Spatial surface-pattern analyses and boundary detection techniques applied in forest ecology

[EN] We review methods for uni- and multivariate surface pattern analysis and boundary detection used in forest ecology. A continuous surface pattern is defined as the locations of points (trees) in the space and the associated variable or variables. We illustrate useful methods to describe spatial patterns and infer the generating processes. We show the statistical basis and applied examples of univariate methods for binary (join counts) and quantitative variables (Moran and Geary correlograms, semivariograms, fractal dimension). We explain the calculus and interpretation of multivariate methods to describe surface patterns (Mantel test and correlogram) and their relationships with ordination methods. Finally, we show examples of techniques for boundary detection. Most analysed patterns corresponded to Pinus uncinata forests from the upper altitudinal limit in the Pyrenees or from a relict population. We discuss the advantages and disadvantages of each methodology and their applications in forest ecology.[ES] En este trabajo se revisan los métodos de análisis univariable y multivariable de los patrones de superficies y de detección de fronteras más utilizados en ecología forestal. El patrón de superficies es un patrón espacial continuo definido por las posiciones de los puntos (árboles) en el espacio y una o varias variables asociadas a cada punto. Se ilustran métodos útiles para describir patrones espaciales e inferir los procesos que los generaron. Se muestra el fundamento estadístico y ejemplos aplicados de métodos de análisis univariables para variables binarias (conteo contiguo) y cuantitativas (correlogramas de Moran y Geary, semivariogramas, dimensión fractal). Se detalla el cálculo e interpretación de métodos multivariables para la descripción de patrones de superficies (correlograma y test de Mantel) y su relación con los métodos de ordenación. Finalmente, se muestran ejemplos de métodos para la detección de fronteras. La mayor parte de los patrones reales analizados provienen de bosques de Pinus uncinata del límite altitudinal superior en los Pirineos o bien de una población relíctica. Se discuten las ventajas y desventajas de cada metodología y sus aplicaciones en ecología forestal.Los datos de Vinuesa se obtuvieron en el proyecto AMB95-0160 (CICyT).Peer reviewe

A Study on Principal Component Analysis over Wireless Channel

Applications in many fields such as the internet of things (IoT), stock market, image compression, food adulteration, wireless physical layer key generation, etc. are becoming progressively complex due to a large number of users and increment in their usage. Data obtained by these applications are in huge amount creating a high computational cost. Further, it is difficult to handle and analyze it. To deal with such problems, dimensionality reduction techniques are used and one of the dimensionality reduction techniques is the Principal Component Analysis (PCA). In this paper, PCA is applied over a wireless Rician channel with AWGN at different SNR. It is concluded that the information content is more in less number of principal components with samples at higher SNR. It is also observed that the different combinations of several groups and elements in the sample space provide a different cumulative percentage of information

Visualization of proteomics data using R and bioconductor.

Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience. Here, we provided a short overview of the application of the R software to the visualization of proteomics data. We present a summary of R's plotting systems and how they are used to visualize and understand raw and processed MS-based proteomics data.LG was supported by the European Union 7th Framework Program (PRIME-XS project, grant agreement number 262067) and a BBSRC Strategic Longer and Larger grant (Award BB/L002817/1). LMB was supported by a BBSRC Tools and Resources Development Fund (Award BB/K00137X/1). TN was supported by a ERASMUS Placement scholarship.This is the final published version of the article. It was originally published in Proteomics (PROTEOMICS Special Issue: Proteomics Data Visualisation Volume 15, Issue 8, pages 1375–1389, April 2015. DOI: 10.1002/pmic.201400392). The final version is available at http://onlinelibrary.wiley.com/doi/10.1002/pmic.201400392/abstract

Navigating Tabular Data Synthesis Research: Understanding User Needs and Tool Capabilities

In an era of rapidly advancing data-driven applications, there is a growing demand for data in both research and practice. Synthetic data have emerged as an alternative when no real data is available (e.g., due to privacy regulations). Synthesizing tabular data presents unique and complex challenges, especially handling (i) missing values, (ii) dataset imbalance, (iii) diverse column types, and (iv) complex data distributions, as well as preserving (i) column correlations, (ii) temporal dependencies, and (iii) integrity constraints (e.g., functional dependencies) present in the original dataset. While substantial progress has been made recently in the context of generational models, there is no one-size-fits-all solution for tabular data today, and choosing the right tool for a given task is therefore no trivial task. In this paper, we survey the state of the art in Tabular Data Synthesis (TDS), examine the needs of users by defining a set of functional and non-functional requirements, and compile the challenges associated with meeting those needs. In addition, we evaluate the reported performance of 36 popular research TDS tools about these requirements and develop a decision guide to help users find suitable TDS tools for their applications. The resulting decision guide also identifies significant research gaps.Comment: 14 pages, 3 figure

Slx8 removes Pli1-dependent protein-SUMO conjugates including SUMOylated Topoisomerase I to promote genome stability

Peer reviewedPublisher PD

Analysis of Sr2Mg (BO3)2Tb3+ Green Emitting Phosphor for Solid State Lighting: Implication for Light Emitting Diode (LED)

With the assist of  customized step wise combustion synthesis method Sr2Mg(BO3)2: Tb3+  phosphors were synthesize along with the luminescent proprieties, XRD, chromaticity coordinates with effect of emission intensity with related with the corresponding concentration were studied. The emission spectrum of Sr2Mg(BO3)2  :Tb3+ (x=0.2 to 2 mol %) excited by 353 nm exhibits a strong green emission among peak location at 546 nm is recognized to F-F transitions of Tb3+ 5D4-7F5 ion. This study suggest that Sr2Mg(BO3)2: Tb3+ phosphor be a prominent material as a green constituent for phosphor- transformed W-LEDs  for SS

Estimation of crop yields

This article does not have an abstract

Studies on tumour inhibitory activity of indigenous drugs: Part I. Tumour inhibitory activity of Hippophae salicifolia, D.DON

The extracts of the bark of Hippophae salicifolia D.DON have been found to possess significant inhibitory activity on mouse fibrosarcoma. The tumour tissues showed that there was a degeneration and even necrosis of tumour calls. The alcoholic extract (B) of the bark also possesses an inhibitory activity against Yoshida sarcoma (ascites), as evidenced by the increase in survival period of the experimental animals. The chemistry of the bark is under investigation

Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe