Photovoltaic energy prediction using machine learning techniques.

Solar energy is becoming one of the most promising power sources in residential, commercial, and industrial applications. Solar photovoltaic (PV) facilities use PV cells that convert solar irradiation into electric power. PV cells can be used in either standalone or grid-connected systems to supply power for home appliances, lighting, and commercial and industrial equipment. Managing uncertainty and fluctuations in energy production is a key challenge in integrating PV systems into power grids and using them as steady, standalone power sources. For this reason, it is very important to forecast solar energy power output. In this paper, we analyze and compare various methods to predict the production of photovoltaic energy for individual installations and network areas around the world, using statistical methods for time series and different machine learning techniques.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Online discussion forums with embedded streamed videos on distance courses

Existing literature on education and technology has frequently highlighted the usefulness of online discussion forums for distance courses; however, the majority of such investigations have focused their attention only on text-based forums. The objective of this paper is to determine if the embedding of streamed videos in online discussion forums generates educational dialogue and consequently the feedback that students need in a Management Accounting Course. The findings suggest some interesting issues, such as: students prefer text answers except in complex questions, and videos never replace text commentaries and explanations, but rather complement themPeer Reviewe

Carbon Emission Evaluation of CO2 Curing in Vibro-Compacted Precast Concrete Made with Recycled Aggregates

The objective of the present study was to explore three types of vibro-compacted precast concrete mixtures replacing fine and coarse gravel with a recycled/mixed concrete aggregate (RCA or MCA). The portlandite phase found in RCA and MCA by XRD is a “potential” CO2 sink. CO2 curing improved the compressive strength in all the mixtures studied. One tonne of the mixtures studied could be decarbonised after only 7 days of curing 13,604, 36,077 and 24,635 m3 of air using natural aggregates, RCA or MCA, respectively. The compressive strength obtained, XRD, TGA/DTA and carbon emission evaluation showed that curing longer than 7 days in CO2 was pointless. The total CO2 emissions by a mixture using CO2 curing at 7 days were 221.26, 204.38 and 210.05 kg CO2 eq/m3 air using natural aggregates, RCA or MCA, respectively. The findings of this study provide a valuable contribution to carbon emission evaluation of CO2 curing in vibro-compacted precast concrete with recycled/mixed concrete aggregates (RCA or MCA). The technology proposed in this research facilitates carbon capture and use and guarantees enhanced compressive strength of the concrete samples

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals

Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our objective was to identify those factors for HIV/HCV co-infected patients (to which clinicians have given careful consideration before treatment uptake) that have not being included among the prioritisation criteria. This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. An evolutionary algorithm was used to determine the architecture and estimate the coefficients of the model. This machine learning methodology found that radial basis neural networks provided a very simple model in terms of the number of patient characteristics to be considered by the classifier (in this case, six), returning a good overall classification accuracy of 0.767 and a minimum sensitivity (for the classification of the minority class, untreated patients) of 0.550. Finally, the area under the ROC curve was 0.802, which proved to be exceptional. The parsimony of the model makes it especially attractive, using just eight connections. The independent variable "recent PWID" is compulsory due to its importance. The simplicity of the model means that it is possible to analyse the relationship between patient characteristics and the probability of belonging to the treated group

The Effect of Acanthocardia tuberculata Shell Powder as Filler on the Performance of Self-Compacting Mortar

In this research, the feasibility of using Acanthocardia tuberculata shell waste from the canning industry in the manufacturing of self-compacting mortar (SCM) was tested. The seashells were finely ground to be used as filler instead of the limestone filler normally used in this type of SCM. First, a physicochemical and microstructural characterisation of all raw materials was carried out, including the particle size distribution of both fillers. Subsequently, the self-compactability properties in the fresh state of SCM were evaluated using a total substitution by volume of limestone filler for seashell powder, using different self-compactiblity parameters. The mineralogical phases of all the SCM tested were identified once hardened by means of X-ray diffraction technique, thermogravimetric and differential thermal analysis. In addition, the mechanical properties, water absorption capacity, dry bulk density and accessible porosity of water of hardened mortars at 28 days of curing were analysed. The effect of replacing limestone filler by Acanthocardia tuberculata filler resulted in a decrease in compressive strength of 29.43, 16.84 and 2.29%, respectively. The results indicate that it is possible to completely replace natural limestone filler with Acanthocardia tuberculata shell filler without significantly affecting the mechanical properties of SCM

Parallel proccessing applied to object detection with a Jetson TX2 embedded system.

Video streams from panoramic cameras represent a powerful tool for automated surveillance systems, but naïve implementations typically require very intensive computational loads for applying deep learning models for automated detection and tracking of objects of interest, since these models require relatively high resolution to reliably perform object detection. In this paper, we report a host of improvements to our previous state-of-the-art software system to reliably detect and track objects in video streams from panoramic cameras, resulting in an increase in the processing framerate in a Jetson TX2 board, with respect to our previous results. Depending on the number of processes and the load profile, we observe up to a five-fold increase in the framerate.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Myeloid-derived suppressor cells are increased in lung transplant recipients and regulated by immunosuppressive therapy

Lung transplantation remains as a primary treatment for end-stage lung diseases. Although remarkable improvement has been achieved due to the immunosuppressive protocols, long-term survival for lung transplant recipients (LTR) is still limited. In the last few decades, an increasing interest has grown in the study of dysregulation of immune mechanisms underlying allograft failure. In this regard, myeloid-derived suppressor cells (MDSCs) could play an important role in the promotion of graft tolerance due to their immune regulatory function. Here, we describe for the first time circulating subsets MDSCs from LTR at several time points and we evaluate the relationship of MDSCs with sort-term lung transplant outcomes. Although no effect of MDSCs subsets on short-term clinical events was observed, our results determine that Mo-MDSCs frequencies are increased after acute cellular rejection (ACR), suggesting a possible role for Mo-MDSCs in the development of chronic lung allograft dysfunction (CLAD). Therefore, whether MDSCs subsets play a role as biomarkers of chronic rejection remains unknown and requires further investigations. Also, the effects of the different immunosuppressive treatments on these subpopulations remain under research and further studies are needed to establish to what extend MDSCs immune modulation could be responsible for allograft acceptance.FUNDING: This work was supported by grants from the FIS-ISCII (PI16/ 01585) to ML-H and NVAL16/22 to DS. ACKNOWLEDGMENTS We are grateful to María José Ortı́z González (IDIVAL, Santander, Spain) for her excellent technical support. ACKNOWLEDGMENTS: We are grateful to María José Ortı́z González (IDIVAL, Santander, Spain) for her excellent technical support

BAMBI (bone morphogenetic protein and activin membrane-bound inhibitor) reveals the involvement of the transforming growth factor-beta family in pain modulation

Transforming growth factors- (TGF- s) signal through type I and type II serine–threonine kinase receptor complexes. During ligand binding, type II receptors recruit and phosphorylate type I receptors, triggering downstream signaling. BAMBI [bone morphogenetic protein (BMP) and activin membrane-bound inhibitor] is a transmembrane pseudoreceptor structurally similar to type I receptors but lacks the intracellular kinase domain. BAMBI modulates negatively pan-TGF- family signaling; therefore, it can be used as an instrument for unraveling the roles of these cytokines in the adult CNS. BAMBI is expressed in regions of the CNS involved in pain transmission and modulation. The lack of BAMBI in mutant mice resulted in increased levels of TGF- signaling activity, which was associated with attenuation of acute pain behaviors, regardless of the modality of the stimuli (thermal, mechanical, chemical/inflammatory). The nociceptive hyposensitivity exhibited by BAMBI / mice was reversed by the opioid antagonist naloxone. Moreover, in a model of chronic neuropathic pain, the allodynic responses of BAMBI / mice also appeared attenuated through a mechanism involving -opioid receptor signaling. BasalmRNAand protein levels of precursor proteins of the endogenous opioid peptides proopiomelanocortin (POMC) and proenkephalin (PENK) appeared increased in the spinal cords of BAMBI / . Transcript levels of TGF- s and their intracellular effectors correlated directly with genes encoding opioid peptides, whereas BAMBI correlated inversely. Furthermore, incubation of spinal cord explants with activin A or BMP-7 increased POMC and/or PENK mRNA levels. Our findings identify TGF- family members as modulators of acute and chronic pain perception through the transcriptional regulation of genes encoding the endogenous opioids

Silver-Free Gold-Catalyzed Heterocyclizations through Intermolecular H-Bonding Activation

Modulable monosulfonyl squaramides have been shown to exert activation of gold(I) chloride complexes through H-bonding in an intermolecular way. Combinations of (PPh3)AuCl or IPrAuCl complexes and an optimal sulfonyl squaramide cocatalyst bearing two 3,5-bis(trifluoromethyl)phenyl groups efficiently catalyzed diverse heterocyclizations and a cyclopropanation reaction, avoiding in all cases undesired side reactions. Computational studies indicate that the Au–Cl bond breaks by transligation to the triple bond in a ternary complex formed by the actual AuCl···HBD catalyst and the substrate