ALBERT

Description: In this work, we present a simple algorithm to calculate automatically the Fourier spectrum of a Sinusoidal Pulse Width Modulation Signal (SPWM). Modulated voltage signals of this kind are used in industry by speed drives to vary the speed of alternating current motors while maintaining a smooth torque. Nevertheless, the SPWM technique produces undesired harmonics, which yield stator heating and power losses. By monitoring these signals without human interaction, it is possible to identify the harmonic content of SPWM signals in a fast and continuous manner. The algorithm is based in the autocorrelation function, commonly used in radar and voice signal processing. Taking advantage of the symmetry properties of the autocorrelation, the algorithm is capable of estimating half of the period of the fundamental frequency; thus, allowing one to estimate the necessary number of samples to produce an accurate Fourier spectrum. To deal with the loss of samples, i.e., the scan backlog, the algorithm iteratively acquires and trims the discrete sequence of samples until the required number of samples reaches a stable value. The simulation shows that the algorithm is not affected by either the magnitude of the switching pulses or the acquisition noise.

Description: Along with being a dynamic process that affects large areas, desertification is also one of the most serious problems in many countries. The effects of this phenomenon threaten the sustainability of natural resources, namely water resources, agricultural production and major basic infrastructure, specifically roads and habitations. Several factors exacerbate this phenomenon such as the climate dryness, the geological and morphological characteristics of the terrain, the irrational use of space, population growth and the over-exploitation of vegetation and water resources. This work aims to evaluate the desertification index in the Oued-El-Maleh watershed, through the integration of key factors involved in the MEDALUS model (Mediterranean Desertification and Land Use) within a GIS. The model includes among its indexes: climate, vegetation, soil and management. Each index was obtained by the combination of sub-indexes. All the factors, measured and integrated into a geographic information system, enabled us to spatialize, on a synthetic map, the degree of the desertification effect throughout the watershed. This map is a managing tool available for decision-making regarding the selection of priority areas in the fight against desertification. High sensitivity to desertification class represents only 35% of the watershed. This class is concentrated in the north of the study area that corresponds to plains and low altitude. This could be explained by the dominance of agro-pastoral activity and the presence of a big population pressure.

Description: Due to their image-based nature, “contextual” approaches are very attractive to estimate evapotranspiration (ET) from remotely-sensed land surface temperature (LST) data. Their application is however limited to highly heterogeneous areas where the soil and vegetation temperature endmembers (Tends) can be observed at the thermal sensor resolution. This paper aims to develop a simple theoretical approach to estimate Tends independently from LST images. Soil Tends are simulated by a soil energy balance model forced by meteorological data. Vegetation Tends are obtained from soil Tends and air temperature. Model-derived soil Tends are first evaluated with in situ measurements made over an irrigated area in Morocco. The root mean square difference (RMSD) between modeled and ground-based soil Tends is estimated as 2.4 ºC. Model-derived soil Tends are next compared with the soil Tends retrieved from 90-m resolution ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data collected over two irrigated areas in Mexico and Spain. Such a comparison reveals a strong consistency between model-derived and high-resolution image-based soil Tends. A recent contextual ET model (SEB-1S) is then applied to 90-m resolution and to 1-km resolution (aggregated) ASTER data using the model-derived or image-based Tends as the input. The RMSD between 90-m resolution SEB-1S and in situ ET is estimated as 65 and 82 W-m2, and the RMSD between 1-km resolution SEB-1S and aggregated SEB-1S ET is estimated as 78 and 56 W-m2 for the image-based and model-derived Tends, respectively. In light of the above results, Tends should be estimated a priori when contextual models are applied to low resolution images. Moreover, the consistency over highly heterogeneous areas between model-derived and high-resolution image-based Ten

