Ultra-dense planar metallic nanowire arrays with extremely large anisotropic optical and magnetic properties

A nanofabrication method for the production of ultra-dense planar metallic nanowire arrays scalable to wafer-size is presented. The method is based on an efficient template deposition process to grow diverse metallic nanowire arrays with extreme regularity in only two steps. First, III–V semiconductor substrates are irradiated by a low-energy ion beam at an elevated temperature, forming a highly ordered nanogroove pattern by a “reverse epitaxy” process due to self-assembly of surface vacancies. Second, diverse metallic nanowire arrays (Au, Fe, Ni, Co, FeAl alloy) are fabricated on these III–V templates by deposition at a glancing incidence angle. This method allows for the fabrication of metallic nanowire arrays with periodicities down to 45 nm scaled up to wafer-size fabrication. As typical noble and magnetic metals, the Au and Fe nanowire arrays produced here exhibited large anisotropic optical and magnetic properties, respectively. The excitation of localized surface plasmon resonances (LSPRs) of the Au nanowire arrays resulted in a high electric field enhancement, which was used to detect phthalocyanine (CoPc) in surface-enhanced Raman scattering (SERS). Furthermore, the Fe nanowire arrays showed a very high in-plane magnetic anisotropy of approximately 412 mT, which may be the largest in-plane magnetic anisotropy field yet reported that is solely induced via shape anisotropy within the plane of a thin film.

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Effects of a startling acoustic stimulus on reaction time in different parkinsonian syndromes

BACKGROUND: The functional assessment of the startle circuit is usually done by analyzing the acoustic startle response (ASR). However, a startling acoustic stimulus (SAS) also induces changes in the excitability of neural structures that can be demonstrated by studying the SAS-induced change in the behavior of certain neurophysiologic responses. OBJECTIVE: To examine the effects induced by an SAS on voluntary reaction time in patients with parkinsonian syndromes (StartReact effect) and to compare the results with those obtained in a group of age-matched healthy volunteers. METHODS: Twelve patients with idiopathic PD (IPD), seven patients with progressive supranuclear palsy (PSP), seven patients with multisystem atrophy (MSA), and seven healthy age-matched control volunteers performed a simple visual reaction time task and received SAS together with the "go" signal in random trials. RESULTS: Baseline reaction time was significantly slower in PSP patients than in control subjects and MSA patients. The SAS induced a significant shortening of the reaction time in control subjects and in patients with IPD and MSA, but not in patients with PSP. The percentage of reaction time shortening with regard to the baseline values also differed significantly between PSP patients and the other groups of subjects. The StartReact effect was consistent throughout the experiment and showed reduced habituation with repeated testing. CONCLUSIONS: The results are consistent with an abnormal function of the startle circuit in patients with PSP and agree with previous studies using the ASR. The reduced habituation of the StartReact effect favors its clinical applicability in the assessment of differences between patients with parkinsonian syndromes.     

Design of product as source of variance in composition of meat-based infant beikosts

The influence of both the design of the product (formulated raw ingredients) and type of product (on the meat type formulated base) on the mineral composition, crude protein (CP), protein digestibility (PD), total dietary fiber (TDF) and phytic acid (FA) contents of meat-based infant beikosts was studied. The product design was the main factor determining the CP, TDF, Ca, Na and K contents, while the type of product was the main factor determining the PD, FA, Zn, Fe and Mn contents. High K and Mn levels were related to high TDF contents. CP and Zn showed a significant relationship but the CP Fe relationship was not significant.     

Diseases of the digestive system and a system for patient classification: diagnostic-related groups (DRG)

In the last years different classification systems for hospitalized patients have been developed in the United States, that allow to evaluate different aspects of any Hospital: The quality, the efficacy and the efficiency. The classification of "The Diagnosis Related Groups" (DRG) relates the hospitalized patients with the expenses that they generate, and it is the most used in Europe. In the version DRG-All Patient, all the diagnoses and procedures of the hospitalized patients, using the International Classification of Diseases, are divided in to 25 Major Diagnostic Categories (MDC) where each one excludes all the others. We describe the behavior with respect to the age, sex and stay of all the GDR integrated in the CDM 6 and 7: diseases and disorders of the digestive tract, and diseases and disorders of the hepatobiliary system and the pancreas. The study has been carried out with a national data base of two millions of cases seen from 214 acute-care Hospitals. The MDC number 6 is the most frequent, with an important number of patients in the pediatric age; it is more frequent in males; the average stay is 8.59 days and 19 GDR (36.5%) have a variation coefficient greater than one. The other MDC, number 7 is less frequent, the majority of the patients are between 60-80 years of age, the average stay is 12.2 days with a coefficient of variation greater than one in 4 GDR (17.4%). Clinical Services should know the characteristics and behavior of their patients, as well as the comparison with the national data bases. This may allow a control of the quality and the costs by using a common "language" with the managers.     

Imhotep: an approach to user and device conscious mobile applications

As the dependence on mobile devices increases, the need for supporting a wider range of users and devices becomes crucial. Elders and people with disabilities adopt new technologies reluctantly, a tendency caused by the lack of adaptation of these technologies to their needs. To address this challenge, this paper describes a framework, Imhotep, whose aim is to aid developers in the accessible application creation process, making the creation of user-centered applications easier and faster. Our framework allows to easily adapt the applications to the constraints imposed by the user capabilities (sensorial, cognitive, and physical capabilities) and device capabilities by providing a repository that will manage the compilation and deployment of applications that include a set of preprocessor directives in the source code. These directives are enhanced with concepts that are automatically adjusted to the current trends of mobile devices by using a Fuzzy Knowledge-Eliciting Reasoner. Our final goal is to increase the number of applications targeted to elders and people with disabilities providing tools that facilitate their development. The paper also describes the evaluation of both the accuracy of the fuzzy terms generated for mobile devices and the usability of the proposed platform.     

Automatic metro map layout using multicriteria optimization

This paper describes an automatic mechanism for drawing metro maps. We apply multicriteria optimization to find effective placement of stations with a good line layout and to label the map unambiguously. A number of metrics are defined, which are used in a weighted sum to find a fitness value for a layout of the map. A hill climbing optimizer is used to reduce the fitness value, and find improved map layouts. To avoid local minima, we apply clustering techniques to the map-the hill climber moves both stations and clusters when finding improved layouts. We show the method applied to a number of metro maps, and describe an empirical study that provides some quantitative evidence that automatically-drawn metro maps can help users to find routes more efficiently than either published maps or undistorted maps. Moreover, we have found that, in these cases, study subjects indicate a preference for automatically-drawn maps over the alternatives.     

Simultaneous learning of perception and action in mobile robots

One of the main problems of robots is the lack of adaptability and the need for adjustment every time the robot changes its working place. To solve this, we propose a learning approach for mobile robots using a reinforcement-based strategy and a dynamic sensor-state mapping. This strategy, practically parameterless, minimises the adjustments needed when the robot operates in a different environment or performs a different task.Our system will simultaneously learn the state space and the action to execute on each state. The learning algorithm will attempt to maximise the time before a robot failure in order to obtain a control policy suited to the desired behaviour, thus providing a more interpretable learning process. The state representation will be created dynamically, starting with an empty state space and adding new states as the robot finds new situations that has not seen before. A dynamic creation of the state representation will avoid the classic, error-prone and cyclic process of designing and testing an ad hoc representation. We performed an exhaustive study of our approach, comparing it with other classic strategies. Unexpectedly, learning both perception and action does not increase the learning time.     

TRIMS,a privacy-aware trust and reputation model for identity management systems

Electronic transactions are becoming more important everyday. Several tasks like buying goods, booking flights or hotel rooms, or paying for streaming a movie, for instance, can be carried out through the Internet. Nevertheless, they are still some drawbacks due to security threats while performing such operations. Trust and reputation management rises as a novel way of solving some of those problems. In this paper we present our work TRIMS (a privacy-aware trust and reputation model for identity management systems), which applies a trust and reputation model to guarantee an acceptable level of security when deciding if a different domain might be considered reliable when receiving certain sensitive user’s attributes. Specifically, we will address the problems which surfaces when a domain needs to decide whether to exchange some information with another possibly unknown domain to effectively provide a service to one of its users. This decision will be determined by the trust deposited in the targeting domain. As far as we know, our proposal is one of the first approaches dealing with trust and reputation management in a multi-domain scenario. Finally, the performed experiments have demonstrated the robustness and accuracy of our model in a wide variety of scenarios.     

A new fast prototype selection method based on clustering

In supervised classification, a training set T is given to a classifier for classifying new prototypes. In practice, not all information in T is useful for classifiers, therefore, it is convenient to discard irrelevant prototypes from T. This process is known as prototype selection, which is an important task for classifiers since through this process the time for classification or training could be reduced. In this work, we propose a new fast prototype selection method for large datasets, based on clustering, which selects border prototypes and some interior prototypes. Experimental results showing the performance of our method and comparing accuracy and runtimes against other prototype selection methods are reported.     

The Effect of Subfilter-Scale Physics on Regularization Models

The subfilter-scale (SFS) physics of regularization models are investigated to understand the regularizations’ performance as SFS models. Suppression of spectrally local SFS interactions and conservation of small-scale circulation in the Lagrangian-averaged Navier-Stokes α-model (LANS-α) is found to lead to the formation of rigid bodies. These contaminate the superfilter-scale energy spectrum with a scaling that approaches k ⁺¹ as the SFS spectra is resolved. The Clark-α and Leray-α models, truncations of LANS-α, do not conserve small-scale circulation and do not develop rigid bodies. LANS-α, however, is closest to Navier-Stokes in intermittency properties. All three models are found to be stable at high Reynolds number. Differences between L ² and H ¹ norm models are clarified. For magnetohydrodynamics (MHD), the presence of the Lorentz force as a source (or sink) for circulation and as a facilitator of both spectrally nonlocal large to small scale interactions as well as local SFS interactions prevents the formation of rigid bodies in Lagrangian-averaged MHD (LAMHD-α). LAMHD-α performs well as a predictor of superfilter-scale energy spectra and of intermittent current sheets at high Reynolds numbers. It may prove generally applicable as a MHD-LES.