Harnessing Selectivity and Sensitivity in Ion Sensing via Supramolecular Recognition: A 3D Hybrid Gold Nanoparticle Network Chemiresistor

The monitoring of K⁺ in saliva, blood, urine, or sweat represents a future powerful alternative diagnostic tool to prevent various diseases. However, several K⁺ sensors are unable to meet the requirements for the development of point-of-care (POC) sensors. To tackle this grand-challenge, the fabrication of chemiresistors (CRs) based on 3D networks of Au nanoparticles covalently bridged by ad-hoc supramolecular receptors for K⁺, namely dithiomethylene dibenzo-18-crown-6 ether is reported here. A multi-technique characterization allows optimizing a new protocol for fabricating high-performing CRs for real-time monitoring of K⁺ in complex aqueous environments. The sensor shows exceptional figures of merit: i) linear sensitivity in the 10^–3 to 10^–6 m concentration range; ii) high selectivity to K⁺ in presence of interfering cations (Na⁺, Ca²⁺, and Mg²⁺); iii) high shelf-life stability ( > 45 days); iv) reversibility of K⁺ binding and release; v) successful device integration into microfluidic systems for real-time monitoring; vi) fast response and recovery times ( < 18 s), and v) K⁺ detection in artificial saliva. All these characteristics make the supramolecular CRs a potential tool for future applications as POC devices, especially for health monitoring where the determination of K⁺ in saliva is pivotal for the early diagnosis of diseases.     

Hybrid job offer recommender system in a social network

Recommender systems (RSs) play a very important role in web navigation, ensuring that the users easily find the information they are looking for. Today's social networks contain a large amount of information and it is necessary that they employ a mechanism that will guide users to the information they are interested in. However, to be able to recommend content according to user preferences, it is necessary to analyse their profiles and determine their preferences. The present work proposes a job offer RS for a career‐oriented social network. The recommendation system is a hybrid, it consists of a case‐based reasoning (CBR) system and an argumentation framework, based on a multi‐agent system (MAS) architecture. The CBR system uses a series of metrics and similar cases to decide whether a job offer is likely to be recommended to a user. Besides, the argumentation framework extends the system with an argumentation CBR, through which old and similar cases can be obtained from the CBR system. Finally, a discussion process is established amongst the agents who debate using their experience from past cases to take a final decision.     

Phonon Polaritons in Monolayers of Hexagonal Boron Nitride

Phonon polaritons in van der Waals materials reveal significant confinement accompanied with long propagation length: important virtues for tasks pertaining to the control of light and energy flow at the nanoscale. While previous studies of phonon polaritons have relied on relatively thick samples, here reported is the first observation of surface phonon polaritons in single atomic layers and bilayers of hexagonal boron nitride (hBN). Using antenna‐based near‐field microscopy, propagating surface phonon polaritons in mono‐ and bilayer hBN microcrystals are imaged. Phonon polaritons in monolayer hBN are confined in a volume about one million times smaller than the free‐space photons. Both the polariton dispersion and their wavelength–thickness scaling law are altered compared to those of hBN bulk counterparts. These changes are attributed to phonon hardening in monolayer‐thick crystals. The data reported here have bearing on applications of polaritons in metasurfaces and ultrathin optical elements.     

Analysis of electricity consumption profiles in public buildings with dimensionality reduction techniques

The analysis of the daily electricity consumption profile of a building and its correlation with environmental factors makes it possible to examine and estimate its electricity demand. As an alternative to the traditional correlation analysis, a new approach is proposed to provide a detailed and visual analysis of the correlations between consumption and environmental variables. Since consumption profiles can be characterized by many components, the input space is high dimensional. For that reason, it is necessary to apply dimensionality reduction techniques that enable a projection of these data onto an easily interpretable 2D space. In this paper, several dimensionality reduction techniques are tested in order to determine the most appropriate one for the stated purpose. Later, the proposed approach uses the chosen algorithm to analyze the influence of the environmental variables on the electricity consumption in public buildings located at the University of León. Finally, electricity profiles from all buildings are compared with regard to two aspects, the magnitude and dynamics of the consumption.     

Optimising lossless stages in a GPU-based MPEG encoder

Modern GPUs excel in parallel computations, so they are an interesting target to perform matrix transformations such as the DCT, a fundamental part of MPEG video coding algorithms. Considering a system to encode synthetic video (e.g., computer-generated frames), this approach becomes even more appealing, since the images to encode are already in the GPU, eliminating the costs of transferring raw video from the CPU to the GPU. However, after a raw frame has been transformed and quantized by the GPU, the resulting coefficients must be reordered, entropy encoded and framed into the resulting MPEG bitstream. These last steps are essentially sequential and their straightforward GPU implementation is inefficient compared to CPU-based implementations. We present different approaches to implement part of these steps in GPU, aiming for a better usage of the memory bus, compensating the suboptimal use of the GPU with the gains in transfer time. We analyze three approaches to perform the zigzag scan and Huffman coding combining GPU and CPU, and two approaches to assemble the results to build the actual output bitstream both in GPU and CPU memory. Our experiments show that optimising the amount of data transferred from GPU to CPU implementing the last sequential compression steps in the GPU, and using a parallel fast scan implementation of the zigzag scanning improve the overall performance of the system. Savings in transfer time outweigh the extra cost incurred in the GPU.     

Forgetting as a way to avoid deception in a repeated imitation game

Adversarial decision making is aimed at determining optimal decision strategies to deal with an adaptive opponent. A clear example of such situation is the repeated imitation game presented here. Two agents compete in an adversarial model where one agent wants to learn how to imitate the actions taken by the other agent by means of the observation and memorization of the past actions. One defense against this adversary is to make decisions that are intended to confuse him. To achieve this, randomized strategies that change along time for one of the agents are proposed and their performance is analysed from both a theoretical and empirical point of view. We also study the ability of the imitator to avoid deception and adapt to a new behaviour by forgetting the oldest observations. The results confirm that wrong assumptions about the imitator’s behaviour lead to dramatic losses due to a failure in causing deception.     

Control theoretic optimization of 802.11 WLANs: Implementation and experimental evaluation

In 802.11 WLANs, adapting the contention parameters to network conditions results in substantial performance improvements. Even though the ability to change these parameters has been available in standard devices for years, so far no adaptive mechanism using this functionality has been validated in a realistic deployment. In this paper we report our experiences with implementing and evaluating two adaptive algorithms based on control theory, one centralized and one distributed, in a large-scale testbed consisting of 18 commercial off-the-shelf devices. We conduct extensive measurements, considering different network conditions in terms of number of active nodes, link qualities, and data traffic. We show that both algorithms significantly outperform the standard configuration in terms of total throughput. We also identify the limitations inherent in distributed schemes, and demonstrate that the centralized approach substantially improves performance under a large variety of scenarios, which confirms its suitability for real deployments.     

Diversity of the vomeronasal system in mammals: the singularities of the sheep model

The enormous morphological diversity and heterogeneity of the vomeronasal system (VNS) in mammals--as well as its complete absence in some cases--complicates the extrapolation of data from one species to another, making any physiological and functional conclusions valid for the whole Mammalian Class difficult and risky to draw. Some highly-evolved macrosmatic mammals, like sheep, have been previously used in interesting behavioral studies concerning the main and accessory olfactory systems. However, in this species, certain crucial morphological peculiarities have not until now been considered. Following histological, histochemical and immunohistochemical procedures, we have studied the vomeronasal organ (VNO) and the accessory olfactory bulb (AOB) of adult sheep. We have determined: (1) that all structures which classically define the VNO in mammals are present and well developed, providing the morphological basis for functional activity. (2) that, conversely, there is only a scant population of scattered mitral/tufted cells. One morphological consequence of both details is that the strata of the AOB in adult sheep are not as sharply defined as in other species; moreover, the small number of the mitral/tufted cells in the AOB may imply that the VNS of adult sheep is not capable of functioning in the way a well-developed VNS does in other species. (3) the zone to zone projection from the apical and basal sensory epithelium of the VNO to the anterior and posterior part of the AOB, respectively, typical in rodents, lagomorphs and marsupials, is not present in adult sheep.     

Iron and vitamin A deficiencies and prevalence of anemia in boys and girls between 6 to 24 months of age in Chaco,Argentina

To determine the prevalence of anemia, and iron (ID) and vitamin A deficiencies aiming at their prevention, 414 children between 6 and 24 months of age, were randomly selected from the whole province of Chaco. A sociodemographic survey was implemented, and hemoglobin (Hb), plasma ferritin and retinol were measured. Anemia prevalence (Hb < 110 g/L) was 66.4%, without differences between age groups, and included 18% with Hb < 90 g/L. These cases were significantly less in children 6-8 month of age (5.1%) than in the others (approximately equal to 20%) (P: 0.007). Mean Hb was also higher in 6-8 months old children and was associated with lower prevalence of ID (ferritin < 12 micrograms/L) (p < 0.000) but not with age (p = 0.8865). ID already present, however, in 36.6% of children in this age group, reached a prevalence of 72.9% in children older than 18 months. Anemia prevalence was significantly higher in males, in children whose birth weight was < 3000 g, in those who had never taken iron supplements and among the poor, both structural and by income. Retinol values < 20 micrograms/dl occurred only in 5.1% of children. Iron nutrition prior to, during pregnancy and in children during the first 2 years of life must be improved by joining strategies based on community empowerment aimed at improving dietary iron, assuring effective preventive supplementation and promoting the opportune umbilical cord ligation.     

Systolic neighborhood search on graphics processing units

In this paper, we propose a parallel processing model based on systolic computing merged with concepts of evolutionary algorithms. The proposed model works over a Graphics Processing Unit using the structure of threads as cells that form a systolic mesh. Data passes through those cells, each one performing a simple computing operation. The systolic algorithm is implemented using NVIDIA’s compute unified device architecture. To investigate the behavior and performance of the proposed model we test it over a NP-complete problem. The study of systolic algorithms on GPU and the different versions of the proposal show that our canonical model is a competitive solver with efficacy and presents a good scalability behavior across different instance sizes.