Evaluación de la asociación agroforestal caoba (Swetenia Macrophylla King) y cacao (Theobroma cacao L.), implementados en el municipio de Tumaco, Nariño

El estudio se realizó en las coordenadas: 1°42´16.51” latitud norte y a 78°40´40.53” longitud oeste, en el municipio de Tumaco - Nariño, al sur oeste de Colombia, donde se evaluó el comportamiento biológico del sistema agroforestal caoba (Swetenia Macrophylla King) y cacao (Theobroma cacao L.) a los siete años de establecido, bajo un diseño de bloques completamente al azar, con seis tratamientos y tres repeticiones. Se tomaron 5 unidades experimentales por sitio de cada componente. El caoba presento diferencias estadísticas significativas para las variables altura de árbol, el (T5) presento el mejor comportamiento con 11.97 m; para DAP el mejor comportamiento fue para el (T5) con 76.43cm y en relación al área de copa el mejor resultado fue para el (T5) con 20.07 m2 ; en cuanto a la variable estado fitosanitario no se vio comprometido en ningún aspecto, ni siquiera por barrenador de tallo (Hypsipyla grandella), que es el principal problema para el caoba en la zona, debido a que ataca a los árboles en las etapas más jóvenes. Con respecto a el cacao el ANAVA, presento diferencias estadísticas significativas para las variables altura de árbol, en donde el (T5) presento el mejor comportamiento con 4.08 m y el índice de mazorca que indica como mejor resultado el (T5) con 24.39 mazorcas para formar un kg de cacao seco; por otra parte el ANAVA evidencia diferencias estadísticas altamente significativas para las variables número de mazorcas formadas por árbol, estableciendo como mejor tratamiento el (T6) con 13.87 mazorcas por árbol, por ultimo para estado fitosanitario se observó que el (T6) presento el mejor comportamiento con 17,33%; para las variables diámetro de tallo e índice presentaron diferencias entre los tratamientos estudiados. Se puede deducir que el sistema agroforestal puede ser viable biológicamente, pero se debe tener en cuenta el comportamiento del cacao a diferentes distancias de siembra, de acuerdo a la presente evaluación los mejores resultados fueron para los tratamientos con las mayores distancias para caoba

Detecting broken Absorber Tubes in CSP plants using intelligent sampling and dual loss

Concentrated solar power (CSP) is one of the growing technologies that is leading the process of changing from fossil fuels to renewable energies. The sophistication and size of the systems require an increase in maintenance tasks to ensure reliability, availability, maintainability and safety. Currently, automatic fault detection in CSP plants using Parabolic Trough Collector systems evidences two main drawbacks: 1) the devices in use needs to be manually placed near the receiver tube, 2) the Machine Learning-based solutions are not tested in real plants. We address both gaps by combining the data extracted with the use of an Unmaned Aerial Vehicle, and the data provided by sensors placed within 7 real plants. The resulting dataset is the first one of this type and can help to standardize research activities for the problem of fault detection in this type of plants. Our work proposes supervised machine-learning algorithms for detecting broken envelopes of the absorber tubes in CSP plants. The proposed solution takes the class imbalance problem into account, boosting the accuracy of the algorithms for the minority class without harming the overall performance of the models. For a Deep Residual Network, we solve an imbalance and a balance problem at the same time, which increases by 5% the Recall of the minority class with no harm to the F1-score. Additionally, the Random Under Sampling technique boost the performance of traditional Machine Learning models, being the Histogram Gradient Boost Classifier the algorithm with the highest increase (3%) in the F1-Score. To the best of our knowledge, this paper is the first providing an automated solution to this problem using data from operating plants

Cavity losses estimation in CSP applications

AIP Conference Proceedings, 2033, Nov. 2018, Article number 210007-1-210007-8Estimations of convection and radiation cavity losses in two common CSP applications have been analyzed; a cavity in a solar tower plant for high temperature (800 K) and in a down facing cavity in a Fresnel configuration for medium temperature (350 K) applications. An analysis regarding the effect of the configuration, geometry and the presence of wind has been also carried out.Ministerio de Ciencia e Innovación MTM2015-65608-PJunta de Andalucía Consejería de Economía y Conocimiento P12-FQM-1658Ministerio de Economía, Industria y Competitividad DPI2016-78887-C3-1-

Neutrino induced weak pion production off the nucleon

We study neutrino-induced one-pion production off the nucleon in and around the Delta resonance region. A part from the Delta-pole mechanism we include background terms required by chiral symmetry. These background terms give size able contributions in all channels. To better reproduce the ANL q(2)-differential cross section data, we make a new fit of the C-5(A)(q(2)) axial nucleon to Delta form factor. The new result C-5(A)(0) = 0.867 +/- 0.075 is some 30% smaller than the commonly accepted value. This correction is compatible with most quark model estimates and a recent lattice calculation.(1

Automatic cerebral hemisphere segmentation in rat MRI with lesions via attention-based convolutional neural networks

We present MedicDeepLabv3+, a convolutional neural network that is the first completely automatic method to segment cerebral hemispheres in magnetic resonance (MR) volumes of rats with lesions. MedicDeepLabv3+ improves the state-of-the-art DeepLabv3+ with an advanced decoder, incorporating spatial attention layers and additional skip connections that, as we show in our experiments, lead to more precise segmentations. MedicDeepLabv3+ requires no MR image preprocessing, such as bias-field correction or registration to a template, produces segmentations in less than a second, and its GPU memory requirements can be adjusted based on the available resources. We optimized MedicDeepLabv3+ and six other state-of-the-art convolutional neural networks (DeepLabv3+, UNet, HighRes3DNet, V-Net, VoxResNet, Demon) on a heterogeneous training set comprised by MR volumes from 11 cohorts acquired at different lesion stages. Then, we evaluated the trained models and two approaches specifically designed for rodent MRI skull stripping (RATS and RBET) on a large dataset of 655 MR rat brain volumes. In our experiments, MedicDeepLabv3+ outperformed the other methods, yielding an average Dice coefficient of 0.952 and 0.944 in the brain and contralateral hemisphere regions. Additionally, we show that despite limiting the GPU memory and the training data, our MedicDeepLabv3+ also provided satisfactory segmentations. In conclusion, our method, publicly available at https://github.com/jmlipman/MedicDeepLabv3Plus, yielded excellent results in multiple scenarios, demonstrating its capability to reduce human workload in rat neuroimaging studies.Comment: Published in NeuroInformatic

Charged and neutral current neutrino induced nucleon emission reactions

By means of a Monte Carlo cascade method, to account for the rescattering of the outgoing nucleon, we study the charged and neutral current inclusive one nucleon knockout reactions off nuclei induced by neutrinos. The nucleon emission process studied here is a clear signal for neutralcurrent neutrino driven reactions, and can be used in the analysis of future neutrino experiments.Nieves Pamplona,Juan Miguel, [email protected] ; Vicente Vacas, Manuel Jose, [email protected]

Influence of seasonal factors in the earned value of construction

[EN] The objectives in each construction process can be multiple. However, the constructions have to be carried out under some restrictions concerning price and terms. They constitute some strategic and interdependent goals. In other words, ¿time is money¿. Several papers support that seasonal effects influence the execution rate of construction. Thus, most of them try to improve the forecasts by evaluating and joining them to the planning, although always measuring their influence indirectly. In this paper, we suggest a methodology to directly measure the influence of the seasonal factors as a whole over the earned value of construction. Additionally, we apply it to a certain case study regarding the subsidised housing of public promotion in the Castilla-La Mancha region (Spain). It is worth mentioning that our results are clarified: we have calculated the average monthly production for each month a year with respect to the annual monthly mean. Moreover, the differences regarding the average monthly production we have contributed are quite significant, and hence they have to be taken into account for each earned value forecast so that a project becomes reliable.The authors would like to thank Gicaman SA, Eres SA, and Urvial SA (construction companies) by the cession of their outcome data corresponding to 161 public promotions that gave rise to 5,319 subsidised housing.Ruiz-Fernández, JP.; Benlloch Marco, J.; López, MA.; Valverde-Gascueña, N. (2019). Influence of seasonal factors in the earned value of construction. Applied Mathematics and Nonlinear Sciences. 4(1):21-34. https://doi.org/10.2478/AMNS.2019.1.00003S213441Koehn, E., & Brown, G. (1985). Climatic Effects on Construction. Journal of Construction Engineering and Management, 111(2), 129-137. doi:10.1061/(asce)0733-9364(1985)111:2(129)El-Rayes, K., & Moselhi, O. (2001). Impact of Rainfall on the Productivity of Highway Construction. Journal of Construction Engineering and Management, 127(2), 125-131. doi:10.1061/(asce)0733-9364(2001)127:2(125)Kenley, R., & Wilson, O. D. (1989). A construction project net cash flow model. Construction Management and Economics, 7(1), 3-18. doi:10.1080/01446198900000002Skitmore, M. (1992). Parameter prediction for cash flow forecasting models. Construction Management and Economics, 10(5), 397-413. doi:10.1080/01446199200000038Chan, D. W. M., & Kumaraswamy, M. M. (1995). A study of the factors affecting construction durations in Hong Kong. Construction Management and Economics, 13(4), 319-333. doi:10.1080/01446199500000037Kaka, A. P., & Price, A. D. F. (1993). Modelling standard cost commitment curves for contractors’ cash flow forecasting. Construction Management and Economics, 11(4), 271-283. doi:10.1080/01446199300000027Blyth, K., & Kaka, A. (2006). A novel multiple linear regression model for forecasting S‐curves. Engineering, Construction and Architectural Management, 13(1), 82-95. doi:10.1108/09699980610646511Khosrowshahi, F., & Kaka, A. P. (2007). A Decision Support Model for Construction Cash Flow Management. Computer-Aided Civil and Infrastructure Engineering, 22(7), 527-539. doi:10.1111/j.1467-8667.2007.00508.