risk if employed in real-life protocols due to a class of adaptive-chosen-plaintext attacks. Although authenticated encryption with associated data are often defined (and are best used) as discrete primitives that authenticate and transmit only complete messages, in practice, these algorithms are easily implemented in a fashion that outputs observable ciphertext data when the algorithm has not received all of the (attacker-controlled) plaintext. For an implementor, this strategy appears to offer seemingly harmless and compliant storage and latency advantages. If the algorithm uses the same state for secret keying information, encryption, and integrity protection, and the internal mixing permutation is not cryptographically strong, an attacker can exploit the ciphertext–plaintext feedback loop to reveal secret state information or even keying material. We conclude that the main advantages of exhaustive, automated cryptanalysis are that it acts as a very necessary sanity check for implementations and gives the cryptanalyst insights that can be used to focus more specific attack methods on given candidates.

Testing the channel-based model of duration perception

The channel-based model of duration perception postulates the existence of neural mechanisms that respond selectively to a narrow range of stimulus durations centred on their preferred duration (Heron et al Proceedings of the Royal Society B 279 690–698). In principle the channel-based model could
explain recent reports of adaptation-induced, visual duration compression effects (Johnston et al Current Biology 16 472–479; Curran and Benton Cognition 122 252–257); from this perspective duration compression is a consequence of the adapting stimuli being presented for a longer duration than the test stimuli. In the current experiment observers adapted to a sequence of moving random dot patterns at the same retinal position, each 340ms in duration and separated by a variable (500–1000ms) interval. Following adaptation observers judged the duration of a 600ms test stimulus at the same location. The test stimulus moved in the same, or opposite, direction as the adaptor. Contrary to the channel-based
model’s prediction, test stimulus duration appeared compressed, rather than expanded, when it moved in the same direction as the adaptor. That test stimulus duration was not distorted when moving in the opposite direction further suggests that visual timing mechanisms are influenced by additional neural processing associated with the stimulus being timed.

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

An evaluation of the effectiveness of an algorithm intervention in reducing inappropriate faecal samples sent for Clostridium difficile testing.

Background: Clostridium difficile (C. difficile) is a leading cause of infectious diarrhoea in hospitals. Sending faecal samples for testing expedites diagnosis and appropriate treatment. Clinical suspicion of C. difficile based on patient history, signs and symptoms is the basis for sampling. Sending faecal samples from patients with diarrhoea ‘just in case’ the patient has C. difficile may be an indication of poor clinical management.

Aim: To evaluate the effectiveness of an intervention by an Infection Prevention and Control Team (IPCT) in reducing inappropriate faecal samples sent for C. difficile testing.

Method: An audit of numbers of faecal samples sent before and after a decision-making algorithm was introduced. The number of samples received in the laboratory was retrospectively counted for 12-week periods before and after an algorithm was introduced.
Findings: There was a statistically significant reduction in the mean number of faecal samples sent post the algorithm. Results were compared to a similar intervention carried out in 2009 in which the same message was delivered by a memorandum. In 2009 the memorandum had no effect on the overall number of weekly samples being sent.

Conclusion: An algorithm intervention had an effect on the number of faecal samples being sent for C. difficile testing and thus contributed to the effective use of the laboratory service.

A primer for use of genetic tools in selecting and testing the suitability of set-aside sites protected from deep-sea seafloor massive sulfide mining activities

Seafloor massive sulfide (SMS) mining will likely occur at hydrothermal systems in the near future. Alongside their mineral wealth, SMS deposits also have considerable biological value. Active SMS deposits host endemic hydrothermal vent communities, whilst inactive deposits support communities of deep water corals and other suspension feeders. Mining activities are expected to remove all large organisms and suitable habitat in the immediate area, making vent endemic organisms particularly at risk from habitat loss and localised extinction. As part of environmental management strategies designed to mitigate the effects of mining, areas of seabed need to be protected to preserve biodiversity that is lost at the mine site and to preserve communities that support connectivity among populations of vent animals in the surrounding region. These "set-aside" areas need to be biologically similar to the mine site and be suitably connected, mostly by transport of larvae, to neighbouring sites to ensure exchange of genetic material among remaining populations. Establishing suitable set-asides can be a formidable task for environmental managers, however the application of genetic approaches can aid set-aside identification, suitability assessment and monitoring. There are many genetic tools available, including analysis of mitochondrial DNA (mtDNA) sequences (e.g. COI or other suitable mtDNA genes) and appropriate nuclear DNA markers (e.g. microsatellites, single nucleotide polymorphisms), environmental DNA (eDNA) techniques and microbial metagenomics. When used in concert with traditional biological survey techniques, these tools can help to identify species, assess the genetic connectivity among populations and assess the diversity of communities. How these techniques can be applied to set-aside decision making is discussed and recommendations are made for the genetic characteristics of set-aside sites. A checklist for environmental regulators forms a guide to aid decision making on the suitability of set-aside design and assessment using genetic tools. This non-technical primer document represents the views of participants in the VentBase 2014 workshop.

Modelling the fresh properties of self-compacting concrete using support vector machine approach

The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.

The Value of Full Scale Prototype Data - Testing Oyster 800 at EMEC, Orkney

This paper demonstrates the unparalleled value of full scale data which has been acquired from ocean trials of Aquamarine Power’s Oyster 800 Wave Energy Converter (WEC) at the European Marine Energy Centre (EMEC), Orkney, Scotland.
High quality prototype and wave data were simultaneously recorded in over 750 distinct sea states (comprising different wave height, wave period and tidal height combinations) and include periods of operation where the hydraulic Power Take-Off (PTO) system was both pressurised (damped operation) and de-pressurised (undamped operation).
A detailed model-prototype correlation procedure is presented where the full scale prototype behaviour is compared to predictions from both experimental and numerical modelling techniques via a high temporal resolution wave-by-wave reconstruction. This unquestionably provides the definitive verification of the capabilities of such research techniques and facilitates a robust and meaningful uncertainty analysis to be performed on their outputs.
The importance of a good data capture methodology, both in terms of handling and accuracy is also presented. The techniques and procedures implemented by Aquamarine Power for real-time data management are discussed, including lessons learned on the instrumentation and infrastructure required to collect high-value data.

An overview of seismic hybrid testing of engineering structures

An overview of research on the development of the hybrid test method is presented. The maturity of the hybrid test method is mapped in order to provide context to individual research in the overall development of the test method. In the pseudo dynamic (PsD) test method, the equations of motion are solved using a time stepping numerical integration technique with the inertia and damping being numerically modelled whilst restoring force is physically measured over an extended timescale. Developments in continuous PsD testing led to the real-time hybrid test method and geographically distributed hybrid tests. A key aspect to the efficiency of hybrid testing is the substructuring technique where the critical structural subassemblies that are fundamental to the overall response of the structure are physically tested whilst the remainder of the structure whose response can be more easily predicted is numerically modelled. Much of the early research focused on developing the accuracy and efficiency of the test method, whereas more recently the method has matured to a level where the test method is applied purely as a dynamic testing technique. Developments in numerical integration methods, substructuring, experimental error reduction, delay compensation and speed of testing have led to a test method now in use as full-scale real-time dynamic testing method that is reliable, accurate, efficient and cost effective.