Representation Independent Analytics Over Structured Data

Database analytics algorithms leverage quantifiable structural properties of the data to predict interesting concepts and relationships. The same information, however, can be represented using many different structures and the structural properties observed over particular representations do not necessarily hold for alternative structures. Thus, there is no guarantee that current database analytics algorithms will still provide the correct insights, no matter what structures are chosen to organize the database. Because these algorithms tend to be highly effective over some choices of structure, such as that of the databases used to validate them, but not so effective with others, database analytics has largely remained the province of experts who can find the desired forms for these algorithms. We argue that in order to make database analytics usable, we should use or develop algorithms that are effective over a wide range of choices of structural organizations. We introduce the notion of representation independence, study its fundamental properties for a wide range of data analytics algorithms, and empirically analyze the amount of representation independence of some popular database analytics algorithms. Our results indicate that most algorithms are not generally representation independent and find the characteristics of more representation independent heuristics under certain representational shifts

El comercio justo en el desarrollo de productores cafetaleros de la Cooperativa Juan Ramón Corea al II semestre del 2011

El presente trabajo es un estudio del comercio justo dentro de los productores cafetaleros, donde su objetivo es buscar la equidad con el comercio internacional, de tal manera que estos puedan vender sus productos con un aumento mínimo al precio que se obtiene en el mercado, por lo que al realizar el estudio de este en la cooperativa Juan Ramón Corea productoras de café, afiliada a CECOCAFEN; significó conocer otra forma de producir y comercializar, donde el pequeño productor tiene acceso, es participe y decide vender o no su producto, al mismo tiempo debe de poner en práctica las políticas medioambientales, de equidad de género y principios y valores que en el comercio convencional no son mencionados y los beneficios obtenidos de los socios al estar en comercio justo. Para realizar este estudio utilizamos métodos empíricos para la recopilación de la información, así como teórico en el proceso de análisis, síntesis, inducción y deducción con enfoques cualitativos y cuantitativos. Las técnicas que se utilizaron en el proceso de investigación fueron La Guía de Observación, Grupo Focal a los socios de la cooperativa, La Encuesta, esta se realizó de acuerdo a los indicadores planteados para darle mayor validez se realizaron los tres instrumentos mencionados. Nuestro universo de estudio fueron los socios que integran la Cooperativa, la cual cuenta con 38 socios activos que comprenden 11 mujeres y 27 Hombres. Las variables medibles fueron tres Cooperativismo, Comercio Justo y Desarrollo humano. Dentro de los principales hallazgos tenemos la participación activa de los socios en la colocación de precios de su producto, el interés por la conservación del medio ambiente como forma de darle mayor valor a su producción y la inclusión de principios y valores como el respeto, la solidaridad, la unidad y tomar en cuenta la participación de la mujer en los procesos productivos, por lo que podemos decir que de manera general el comercio justo es otra forma de comercio en la forma de dar valor a la forma de actuar y valora del hombre el medio que le rodea y de no ser otra forma de vender y acumular riquezas, siendo esta la parte más interesante y de mayor valor para una sociedad como la nuestra que aspira a tener un mejor nivel de vida y de desarrollo socia

Representationally Robust and Scalable Learning over Relational Databases

Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the same data may be represented under different representations. The current approach to effectively use learning algorithms is to find the desired representations for these algorithms, transform the data to these representations, and clean the data. These tasks are hard and time-consuming and are major obstacles for unlocking the value of data. This thesis demonstrates that it is possible to develop robust learning algorithms that learn in the presence of representational variations. We develop two systems called Castor and CastorX, which exploit data dependencies to be robust against different types of representational variations. Further, we propose several techniques that allow these systems to learn efficiently over large databases. The proposed systems learn over the original data, removing the need for transforming the data before applying learning algorithms. Our results show that Castor and CastorX learn accurately and efficiently over real-world databases. This work paves the way for new approaches that replace pre-processing tasks such as data wrangling with robust learning algorithms

Propuesta de Plan de Mejora para sistema de Mantenimiento preventivo a los Equipos de transporte de carga pesada en empresa comercializadora de Maní S.A. COMASA

Presenta propuesta de Plan de Mejora para sistema de Mantenimiento preventivo a los Equipos de transporte de carga pesada en empresa comercializadora de Maní S.A. COMASA en el cual se realizó un estudio de la situación actual así como el establecimiento de indicadores de mantenimiento a implementar

Derivation and validation of a clinical prediction rule for sleep apnoea syndrome for use in primary care

Background: Several clinical prediction rules (CPRs) are available for sleep apnoea-hypopnoea syndrome (OSAH), but they are difficult to apply in primary care (PC). Aim: Derivation and validation of a CPR using simple measurements available in PC. Design & setting: A prospective study conducted in health centres from the area of influence of three Spanish hospitals. Method: Patients (aged 18-70 years) who attended for any reason; who presented with at least one of the three key symptoms for OSAH (snoring, breathing pauses while sleeping, and daytime sleepiness); and who were not undergoing non-invasive ventilation or prior treatment with continuous positive airway pressure (CPAP) were included. Anthropometric data, smoking habit, comorbidities, and Epworth test were collected. Patients were subsequently referred to the sleep unit (SU), where the decision was taken whether or not to instigate treatment. A multivariate logistic model was constructed using a sub-sample and scores assigned based on the regression coefficients; the CPR was validated with the remaining sample. Both receiver operating characteristic (ROC) curves were plotted and the sensitivity, specificity, and predictive values calculated. Results: The derivation sample comprised 352 patients, with 260 in the validation sample. The final factors (arterial hypertension [AHT], age, body mass index [BMI], and sex) were used to develop a rule with scores ranging from 0.00-5.50. The cut-off point that optimises the area under the curve (AUC) is ?2.50 points (AUC = 0.78; sensitivity = 86%; specificity = 54%; positive predictive value [PPV] = 45%; negative predictive value [NPV] = 90%; likelihood ratio [LR] = 0.26). The properties for the validation sample with this cut-off point are as follows: AUC = 0.68; sensitivity = 81%; specificity = 43%; PPV = 61%; NPV = 68%; LR = 0.44. Conclusion: As in similar cases, the specificity is low, meaning that healthy people are referred to a specialist. A negative result rules out the disease in most cases

Altered White Matter Integrity at Illness Onset in Adolescents With a First Episode of Psychosis

Background: Disruption in white matter integrity has been consistently observed in individuals with psychosis. However, whether such abnormalities are already present at illness onset or are related to downstream processes remains elusive. The study of adolescents with a recent onset of psychosis provides the opportunity to evaluate white matter integrity proximally to disease onset. Methods: Twenty-six adolescents (aged 15.9 ± 1.3 years) with a first episode of psychosis (FEP) (less than 6 months duration) were compared with 26 age and sex-matched healthy controls (HC) (16.8 ± 2 years). In participants with a FEP, clinical diagnoses were confirmed after a minimum of 1 year follow-up (main categories: schizophrenia, bipolar disorder, or schizoaffective disorder). Anatomical images and diffusion tensor sequences were acquired using a 1.5T scanner. Whole brain, voxel-wise group differences in fractional anisotropy (FA) were investigated between participants with a FEP and controls. Results: Relative to HC, FEP participants displayed decreased FA in the right posterior cingulate gyrus, encompassing the right superior and posterior corona radiata, and the right parahippocampal gyrus, including the cingulum and fornix. FEP patients showed no areas of increased FA relative to HC. The results remained significant after controlling for medication, cannabis use and intelligence. Conclusion: Our findings indicate that adolescents with recent onset of psychotic disorders show decreased white matter integrity in circuits implicated in cognitive functions and emotion regulation

Cancer immunotherapy in special challenging populations: recommendations of the Advisory Committee of Spanish Melanoma Group (GEM)

Cancer immunotherapy based on the use of antibodies targeting the so-called checkpoint inhibitors, such as programmed cell death-1 receptor, its ligand, or CTLA-4, has shown durable clinical benefit and survival improvement in melanoma and other tumors. However, there are some special situations that could be a challenge for clinical management. Persons with chronic infections, such as HIV-1 or viral hepatitis, latent tuberculosis, or a history of solid organ transplantation, could be candidates for cancer immunotherapy, but their management requires a multidisciplinary approach. The Spanish Melanoma Group (GEM) panel in collaboration with experts in virology and immunology from different centers in Spain reviewed the literature and developed evidence-based guidelines for cancer immunotherapy management in patients with chronic infections and immunosuppression. These are the first clinical guidelines for cancer immunotherapy treatment in special challenging populations. Cancer immunotherapy in chronically infected or immunosuppressed patients is feasible but needs a multidisciplinary approach in order to decrease the risk of complications related to the coexistent comorbidities

Virological and immunological outcome of treatment interruption in HIV-1-infected subjects vaccinated with MVA-B

The most relevant endpoint in therapeutic HIV vaccination is the assessment of time to viral rebound or duration of sustained control of low-level viremia upon cART treatment cessation. Structured treatment interruptions (STI) are however not without risk to the patient and reliable predictors of viral rebound/control after therapeutic HIV-1 vaccination are urgently needed to ensure patient safety and guide therapeutic vaccine development. Here, we integrated immunological and virological parameters together with viral rebound dynamics after STI in a phase I therapeutic vaccine trial of a polyvalent MVA-B vaccine candidate to define predictors of viral control. Clinical parameters, proviral DNA, host HLA genetics and measures of humoral and cellular immunity were evaluated. A sieve effect analysis was conducted comparing pre-treatment viral sequences to breakthrough viruses after STI. Our results show that a reduced proviral HIV-1 DNA at study entry was independently associated with two virological parameters, delayed HIV-1 RNA rebound (p = 0.029) and lower peak viremia after treatment cessation (p = 0.019). Reduced peak viremia was also positively correlated with a decreased number of HLA class I allele associated polymorphisms in Gag sequences in the rebounding virus population (p = 0.012). Our findings suggest that proviral DNA levels and the number of HLA-associated Gag polymorphisms may have an impact on the clinical outcome of STI. Incorporation of these parameters in future therapeutic vaccine trials may guide refined immunogen design and help conduct safer STI approaches