Description: We described the occult bacteremia (OB) and bacteremia with diagnosed focus (BwF) picture among children managed as outpatients at the pediatric emergency room (PER) in southern Israel, before and after the introduction of pneumococcal conjugate vaccines (PCVs) introduction in a retrospective study enrolling all three- to 36-month-old patients with fever >38.0 °C during 2005–2014. Of 511 (0.82% of all febrile patients) true bacteremias, 230 (45%) were managed as outpatients; 96 of 230 (41.7%) had OB and 134 (3.59%) had BwF. OB and BwF rates were 0.22% and 3.02%, respectively. A significant decrease was noted in OB and BwF rates (p = 0.0008 and p = 0.02, respectively). S. pneumoniae (SP, 37.5%), K. kingae (11.4%) and Brucella spp. (8.7%) were the most common OB pathogens and SP (29.8%), S. viridans (13.4%), and Brucella spp. (12.7%) were the most common in BwF patients. PCV13 serotypes were not found among the serotypes isolated post-PCV13 introduction. During 2010–2014 there was an increase in non-PCV13 serotype isolation (p = 0.005). SP was the main pathogen isolated among patients with pneumonia, acute otitis media (AOM) and periorbital cellulitis (62.5%, 33.3% and 60%, respectively). OB and BwF decreased following the introduction of PCVs and SP was the main pathogen in both conditions. Vaccine-SP serotypes were not isolated in OB after PCV13 introduction and non-vaccine serotypes increased significantly.

Description: Modeling and mapping of soil properties has been identified as key for effective land degradation management and mitigation. The ability to model and map soil properties at sufficient accuracy for a large agriculture area is demonstrated using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Soil samples were collected in the El-Tina Plain, Sinai, Egypt, concurrently with the acquisition of ASTER imagery, and measured for soil electrical conductivity (ECe), clay content and soil organic matter (OM). An ASTER image covering the study area was preprocessed, and two predictive models, multivariate adaptive regression splines (MARS) and the partial least squares regression (PLSR), were constructed based on the ASTER spectra. For all three soil properties, the results of MARS models were better than those of the respective PLSR models, with cross-validation estimated R2 of 0.85 and 0.80 for ECe, 0.94 and 0.90 for clay content and 0.79 and 0.73 for OM. Independent validation of ECe, clay content and OM maps with 32 soil samples showed the better performance of the MARS models, with R2 = 0.81, 0.89 and 0.73, respectively, compared to R2 = 0.78, 0.87 and 0.71 for the PLSR models. The results indicated that MARS is a more suitable and superior modeling technique than PLSR for the estimation and mapping of soil salinity (ECe), clay content and OM. The method developed in this paper was found to be reliable and accurate for digital soil mapping in arid and semi-arid environments.

Description: We present the first comparison between new fAPAR and LAI products derived from the GlobAlbedo dataset and the widely-used MODIS fAPAR and LAI products. The GlobAlbedo-derived products are produced using a 1D two-stream radiative transfer (RT) scheme designed explicitly for global parameter retrieval from albedo, with consistency between RT model assumptions and observations, as well as with typical large-scale land surface model RT schemes. The approach does not require biome-specific structural assumptions (e.g., cover, clumping, understory), unlike more detailed 3D RT model approaches. GlobAlbedo-derived values of fAPAR and LAI are compared with MODIS values over 2002–2011 at multiple flux tower sites within selected biomes, over 1200 × 1200 km regions and globally. GlobAlbedo-derived fAPAR and LAI values are temporally more stable than the MODIS values due to the smoothness of the underlying albedo, derived via optimal estimation (assimilation) using an a priori estimate of albedo derived from an albedo “climatology” (composited multi-year albedo observations). Parameters agree closely in timing but with GlobAlbedo values consistently lower than MODIS, particularly for LAI. Larger differences occur in winter (when values are lower) and in the Southern hemisphere. Globally, we find that: GlobAlbedo-derived fAPAR is ~0.9–1.01 × MODIS fAPAR with an intercept of ~0.03; GlobAlbedo-derived LAI is ~0.6 × MODIS LAI with an intercept of ~0.2. Differences arise due to the RT model assumptions underlying the products, meaning care is required in interpreting either set of values, particularly when comparing to fine-scale ground-based estimates. We present global transformations between GlobAlbedo-derived and MODIS products.

Description: Although graphene and its derivatives have been proven to be suitable for several biomedical applications such as for cancer therapy and biosensing, the use of graphene for stem cell research is a relatively new area that has only recently started to be investigated. For stem cell applications, graphene has been utilized by itself or in combination with other types of materials such as nanoparticles, nanofibers, and polymer scaffolds to take advantage of the several unique properties of graphene, such as the flexibility in size, shape, hydrophilicity, as well as its excellent biocompatibility. In this review, we will highlight a number of previous studies that have investigated the potential of graphene or its derivatives for stem cell applications, with a particular focus on guiding stem cell differentiation into specific lineages (e.g., osteogenesis, neurogenesis, and oligodendrogenesis), promoting stem cell growth, stem cell delivery/transplantation, and effective monitoring of their differentiation. We hope that this review promotes and accelerates the use of graphene-based materials for regenerative therapies, especially for stem cell-based approaches to cure various incurable diseases/disorders such as neurological diseases (e.g., Alzheimer’s disease and Parkinson’s disease), stroke, spinal cord injuries, bone/cartilage defects, and cardiovascular diseases.

