Torque control strategy for an axial flux switched reluctance machine

This paper reflects the work done to design a torque control strategy for an axial flux switched reluctance machine. The general electrical model is first presented but as the switched reluctance machine behaves nonlinearly1 a (three-dimensional) finite element method characterization is performed, so the nonlinearity may be considered. Once the machine is characterized in FEM a Simulink model is developed where a torque control strategy is proposed. Then, both the machine and the control are experimentally tested. The control setting, and the obtained real performance results are also presented in this document. Finally, the most outstanding conclusions about the control strategy are captured. Main difficulties encountered during the implementation of the control strategy are also collected

A Certification Framework for Cloud Security Properties: The Monitoring Path

In this paper we describe the structure and functionality of a certification integrated framework aimed to support the certification of security properties of a Cloud infrastructure (IaaS), a platform (PaaS), or the software layer (SaaS). Such framework will bring service users, service providers and cloud suppliers to work together with certification authorities in order to ensure security properties and certificates validity in the continuously evolving cloud environment. For this purpose, the framework relies on multiple types of evidence gathering with respect to security, e.g., testing services, monitoring agents or trusted computing proofs. In this paper we will focus only on the monitoring case and will illustrate its use. Yet, this framework is designed to be able to follow models for hybrid, incremental and multi-layer security certification since cloud security has to build upon the entire cloud stack

Linking thermal imaging and soil remote sensing to enhance irrigation management of sugar beet

The use of reliable information and data that are rapidly and easily acquired is essential for farm water management and appropriate irrigation strategies. Over the past decade, new advances have been made in irrigation technology, such as platforms that continuously transmit data between irrigation controllers and field sensors, mobile apps, and equipment for variable rate irrigation. In this study, images captured with a thermal imaging camera mounted on an unmanned aerial vehicle (UAV) were used to evaluate the water status of sugar beet plants in a plot with large spatial variability in terms of soil properties. The results were compared with those of soil moisture measurements. No direct relationship was observed between the water status of the soil and that of the crops. However, the fresh root mass and sugar content tended to decrease when higher levels of water stress were detected in the crop using thermal imaging, with coefficients of determination of 0.28 and 0.94 for fresh root mass and sugar content, respectively. Differences were observed be tween different soil types, and therefore different irrigation strategies are needed in highly heterogeneous plots

Plasma cytokines as potential biomarkers of kidney damage in patients with systemic lupus erythematosus

Background: Systemic lupus erythematosus is a heterogeneous chronic inflammatory autoimmune disorder characterized by an exacerbated expression of cytokines and chemokines in different tissues and organs. Renal involvement is a significant contributor to the morbidity and mortality of systemic lupus erythematosus, and its diagnosis is based on renal biopsy, an invasive procedure with a high risk of complications. Therefore, the development of alternative, non-invasive diagnostic tests for kidney disease in patients with systemic lupus erythematosus is a priority. Aim: To evaluate the plasma levels of a panel of cytokines and chemokines using multiplex xMAP technology in a cohort of Colombian patients with active and inactive systemic lupus erythematosus, and to evaluate their potential as biomarkers of renal involvement. Results: Plasma from 40 systemic lupus erythematosus non-nephritis patients and 80 lupus nephritis patients with different levels of renal involvement were analyzed for 39 cytokines using Luminex xMAP technology. Lupus nephritis patients had significantly increased plasma eotaxin, TNF-a, interleukin-17-a, interleukin-10, and interleukin-15 as compared to the systemic lupus erythematosus non-nephritis group. Macrophage-derived chemokine, growth regulated oncogene alpha, and epidermal growth factor were significantly elevated in systemic lupus erythematosus non-nephritis patients when compared to lupus nephritis individuals. Plasma eotaxin levels allowed a discrimination between systemic lupus erythematosus non-nephritis and lupus nephritis patients, for which we performed a receiver operating characteristic curve to confirm. We observed a correlation of eotaxin levels with active nephritis (Systemic Lupus Erythematosus Disease Activity Index). Our data indicate that circulating cytokines and chemokines could be considered good predictors of renal involvement in individuals with systemic lupus erythematosus

Relative equilibria and bifurcations in the generalized van der Waals 4-D oscillator

A uniparametric 4-DOF family of perturbed Hamiltonian oscillators in 1:1:1:1 resonance is studied as a generalization for several models for perturbed Keplerian systems. Normalization by Lie-transforms (only first order is considered here) as well as geometric reduction related to the invariants associated to the symmetries is used based on previous work of the authors. A description is given of the lower dimensional relative equilibria in such normalized systems. In addition bifurcations of relative equilibria corresponding to three dimensional tori are studied in some particular cases where we focus on Hamiltonian Hopf bifurcations and bifurcations in the 3-D van der Waals and Zeeman systems

Leaf area index estimations by deep learning models using RGB images and data fusion in maize

The leaf area index (LAI) is a biophysical crop parameter of great interest for agronomists and plant breeders. Direct methods for measuring LAI are normally destructive, while indi rect methods are either costly or require long pre- and post-processing times. In this study, a novel deep learning-based (DL) model was developed using RGB nadir-view images taken from a high-throughput plant phenotyping platform for LAI estimation of maize. The study took place in a commercial maize breeding trial during two consecutive grow ing seasons. Ground-truth LAI values were obtained non-destructively using an allometric relationship that was derived to calculate the leaf area of individual leaves from their main leaf dimensions (length and maximum width). Three convolutional neural network (CNN)- based DL model approaches were proposed using RGB images as input. One of the models tested is a classifcation model trained with a set of RGB images tagged with previously measured LAI values (classes). The second model provides LAI estimates from CNN based linear regression and the third one uses a combination of RGB images and numeri cal data as input of the CNN-based model (multi-input model). The results obtained from the three approaches were compared against ground-truth data and LAI estimations from a classic indirect method based on nadir-view image analysis and gap fraction theory. All DL approaches outperformed the classic indirect method. The multi-input_model showed the least error and explained the highest proportion of the observed LAI variance. This work represents a major advance for LAI estimation in maize breeding plots as compared to pre vious methods, in terms of processing time and equipment costs

Age-dependent changes in insulin-like immunoreactivity in rat submandibular salivary glands.

In recent years, a growing interest had arisen in hormonal factors in salivary glands. We have investigated the changes in the content of an insulin-like immunoreactive (ILI) compound in the submandibular salivary glands of Sprague Dawley rats during physiological aging, in the range 15 days-27 months. The amount of ILI in the submandibular glands of young adult rats was found to be doubled in the post-natal period until the age of puberty and was maintained in senescence. No significant correlation was found between age-dependent variations in ILI levels of submandibular salivary glands and circulating insulin concentrations, further supporting previous indications that ILI is being synthesized in situ. It is possible that ILI could exert paracrine effects within the glands, as regards the development of other glandular structures during the first months of life, as well as the preservation of glandular function in senescent animals as well

Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV

Accurate and early estimation of citrus yields is important for both producers and agricultural cooperatives to be competitive and make informed decisions when selling their products. Yield estimation is key for predicting stock volumes, avoiding stock ruptures and planning harvesting operations. Visual yield estimations have tra ditionally been employed, resulting in inaccurate and misleading information. The main goal of this study was to develop an automated image processing methodology to detect, count and estimate the size of citrus fruits on individual trees using deep learning techniques. During 3 consecutive annual campaigns, a total of 20 trees from a commercial citrus grove were monitored using images captured from an unmanned aerial vehicle (UAV). These trees were harvested manually, and fruit sizes were measured. A Faster R-CNN Deep Learning model was trained using a custom dataset to detect oranges in the obtained images. An average standard error (SE) of 6.59 % was obtained between visual counting and the model’s fruit detection. Using the detected fruits, fruit size estimation was also performed. The promising results obtained indicate that this size estimation method can be employed for size discrimination prior to harvest. A model based on Long Short-term Memory (LSTM) was trained for yield estimation per tree and for a total yield estimation. The actual and estimated yields per tree were compared, resulting in an approximate error of SE = 4.53 % and a standard deviation of SD = 0.97 Kg. The actual total yield, the estimated total yield and the total yield estimated by an expert technician were compared. The error in the estimation by the technician was SE = 13.74 %, while the errors in the model were SE = 7.22 % and SD = 4083.58 Kg. These promising results demonstrate the potential of the present technique to provide yield esti mates for citrus fruits or even other types of fruit

Visual population receptive fields in people with schizophrenia have reduced inhibitory surrounds

People with schizophrenia (SZ) experience abnormal visual perception on a range of visual tasks, which have been linked to abnormal synaptic transmission and an imbalance between cortical excitation and inhibition. However differences in the underlying architecture of visual cortex neurons, which might explain these visual anomalies, have yet to be reported in vivo. Here, we probe the neural basis of these deficits by using functional MRI (fMRI) and population receptive field (pRF) mapping to infer properties of visually responsive neurons in people with SZ. We employed a Difference-of-Gaussian (DoG) model to capture the centre-surround configuration of the pRF, providing critical information about the spatial scale of the pRFs inhibitory surround. Our analysis reveals that SZ is associated with reduced pRF size in early retinotopic visual cortex as well as a reduction in size and depth of the inhibitory surround in V1, V2 and V4. We consider how reduced inhibition might explain the diverse range of visual deficits reported in SZ. SIGNIFICANCE STATEMENT: People with schizophrenia (SZ) experience abnormal perception on a range of visual tasks, which has been linked to abnormal synaptic transmission and an imbalance between cortical excitation/inhibition. However associated differences in the underlying architecture of visual cortex neurons have yet to be reported in vivo. We used fMRI and population receptive field (pRF) mapping to demonstrate that the fine-grained functional architecture of visual cortex in people with SZ differs from unaffected controls. SZ is associated with reduced pRF size in early retinotopic visual cortex, largely due to reduced inhibitory surrounds. An imbalance between cortical excitation and inhibition could drive such a change in the centre-surround pRF configuration, and ultimately explain the range of visual deficits experienced in SZ

CONTRIBUCIÓN AL ESTUDIO LIQUENOLÓGICO DE ANDALUCIA OCCIDENTAL, 11. COMUNIDADES SOBRE GRANITOIDES EN LA ZONA MÁS TÉRMICA DE LA PROVINCIA DE SEVILLA

Four localities (Gerena, Guillena. Lora del Rio and Almadén de la Plata) from Sevilla district have been studied in detail. The results are presented of 49 relévés which represent the lichen vegetation of these areas. The communities on sunny and exposed to rain surfaces (PurmelieRhizocurpefum tetrasporii), sunny and sheltered surfaces (Acarosporelum epithallinohilaris), shady and variously exposed to rain surfaces (Lusallielum pustulafrie and community of Pertusuria leucosora) and runoff surfaces (Peltuletum euplocae) are given.Se han explorado con detalle cuatro localidades de la provincia de Sevilla (Cierena, Ciuillena, Lora del Río y Almadén de la Plata). De los inventarias levantados en el campo, se transcriben en este trabajo 49 de ellos, por ser los que mejor definen la vegetación liquénica. Se estudian las comunidades de superficie soleadas totalmente abiertas a la lluvia (Parmelio Rhizocarpetumle trasporii), superficies soleadas pero protegidas de la lluvia (Lasallieturn pustulutae y comunidades con Pertusariu leucosora). y por último se estudian las comunidades de supsrficies tle escorrentía (Pelluletum euplocue)