Estadística Descriptiva y Probabilidad: (Teoría y problemas)

XXXIV, 261 p. ; 24 cm.Libro ElectrónicoÍndice Bibliografía: p. [256]-258 Manual para alumnos de titulaciones experimentales que proporciona una visión práctica e intuitiva de la estadística descriptiva y el cálculo de probabilidades, campos básicos y fundamentales de la ciencia estadísticaLibro : Español (spa) : 3a. edIndice general Prólogo XIII 1. Introducción XIII 2. History (Histórico) XV 3. Licencia de Documentación Libre de GNU XVI 4. GNU Free Documentation License XXVI A Estadística Descriptiva 1 1 Síntesis de la información 7 1. Rese˜na histórica 7 2. La organización de la información 9 3. Representaciones grá?cas 15 4. Medidas centrales 17 5. Medidas de posición 26 6. Medidas de dispersión 27 7. Desigualdad de Tchebychev 31 8. Momentos de la distribución 31 9. Medidas de forma 33 10. Transformaciones 36 11. Análisis exploratorio de datos 37 12. Ejercicios 40 2 Análisis conjunto de variables. 53 1. Distribución conjunta de dos caracteres 53 2. Distribuciones marginales 55 3. Distribuciones condicionadas 55 4. Independencia 60 5. Medidas de dependencia. Coeficientes de relación 61 6. Ejercicios 78 3 Ajuste y regresión bidimensional 89 1. Introducción 89 2. Ajuste. Criterio de los mínimos cuadrados 91 3. Análisis de la bondad del ajuste 97 4. Regresión. Método de regresión a la media 100 5. Análisis de la bondad de la regresión 102 6. Notas y conclusiones 104 7. Ejercicios 105 B Probabilidad 113 4 Teoría de la probabilidad 117 1. Evolución histórica 117 2. Conjuntos. Operaciones 120 3. Algebra de sucesos 122 4. Distintas de?niciones del concepto de probabilidad 126 5. Propiedades de la función de probabilidad 129 6. Probabilidad condicionada. Independencia 131 7. Dependencia e independencia 132 8. Teorema de la probabilidad total. Teorema de Bayes 133 9. Ejercicios 136 5 Variable aleatoria 145 1. Concepto 145 2. Variables discretas y continuas 146 3. Variables unidimensionales 147 4. Variables multidimensionales 161 5. Ejercicios 173 6 Algunos modelos probabilísticos 185 1. Distribución uniforme discreta 185 2. Experimento de Bernouilli 186 3. Distribución hipergeométrica 191 4. Proceso de Poisson 192 5. Distribución uniforme continua 195 6. Distribución normal 197 7. Relación entre binomial, Poisson y normal 200 8. Teorema central del límite 201 9. Distribución gamma 202 10. Distribución beta 203 11. Distribución de Cauchy 204 12. Distribuciones derivadas de la normal 206 13. Distribución de Laplace 210 14. Distribución logística 211 15. Distribución de Pareto 211 16. Algunos modelos multidimensionales 212 17. Ejercicios 215 A Combinatoria 225 1. Introducción 225 2. Variaciones con repetición 225 3. Variaciones 226 4. Permutaciones 226 5. Permutaciones con repetición 226 6. Combinaciones sin repetición 227 7. Combinaciones con repetición 228 8. Ejercicios 228 B Tablas Estadísticas 233 C Bibliografía 25

Springtime coupled modes of regional wind in the Iberian Peninsula and large-scale variability patterns

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Imported eosinophilic fever with myositis: A diagnostic challenge

A 39-year-old caucasian man presented to our hospital in Barcelona with fever, dry cough, headache and weight loss of 4 kg. Symptoms started 5 days after returning from a 21-day travel to Malaysia. His physical examination was unremarkable except for a splenomegaly. Laboratory tests showed mild elevation of transaminases, elevated levels of lactate dehydrogenase (468 UI/L) and a normal blood cell count. Blood cultures, thick and thin blood smear and serologic tests for dengue, chikungunya, HIV, cytomegalovirus, Epstein-Barr virus, herpes virus 6, parvovirus B19, Toxoplasma spp and Rickettsia conorii were negative

A self-driven approach for multi-class discrimination in Alzheimer’s disease based on wearable EEG

Early detection is critical to control Alzheimer’s disease (AD) progression and postpone cognitive decline. Traditional medical procedures such as magnetic resonance imaging are costly, involve long waiting lists, and require complex analysis. Alternatively, for the past years, researchers have successfully evaluated AD detection approaches based on machine learning and electroencephalography (EEG). Nonetheless, these approaches frequently rely upon manual processing or involve non-portable EEG hardware. These aspects are suboptimal regarding automated diagnosis, since they require additional personnel and hinder porta- bility. In this work, we report the preliminary evaluation of a self-driven AD multi-class discrimination approach based on a commercial EEG acquisition system using sixteen channels. For this purpose, we recorded the EEG of three groups of participants: mild AD, mild cognitive impairment (MCI) non-AD, and controls, and we implemented a self-driven analysis pipeline to discriminate the three groups. First, we applied automated artifact rejection algorithms to the EEG recordings. Then, we extracted power, entropy, and complexity features from the preprocessed epochs. Finally, we evaluated a multi-class classification problem using a multi-layer perceptron through leave-one-subject-out cross-validation. The preliminary results that we obtained are comparable to the best in literature (0.88 F1-score), what suggests that AD can potentially be detected through a self-driven approach based on commercial EEG and machine learn- ing. We believe this work and further research could contribute to opening the door for the detection of AD in a single consultation session, therefore reducing the costs associated to AD screening and poten- tially advancing medical treatment.Spanish Government PGC2018-098813-B-C31European Commission Operative Program FEDER 2014-2020 BTIC-352-UGR20Economy, Universities and Science Office of the Andalusian Regional GovernmentUniversidad de Granada/CBU

An Automated Approach for the Detection of Alzheimer’s Disease From Resting State Electroencephalography

Early detection is crucial to control the progression of Alzheimer’s disease and to postpone intellectual decline. Most current detection techniques are costly, inaccessible, or invasive. Furthermore, they require laborious analysis, what delays the start of medical treatment. To overcome this, researchers have recently investigated AD detection based on electroencephalography, a non-invasive neurophysiology technique, and machine learning algorithms. However, these approaches typically rely on manual procedures such as visual inspection, that requires additional personnel for the analysis, or on cumbersome EEG acquisition systems. In this paper, we performed a preliminary evaluation of a fully-automated approach for AD detection based on a commercial EEG acquisition system and an automated classification pipeline. For this purpose, we recorded the resting state brain activity of 26 participants from three groups: mild AD, mild cognitive impairment (MCI-non-AD), and healthy controls. First, we applied automated data-driven algorithms to reject EEG artifacts. Then, we obtained spectral, complexity, and entropy features from the preprocessed EEG segments. Finally, we assessed two binary classification problems: mild AD vs. controls, and MCI-non-AD vs. controls, through leave-one-subject-out cross-validation. The preliminary results that we obtained are comparable to the best reported in literature, what suggests that AD detection could be automatically detected through automated processing and commercial EEG systems. This is promising, since it may potentially contribute to reducing costs related to AD screening, and to shortening detection times, what may help to advance medical treatment.PID2021-128529OA-I00 Spanish Ministry of Science, Innovation and UniversitiesEuropean Regional Development FundsBTIC- 352-UGR20Operative Program FEDER 2014–2020Economy, Universities and Science Office of the Andalusian Regional Governmen

Preliminary Study on the Effect of an Early Physical Therapy Intervention after Sentinel Lymph Node Biopsy: A Multicenter Non-Randomized Controlled Trial

Selective sentinel lymph node biopsy (SLNB) represents a minimally invasive surgery in patients with breast cancer. The purpose of this study was to explore the possible effect of an early physiotherapy intervention for the recovery of the upper limb and the surgical scars after SLNB in comparison with usual care. A total of 40 patients were enrolled in either the control group (n = 20) or the experimental group (n = 20). The intervention group performed an early physiotherapy program based on functional exercises, scar manual therapy, and educational tips. The control group received usual care. Shoulder range of motion (ROM), grip strength, upper limb pain and disability (SPADI), scar recovery (POSAS), myofascial adhesions (MAP-BC), quality of life (EORTCQLA-BR-23) and the presence of axillary web syndrome (AWS) and lymphoedema were assessed at baseline and immediately after intervention. A follow-up period of 6 months was performed for lymphoedema surveillance. Between groups significant differences in favor of the intervention were found for ROM (r = 0.43), grip strength (r = 0.32), SPADI (d = 0.45), POSAS (d = 1.28), MAP-BC (d = 1.82) and EORTCQLQ-BR 23 general function subscale (d = 0.37) (p < 0.05 for all variables). Our results suggest that an early physical therapy program seems to be more effective than usual care in women after SLNB. However, results should be interpreted with caution and future randomized trial with a larger sample size is neededThis research was partially supported by ICPFA. Grant number 04722/19P/MA. The funder had no role in the design of the study and collection, analysis, and interpretation of data, and in writing the manuscript. Partial funding for open access charge: Universidad de Málag