Description: Future Internet, Vol. 10, Pages 93: Proactive Caching at the Edge Leveraging Influential User Detection in Cellular D2D Networks Future Internet doi: 10.3390/fi10100093 Authors: Anwar Said Syed Waqas Haider Shah Hasan Farooq Adnan Noor Mian Ali Imran Jon Crowcroft Caching close to users in a radio access network (RAN) has been identified as a promising method to reduce a backhaul traffic load and minimize latency in 5G and beyond. In this paper, we investigate a novel community detection inspired by a proactive caching scheme for device-to-device (D2D) enabled networks. The proposed scheme builds on the idea that content generated/accessed by influential users is more probable to become popular and thus can be exploited for pro-caching. We use a Clustering Coefficient based Genetic Algorithm (CC-GA) for community detection to discover a group of cellular users present in close vicinity. We then use an Eigenvector Centrality measure to identify the influential users with respect to the community structure, and the content associated to it is then used for pro-active caching using D2D communications. The numerical results show that, compared to reactive caching, where historically popular content is cached, depending on cache size, load and number of requests, up to 30% more users can be satisfied using a proposed scheme while achieving significant reduction in backhaul traffic load.

Description: The Riemannian geometry of the space Pm, of m × m symmetric positive definite matrices, has provided effective tools to the fields of medical imaging, computer vision and radar signal processing. Still, an open challenge remains, which consists of extending these tools to correctly handle the presence of outliers (or abnormal data), arising from excessive noise or faulty measurements. The present paper tackles this challenge by introducing new probability distributions, called Riemannian Laplace distributions on the space Pm. First, it shows that these distributions provide a statistical foundation for the concept of the Riemannian median, which offers improved robustness in dealing with outliers (in comparison to the more popular concept of the Riemannian center of mass). Second, it describes an original expectation-maximization algorithm, for estimating mixtures of Riemannian Laplace distributions. This algorithm is applied to the problem of texture classification, in computer vision, which is considered in the presence of outliers. It is shown to give significantly better performance with respect to other recently-proposed approaches.

Description: Sensors, Vol. 18, Pages 3037: Fecal Volatile Organic Compounds in Preterm Infants Are Influenced by Enteral Feeding Composition Sensors doi: 10.3390/s18093037 Authors: Sofia el Manouni el Hassani Hendrik J. Niemarkt Hager Said Daniel J. C. Berkhout Anton H. van Kaam Richard A. van Lingen Marc A. Benninga Nanne K. H. de Boer Tim G. J. de Meij Fecal volatile organic compound (VOC) analysis has shown great potential as a noninvasive diagnostic biomarker for a variety of diseases. Before clinical implementation, the factors influencing the outcome of VOC analysis need to be assessed. Recent studies found that the sampling conditions can influence the outcome of VOC analysis. However, the dietary influences remains unknown, especially in (preterm) infants. Therefore, we assessed the effects of feeding composition on fecal VOC patterns of preterm infants (born at <30 weeks gestation). Two subgroups were defined: (1) daily intake >75% breastmilk (BM) feeding and (2) daily intake >75% formula milk (FM) feeding. Fecal samples, which were collected at 7, 14 and 21 days postnatally, were analyzed by an electronic nose device (Cyranose 320®). In total, 30 preterm infants were included (15 FM, 15 BM). No differences in the fecal VOC patterns were observed at the three predefined time-points. Combining the fecal VOC profiles of these time-points resulted in a statistically significant difference between the two subgroups although this discriminative accuracy was only modest (AUC [95% CI]; p-value; sensitivity; and specificity of 0.64 [0.51–0.77]; 0.04; 68%; and 51%, respectively). Our results suggest that the influence of enteral feeding on the outcome of fecal VOC analysis cannot be ignored in this population. Furthermore, in both subgroups, the fecal VOC patterns showed a stable longitudinal course within the first month of life.