Road Network Layout Planning based on Evaluation of Connectivity and Asset Criticality

State of the art research in ensuring transport infrastructure resilience focuses on adopting a network perspective. However, there is no comprehensive, widespread method for evaluating connectivity and proposing alternative routes to improve it. Presented herein is a framework that: assesses road network connectivity, using a “closeness” measure and focusing on routes passing by the vulnerable asset of bridges; and proposes the development of optimal alternative routes, using a genetic algorithm. The results showed a significant improvement of network connectivity and the potential of the method to serve as the basis for updated transport infrastructure planning practices.H2020 Programme MG7-1-2017 Resilience to extreme (natural and man-made) events, under Grant [769255] ‘‘GIS-based infrastructure management system for optimized response to extreme events of terrestrial transport networks (SAFEWAY)’’

Dataset for "Winter thermal comfort and health in the elderly"

The data within this dataset was collected from 43 homes, all in Bath, UK, with at least one occupant aged 65 or over. Sensors were placed in the living rooms and bedrooms of the participating homes to measure temperature at 90-minute intervals throughout the phases of the project. There were four phases in total: November 2016 – March 2017; June 2017 – September 2017; November 2017 – March 2018; June 2018 – September 2018. Corresponding questionnaires were completed on a monthly basis throughout the phases of the project, gathering data about thermal comfort and health. Within this dataset the measured internal temperatures, participant self-reported thermal comfort and health problems are contained in either Excel or CSV files.Longitudinal Temperature Monitoring - Between November 2016 until March 2017 and November 2017 until March 2018, sensors were deployed in the 43 participating homes measuring internal temperatures (in the living room and bedroom) at 90 minute intervals.iButton DS1922L sensors were used

Remote (250 km) Fiber Bragg Grating Multiplexing System

We propose and demonstrate two ultra-long range fiber Bragg grating (FBG) sensor interrogation systems. In the first approach four FBGs are located 200 km from the monitoring station and a signal to noise ratio of 20 dB is obtained. The second improved version is able to detect the four multiplexed FBGs placed 250 km away, offering a signal to noise ratio of 6–8 dB. Consequently, this last system represents the longest range FBG sensor system reported so far that includes fiber sensor multiplexing capability. Both simple systems are based on a wavelength swept laser to scan the reflection spectra of the FBGs, and they are composed by two identical-lengths optical paths: the first one intended to launch the amplified laser signal by means of Raman amplification and the other one is employed to guide the reflection signal to the reception system

Working Conditions, Workplace Violence, and Psychological Distress in Andean Miners: A Cross-sectional Study Across Three Countries

Background: Psychosocial working conditions are well-known determinants of poor mental health. However, studies in mining populations where employment and working conditions are frequently precarious have, to our knowledge, only focused on occupational accidents and diseases. Objectives: The aim of this study was to assess psychosocial working conditions and psychological distress in Andean underground miners. Methods: The study population consisted of 153 Bolivian miners working in a silver mining cooperative, 137 Chilean informal gold miners, and 200 formal Peruvian silver miners employed in a remote setting. High work demands, minimal work control, minimal social support at work, and workplace exposure to violence and bullying were assessed using the Spanish short form of the European Working Condition Survey. A general health questionnaire score >4 was used as cutoff for psychological distress. Associations between psychosocial work environment and psychological distress were tested using logistic regression models controlling for potential confounding and effect modification by country. Findings: Prevalence of psychological distress was 82% in the Bolivian cooperative miners, 29% in the Peruvian formal miners, and 22% in the Chilean informal miners (pχ2 < 0.001). 55% of the miners had suffered violence during the 12-months before the survey. Workplace demands were high (median 12.5 on a scale from 7-14), as was social support (median 5.5 on a scale from 3-6). After adjustment for country and other relevant exposure variables and considering interactions between country and job strain, miners in active (odds ratio [OR], 6.8; 95% confidence interval [CI] 2.1-22.7) and high strain jobs (OR, 7.2; 95% CI, 1.7-29.9) were at increased odds of distress compared with those in low strain jobs. Violence at work also contributed to increased odds of distress (OR, 1.86; 95% CI, 1.1-3.1). Conclusions: Psychological distress is associated with the psychosocial work environment in Andean underground miners. Interventions in mining populations should take the psychosocial work environment into account

PLANEACIÓN DIDÁCTICA GENERAL DE LA ASIGNATURA: CÁLCULO DIFERENCIAL 2017-B

GUÍA DIDÁCTICA / PLANEACIÓN DIDÁCTICA (NMS

PLANEACIÓN DIDÁCTICA GENERAL DE LA ASIGNATURA: ARITMÉTICA Y LENGUAJE MATEMÁTICO 2017B

GUÍA DIDÁCTICA / PLANEACIÓN DIDÁCTICA (NMS

PLANEACIÓN DIDÁCTICA GENERAL DE LA ASIGNATURA: TRIGONOMETRÍA 2017- B

GUÍA DIDÁCTICA / PLANEACIÓN DIDÁCTICA (NMS

Optical Fiber Networks for Remote Fiber Optic Sensors

This paper presents an overview of optical fiber sensor networks for remote sensing. Firstly, the state of the art of remote fiber sensor systems has been considered. We have summarized the great evolution of these systems in recent years; this progress confirms that fiber-optic remote sensing is a promising technology with a wide field of practical applications. Afterwards, the most representative remote fiber-optic sensor systems are briefly explained, discussing their schemes, challenges, pros and cons. Finally, a synopsis of the main factors to take into consideration in the design of a remote sensor system is gathered

An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks

Over the past few years, Intelligent Spaces (ISs) have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a) an optimized design for the inference engine; (b) a visual interface; (c) a module to reduce the redundancy and complexity of the knowledge bases; (d) a module to evaluate the accuracy of the new knowledge base; (e) a module to adapt the format of the rules to the structure used by the inference engine; and (f) a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern.) and repilo (caused by the fungus Spilocaea oleagina). The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery) without a substantial decrease in the accuracy of the inferred values

The spatial evolution of young massive clusters - I. A new tool to quantitatively trace stellar clustering

Context. There are a number of methods that identify stellar sub-structure in star forming regions, but these do not quantify the degree of association of individual stars – something which is required if we are to better understand the mechanisms and physical processes that dictate structure. Aims. We present the new novel statistical clustering tool “INDICATE” which assesses and quantifies the degree of spatial clustering of each object in a dataset, discuss its applications as a tracer of morphological stellar features in star forming regions, and to look for these features in the Carina Nebula (NGC 3372). Methods. We employ a nearest neighbour approach to quantitatively compare the spatial distribution in the local neighbourhood of an object with that expected in an evenly spaced uniform (i.e. definitively non-clustered) field. Each object is assigned a clustering index (“I”) value, which is a quantitative measure of its clustering tendency. We have calibrated our tool against random distributions to aid interpretation and identification of significant I values. Results. Using INDICATE we successfully recover known stellar structure of the Carina Nebula, including the young Trumpler 14-16, Treasure Chest and Bochum 11 clusters. Four sub-clusters contain no, or very few, stars with a degree of association above random which suggests these sub-clusters may be fluctuations in the field rather than real clusters. In addition we find: (1) Stars in the NW and SE regions have significantly different clustering tendencies, which is reflective of differences in the apparent star formation activity in these regions. Further study is required to ascertain the physical origin of the difference; (2) The different clustering properties between the NW and SE regions are also seen for OB stars and are even more pronounced; (3) There are no signatures of classical mass segregation present in the SE region – massive stars here are not spatially concentrated together above random; (4) Stellar concentrations are more frequent around massive stars than typical for the general population, particularly in the Tr14 cluster; (5) There is a relation between the concentration of OB stars and the concentration of (lower mass) stars around OB stars in the centrally concentrated Tr14 and Tr15, but no such relation exists in Tr16. We conclude this is due to the highly sub-structured nature of Tr16. Conclusions. INDICATE is a powerful new tool employing a novel approach to quantify the clustering tendencies of individual objects in a dataset within a user-defined parameter space. As such it can be used in a wide array of data analysis applications. In this paper we have discussed and demonstrated its application to trace morphological features of young massive clusters