Label-free Detection of Microcystin-LR in Waters Using Real-Time Potentiometric Biosensors Based on Single-Walled Carbon Nanotubes Imprinted Polymers

Microcystin-LR (MC-LR) is a dangerous toxin found in environmental waters, quantified by high performance liquid chromatography and/or enzyme-linked immunosorbent assays. Quick, low cost and on-site analysis is thus required to ensure human safety and wide screening programs. This work proposes label-free potentiometric sensors made of solid-contact electrodes coated with a surface imprinted polymer on the surface of Multi-Walled Carbon NanoTubes (CNTs) incorporated in a polyvinyl chloride membrane. The imprinting effect was checked by using non-imprinted materials. The MC-LR sensitive sensors were evaluated, characterized and applied successfully in spiked environmental waters. The presented method offered the advantages of low cost, portability, easy operation and suitability for adaptation to flow methods.

Standing balance in individuals with Parkinson's disease during single and dual-task conditions

This study aimed to examine the differences in standing balance between individuals with Parkinson's disease (PD) and subjects without PD (control group), under single and dual-task conditions. A cross-sectional study was designed using a non-probabilistic sample of 110 individuals (50 participants with PD and 60 controls) aged 50 years old and over. The individuals with PD were in the early or middle stages of the disease (characterized by Hoehn and Yahr as stages 1-3). The standing balance was assessed by measuring the centre of pressure (CoP) displacement in single-task (eyes-open/eyes-closed) and dual-task (while performing two different verbal fluency tasks). No significant differences were found between the groups regarding sociodemographic variables. In general, the standing balance of the individuals with PD was worse than the controls, as the CoP displacement across tasks was significantly higher for the individuals with PD (p<0.01), both in anteroposterior and mediolateral directions. Moreover, there were significant differences in the CoP displacement based parameters between the conditions, mainly between the eyes-open condition and the remaining conditions. However, there was no significant interaction found between group and condition, which suggests that changes in the CoP displacement between tasks were not influenced by having PD. In conclusion, this study shows that, although individuals with PD had a worse overall standing balance than individuals without the disease, the impact of performing an additional task on the CoP displacement is similar for both groups.

Ball Sensing in a Leg Like Robotic Kicker

The trend to have more cooperative play and the increase of game dynamics in Robocup MSL League motivates the improvement of skills for ball passing and reception. Currently the majority of the MSL teams uses ball handling devices with rollers to have more precise kicks but limiting the capability to kick a moving ball without stopping it and grabbing it. This paper addresses the problem to receive and kick a fast moving ball without having to grab it with a roller based ball handling device. Here, the main difficulty is the high latency and low rate of the measurements of the ball sensing systems, based in vision or laser scanner sensors.Our robots use a geared leg coupled to a motor that acts simultaneously as the kicking device and low level ball sensor. This paper proposes a new method to improve the capability for ball sensing in the kicker, by combining high rate measurements from the torque and energy in the motor and angular position of the kicker leg. The developed method endows the kicker device with an effective ball detection ability, validated in several game situations like in an interception to a fast pass or when chasing the ball where the relative speed from robot to ball is low. This can be used to optimize the kick instant or by the embedded kicker control system to absorb the ball energy.

Adhesive selection for single lap bonded joints: Experimentation and advanced techniques for strength prediction

The integrity of multi-component structures is usually determined by their unions. Adhesive-bonding is often used over traditional methods because of the reduction of stress concentrations, reduced weight penalty, and easy manufacturing. Commercial adhesives range from strong and brittle (e.g., Araldite® AV138) to less strong and ductile (e.g., Araldite® 2015). A new family of polyurethane adhesives combines high strength and ductility (e.g., Sikaforce® 7888). In this work, the performance of the three above-mentioned adhesives was tested in single lap joints with varying values of overlap length (LO). The experimental work carried out is accompanied by a detailed numerical analysis by finite elements, either based on cohesive zone models (CZM) or the extended finite element method (XFEM). This procedure enabled detailing the performance of these predictive techniques applied to bonded joints. Moreover, it was possible to evaluate which family of adhesives is more suited for each joint geometry. CZM revealed to be highly accurate, except for largely ductile adhesives, although this could be circumvented with a different cohesive law. XFEM is not the most suited technique for mixed-mode damage growth, but a rough prediction was achieved.

A simplified four-branch model for the analytical study of the out-of-plane performance of regular stone URM walls

During the last years, several studies have been made aiming to assess the out-of-plane seismic response of unreinforced stone masonry structures. This fact led to the development of a wide variety of models and approaches, ranging from simple kinematic based analytical models up to complex numerical simulations. Nevertheless, for the sake of simplicity, the out-of-plane seismic response of a masonry wall pier may be obtained by means of a simple single-degree-of-freedom system while still providing good results. In fact, despite the assumptions associated with such a simple formulation, it is also true that the epistemic uncertainty inherent with the selection of appropriate input parameters in more complex models may render them truly ineffective. In this framework, this paper focuses on the study of the out-of-plane bending of unreinforced stone masonry walls (cantilevers) by proposing a simplified analytical approach based on the construction of a linearized four-branch model, which is used to characterize the linear and nonlinear response of such structural elements through an overturning moment-rotation relationship. The formulation of the four-branch model is presented and described in detail and the meaningful parameters used for its construction are obtained from a set of experimental laboratory tests performed on six full-scale unreinforced regular sacco stone masonry specimens. Moreover, a parametric analysis aiming to evaluate the effect of these parameters’ variation on the final configuration of the model is presented and critically discussed. Finally, the results obtained from the application of the developed four-branch model on real unreinforced regular sacco stone masonry walls are thoroughly analysed and the main conclusions obtained from its application are summarized.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Strength and damage analysis of composite-aluminium adhesively-bonded single-lap joints

With the need to find an alternative way to mechanical and welding joints, and at the same time to overcome some limitations linked to these traditional techniques, adhesive bonds can be used. Adhesive bonding is a permanent joining process that uses an adhesive to bond the components of a structure. Composite materials reinforced with fibres are becoming increasingly popular in many applications as a result of a number of competitive advantages. In the manufacture of composite structures, although the fabrication techniques reduce to the minimum by means of advanced manufacturing techniques, the use of connections is still required due to the typical size limitations and design, technological and logistical aspects. Moreover, it is known that in many high performance structures, unions between composite materials with other light metals such as aluminium are required, for purposes of structural optimization. This work deals with the experimental and numerical study of single lap joints (SLJ), bonded with a brittle (Nagase Chemtex Denatite XNRH6823) and a ductile adhesive (Nagase Chemtex Denatite XNR6852). These are applied to hybrid joints between aluminium (AL6082-T651) and carbon fibre reinforced plastic (CFRP; Texipreg HS 160 RM) adherends in joints with different overlap lengths (LO) under a tensile loading. The Finite Element (FE) Method is used to perform detailed stress and damage analyses allowing to explain the joints’ behaviour and the use of cohesive zone models (CZM) enables predicting the joint strength and creating a simple and rapid design methodology. The use of numerical methods to simulate the behaviour of the joints can lead to savings of time and resources by optimizing the geometry and material parameters of the joints. The joints’ strength and failure modes were highly dependent on the adhesive, and this behaviour was successfully modelled numerically. Using a brittle adhesive resulted in a negligible maximum load (Pm) improvement with LO. The joints bonded with the ductile adhesive showed a nearly linear improvement of Pm with LO.