Study on the Impact of the NS in the Performance of Meta-Heuristics in the TSP

Meta-heuristics have been applied for a long time to the Travelling Salesman Problem (TSP) but information is still lacking in the determination of the parameters with the best performance. This paper examines the impact of the Simulated Annealing (SA) and Discrete Artificial Bee Colony (DABC) parameters in the TSP. One special consideration of this paper is how the Neighborhood Structure (NS) interact with the other parameters and impacts the performance of the meta-heuristics. NS performance has been the topic of much research, with NS proposed for the best-known problems, which seem to imply that the NS influences the performance of meta-heuristics, more that other parameters. Moreover, a comparative analysis of distinct meta-heuristics is carried out to demonstrate a non-proportional increase in the performance of the NS.This work is supported by FEDER Funds through the "Programa Operacional Factores de Competitividade - COMPETE" program and by National Funds through FCT "FundaqAo para a Ciencia e a Tecnologia" under the project: FCOMP-01-0124-FEDER-PEst-OE/EEl/U10760/2011, PEst-OE/EEI/UI0760/2014, and PEst2015-2020.info:eu-repo/semantics/publishedVersio

Data-driven disaster management in a smart city

Disasters, both natural and man-made, are extreme and complex events with consequences that translate into a loss of life and/or destruction of properties. The advances in IT and Big Data analysis represent an opportunity for the development of resilient environments once the application of analytical methods allows extracting information from a significant amount of data, optimizing the decision-making processes. This research aims to apply the CRISP-DM methodology to extract information about incidents that occurred in the city of Lisbon with emphasis on occurrences that affected buildings, constituting a tool to assist in the management of the city. Through this research, it was verified that there are temporal and spatial patterns of occurrences that affected the city of Lisbon, with some types of occurrences having a higher incidence in certain periods of the year, such as floods and collapses that occur when there are high levels of precipitation. On the other hand, it was verified that the downtown area of the city is the area most affected by occurrences. Finally, machine learning models were applied to the data and the predictive model Random Forest obtained the best result with an accuracy of 58%.info:eu-repo/semantics/publishedVersio

Oxidation of clofibric acid in aqueous solution using a non-thermal plasma discharge or gamma radiation

In this work, we study degradation of clofibric acid (CFA) in aqueous solution using either ionizing radiation from a $^{60}$Co source or a non-thermal plasma produced by discharges in the air above the solution. The results obtained with the two technologies are compared in terms of effectiveness of CFA degradation and its by-products. In both cases the CFA degradation follows a quasi-exponential decay in time well modelled by a kinetic scheme which considers the competition between CFA and all reaction intermediates for the reactive species generated in solution as well as the amount of the end product formed. A new degradation law is deduced to explain the results. Although the end-product CO$_2$ was detected and the CFA conversion found to be very high under the studied conditions, HPLC analysis reveals several degradation intermediates still bearing the aromatic ring with the chlorine substituent. The extent of mineralization is rather limited. The energy yield is found to be higher in the gamma radiation experiments.Comment: 25 pages, 7 figure

Remote Monitor System for Alzheimer disease

Health Remote Monitoring Systems (HRMS) offer the ability to address health-care human resource concerns. In developing nations, where pervasive mobile networks and device access are linking people like never before, HRMS are of special relevance. A fundamental aim of this research work is the realization of technological-based solution to triage and follow-up people living with dementias so as to reduce pressure on busy staff while doing this from home so as to avoid all unnecessary visits to hospital facilities, increasingly perceived as dangerous due to COVID-19 but also raising nosocomial infections, raising alerts for abnormal values. Sensing approaches are complemented by advanced predictive models based on Machine Learning (ML) and Artificial Intelligence (AI), thus being able to explore novel ways of demonstrating patient-centered predictive measures. Low-cost IoT devices composing a network of sensors and actuators aggregated to create a digital experience that will be used and exposure to people to simultaneously conduct several tests and obtain health data that can allow screening of early onset dementia and to aid in the follow-up of selected cases. The best ML for predicting AD was logistic regression with an accuracy of 86.9%. This application as demonstrated to be essential for caregivers once they can monitor multiple patients in real-time and actuate when abnormal values occur.info:eu-repo/semantics/acceptedVersio

Preparation of cotton materials using CORONA discharge

The present work concerns the study of preparation processes when this operation is preceded by a CORONA discharge made on dry raw fabrics. The influence in the whiteness degree, hydrophility, starch removal and uniformity of properties of the cellulosic material after preparation is studied. Combined preparation processes are widely used in order to replace solutions where desizing, alkaline boiling and bleaching are individual operations, being a main interest to find the optimal conditions to achieve alkaline oxidative treatments with an uniform and more intense cleaning action. CORONA discharge is able to strongly modify hydrophility of cotton fabrics in raw stage, which is determinant to increase liquids absorption and uniformity of processed fabrics. Results of long-bath, pad-roll, pad-batch and pad-steam bleaching processes in laboratory conditions are compared using or not wetting agent in the recipes and including CORONA discharge as a preparation operation. The transfer of this technology to industry regarding the implementation in textile plant in a very near future is being worked, supported by results as the present ones.(undefined

Concentraciones de nutrientes en aguas costeras: impacto del Río Guadiana

Water samples were collected over an area of 900 km(2) adjacent to the outflow of the Guadiana River in January 1999 to characterize the concentrations and spatial distribution of nutrients (ammonium, nitrite, nitrate, phosphate and silicate) in the water column. The purpose of the study was to characterize a winter situation of low discharge in terms of nutrient concentrations in the coastal area adjacent to the Guadiana outflow, before the reduction of the river flow due to the completion of the Alqueva Dam. The results show that the maximum influence of the Guadiana outflow was close to the mouth of the Guadiana River, where the highest nutrient concentrations and the minimum of salinity were registered. At the surface, the nutrient concentrations decreased gradually as the distance from the coast increased. The influence of the Guadiana outflow at the surface, despite being small, was evident in the area of about 90 km(2) that extends westwards from the mouth of the river. In this area, the increase in N compounds was more significant than in P and Si. The vertical influence of the outflow of the Guadiana River, until over the isobath lower than 30 m, was reflected in nutrient concentrations that decreased with the increase in depth. However, when the depth of the water column was greater than 30 m, the nutrient concentrations increased with the increase in depth. It is expected that with the completion of the Alqueva Dam, the outflow of the Guadiana River will be reduced even further. Nutrient concentrations will also be reduced and the influence of the river in the coastal zone will be even smaller. This could have a negative impact on the nutrient biogeochemical cycles and on the overall productivity of the area.En un área de 900 km2 alrededor de la desembocadura del Río Guadiana se recolectaron muestras de agua para caracterizar las concentraciones y distribución espacial de nutrientes (amonio, nitritos, nitratos, fosfatos y silicatos) en la columna de agua. El propósito de este estudio fue caracterizar la condición invernal de pocas descargas, en términos de concentración de nutrientes en el área costera adyacente a la desembocadura del Guadiana, antes de que el flujo del río se vea reducido por la conclusión de la Presa Alqueva. Los resultados indican que la mayor influencia de la descarga del Guadiana se observó cerca de la boca del río, donde se registraron las mayores concentraciones de nutrientes y la salinidad más baja. En superficie, las concentraciones de nutrientes disminuyeron gradualmente con el aumento de la distancia a la costa. La influencia de la descarga del Guadiana en superficie, aunque pequeña, fue evidente en el área de ~90 km2 que se extiende de la boca del río hacia el oeste. En esta área el incremento de compuestos de N fue más significativo que el de los de P y Si. La influencia vertical de la descarga del Río Guadiana, hasta por encima de la isóbata < 30 m se reflejó en las concentraciones de nutrientes que disminuyeron conforme aumentaba la profundidad. Sin embargo, cuando la profundidad de la columna de agua era > 30 m las concentraciones de nutrientes aumentaron con la profundidad. Es de esperar que con la terminación de la Presa Alqueva la descarga del río se vea aún más disminuida. Las concentraciones también se verán reducidas y la influencia del río en la zona costera será aún menor. Esto podría tener un impacto negativo en los ciclos biogeoquímicos de nutrientes y en la productividad global del área.proyecto SIRIA, financiado conjuntamente entre el Ministerio de Defensa y la Fundación de las Universidades de Portugal, en el marco del Programa Medio Ambiente y Defensainfo:eu-repo/semantics/publishedVersio

DNA-PKCS binding to p53 on the p21WAF1/CIP1 promoter blocks transcription resulting in cell death

A key determinant of p53-mediated cell fate following various DNA damage modalities is p21WAF1/CIP1 expression, with elevated p21 expression triggering cell cycle arrest and repressed p21 expression promoting apoptosis. We show that under pro-death DNA damage conditions, the DNA-dependent protein kinase (DNA-PKCS) is recruited to the p21 promoter where it forms a protein complex with p53. The DNA-PKCS-associated p53 displays post-translational modifications that are distinct from those under pro-arrest conditions, ablating p21 transcription and inducing cell death. Inhibition of DNA-PK activity prevents DNA-PKCS binding to p53 on the p21 promoter, restores p21 transcription and significantly reduces cell death. These data demonstrate that DNA-PKCS negatively regulates p21 expression by directly interacting with the p21 transcription machinery via p53, driving the cell towards apoptosis

Data fusion and visualization towards city disaster management: Lisbon case study

INTRODUCTION: Due to the high level of unpredictability and the complexity of the information requirements, disaster management operations are information demanding. Emergency response planners should organize response operations efficiently and assign rescue teams to particular catastrophe areas with a high possibility of surviving. Making decisions becomes more difficult when the information provided is heterogeneous, out of date, and often fragmented. OBJECTIVES: In this research work a data fusion of different information sources and a data visualization process was applied to provide a big picture about the disruptive events in a city. This high-level knowledge is important for emergency management authorities. This holistic process for managing, processing, and analysing the seven Vs (Volume, Velocity, Variety, Variability, Veracity, Visualization, and Value) in order to generate actionable insights for disaster management. METHODS: A CRISP-DM methodology over smart city-data was applied. The fusion approach was introduced to merge different data sources. RESULTS: A set of visual tools in dashboards were produced to support the city municipality management process. Visualization of big picture based on different data available is the proposed work. CONCLUSION: Through this research, it was verified that there are temporal and spatial patterns of occurrences that affected the city of Lisbon, with some types of occurrences having a higher incidence in certain periods of the year, such as floods and collapses that occur when there are high levels of precipitation. On the other hand, it was verified that the downtown area of the city is the most affected area.info:eu-repo/semantics/publishedVersio