Beneficial Effects of a Semi-Intensive Stroke Unit are Beyond the Monitor.

BACKGROUND AND PURPOSE Precise mechanisms underlying the effectiveness of the stroke unit (SU) are not fully established. Studies that compare monitored stroke units (semi-intensive type, SI-SU) versus an intensive care unit (ICU)-based mobile stroke team (MST-ICU) are lacking. Although inequalities in access to stroke unit care are globally improving, acute stroke patients may be admitted to Intensive Care Units for monitoring and followed by a mobile stroke team in hospital's lacking an SU with continuous cardiovascular monitoring. We aimed at comparing the stroke outcome between SI-SU and MST-ICU and hypothesized that the benefits of SI-SU are driven by additional elements other than cardiovascular monitoring, which is equally offered in both care systems. METHODS In a single-center setting, we compared the unfavorable outcomes (dependency and mortality) at 3 months in consecutive patients with ischemic stroke or spontaneous intracerebral hemorrhage admitted to a stroke unit with semi-intensive monitoring (SI-SU) to a cohort of stroke patients hospitalized in an ICU and followed by a mobile stroke team (MST-ICU) during an equal observation period of 27 months. Secondary objectives included comparing mortality and the proportion of patients with excellent outcomes (modified Rankin Score (mRS) 0-1). Equal cardiovascular monitoring was offered in patients admitted in both SI-SU and MST-ICU. RESULTS 458 patients were treated in the SI-SU and compared to the MST-ICU (n = 370) cohort. The proportion of death and dependency after 3 months was significantly improved for patients in the SI-SU compared to MST-ICU (p < 0.001; aOR = 0.45; 95% CI: 0.31-0.65). The shift analysis of the mRS distribution showed significant shift to the lower mRS in the SI-SU group, p < 0.001. The proportion of mortality in patients after 3 months also differed between the MST-ICU and the SI-SU (p < 0.05), but after adjusting for confounders this association was not significant (aOR = 0.59; 95% CI: 0.31-1.13). The proportion of patients with excellent outcome was higher in the SI-SU (59.4 vs. 44.9%, p < 0.001) but the relationship was no more significant after adjustment (aOR = 1.17; 95% CI: 0.87-1.5). CONCLUSIONS Our study shows that moving from a stroke team in a monitored setting (ICU) to an organized stroke unit leads to a significant reduction in the 3 months unfavorable outcome in patients with an acute ischemic or hemorrhagic stroke. Cardiovascular monitoring is indispensable, but benefits of a semi-intensive Stroke Unit are driven by additional elements beyond intensive cardiovascular monitoring. This observation supports the ongoing development of Stroke Centers for efficient stroke care. © 2015 S. Karger AG, Basel.

Complementary Medicine in Nursing Homes - Results of a Mixed Methods Pilot Study

Background ‘Kneipp Therapy’ (KT) is a form of Complementary and Alternative Medicine (CAM) that includes a combination of hydrotherapy, herbal medicine, mind-body medicine, physical activities, and healthy eating. Since 2007, some nursing homes for older adults in Germany began to integrate CAM in the form of KT in care. The study investigated how KT is used in daily routine care and explored the health status of residents and caregivers involved in KT. Methods We performed a cross-sectional pilot study with a mixed methods approach that collected both quantitative and qualitative data in four German nursing homes in 2011. Assessments in the quantitative component included the Quality of Life in Dementia (QUALIDEM), the Short Form 12 Health Survey (SF-12), the Barthel-Index for residents and the Work Ability Index (WAI) and SF-12 for caregivers. The qualitative component addressed the residents’ and caregivers’ subjectively experienced changes after integration of KT. It was conceptualized as an ethnographic rapid appraisal by conducting participant observation and semi-structured interviews in two of the four nursing homes. Results The quantitative component included 64 residents (53 female, 83.2 ± 8.1 years (mean and SD)) and 29 caregivers (all female, 42.0 ± 11.7 years). Residents were multimorbid (8 ± 3 diagnoses), and activities of daily living were restricted (Barthel-Index 60.6 ± 24.4). The caregivers’ results indicated good work ability (WAI 37.4 ± 5.1), health related quality of life was superior to the German sample (SF-12 physical CSS 49.2 ± 8.0; mental CSS 54.1 ± 6.6). Among both caregivers and residents, 89% considered KT to be positive for well-being. The qualitative analysis showed that caregivers perceived emotional and functional benefits from more content and calmer residents, a larger variety in basic care practices, and a more self-determined scope of action. Residents reported gains in attention and caring, and recognition of their lay knowledge. Conclusion Residents showed typical characteristics of nursing home inhabitants. Caregivers demonstrated good work ability. Both reported to have benefits from KT. The results provide a good basis for future projects, e.g. controlled studies to evaluate the effects of CAM in nursing homes.

Explicit vs implicit affiliation motives predict different social behavior in sports competition

Objectives The present study investigated the predictive value of the explicit and implicit affiliation motive for social behavior in sport competitions. From an information processing perspective, an explicit motive is linked to verbal cues and respondent behavior. The implicit motive in turn is linked to nonverbal stimuli and operant behavior (McClelland, Koestner, & Weinberger, 1989; Schultheiss, 2008). Both respondent affiliative behavior (e.g., verbal interactions with teammates) and operant nonverbal social behavior (e.g., pleasant to opponents) can be observed in racquet sports team competitions. Design & Methods Fifty-two male racquet sportsmen completed the Personality Research Form (explicit affiliation motive) and the Operant Motive Test (implicit affiliation motive). Motive measures were used to predict social behavior during competitions using multiple regression analyses. To this aim real competitive matches were videotaped and analyzed. Results Results show that the explicit affiliation motive is associated with time spent in verbal team contact. The implicit affiliation motive, by contrast, is linked to pleasant nonverbal behavior shown toward opponents. Conclusions Findings suggest that implicit and explicit affiliation motives predict different kinds of social behavior in sports competition respectively. Indirect motive measures may be of additional predictive value for different behavior in real sports settings.

Timing of extreme drought modifies reproductive output in semi-natural grassland

Questions Do extreme dry spells in late summer or in spring affect abundance and species composition of the reproductive shoots and the seed rain in the next annual crop? Are drought effects on reproductive shoots related to the rooting depths of species? Location Species-rich semi-natural grassland at Negrentino, Switzerland. Methods In plots under automated rain-out shelters, rainwater was added to simulate normal conditions and compare them with two experimentally effected long dry spells, in late summer (2004) and in the following spring (2005). For 28 plots, numbers of reproductive shoots per species were counted in 1-m2 areas and seed rain was estimated using nine sticky traps of 102 cm2 after dry spells. Results The two extreme dry spells in late summer and spring were similar in length and their probability of recurrence. They independently reduced the subsequent reproductive output of the community, while their seasonal timing modified its species composition. Compared to drought in spring, drought in late summer reduced soil moisture more and reduced the number of reproductive shoots of more species. The negative effects of summer drought decreased with species’ rooting depth. The shallow-rooted graminoids showed a consistent susceptibility to summer drought, while legumes and other forbs showed more varied responses to both droughts. Spring drought strongly reduced density (–53%) and species richness (–43%) of the community seed rain, while summer drought had only a marginally significant impact on seed density of graminoids (–44%). Reductions in seed number per shoot vs reproductive shoot density distinguished the impacts of drought with respect to its seasonal timing. Conclusion The essentially negative impact of drought in different seasons on reproductive output suggests that more frequent dry spells could contribute to local plant diversity loss by aggravating seed deficiency in species-rich grassland.

Coping Methods and Meaning Making of Liberian Refugees in the Buduburam Refugee Camp of Ghana

The mental health of war-impacted individuals has been an issue of growing concern to many researchers and practitioners internationally (Miller, Kulkarni, & Kushner, 2006). According to the United Nations High Commissioner for Refugees (2006a), Africans are disproportionately impacted by conflict-related displacement. To date, however, much of the research on the mental health of refugees has been based mostly on Western views of health and trauma. The current study is a mixed-methods investigation of stressors, coping strategies, and meaning making of Liberian refugees in the Buduburam Refugee Camp of Ghana. Results from the Brief COPE, focus groups, and semi-structured ethnographic interviews are discussed. Understanding stressors and coping among this population can contribute to culturally informed research and practice.

Extension of k-ratio methods to rank-based analyses

An extension of k-ratio multiple comparison methods to rank-based analyses is described. The new method is analogous to the Duncan-Godbold approximate k-ratio procedure for unequal sample sizes or correlated means. The close parallel of the new methods to the Duncan-Godbold approach is shown by demonstrating that they are based upon different parameterizations as starting points.^ A semi-parametric basis for the new methods is shown by starting from the Cox proportional hazards model, using Wald statistics. From there the log-rank and Gehan-Breslow-Wilcoxon methods may be seen as score statistic based methods.^ Simulations and analysis of a published data set are used to show the performance of the new methods. ^

Evaluation of Non-Survey International IO Construction Methods with the Asian-Pacific Input-Output Table

This paper presents four non-survey methods to construct a full-information international input-output table from national IO tables and international import and export statistics, and this paper tests these four methods against the semi-survey international IO table for nine East-Asian countries and the USA, which is constructed by the Institute of Developing Economies in Japan. The tests show that the impact on the domestic flows of using self-sufficiency ratios is small, except for Singapore and Malaysia, two countries with large volumes of smuggling and transit trade. As regards the accuracy of the international flows, all methods show considerable errors, of 10%-40% for commodities and of 10%-70% for services. When more information is added, i.e. going from Method 1 to 4, the accuracy increases, except for Method 2 that generally produces larger errors than Method 1. In all, it seems doubtful whether replacing the semi-survey Asian-Pacific IO table with one of the four non-survey tables is justified, except when the semi-survey table itself is also considered to be just another estimate.

Semi-supervised subspace clustering and applications to neuroscience

Machine learning techniques are used for extracting valuable knowledge from data. Nowa¬days, these techniques are becoming even more important due to the evolution in data ac¬quisition and storage, which is leading to data with different characteristics that must be exploited. Therefore, advances in data collection must be accompanied with advances in machine learning techniques to solve new challenges that might arise, on both academic and real applications. There are several machine learning techniques depending on both data characteristics and purpose. Unsupervised classification or clustering is one of the most known techniques when data lack of supervision (unlabeled data) and the aim is to discover data groups (clusters) according to their similarity. On the other hand, supervised classification needs data with supervision (labeled data) and its aim is to make predictions about labels of new data. The presence of data labels is a very important characteristic that guides not only the learning task but also other related tasks such as validation. When only some of the available data are labeled whereas the others remain unlabeled (partially labeled data), neither clustering nor supervised classification can be used. This scenario, which is becoming common nowadays because of labeling process ignorance or cost, is tackled with semi-supervised learning techniques. This thesis focuses on the branch of semi-supervised learning closest to clustering, i.e., to discover clusters using available labels as support to guide and improve the clustering process. Another important data characteristic, different from the presence of data labels, is the relevance or not of data features. Data are characterized by features, but it is possible that not all of them are relevant, or equally relevant, for the learning process. A recent clustering tendency, related to data relevance and called subspace clustering, claims that different clusters might be described by different feature subsets. This differs from traditional solutions to data relevance problem, where a single feature subset (usually the complete set of original features) is found and used to perform the clustering process. The proximity of this work to clustering leads to the first goal of this thesis. As commented above, clustering validation is a difficult task due to the absence of data labels. Although there are many indices that can be used to assess the quality of clustering solutions, these validations depend on clustering algorithms and data characteristics. Hence, in the first goal three known clustering algorithms are used to cluster data with outliers and noise, to critically study how some of the most known validation indices behave. The main goal of this work is however to combine semi-supervised clustering with subspace clustering to obtain clustering solutions that can be correctly validated by using either known indices or expert opinions. Two different algorithms are proposed from different points of view to discover clusters characterized by different subspaces. For the first algorithm, available data labels are used for searching for subspaces firstly, before searching for clusters. This algorithm assigns each instance to only one cluster (hard clustering) and is based on mapping known labels to subspaces using supervised classification techniques. Subspaces are then used to find clusters using traditional clustering techniques. The second algorithm uses available data labels to search for subspaces and clusters at the same time in an iterative process. This algorithm assigns each instance to each cluster based on a membership probability (soft clustering) and is based on integrating known labels and the search for subspaces into a model-based clustering approach. The different proposals are tested using different real and synthetic databases, and comparisons to other methods are also included when appropriate. Finally, as an example of real and current application, different machine learning tech¬niques, including one of the proposals of this work (the most sophisticated one) are applied to a task of one of the most challenging biological problems nowadays, the human brain model¬ing. Specifically, expert neuroscientists do not agree with a neuron classification for the brain cortex, which makes impossible not only any modeling attempt but also the day-to-day work without a common way to name neurons. Therefore, machine learning techniques may help to get an accepted solution to this problem, which can be an important milestone for future research in neuroscience. Resumen Las técnicas de aprendizaje automático se usan para extraer información valiosa de datos. Hoy en día, la importancia de estas técnicas está siendo incluso mayor, debido a que la evolución en la adquisición y almacenamiento de datos está llevando a datos con diferentes características que deben ser explotadas. Por lo tanto, los avances en la recolección de datos deben ir ligados a avances en las técnicas de aprendizaje automático para resolver nuevos retos que pueden aparecer, tanto en aplicaciones académicas como reales. Existen varias técnicas de aprendizaje automático dependiendo de las características de los datos y del propósito. La clasificación no supervisada o clustering es una de las técnicas más conocidas cuando los datos carecen de supervisión (datos sin etiqueta), siendo el objetivo descubrir nuevos grupos (agrupaciones) dependiendo de la similitud de los datos. Por otra parte, la clasificación supervisada necesita datos con supervisión (datos etiquetados) y su objetivo es realizar predicciones sobre las etiquetas de nuevos datos. La presencia de las etiquetas es una característica muy importante que guía no solo el aprendizaje sino también otras tareas relacionadas como la validación. Cuando solo algunos de los datos disponibles están etiquetados, mientras que el resto permanece sin etiqueta (datos parcialmente etiquetados), ni el clustering ni la clasificación supervisada se pueden utilizar. Este escenario, que está llegando a ser común hoy en día debido a la ignorancia o el coste del proceso de etiquetado, es abordado utilizando técnicas de aprendizaje semi-supervisadas. Esta tesis trata la rama del aprendizaje semi-supervisado más cercana al clustering, es decir, descubrir agrupaciones utilizando las etiquetas disponibles como apoyo para guiar y mejorar el proceso de clustering. Otra característica importante de los datos, distinta de la presencia de etiquetas, es la relevancia o no de los atributos de los datos. Los datos se caracterizan por atributos, pero es posible que no todos ellos sean relevantes, o igualmente relevantes, para el proceso de aprendizaje. Una tendencia reciente en clustering, relacionada con la relevancia de los datos y llamada clustering en subespacios, afirma que agrupaciones diferentes pueden estar descritas por subconjuntos de atributos diferentes. Esto difiere de las soluciones tradicionales para el problema de la relevancia de los datos, en las que se busca un único subconjunto de atributos (normalmente el conjunto original de atributos) y se utiliza para realizar el proceso de clustering. La cercanía de este trabajo con el clustering lleva al primer objetivo de la tesis. Como se ha comentado previamente, la validación en clustering es una tarea difícil debido a la ausencia de etiquetas. Aunque existen muchos índices que pueden usarse para evaluar la calidad de las soluciones de clustering, estas validaciones dependen de los algoritmos de clustering utilizados y de las características de los datos. Por lo tanto, en el primer objetivo tres conocidos algoritmos se usan para agrupar datos con valores atípicos y ruido para estudiar de forma crítica cómo se comportan algunos de los índices de validación más conocidos. El objetivo principal de este trabajo sin embargo es combinar clustering semi-supervisado con clustering en subespacios para obtener soluciones de clustering que puedan ser validadas de forma correcta utilizando índices conocidos u opiniones expertas. Se proponen dos algoritmos desde dos puntos de vista diferentes para descubrir agrupaciones caracterizadas por diferentes subespacios. Para el primer algoritmo, las etiquetas disponibles se usan para bus¬car en primer lugar los subespacios antes de buscar las agrupaciones. Este algoritmo asigna cada instancia a un único cluster (hard clustering) y se basa en mapear las etiquetas cono-cidas a subespacios utilizando técnicas de clasificación supervisada. El segundo algoritmo utiliza las etiquetas disponibles para buscar de forma simultánea los subespacios y las agru¬paciones en un proceso iterativo. Este algoritmo asigna cada instancia a cada cluster con una probabilidad de pertenencia (soft clustering) y se basa en integrar las etiquetas conocidas y la búsqueda en subespacios dentro de clustering basado en modelos. Las propuestas son probadas utilizando diferentes bases de datos reales y sintéticas, incluyendo comparaciones con otros métodos cuando resulten apropiadas. Finalmente, a modo de ejemplo de una aplicación real y actual, se aplican diferentes técnicas de aprendizaje automático, incluyendo una de las propuestas de este trabajo (la más sofisticada) a una tarea de uno de los problemas biológicos más desafiantes hoy en día, el modelado del cerebro humano. Específicamente, expertos neurocientíficos no se ponen de acuerdo en una clasificación de neuronas para la corteza cerebral, lo que imposibilita no sólo cualquier intento de modelado sino también el trabajo del día a día al no tener una forma estándar de llamar a las neuronas. Por lo tanto, las técnicas de aprendizaje automático pueden ayudar a conseguir una solución aceptada para este problema, lo cual puede ser un importante hito para investigaciones futuras en neurociencia.

Biostimulation methods associated with early weaning and reproductive rhythms in primiparous rabbit does

El objetivo general de esta Tesis Doctoral ha sido tratar de mejorar los parámetros reproductivos de las conejas primíparas lactantes, empleando dos métodos de manejo (destete temprano y extensificación del ritmo reproductivo), que están directamente relacionados con su balance energético. Para ello, se diseñaron 2 experimentos en este tipo de hembras. En el primero, se estudió el efecto del destete a 25 días post-parto (dpp) sobre la actividad ovárica y el metabolismo energético de las conejas una semana más tarde (32 dpp). Un total de 34 primíparas lactantes con 8 gazapos fueron distribuidas en tres grupos: 10 conejas se sacrificaron a los 25 dpp (grupo L25), 13 fueron destetadas a los 25 dpp y sacrificadas a los 32 dpp (grupo NL32), y 11 conejas no se destetaron y fueron sacrificadas a los 32 dpp (grupo L32). No se observaron diferencias significativas entre grupos en el peso corporal, el peso del ovario, ni en las concentraciones séricas de ácidos grasos no esterificados y de proteínas totales. A pesar de que el grupo NL32 presentó un bajo consumo de alimento (122 ± 23,5 g / día, p <0,001), su contenido corporal estimado de lípidos (16,9 ± 1,09%, P <0,008), proteínas (19,7 ± 0,07%, P <0,0001), y energía (1147 ± 42,7 MJ / kg, p <0,006) fueron más elevados y las concentraciones séricas de glucosa (158 ± 24,5 mg/dl, p <0,04) más bajas que en los grupos L25 (11,9 ± 1,3%, 18,5 ± 0,08%, 942 ± 51,3 MJ/kg y 212 ± 27,9 mg/dl) y L32 (13,4 ± 1,03%, 18,5 ± 0,1%, 993 ± 40,4 MJ/kg y 259 ± 29,5 mg/dl), respectivamente. En el grupo L25 se observó un menor número medio de folículos ≥ 1 mm en la superficie ovárica en comparación con los grupos NL32 y L32 (12,7 ± 1,5 vs. 18,0 ± 1,45 y 17,6 ± 1,67, p <0,05). La población folicular ovárica en las secciones histológicas y la inmunolocalización de los receptores de prolactina fueron similares en todos los grupos. En el grupo L25, tanto la maduración nuclear de oocitos, medida en términos de tasas alcanzadas de Metafase II (67,0 vs. 79,7 y 78,3%, P <0.05) y la maduración citoplasmática, medida por el porcentaje de gránulos corticales (GC) total o parcialmente migrados en los oocitos, fueron significativamente menores que en los grupos NL32 y L32 (16,0 vs 38,3 y 60,0%, P <0.05). En conclusión, a pesar de que el destete precoz a 25 dpp pareció mejorar las reservas de energía de las conejas primíparas, este hecho no se reflejó claramente a nivel ovárico a los 32 dpp y fue similar independientemente del destete, por lo que éste último podría llevarse a cabo más tarde. En el segundo experimento, se compararon dos ritmos reproductivos. Se utilizaron un total de 48 conejas primíparas lactantes con 8 gazapos que se asignaron al azar en dos grupos experimentales: a) lactantes sacrificadas a comienzos del post-parto (11 dpp) de acuerdo a un ritmo semi-intensivo (n = 24), y b) lactantes sacrificadas al final del período post-parto (25 dpp) de acuerdo con un ritmo más extensivo (n = 24). En ellas, se estudió el peso vivo, la composición corporal estimada, parámetros metabólicos y endocrinos (estradiol y progesterona) y características ováricas como la población folicular y la tasa de atresia, así como la maduración nuclear y citoplásmica de los oocitos. En este estudio, el peso vivo, el contenido de energía corporal, los depósitos grasos y los ácidos grasos no esterificados disminuyeron a lo largo del post-parto con respecto al momento del parto (P <0,05). Las concentraciones séricas de proteínas y glucosa aumentaron en el mismo periodo post-parto (P <0,05). Se observaron similares niveles de estradiol y progesterona en ambos ritmos, así como una población folicular, tasas de maduración nuclear (tasa de oocitos en metafase II) y citoplasmática (porcentaje de oocitos con gránulos corticales migrados), similares en ambos momentos del post-parto. Sin embargo, el número de folículos preovulatorios en la superficie ovárica fue menor (P <0,05) y la tasa de atresia tendió a ser mayor con un porcentaje también menor de folículos sanos (P <0,1) en los ovarios de las hembras sometidas al ritmo extensivo. En conclusión, al final del post-parto (25 días), las conejas primíparas sin destetar muestran un deterioro de sus reservas corporales, de sus parámetros metabólicos séricos y de la calidad de sus oocitos; incluso se ha observado una ligera influencia negativa en el desarrollo de sus folículos ováricos. Por esta razón, se considera que en las conejas primíparas lactantes el manejo reproductivo extensivo (25 dpp) no presenta ninguna ventaja en comparación con el semi-intensivo (11 dpp). A la vista de los resultados de estos dos experimentos, podemos decir que ni el destete temprano, ni la extensificación del ritmo reproductivo han conseguido una mejora en los parámetros reproductivos de una hembra primípara. Por ello, son necesarios más estudios sobre el estado metabólico de la coneja primípara lactante para conseguir métodos o estrategias que lo mejoren y tengan consecuencias directas sobre la actividad reproductiva y sobre su éxito productivo. The general aim of this Thesis was to study two management methods (early weaning and extensive reproductive rhythm) linked to the energy balance of the primiparous rabbit does to improve their reproductive performance. In this sense, 2 experiments were conducted using this kind of females. In the first experiment, the effect of weaning at 25 days post-partum (dpp) on ovarian activity and energetic metabolism one week later (32 dpp) was studied. A total of 34 primiparous lactating rabbit does were used and distributed among three groups: 10 does euthanized at 25 dpp (group L25), 13 does weaned at 25 dpp and euthanized at 32 dpp (group NL32), and 11 non weaned does euthanized at 32 dpp (group L32). No significant differences were observed in live body weight, ovary weight, serum non esterified fatty acids (NEFA) and total protein concentration among groups. Although NL32 does had a low feed intake (122±23.5 g/Day; P < 0.001), their estimated lipids (16.9±1.09%, P < 0.008), protein (19.7±0.07%, P < 0.0001), and energy (1147±42.7 MJ/kg, P < 0.006) body contents were higher and their serum glucose concentrations (158±24.5 mg/dl, P < 0.04) were lower compared to L25 does (11.9±1.3%, 18.5±0.08%, 942±51.3 MJ/kg and 212±27.9 mg/dl) and L32 does (13.4±1.03%, 18.5±0.1%, 993±40.4 MJ/kg and 259±29.5 mg/dl, respectively). A lower number of follicles ≥1mm was observed compared to NL32 and L32 groups (12.7±1.5 vs. 18.0±1.45 and 17.6 ±1.67; P < 0.05) in the ovarian surface of L25 does. Follicular population in the histological ovarian sections and immunolocalization of prolactin receptor were similar in all groups. In group L25, both nuclear maturation of oocytes in terms of Metaphase II rate (67.0 vs. 79.7 and 78.3%; P < 0.05) and cytoplasmic maturation measured by percentage of cortical granules (CG), totally or partially migrated in oocytes were significantly lower than in groups NL32 and L32 (16.0 vs. 38.3 and 60.0%; P < 0.05). Consequently, a higher rate of oocytes with non-migrated CGs was found in group L25 than in groups NL32 and L32 (76.0 vs. 46.8 and 33.3%; P < 0.05). In conclusion, even though early weaning at 25 dpp seemed to improve body energy stored in primiparous does, this fact was not well reflected on the ovarian status at 32 dpp, which was similar regardless of weaning time. In the second experiment, two reproductive rhythms were compared. A total of 48 primiparous Californian x New Zealand White rabbit does suckling 8 kits were randomly allocated in two experimental groups: a) lactating does euthanized at early post-partum period (11 dpp) according to a semi-intensive rhythm (n = 24), and b) lactating does euthanized on later post-partum period (25 dpp) according to a more extensive rhythm (n = 24). Live weight, estimated body composition, serum metabolic and endocrine parameters (oestradiol and progesterone concentrations) and ovarian features like follicle population and atresia rate, and oocyte maturation were studied. Live weight, body energy content, lipid depots and serum non esterified fatty acids (NEFA) concentrations diminished from parturition time to post-partum period (P < 0.05). In addition, serum protein and glucose concentrations increased along postpartum time (P < 0.05). Similar oestradiol and progesterone levels were shown in rhythms as well as similar follicle population and nuclear and cytoplasmic maturation rates measured as metaphase II and cortical granule migration, respectively in both postpartum times. However, number of preovulatory follicles on the ovarian surface was lower (P < 0.05) and atresia rate tended to be higher with also lower percentage of healthy follicles (P < 0.1) in ovaries of females of extensive group. In conclusion, primiparous non-weaned rabbits does at late post-partum time (25 days), Did no show any improvement regarding body reserves, serum metabolic parameters and oocyte quality; even a slight negative influence has been observed in the development of their ovarian follicles. Thus this reproductive management does not present any advantage compared to earlier post-partum (11 days) reproductive rhythm. In summary, according to the obtained results from these two experiments, we can say that the application of early weaning and the extensive rhythms did not achieve an improvement in the reproductive performance of primiparous does. Thus, it is necessary to conduct more studies about the metabolic status of the primiparous lactating doe to achieve strategies in order to improve it and consequently, to improve the reproductive activity and their productive success.

Adams methods: implementation as predictor-corrector methods

In this paper, Adams explicit and implicit formulas are obtained in a simple way and a relationship between them is established, allowing for their joint implementation as predictor-corrector methods. It is shown the purposefulness, from a didactic point of view, of Excel spreadsheets for calculations and for the orderly presentation of results in the application of Adams methods to solving initial value problems in ordinary differential equations.

Spatial sampling methods for improved communication for wireless relay robots

Having reliable wireless communication in a network of mobile robots is an ongoing challenge, especially when the mobile robots are given tasks in hostile or harmful environments such as radiation environments in scientific facilities, tunnels with large metallic components and complicated geometries as found at CERN. In this paper, we propose a decentralised method for improving the wireless network throughput by optimizing the wireless relay robot position to receive the best wireless signal strength using implicit spatial diversity concepts and gradient-search algorithms. We experimentally demonstrate the effectiveness of the proposed solutions with a KUKA Youbot omni-directional mobile robot. The performance of the algorithms is compared under various scenarios in an underground scientific facility at CERN.

Classifying GABAergic interneurons with semi-supervised projected model-based clustering

Objectives: A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names.We sought to automatically classify digitally reconstructed interneuronal morphologies according tothis scheme. Simultaneously, we sought to discover possible subtypes of these types that might emergeduring automatic classification (clustering). We also investigated which morphometric properties weremost relevant for this classification.Materials and methods: A set of 118 digitally reconstructed interneuronal morphologies classified into thecommon basket (CB), horse-tail (HT), large basket (LB), and Martinotti (MA) interneuron types by 42 of theworld?s leading neuroscientists, quantified by five simple morphometric properties of the axon and fourof the dendrites. We labeled each neuron with the type most commonly assigned to it by the experts. Wethen removed this class information for each type separately, and applied semi-supervised clustering tothose cells (keeping the others? cluster membership fixed), to assess separation from other types and lookfor the formation of new groups (subtypes). We performed this same experiment unlabeling the cells oftwo types at a time, and of half the cells of a single type at a time. The clustering model is a finite mixtureof Gaussians which we adapted for the estimation of local (per-cluster) feature relevance. We performedthe described experiments on three different subsets of the data, formed according to how many expertsagreed on type membership: at least 18 experts (the full data set), at least 21 (73 neurons), and at least26 (47 neurons).Results: Interneurons with more reliable type labels were classified more accurately. We classified HTcells with 100% accuracy, MA cells with 73% accuracy, and CB and LB cells with 56% and 58% accuracy,respectively. We identified three subtypes of the MA type, one subtype of CB and LB types each, andno subtypes of HT (it was a single, homogeneous type). We got maximum (adapted) Silhouette widthand ARI values of 1, 0.83, 0.79, and 0.42, when unlabeling the HT, CB, LB, and MA types, respectively,confirming the quality of the formed cluster solutions. The subtypes identified when unlabeling a singletype also emerged when unlabeling two types at a time, confirming their validity. Axonal morphometricproperties were more relevant that dendritic ones, with the axonal polar histogram length in the [pi, 2pi) angle interval being particularly useful.Conclusions: The applied semi-supervised clustering method can accurately discriminate among CB, HT, LB, and MA interneuron types while discovering potential subtypes, and is therefore useful for neuronal classification. The discovery of potential subtypes suggests that some of these types are more heteroge-neous that previously thought. Finally, axonal variables seem to be more relevant than dendritic ones fordistinguishing among the CB, HT, LB, and MA interneuron types.

Comparison of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based on Lorenz Curves

The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

Simulación eficiente de mecanismos flexibles mediante formulaciones topológicas

El objetivo de esta Tesis es presentar un método eficiente para la evaluación de sistemas multi-cuerpo con elementos flexibles con pequeñas deformaciones, basado en métodos topológicos para la simulación de sistemas tan complejos como los que se utilizan en la práctica y en tiempo real o próximo al real. Se ha puesto un especial énfasis en la resolución eficiente de aquellos aspectos que conllevan mayor coste computacional, tales como la evaluación de las ecuaciones dinámicas y el cálculo de los términos de inercia. Las ecuaciones dinámicas se establecen en función de las variables independientes del sistema, y la integración de las mismas se realiza mediante formulaciones implícitas de index-3. Esta Tesis se articula en seis Capítulos. En el Capítulo 1 se realiza una revisión bibliográfica de la simulación de sistemas flexibles y los métodos más relevantes de integración de las ecuaciones diferenciales del movimiento. Asimismo, se presentan los objetivos de esta Tesis. En el Capítulo 2 se presenta un método semi-recursivo para la evaluación de las ecuaciones de los sistemas multi-cuerpo con elementos flexibles basado en formulaciones topológicas y síntesis modal. Esta Tesis determina la posición de cada punto del cuerpo flexible en función de un sistema de referencia flotante que se mueve con dicho cuerpo y de las amplitudes de ciertos modos de deformación calculados a partir de un mallado obtenido mediante el Método de Elementos Finitos. Se presta especial atención en las condiciones de contorno que se han de tener en cuenta a la hora de establecer las variables que definen la deformación del cuerpo flexible. El Capítulo 3 se centra en la evaluación de los términos de inercia de los sistemas flexibles que generalmente conllevan un alto coste computacional. Se presenta un método que permite el cálculo de dichos términos basado en el uso de 24 matrices constantes que pueden ser calculadas previamente al proceso de integración. Estas matrices permiten evaluar la matriz de masas y el vector de fuerzas de inercia dependientes de la velocidad sin que sea necesario evaluar la posición deformada de todos los puntos del cuerpo flexible. Se realiza un análisis pormenorizado de dichas matrices con el objetivo de optimizar su cálculo estableciendo aproximaciones que permitan reducir el número de dichos términos y optimizar aún más su evaluación. Se analizan dos posibles simplificaciones: la primera utiliza una discretización no-consistente basada en elementos finitos en los que se definen únicamente los desplazamientos axiales de los nodos; en la segunda propuesta se hace uso de una matriz de masas concentradas (Lumped Mass). Basándose en la formulación presentada, el Capítulo 4 aborda la integración eficiente de las ecuaciones dinámicas. Se presenta un método iterativo para la integración con fórmulas de index-3 basado en la proyección de las ecuaciones dinámicas según las variables independientes del sistema multi-cuerpo. El cálculo del residuo del sistema de ecuaciones no lineales que se ha de resolver de modo iterativo se realiza mediante un proceso recursivo muy eficiente que aprovecha la estructura topológica del sistema. Se analizan tres formas de evaluar la matriz tangente del citado sistema no lineal: evaluación aproximada, numérica y recursiva. El método de integración presentado permite el uso de distintas fórmulas. En esta Tesis se analizan la Regla Trapezoidal, la fórmula BDF de segundo orden y un método híbrido TR-BDF2. Para este último caso se presenta un algoritmo de paso variable. En el Capítulo 5 plantea la implementación del método propuesto en un programa general de simulación de mecanismos que permita la resolución de cualquier sistema multi-cuerpo definiéndolo mediante un fichero de datos. La implementación de este programa se ha realizado tanto en C++ como en Java. Se muestran los resultados de las formulaciones presentadas en esta Tesis mediante la simulación de cuatro ejemplos de distinta complejidad. Mediante análisis concretos se comparan la formulación presentada con otras existentes. También se analiza el efecto del lenguaje de programación utilizado en la implementación y los efectos de las posibles simplificaciones planteadas. Por último, el Capítulo 6 resume las principales conclusiones alcanzadas en la Tesis y las futuras líneas de investigación que con ella se abren. ABSTRACT This Thesis presents an efficient method for solving the forward dynamics of a multi-body sys-tem formed by rigid and flexible bodies with small strains for real-time simulation of real-life models. It is based on topological formulations. The presented work focuses on the efficient solution of the most time-consuming tasks of the simulation process, such as the numerical integration of the motion differential equations and in particular the evaluation of the inertia terms corresponding to the flexible bodies. The dynamic equations are formulated in terms of independent variables of the muti-body system, and they are integrated by means of implicit index-3 formulae. The Thesis is arranged in six chapters. Chapter 1 presents a review of the most relevant and recent contributions related to the modelization of flexible multi-body systems and the integration of the corresponding dynamic equations. The main objectives of the Thesis are also presented in detail. Chapter 2 presents a semi-recursive method for solving the equations of a multi-body system with flexible bodies based on topological formulations and modal synthesis. This Thesis uses the floating frame approach and the modal amplitudes to define the position of any point at the flexible body. These modal deformed shapes are obtained by means of the Finite Element Method. Particular attention has been taken to the boundary conditions used to define the deformation of the flexible bodies. Chapter 3 focuses on the evaluation of the inertia terms, which is usually a very time-consuming task. A new method based on the use of 24 constant matrices is presented. These matrices are evaluated during the set-up step, before the integration process. They allow the calculation of the inertia terms in terms of the position and orientation of the local coordinate system and the deformation variables, and there is no need to evaluate the position and velocities of all the nodes of the FEM mesh. A deep analysis of the inertia terms is performed in order to optimize the evaluation process, reducing both the terms used and the number of arithmetic operations. Two possible simplifications are presented: the first one uses a non-consistent approach in order to define the inertia terms respect to the Cartesian coordinates of the FEM mesh, rejecting those corresponding to the angular rotations; the second approach makes use of lumped mass matrices. Based on the previously presented formulation, Chapter 4 is focused on the numerical integration of the motion differential equations. A new predictor-corrector method based on index-3 formulae and on the use of multi-body independent variables is presented. The evaluation of the dynamic equations in a new time step needs the solution of a set on nonlinear equations by a Newton-Raphson iterative process. The computation of the corresponding residual vector is performed efficiently by taking advantage of the system’s topological structure. Three methods to compute the tangent matrix are presented: an approximated evaluation that considers only the most relevant terms, a numerical approach based on finite differences and a recursive method that uses the topological structure. The method presented for integrating the dynamic equations can use a variety of integration formulae. This Thesis analyses the use of the trapezoidal rule, the 2nd order BDF formula and the hybrid TR-BDF2 method. A variable-time step strategy is presented for the last one. Chapter 5 describes the implementation of the proposed method in a general purpose pro-gram for solving any multibody defined by a data file. This program is implemented both in C++ and Java. Four examples are used to check the validity of the formulation and to compare this method with other methods commonly used to solve the dynamic equations of multi-body systems containing flexible bodies. The efficiency of the programming methodology used and the effect of the possible simplifications proposed are also analyzed. Chapter 6 summarizes the main Conclusions obtained in this Thesis and the new lines of research that have been opened.

Methods and Techniques for the Generation and Eficient Exploitation of RDB2RDF Mappings

RDB to RDF Mapping Language (R2RML) es una recomendación del W3C que permite especificar reglas para transformar bases de datos relacionales a RDF. Estos datos en RDF se pueden materializar y almacenar en un sistema gestor de tripletas RDF (normalmente conocidos con el nombre triple store), en el cual se pueden evaluar consultas SPARQL. Sin embargo, hay casos en los cuales la materialización no es adecuada o posible, por ejemplo, cuando la base de datos se actualiza frecuentemente. En estos casos, lo mejor es considerar los datos en RDF como datos virtuales, de tal manera que las consultas SPARQL anteriormente mencionadas se traduzcan a consultas SQL que se pueden evaluar sobre los sistemas gestores de bases de datos relacionales (SGBD) originales. Para esta traducción se tienen en cuenta los mapeos R2RML. La primera parte de esta tesis se centra en la traducción de consultas. Se propone una formalización de la traducción de SPARQL a SQL utilizando mapeos R2RML. Además se proponen varias técnicas de optimización para generar consultas SQL que son más eficientes cuando son evaluadas en sistemas gestores de bases de datos relacionales. Este enfoque se evalúa mediante un benchmark sintético y varios casos reales. Otra recomendación relacionada con R2RML es la conocida como Direct Mapping (DM), que establece reglas fijas para la transformación de datos relacionales a RDF. A pesar de que ambas recomendaciones se publicaron al mismo tiempo, en septiembre de 2012, todavía no se ha realizado un estudio formal sobre la relación entre ellas. Por tanto, la segunda parte de esta tesis se centra en el estudio de la relación entre R2RML y DM. Se divide este estudio en dos partes: de R2RML a DM, y de DM a R2RML. En el primer caso, se estudia un fragmento de R2RML que tiene la misma expresividad que DM. En el segundo caso, se representan las reglas de DM como mapeos R2RML, y también se añade la semántica implícita (relaciones de subclase, 1-N y M-N) que se puede encontrar codificada en la base de datos. Esta tesis muestra que es posible usar R2RML en casos reales, sin necesidad de realizar materializaciones de los datos, puesto que las consultas SQL generadas son suficientemente eficientes cuando son evaluadas en el sistema gestor de base de datos relacional. Asimismo, esta tesis profundiza en el entendimiento de la relación existente entre las dos recomendaciones del W3C, algo que no había sido estudiado con anterioridad. ABSTRACT. RDB to RDF Mapping Language (R2RML) is a W3C recommendation that allows specifying rules for transforming relational databases into RDF. This RDF data can be materialized and stored in a triple store, so that SPARQL queries can be evaluated by the triple store. However, there are several cases where materialization is not adequate or possible, for example, if the underlying relational database is updated frequently. In those cases, RDF data is better kept virtual, and hence SPARQL queries over it have to be translated into SQL queries to the underlying relational database system considering that the translation process has to take into account the specified R2RML mappings. The first part of this thesis focuses on query translation. We discuss the formalization of the translation from SPARQL to SQL queries that takes into account R2RML mappings. Furthermore, we propose several optimization techniques so that the translation procedure generates SQL queries that can be evaluated more efficiently over the underlying databases. We evaluate our approach using a synthetic benchmark and several real cases, and show positive results that we obtained. Direct Mapping (DM) is another W3C recommendation for the generation of RDF data from relational databases. While R2RML allows users to specify their own transformation rules, DM establishes fixed transformation rules. Although both recommendations were published at the same time, September 2012, there has not been any study regarding the relationship between them. The second part of this thesis focuses on the study of the relationship between R2RML and DM. We divide this study into two directions: from R2RML to DM, and from DM to R2RML. From R2RML to DM, we study a fragment of R2RML having the same expressive power than DM. From DM to R2RML, we represent DM transformation rules as R2RML mappings, and also add the implicit semantics encoded in databases, such as subclass, 1-N and N-N relationships. This thesis shows that by formalizing and optimizing R2RML-based SPARQL to SQL query translation, it is possible to use R2RML engines in real cases as the resulting SQL is efficient enough to be evaluated by the underlying relational databases. In addition to that, this thesis facilitates the understanding of bidirectional relationship between the two W3C recommendations, something that had not been studied before.