ASSESSING RESILIENCE OF INFRASTRUCTURES TOWARDS EXOGENOUS EVENTS BY USING PS-INSAR-BASED SURFACE MOTION ESTIMATES AND MACHINE LEARNING REGRESSION TECHNIQUES

Abstract. Technologically advanced strategies in infrastructural maintenance are increasingly required in countries such as Italy, where recovery and rehabilitation interventions are preferred to new works. For this purpose, Interferometric Synthetic Aperture Radar (InSAR) techniques have been employed in recent years, achieving reliable outcomes in the identification of infrastructural instabilities. Nevertheless, using the InSAR survey exclusively, it is not feasible to recognize the reasons for such vulnerabilities, and further in-depth investigations are essential.The primary purpose of this paper is to predict infrastructural displacements connected to surface motion and the related causes by combining InSAR techniques and Machine Learning algorithms. The development and application of a Regression Tree-based algorithm have been carried out for estimating the displacement of road pavement structures detected by the Persistent Scatterer InSAR technique.The study area is located in the province of Pistoia, Tuscany, Italy. Sentinel-1 images from 2014 to 2019 were used for the interferometric process, and a set of 29 environmental parameters was collected in a GIS platform. The database is randomly split into a Training (70%) and Test sets (30%). With the Training set, through a 10-Fold Cross-Validation, the model is trained, validated, and the Goodness-of-Fit is evaluated. Also, with the Test set, the Predictive Performance of the model is assessed. Lastly, we applied the model onto a stretch of a two-lane rural road that crosses the area. Results show that the suggested procedure can be used for supporting decision-making processes on planning road maintenance by National Road Authorities

Surface motion prediction and mapping for road infrastructures management by PS-InSAR measurements and machine learning algorithms

This paper introduces a methodology for predicting and mapping surface motion beneath road pavement structures caused by environmental factors. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) measurements, geospatial analyses, and Machine Learning Algorithms (MLAs) are employed for achieving the purpose. Two single learners, i.e., Regression Tree (RT) and Support Vector Machine (SVM), and two ensemble learners, i.e., Boosted Regression Trees (BRT) and Random Forest (RF) are utilized for estimating the surface motion ratio in terms of mm/year over the Province of Pistoia (Tuscany Region, central Italy, 964 km2), in which strong subsidence phenomena have occurred. The interferometric process of 210 Sentinel-1 images from 2014 to 2019 allows exploiting the average displacements of 52,257 Persistent Scatterers as output targets to predict. A set of 29 environmental-related factors are preprocessed by SAGA-GIS, version 2.3.2, and ESRI ArcGIS, version 10.5, and employed as input features. Once the dataset has been prepared, three wrapper feature selection approaches (backward, forward, and bi-directional) are used for recognizing the set of most relevant features to be used in the modeling. A random splitting of the dataset in 70% and 30% is implemented to identify the training and test set. Through a Bayesian Optimization Algorithm (BOA) and a 10-Fold Cross-Validation (CV), the algorithms are trained and validated. Therefore, the Predictive Performance of MLAs is evaluated and compared by plotting the Taylor Diagram. Outcomes show that SVM and BRT are the most suitable algorithms; in the test phase, BRT has the highest Correlation Coefficient (0.96) and the lowest Root Mean Square Error (0.44 mm/year), while the SVM has the lowest difference between the standard deviation of its predictions (2.05 mm/year) and that of the reference samples (2.09 mm/year). Finally, algorithms are used for mapping surface motion over the study area. We propose three case studies on critical stretches of two-lane rural roads for evaluating the reliability of the procedure. Road authorities could consider the proposed methodology for their monitoring, management, and planning activities

Modeling of the Rheological Properties of Asphalt Binder and Asphalt Mortar Containing Recycled Asphalt Material

Abstract The use of recycled materials in asphalt pavements increased significantly over the years, determining well known environmental and economic benefits. Many research agencies and road authorities evaluated the impact of Recycled Asphalt Pavement (RAP) on pavement performance. Nevertheless, the mechanism governing the interaction between virgin asphalt binder and aged RAP binder is not well understood. In this paper, the effect of RAP on the rheological properties of asphalt binders and mortars is experimentally evaluated, and theoretically modeled with the objective of defining a relationship between the linear viscoelastic (LVE) properties of binders and those of the corresponding mortars. Three asphalt binder types, obtained by blending a hard and a soft binder at three different percentages, were mixed with three different contents of a Selected fraction of Recycled Asphalt Pavement, called SRAP, for preparing the asphalt mortar samples. Dynamic Shear Rheomether tests were performed on binders and mortars to determining the complex modulus over a wide range of temperatures and frequencies. The rheological properties of the compound of virgin and RAP binder were evaluated by using a new approach based on a modified version of the Nielsen model, avoiding the extraction and recovery method. The results were then modelled by using the analogical 2S2P1D model, consisting of one spring, two parabolic and one-dashpot elements combined in series and then assembled together with a second spring in parallel. Based on test results, a simple experimental relationship between the characteristic times of the binder and the percentage of RAP in the mortar was found

Associations between sedentary time, physical activity and bone health among older people using compositional data analysis

Introduction : Aging is associated with a progressive decrease in bone mass (BM), and being physical active is one of the main strategies to combat this continuous loss. Nonetheless, because daily time is limited, time spent on each movement behavior is co-dependent. The aim of this study was to determine the relationship between BM and movement behaviors in elderly people using compositional data analysis. Methods : We analyzed 871 older people [395 men (76.9 +/- 5.3y) and 476 women (76.7 +/- 4.7y)]. Time spent in sedentary behavior (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA), was assessed using accelerometry. BM was determined by bone densitometry (DXA). The sample was divided according to sex and bone health indicators. Results : The combined effect of all movement behaviors (PA and SB) was significantly associated with whole body, leg and femoral region BM in the whole sample (p<0.05), with leg and pelvic BM (p<0.05) in men and, with whole body, arm and leg BM (p<0.05) in women. In men, arm and pelvic BM were negatively associated with SB and whole body, pelvic and leg BM were positively associated with MVPA (p<0.05). In women, whole body and leg BM were positively associated with SB. Arm and whole body BM were positively associated and leg BM was negatively associated with LPA and arm BM was negatively associated with MVPA (p<0.05). Women without bone fractures spent less time in SB and more in LPA and MVPA than the subgroup with bone fractures. Conclusion : We identified that the positive effect of MVPA relative to the other behaviors on bone mass is the strongest overall effect in men. Furthermore, women might decrease bone fracture risk through PA increase and SB reduction, despite the fact that no clear benefits of PA for bone mass were found

Multipole strength function of deformed superfluid nuclei made easy

We present an efficient method for calculating strength functions using the finite amplitude method (FAM) for deformed superfluid heavy nuclei within the framework of the nuclear density functional theory. We demonstrate that FAM reproduces strength functions obtained with the fully self-consistent quasi-particle random-phase approximation (QRPA) at a fraction of computational cost. As a demonstration, we compute the isoscalar and isovector monopole strength for strongly deformed configurations in $^{240}$Pu by considering huge quasi-particle QRPA spaces. Our approach to FAM, based on Broyden's iterative procedure, opens the possibility for large-scale calculations of strength distributions in well-bound and weakly bound nuclei across the nuclear landscape.Comment: 5 pages, 3 figure

The accuracy of the motor imagery and the ball reception in children

Estudios recientes observaron que las imágenes motrices se desarrollan de forma entrelazada con el desarrollo de las habilidades motrices en niños. La finalidad de este estudio es analizar en qué medida la imagen motriz de los elementos necesarios para resolver un problema motor (la recepción de un balón), se relaciona con los niveles de habilidad en niños (3 - 9 años). La muestra estuvo formada por 215 participantes (87 chicos y 118 chicas), (M = 5,94, DT = 1,47). Se ha utilizado una metodología mixta: dibujos, indicaciones gestuales, verbalización del pensamiento y una prueba práctica de recepción de balón. El MANOVA reveló diferencias significativas en las capacidades meta-cognitivas y motrices en función de las etapas de desarrollo. Un análisis de ecuaciones estructurales reveló que las capacidades meta-cognitivas median la relación entre las etapas de desarrollo y la habilidad de recepción de móviles. Se discuten sus repercusiones en el aprendizaje motorRecent studies have found that motor imaginery is developed linked to the development of motor skills in children. The purpose of this study is to analyze how the motor imaginery of the principal elements to solve a motor problem (ball reception) relates to the motor skill levels in children (3-9 years). The sample consisted of 215 participants (87 boys and 118 girls), (M = 5.94, SD = 1.47).We used a mixed methodology: drawings, gestural prompts, verbalization of thought and a practical test of ball reception. The MANOVA revealed significant differences in the meta-cognitive abilities and motor function of the developmental stages. A structural equation analysis revealed that meta-cognitive abilities mediate the relationship between the stages of development and the ability in the reception of moving objects. Their implications in motor learning are discusse

Linear response of light deformed nuclei investigated by self-consistent quasiparticle random-phase-approximation

We present a calculation of the properties of vibrational states in deformed, axially--symmetric even--even nuclei, within the framework of a fully self--consistent Quasparticle Random Phase Approximation (QRPA). The same Skyrme energy density and density-dependent pairing functionals are used to calculate the mean field and the residual interaction in the particle-hole and particle-particle channels. We have tested our software in the case of spherical nuclei against fully self consistent calculations published in the literature, finding excellent agreement. We investigate the consequences of neglecting the spin-orbit and Coulomb residual interactions in QRPA. Furthermore we discuss the improvement obtained in the QRPA result associated with the removal of spurious modes. Isoscalar and isovector responses in the deformed ${}^{24-26}$Mg, $^{34}$Mg isotopes are presented and compared to experimental findings

Nerve growth factor and bromocriptine: a sequential therapy for human bromocriptine-resistant prolactinomas.

Nerve growth factor (NGF) administration to athymic mice with transplanted human bromocriptine-resistant prolactinoma, results in the expression of dopamine D-2 receptors in the tumour and restores sensitivity to subsequent treatment with bromocriptine, which then produces normalisation of plasma prolactin and tumour regression. Sequential administration of NGF and bromocriptine thus may be a promising therapy for patients refractory to bromocriptine