A learning experience toward the understanding of abstraction-level interactions in parallel applications

In the curriculum of a Computer Engineering program, concepts like parallelism, concurrency, consistency, or atomicity are usually addressed in separate courses due to their thoroughness and extension. Isolating such concepts in courses helps students not only to focus on specific aspects, but also to experience the reality of working with modern computer systems, where those concepts are often detached in different abstraction levels. However, due to such an isolation, it exists a risk of inducing to the students an absence of interactions between these concepts, and, by extension, between the different abstraction levels of a system. This paper proposes a learning experience showcasing the interactions between abstraction levels addressed in laboratory sessions of different courses. The driving example is a parallel ray tracer. In the different courses, students implement and assemble components of this application from the algorithmic level of the tracer to the assembly instructions required to guarantee atomicity. Each lab focuses on a single abstraction level, but shows students the interactions with the rest of the levels. Technical results and student learning outcomes through the analysis of surveys validate the proposed experience and confirm the students learning improvement with a more integrated view of the system

Post-splenectomy acute glomerulonephritis due to a chronic infection with Plasmodium falciparum and malariae

A 38-year-old Senegalese man with no previous medical history and living in Spain since 2004 was admitted due to fever, hypotension and edemas. The patient had not traveled to malaria endemic areas for the last 2 years, and 43 days before this episode he underwent an elective splenectomy in order to rule out a hematologic neoplasm due to a 27-cm splenomegaly and pancytopenia

Sporotrichoid dissemination of cutaneous leishmaniasis possibly triggered by a diagnostic puncture

Case report: A 31 year old Spanish woman attended Hospital Clinic in Barcelona in August 2018, after working in La Paz (Bolivia) for six months. She remembered an insect bite on her right thigh, during a trip to Beni (Brazilian border) with progression to a papule with a central crater within one month. Treatment with oral moxicillin/clavulanic acid yielded no improvement. Thereupon, a diagnostic puncture of the ulcer was performed, with a positive result of polymerase chain eaction (PCR) for Leishmania spp. without bacterial isolates in the culture. She then decided to return to Spain for management

Short-term effects of four tillage practices on soil physical properties, soil water potential, and maize yield

The area cultivated using conservation tillage has recently increased in central Spain. However, soil compaction and water retention with conservation tillage still remains a genuine concern for landowners in this region be- cause of its potential effect on the crop growth and yield. The aim of this research is to determine the short- term influences of four tillage treatments on soil physical properties. In the experiment, bulk density, cone index, soil water potential, soil temperature and maize (Zea mays L.) productivity have been measured. A field experiment was established in spring of 2013 on a loamy soil. The experiment compared four tillage methods (zero tillage, ZT; reservoir tillage, RT; minimum tillage, MT; and conventional tillage, CT). Soil bulk density and soil cone index were measured during maize growing season and at harvesting time. Furthermore, the soil water potential was monitored by using a wireless sensors network with sensors at 20 and 40 cm depths. Also, soil temperatures were registered at depths of 5 and 12 cm. Results indicated that there were significant differ- ences between soil bulk density and cone index of ZT method and those of RT, MT, and CT, during the growing season; although, this difference was not significant at the time of harvesting in some soil layers. Overall, in most soil layers, tillage practice affected bulk density and cone index in the order: ZT N RT N MT N CT. Regardless oftheentireobservationperiod,results exhibited that soils under ZT and RT treatments usually resulted in higher water potential and lower soil temperature than the other two treatments at both soil depths. In addition, clear differences in maize grain yield were observed between ZT and CT treatments, with a grain yield (up to 15.4%) increase with the CT treatment. On the other hand, no significant differences among (RT, MT, and CT) on maizeyieldwerefound.Inconclusion,the impact of soil compaction increase and soil temperature decrease,pro- duced by ZT treatment is a potential reason for maize yield reduction in this tillage method. We found that RT could be certainly a viable option for farmers incentral Spain,particularly when switching to conservation tillage from conventional tillage. This technique showed a moderate and positive effect on soil physical properties and increased maize yields compared to ZT and MT, and provides an opportunity to stabilize maize yields compared to CT