Determining Principal Component Cardinality through the Principle of Minimum Description Length

PCA (Principal Component Analysis) and its variants areubiquitous techniques for matrix dimension reduction and reduced-dimensionlatent-factor extraction. One significant challenge in using PCA, is thechoice of the number of principal components. The information-theoreticMDL (Minimum Description Length) principle gives objective compression-based criteria for model selection, but it is difficult to analytically applyits modern definition - NML (Normalized Maximum Likelihood) - to theproblem of PCA. This work shows a general reduction of NML prob-lems to lower-dimension problems. Applying this reduction, it boundsthe NML of PCA, by terms of the NML of linear regression, which areknown.Comment: LOD 201

Temperature dependence on the mass susceptibility and mass magnetization of superparamagnetic Mn–Zn–ferrite nanoparticles as contrast agents for magnetic imaging of oil and gas reservoirs

The mass susceptibility (χmass) and mass magnetization (Mmass) were determined for a series of ternary manganese and zinc ferrite nanoparticles (Mn–Zn ferrite NPs, MnxZn1−xFe2O4) with different Mn:Zn ratios (0.08 ≤ x ≤ 4.67), prepared by the thermal decomposition reaction of the appropriate metal acetylacetonate complexes, and for the binary homologs (MxFe3−xO4, where M = Mn or Zn). Alteration of the Mn:Zn ratio in Mn–Zn ferrite NPs does not significantly affect the particle size. At room temperature and low applied field strength the mass susceptibility increases sharply as the Mn:Zn ratio increases, but above a ratio of 0.4 further increase in the amount of manganese results in the mass susceptibility decreasing slightly, reaching a plateau above Mn:Zn ≈ 2. The compositional dependence of the mass magnetization shows less of a variation at room temperature and high applied fields. The temperature dependence of the mass magnetization of Mn–Zn ferrite NPs is significantly less for Mn-rich compositions making them more suitable for downhole imaging at higher temperatures (>100 °C). For non-shale reservoirs, replacement of nMag by Mn-rich Mn–Zn ferrites will allow for significant signal-to-noise enhancement of 6.5× over NP magnetite

Two remarks on generalized entropy power inequalities

This note contributes to the understanding of generalized entropy power inequalities. Our main goal is to construct a counter-example regarding monotonicity and entropy comparison of weighted sums of independent identically distributed log-concave random variables. We also present a complex analogue of a recent dependent entropy power inequality of Hao and Jog, and give a very simple proof.Comment: arXiv:1811.00345 is split into 2 papers, with this being on

Magnetic Diagram of the High-Pressure Stabilized Multiferroic Perovskites of the BiFe1-yScyO3 Series

Magnetic properties of the high-pressure stabilized perovskite BiFe1-yScyO3 phases (0.1 ≤ y ≤ 0.9) have been studied by means of magnetization measurements and neutron diffraction. The metastable perovskites of this series undergo irreversible polymorphic transformations upon annealing, the phenomenon referred to as conversion polymorphism. It has been found that the solid solutions with y ≥ 0.70 exhibit no long-range magnetic ordering regardless of their polymorph modification, while those with y ≤ 0.60 are all antiferromagnets. Depending on the scandium content, temperature and structural distortions, three types of the antiferromagnetic orderings, involving collinear, canted and cycloidal spin arrangements, have been revealed in the phases obtained via conversion polymorphism and the corresponding magnetic phase diagram has been suggested

A generalization of the Entropy Power Inequality to Bosonic Quantum Systems

In most communication schemes information is transmitted via travelling modes of electromagnetic radiation. These modes are unavoidably subject to environmental noise along any physical transmission medium and the quality of the communication channel strongly depends on the minimum noise achievable at the output. For classical signals such noise can be rigorously quantified in terms of the associated Shannon entropy and it is subject to a fundamental lower bound called entropy power inequality. Electromagnetic fields are however quantum mechanical systems and then, especially in low intensity signals, the quantum nature of the information carrier cannot be neglected and many important results derived within classical information theory require non-trivial extensions to the quantum regime. Here we prove one possible generalization of the Entropy Power Inequality to quantum bosonic systems. The impact of this inequality in quantum information theory is potentially large and some relevant implications are considered in this work

A relocatable ocean model in support of environmental emergencies

During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive Relocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, and to the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.MEDESS4MS Project; TESSA Project; MyOcean2 Projectinfo:eu-repo/semantics/publishedVersio

Towards causal benchmarking of bias in face analysis algorithms

Measuring algorithmic bias is crucial both to assess algorithmic fairness, and to guide the improvement of algorithms. Current methods to measure algorithmic bias in computer vision, which are based on observational datasets, are inadequate for this task because they conflate algorithmic bias with dataset bias. To address this problem we develop an experimental method for measuring algorithmic bias of face analysis algorithms, which manipulates directly the attributes of interest, e.g., gender and skin tone, in order to reveal causal links between attribute variation and performance change. Our proposed method is based on generating synthetic ``transects'' of matched sample images that are designed to differ along specific attributes while leaving other attributes constant. A crucial aspect of our approach is relying on the perception of human observers, both to guide manipulations, and to measure algorithmic bias. Besides allowing the measurement of algorithmic bias, synthetic transects have other advantages with respect to observational datasets: they sample attributes more evenly allowing for more straightforward bias analysis on minority and intersectional groups, they enable prediction of bias in new scenarios, they greatly reduce ethical and legal challenges, and they are economical and fast to obtain, helping make bias testing affordable and widely available. We validate our method by comparing it to a study that employs the traditional observational method for analyzing bias in gender classification algorithms. The two methods reach different conclusions. While the observational method reports gender and skin color biases, the experimental method reveals biases due to gender, hair length, age, and facial hair

Molybdenum and Phosphorus Interact to Constrain Asymbiotic Nitrogen Fixation in Tropical Forests

Biological di-nitrogen fixation (N2) is the dominant natural source of new nitrogen to land ecosystems. Phosphorus (P) is thought to limit N2 fixation in many tropical soils, yet both molybdenum (Mo) and P are crucial for the nitrogenase reaction (which catalyzes N2 conversion to ammonia) and cell growth. We have limited understanding of how and when fixation is constrained by these nutrients in nature. Here we show in tropical forests of lowland Panama that the limiting element on asymbiotic N2 fixation shifts along a broad landscape gradient in soil P, where Mo limits fixation in P-rich soils while Mo and P co-limit in P-poor soils. In no circumstance did P alone limit fixation. We provide and experimentally test a mechanism that explains how Mo and P can interact to constrain asymbiotic N2 fixation. Fixation is uniformly favored in surface organic soil horizons - a niche characterized by exceedingly low levels of available Mo relative to P. We show that soil organic matter acts to reduce molybdate over phosphate bioavailability, which, in turn, promotes Mo limitation in sites where P is sufficient. Our findings show that asymbiotic N2 fixation is constrained by the relative availability and dynamics of Mo and P in soils. This conceptual framework can explain shifts in limitation status across broad landscape gradients in soil fertility and implies that fixation depends on Mo and P in ways that are more complex than previously thought

Differential protein profiling as a potential multi-marker approach for TSE diagnosis

Rona Barron - ORCID: 0000-0003-4512-9177 https://orcid.org/0000-0003-4512-9177This "proof of concept" study, examines the use of differential protein expression profiling using surface enhanced laser desorption and ionisationtime of flight mass spectrometry (SELDI-TOF) for the diagnosis of TSE disease. Spectral output from all proteins selectively captured from individual murine brain homogenate samples, are compared as "profiles" in groups of infected and non-infected animals. Differential protein expression between groups is thus highlighted and statistically significant protein "peaks" used to construct a panel of disease specific markers. Studies at both terminal stages of disease and throughout the time course of disease have shown a disease specific protein profile or "disease fingerprint" which could be used to distinguish between groups of TSE infected and uninfected animals at an early time point of disease. Results Our results show many differentially expressed proteins in diseased and control animals, some at early stages of disease. Three proteins identified by SELDI-TOF analysis were verified by immunohistochemistry in brain tissue sections. We demonstrate that by combining the most statistically significant changes in expression, a panel of markers can be constructed that can distinguish between TSE diseased and normal animals. Conclusion Differential protein expression profiling has the potential to be used for the detection of disease in TSE infected animals. