An association rule mining method for estimating the impact of project management policies on software quality, development time and effort

Accurate and early estimations are essential for effective decision making in software project management. Nowadays, classical estimation models are being replaced by data mining models due to their application simplicity and the rapid production of profitable results. In this work, a method for mining association rules that relate project attributes is proposed. It deals with the problem of discretizing continuous data in order to generate a manageable number of high confident association rules. The method was validated by applying it to data from a Software Project Simulator. The association model obtained allows us to estimate the influence of certain management policy factors on various software project attributes simultaneously

Sentiment Analysis Based on Deep Learning: A Comparative Study

The study of public opinion can provide us with valuable information. The analysis of sentiment on social networks, such as Twitter or Facebook, has become a powerful means of learning about the users' opinions and has a wide range of applications. However, the efficiency and accuracy of sentiment analysis is being hindered by the challenges encountered in natural language processing (NLP). In recent years, it has been demonstrated that deep learning models are a promising solution to the challenges of NLP. This paper reviews the latest studies that have employed deep learning to solve sentiment analysis problems, such as sentiment polarity. Models using term frequency-inverse document frequency (TF-IDF) and word embedding have been applied to a series of datasets. Finally, a comparative study has been conducted on the experimental results obtained for the different models and input feature

Predictores del estado post-ictus en el alta hospitalaria. Importancia en enfermería

Nurses are often asked to predict factors that influence post-stroke outcome by the patient and family. Many studies have been carried out in order to determine the factors that influence the neurological status of the post-stroke patient at the moment of the discharge from the hospital. However, machine learning techniques have not been used for this purpose. Therefore, with the objective of obtaining association rules of neurological prognosis, a double analysis, both clinical and with machine learning techniques of the possible associations of factors that influence the neurological status of the post-stroke patients has been carried out. The Apriori algorithm detected several association rules with high confidence (≥ 95%), from which the following pattern: In patients in the age range of 50-80 years, the association of a NIHSS between 11 and 15 points (intermediate/low NIHSS), along with thrombectomy, leads to recovery ad integrum at discharge. With the SMOTE resampling technique, the 100% confidence was reached for the association of high NIHSS (>20) and involvement of the carotid and basilar arteries, with a dire prognosis (exitus). These rules confirm, for the first time with machine learning, the importance of the association of some predictors, in the post-stroke prognosis. The knowledge by the nurses of these association rules can successfully improve stroke outcome. In addition, the role of nurses in education programs that teach knowledge of risk factors and stroke prognosis becomes essential.A menudo, por parte del paciente y de la familia, se solicita a los profesionales de enfermería que predigan los factores que influyen en el estado post-ictus. Se han realizado numerosos estudios para determinar los factores que influyen en el estado neurológico post-ictus en el momento del alta hospitalaria. Sin embargo, las técnicas de aprendizaje automático no se han utilizado para este propósito. Con el objetivo de obtener reglas de asociación del pronóstico neurológico, se ha llevado a cabo un doble análisis, tanto clínico como con técnicas de aprendizaje automático, de las posibles asociaciones de factores que influyen en el estado neurológico de los pacientes post-ictus. El algoritmo Apriori detectó varias reglas de asociación con alta confianza (≥ 95%), con el siguiente patrón: En pacientes en el rango de edad de 50-80 años, la asociación de un NIHSS entre 11 y 15 puntos (NIHSS intermedio/bajo), junto con la trombectomía, conduce a la recuperación ad integrum al alta. Con la técnica de remuestreo SMOTE, se alcanzó el 100% de confianza para la asociación de NIHSS elevado (>20) y afectación de las arterias carótida y basilar, con pronóstico nefasto (exitus). Estas reglas confirman, por primera vez con aprendizaje automático, la importancia de la asociación de algunos predictores, en el pronóstico post-ictus. El conocimiento por parte de las enfermeras de estas reglas puede mejorar los resultados del ictus. Adicionalmente, el papel de la enfermería en los programas de educación sobre los factores de riesgo, y pronóstico de un ictus se torna imprescindible

Traffic Optimization Through Waiting Prediction and Evolutive Algorithms

Traffic optimization systems require optimization procedures to optimize traffic light timing settings in order to improve pedestrian and vehicle mobility. Traffic simulators allow obtaining accurate estimates of traffic behavior by applying different timing configurations, but require considerable computational time to perform validation tests. For this reason, this project proposes the development of traffic optimizations based on the estimation of vehicle waiting times through the use of different prediction techniques and the use of this estimation to subsequently apply evolutionary algorithms that allow the optimizations to be carried out. The combination of these two techniques leads to a considerable reduction in calculation time, which makes it possible to apply this system at runtime. The tests have been carried out on a real traffic junction on which different traffic volumes have been applied to analyze the performance of the system

GSK-3β orchestrates the inhibitory innervation of adult-born dentate granule cells in vivo

Adult hippocampal neurogenesis enhances brain plasticity and contributes to the cognitive reserve during aging. Adult hippocampal neurogenesis is impaired in neurological disorders, yet the molecular mechanisms regulating the maturation and synaptic integration of new neurons have not been fully elucidated. GABA is a master regulator of adult and developmental neurogenesis. Here we engineered a novel retrovirus encoding the fusion protein Gephyrin:GFP to longitudinally study the formation and maturation of inhibitory synapses during adult hippocampal neurogenesis in vivo. Our data reveal the early assembly of inhibitory postsynaptic densities at 1 week of cell age. Glycogen synthase kinase 3 Beta (GSK-3β) emerges as a key regulator of inhibitory synapse formation and maturation during adult hippocampal neurogenesis. GSK-3β-overexpressing newborn neurons show an increased number and altered size of Gephyrin+ postsynaptic clusters, enhanced miniature inhibitory postsynaptic currents, shorter and distanced axon initial segments, reduced synaptic output at the CA3 and CA2 hippocampal regions, and impaired pattern separation. Moreover, GSK-3β overexpression triggers a depletion of Parvalbumin+ interneuron perineuronal nets. These alterations might be relevant in the context of neurological diseases in which the activity of GSK-3β is dysregulatedPID2020-113007RB-I00, SAF-2017-82185-R, PID2020-112824GB-10

Spatial similarities between European agroforestry systems and ecosystem services at the landscape scale

This is a post-peer-review, pre-copyedit version of an article published in Agroforestry Systems. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10457-017-0132-3Agroforestry systems are known to provide ecosystem services which differ in quantity and quality from conventional agricultural practices and could enhance rural landscapes. In this study we compared ecosystem services provision of agroforestry and non-agroforestry landscapes in case study regions from three European biogeographical regions: Mediterranean (montado and dehesa), Continental (orchards and wooded pasture) and Atlantic agroforestry systems (chestnut soutos and hedgerows systems). Seven ecosystem service indicators (two provisioning and five regulating services) were mapped, modelled and assessed. Clear variations in amount and provision of ecosystem services were found between different types of agroforestry systems. Nonetheless regulating ecosystems services were improved in all agroforestry landscapes, with reduced nitrate losses, higher carbon sequestration, reduced soil losses, higher functional biodiversity focussed on pollination and greater habitat diversity reflected in a high proportion of semi-natural habitats. The results for provisioning services were inconsistent. While the annual biomass yield and the groundwater recharge rate tended to be higher in agricultural landscapes without agroforestry systems, the total biomass stock was reduced. These broad relationships were observed within and across the case study regions regardless of the agroforestry type or biogeographical region. Overall our study underlines the positive influence of agroforestry systems on the supply of regulating services and their role to enhance landscape structureWe acknowledge funding through Grant 613520 from the European Commission (Project AGFORWARD, 7th Framework Program), the Xunta de Galicia, Consellería de Cultura, Educación e Ordenación Universitaria (“Programa de axudas á etapa posdoutoral DOG no. 122, 29/06/2016 p.27443, exp: ED481B 2016/071-0”), the Forest Research Center strategic project (PEst OE/AGR/UI0239/2014) and the Portuguese Foundation for Science and Technology through the contract SFRH/BD/52691/2014S

Spatial similarities between European agroforestry systems and ecosystem services at the landscape scale

Agroforestry systems are known to provide ecosystem services which differ in quantity and quality from conventional agricultural practices and could enhance rural landscapes. In this study we compared ecosystem services provision of agroforestry and non-agroforestry landscapes in case study regions from three European biogeographical regions: Mediterranean (montado and dehesa), Continental (orchards and wooded pasture) and Atlantic agroforestry systems (chestnut soutos and hedgerows systems). Seven ecosystem service indicators (two provisioning and five regulating services) were mapped, modelled and assessed. Clear variations in amount and provision of ecosystem services were found between different types of agroforestry systems. Nonetheless regulating ecosystems services were improved in all agroforestry landscapes, with reduced nitrate losses, higher carbon sequestration, reduced soil losses, higher functional biodiversity focussed on pollination and greater habitat diversity reflected in a high proportion of semi-natural habitats. The results for provisioning services were inconsistent. While the annual biomass yield and the groundwater recharge rate tended to be higher in agricultural landscapes without agroforestry systems, the total biomass stock was reduced. These broad relationships were observed within and across the case study regions regardless of the agroforestry type or biogeographical region. Overall our study underlines the positive influence of agroforestry systems on the supply of regulating services and their role to enhance landscape structure

Physical Therapy and Occupational Therapy student's motivation. A Comparative study in the University of Malaga, Spain

Purpose: The main purpose of this study is to know and compare motivational facts and vocational behaviour among students of physical therapy and occupational therapy. Other secondary objectives are: • To know the satisfaction these students report with their university studies • To analyze the level of academic decision about their professional future. • To know if these students have an effective academic behavior. Participants. Participants were 141 Spanish collegue students who volunteered for the study. They were students of second and third year of Physical therapy (69) and Occupational therapy (72) in the University of Malaga. Methods: Cross-sectional design. Paticipants completed in one setting the “Cuestionario de Biodatos Universitarios - CBU- The CBU is a 9 item scale that offers information about student academic motivation, academic decisions, satisfaction or future professional purpose. Each questionnaire response is assigned a value with a maximum possible total score of 26. Results: Regarding student satisfaction, 68.1% of physical therapy (PT) student are very satisfied with the career choices they made in thei day, like the 56.95% of students in occupational therapy (OT). Regarding the degree of academic decision on the professional expertise they would like to pursue in the future, 44,9% doe not have anything decided in PT, similar to the 36,1% found in OT. After completing his studies, 48,62% of OT students planning to do a Master or postgraduate course compared with the 81.1% referring this intention in PT. In relation to the exercise of the profession immediately obtained similar results in both degrees, 56.95% in OT and 66.2% in PT. Only 6.95% of repondents in OT and 14.49% in PT have not decided yet. Among the difficulties or problems for a decision by a specialty or area of works, 57.9% highlights the lack of information on the characteristics of that product in PT and 31.95% at OT, whereas only 2.9% and 5.56% refer to that no option would fully satisfied respectively. Comprehensively analyzed, and pre-vocational behaviour of respondents was fully efficient, so that in all cases there is an effective career development, slightly better in pupils PT. Conclusions: The descriptive analysis of a sample CBU draws us highly satisfied with their university studies, with an efficient vocational behaviour, who knows the need for specialization through graduate school, but lacks sufficient information in making their decisions.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech