Promoting Pollinating Insects in Intensive Agricultural Matrices: Field-Scale Experimental Manipulation of Hay-Meadow Mowing Regimes and Its Effects on Bees

Bees are a key component of biodiversity as they ensure a crucial ecosystem service: pollination. This ecosystem service is nowadays threatened, because bees suffer from agricultural intensification. Yet, bees rarely benefit from the measures established to promote biodiversity in farmland, such as agri-environment schemes (AES). We experimentally tested if the spatio-temporal modification of mowing regimes within extensively managed hay meadows, a widespread AES, can promote bees. We applied a randomized block design, replicated 12 times across the Swiss lowlands, that consisted of three different mowing treatments: 1) first cut not before 15 June (conventional regime for meadows within Swiss AES); 2) first cut not before 15 June, as treatment 1 but with 15% of area left uncut serving as a refuge; 3) first cut not before 15 July. Bees were collected with pan traps, twice during the vegetation season (before and after mowing). Wild bee abundance and species richness significantly increased in meadows where uncut refuges were left, in comparison to meadows without refuges: there was both an immediate (within year) and cumulative (from one year to the following) positive effect of the uncut refuge treatment. An immediate positive effect of delayed mowing was also evidenced in both wild bees and honey bees. Conventional AES could easily accommodate such a simple management prescription that promotes farmland biodiversity and is likely to enhance pollination services.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.

Pauli Spin Matrices

The Pauli Spin Matrix representation of Spin Operators in Quantum Mechanics are explicitly demonstrated and illustrated in detail for one and two spin systems.

Antropología, violencia y justicia. Repensando matrices de sociabilidad contemporánea en el campo del género y de la familia. En: Avá, nº 18

¿Cómo abordar conceptualmente a la violencia y la justicia en un entramado de relaciones sociales tan complejo como el género y la familia? Esta pregunta recorre el libro compilado por Theophilos Rifiotis y Natalia Castelnuevo. La complejidad de la pregunta se acrecienta al sumar el carácter comparativo a la compilación, ya que la obra pone en diálogo investigaciones de Argentina, Brasil, Colombia y, hasta, Timor Oriental. Una introducción y nueve artículos ordenan este atrayente y estimulante ejercicio comparativo.

Archivos de narrativa y matrices folklóricas : Oralidad, escritura y génesis

Revisito una aproximación al relato folklórico, a partir de un archivo de narrativa folklórica riojana. El enfoque teórico combina aportes de la crítica genética con la teoría informática del hipertexto. El archivo incluye versiones orales reunidas en investigaciones de campo (1985-1999), alrededor de la matriz "La dama fantasma", con elementos del motivo folklórico E 322.3.3.1 "The vanishing hitchhiker". Comprende también recreaciones escriturarias, fílmicas y registros virtuales. El trabajo se encuadra en una investigación sobre "Archivos de Narrativa Tradicional Argentina", que revisa criterios de archivación de narrativa tradicional, de la Encuesta Folklórica de 1921 a 2005

Test de matrices progresivas de Raven: construcción de baremos y constatación del "efecto Flynn"

En este trabajo se presentan los baremos del Test de Matrices Progresivas de Raven, Escala General y Escala Avanzada, Serie II, para la población estudiantil (Tercer ciclo EGB y Polimodal) de la ciudad de La Plata. Se hacen consideraciones sobre el incremento de puntajes (efecto Flynn)que se observa respecto del baremo anterior (1964); sobre las diferencias de las puntuaciones medias según dos grupos etareos (13-16 y 17-18 años) y según modalidad educativa. Los resultados encontrados permiten hacer inferencias respecto de la significación del incremento, especialmente en el caso de las puntuaciones de mayor magnitud en la población que concurre a un tipo especial de establecimiento educativo.

Raven's progressive matrices test: scale construction and verification of "Flynn effect"

In this paper, the scales of Raven's Progressive Matrices Test, General Scale and Advanced Scale, Series II, for the student population (third cycle of EGB and Polimodal ) in the city of La Plata are presented. Considerations are made as regards both the increase in scores (Flynn effect) observed in relation to the previous scale (1964) and the different mean scores according to two age groups (13-16 and 17-18 years of age) and education mode. The findings enabled inferences related to the significance of the increase, particularly in the case of the higher scores in the population attending a special kind of educational institution.

El Conflicto del Campo : Matrices culturales e identificaciones políticas

Este trabajo intenta demostrar cómo el denominado "Conflicto del Campo" (2008) puede ser comprendido a partir de la relación entre la cultura y la política. De esta manera, se parte de los cambios que el sector agropecuario experimentó durante los noventa, para luego exponer cómo durante el Conflicto se posicionaron distintos intereses en un mismo lado. Se mencionan, además, los estudios que otros investigadores realizaron sobre el mismo. La mencionada escena política fue estudiada a partir de la realización de entrevistas en profundidad, con el fin de exponer la relación entre procesos de identificación política y matrices culturales.

Test de matrices progresivas de Raven: construcción de baremos y constatación del "efecto Flynn"

En este trabajo se presentan los baremos del Test de Matrices Progresivas de Raven, Escala General y Escala Avanzada, Serie II, para la población estudiantil (Tercer ciclo EGB y Polimodal) de la ciudad de La Plata. Se hacen consideraciones sobre el incremento de puntajes (efecto Flynn)que se observa respecto del baremo anterior (1964); sobre las diferencias de las puntuaciones medias según dos grupos etareos (13-16 y 17-18 años) y según modalidad educativa. Los resultados encontrados permiten hacer inferencias respecto de la significación del incremento, especialmente en el caso de las puntuaciones de mayor magnitud en la población que concurre a un tipo especial de establecimiento educativo.

Raven's progressive matrices test: scale construction and verification of "Flynn effect"

In this paper, the scales of Raven's Progressive Matrices Test, General Scale and Advanced Scale, Series II, for the student population (third cycle of EGB and Polimodal ) in the city of La Plata are presented. Considerations are made as regards both the increase in scores (Flynn effect) observed in relation to the previous scale (1964) and the different mean scores according to two age groups (13-16 and 17-18 years of age) and education mode. The findings enabled inferences related to the significance of the increase, particularly in the case of the higher scores in the population attending a special kind of educational institution.