Continuous hyperspectral absorption measurements of colored dissolved organic material in aquatic systems

The majority of organic carbon in the oceans is present as dissolved organic matter (DOM); therefore understanding the distribution and dynamics of DOM is central to understanding global carbon cycles. Describing the time-space variability in colored dissolved organic matter (CDOM) has been difficult, as standard spectrophotometric methods for CDOM determination are laborious and susceptible to methodological biases. Previously, measurements of CDOM absorption in discrete water samples by use of a liquid-waveguide capillary cell (LWCC) compared favorably with measurements made with a benchtop spectrophotometer. Given this, we focused on automating the LWCC technique to improve our spatial and temporal sampling capabilities for CDOM. We found strong correlations between CDOM absorption spectra collected from discrete water samples using standard methods and selected corresponding CDOM spectra collected by the automated LWCC system. The near-continuous measurements by the LWCC system made it possible to map the temporal, spatial, and spectral variability of CDOM absorption along the ship track.     

Identification of protein ligands in complex biological samples using intensity-fading MALDI-TOF mass spectrometry

The easy detection of biomolecular interactions in complex mixtures using a minimum amount of material is of prime interest in molecular and cellular biology research. In this work, a mass spectrometry MALDI-TOF based approach, which we call intensity-fading (IF MALDI-TOFMS), and which was designed for just such a purpose, is reported. This methodology is based on the use of the MALDI ion intensities to detect quickly the formation of complexes between nonimmobilized biomolecules in which a protein is one of the partners (protein-protein, protein-peptide, protein-organic molecule, and protein-nucleic acid complexes). The complex is detected through the decrease (fading) of the molecular ion intensities of the partners as directly compared to the MALDI mass spectrum of the mixture (problem and control molecules) following the addition of the target molecule. The potential of the approach is examined in several examples of model interactions, mainly involving small nonprotein and protein inhibitors of proteases, at both the qualitative and semiquantitative levels. Using this method, different protein ligands of proteolytic enzymes in total extracts of invertebrate organisms have been identified in a simple way. The proposed procedure should be easily applied to the high-throughput screening of biomolecules, opening a new experimental strategy in functional proteomics.     

A ROBUST TERMINAL SLIDING COMPOSITE ADAPTIVE CONTROL SCHEME FOR RIGID ROBOTS

In this article is presented a robust adaptive control scheme for mechanical manipulators with finite error convergence time. The design combines, on the one hand, a composite adaptive controller that implements a feedback linearization control law that compensates the modelled dynamics, and, on the other hand, a terminal sliding mode control law that overcomes the uncertainties usually present in the real systems. Then, to avoid the chattering phenomenon inherent to the sliding schemes, the control law is also smoothed out. It is proved that the resulting closed loop system is stable and that the trajectory-tracking error converges to zero in finite time. Moreover, an upper bound of this error convergence time is calculated. Finally, the design is evaluated by means of simulations.     

A cognitive-behavioral model of problematic online gaming in adolescents aged 12–22 years

The aim of this study was to apply the cognitive behavioral model of problematic Internet use to the context of online game use to obtain a better understanding of problematic use of online games and its negative consequences. In total, 597 online game playing adolescents aged 12–22 years participated in this study. Results showed that the cognitive behavioral model of problematic Internet use can also be used in the context of online game use. More specifically, preference for online social interaction, mood regulation and deficient self-regulation appeared to play an important role in predicting negative outcomes from problematic online game use. Together, these cognitions and behaviors explained 79% of the variance of negative outcomes scores. These findings can be used to develop strategies that aim at reducing problematic online game behavior and its negative consequences.     

A Parallel Dynamic Binary Translator for Efficient Multi-Core Simulation

In recent years multi-core processors have seen broad adoption in application domains ranging from embedded systems through general-purpose computing to large-scale data centres. Simulation technology for multi-core systems, however, lags behind and does not provide the simulation speed required to effectively support design space exploration and parallel software development. While state-of-the-art instruction set simulators (Iss) for single-core machines reach or exceed the performance levels of speed-optimised silicon implementations of embedded processors, the same does not hold for multi-core simulators where large performance penalties are to be paid. In this paper we develop a fast and scalable simulation methodology for multi-core platforms based on parallel and just-in-time (Jit) dynamic binary translation (Dbt). Our approach can model large-scale multi-core configurations, does not rely on prior profiling, instrumentation, or compilation, and works for all binaries targeting a state-of-the-art embedded multi-core platform implementing the ARCompact instruction set architecture (Isa). We have evaluated our parallel simulation methodology against the industry standard Splash-2 and Eembc MultiBench benchmarks and demonstrate simulation speeds up to 25,307 Mips on a 32-core x86 host machine for as many as 2,048 target processors whilst exhibiting minimal and near constant overhead, including memory considerations.     

Multi-agent location system in wireless networks

In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks.The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization.The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer.In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building.Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room.     

A review on the applications of type-2 fuzzy logic in classification and pattern recognition

In this paper a review of type-2 fuzzy logic applications in pattern recognition, classification and clustering problems is presented. Recently, type-2 fuzzy logic has gained popularity in a wide range of applications due to its ability to handle higher degrees of uncertainty. In particular, there have been recent applications of type-2 fuzzy logic in the fields of pattern recognition, classification and clustering, where it has helped improving results over type-1 fuzzy logic. In this paper a concise and representative review of the most successful applications of type-2 fuzzy logic in these fields is presented.     

Developing control logic using aspect-oriented programming and sequence planning

A fundamental functionality of a Programmable Logic Controller (PLC) is to control and execute a set of operations. But a large part of the program code is more involved in supporting the user with concerns like alarm, HMI, communication, safety and manual control. Code related to these supporting concerns is often tangled with operation execution code, the core concerns, which makes it hard to reuse.This paper describes a method to reuse code and functionality when developing PLC programs and code libraries. The method proposes that core concerns are planned with a software tool called Sequence Planner, and the supporting concerns are integrated into the core concerns with a tool based on aspect-oriented programming.     

Using C/X-band SAR interferometry and GNSS measurements for the Assisi landslide analysis

This work presents an analysis of the applicability of synthetic aperture radar (SAR) interferometry to landslide monitoring. This analysis was carried out by using different interferometric approaches, different spaceborne SAR data (both in the C-band and in the X-band), and in situ global navigation satellite system (GNSS) measurements. In particular, we investigated both the reliability of displacement monitoring and the issues of the cross-comparison and validation of the interferometric synthetic aperture radar (InSAR) results. The work was focused on the slow-moving landslide that affects a relevant part of the urban area of the historical town of Assisi (Italy).

A C-band ENVISAT advanced synthetic aperture radar (ENVISAT ASAR) dataset acquired between 2003 and 2010 was processed by using two different interferometric techniques, to allow cross-comparison of the obtained displacement maps. Good correspondence between the results was found, and a deeper analysis of the movement field was possible. Results were further compared to a set of GNSS measurements with a 7 year overlap with SAR data. A comparison was made for each GNSS marker with the surrounding SAR scatterers, trying to take into account local topological effects, when possible.

Further, the high-resolution X-band acquired on both ascending and descending tracks by the COSMO-SkyMed (CSK) constellation was processed. The resultant displacement fields show good agreement with C-band and GNSS measurements and a sensible increase in the density of measurements.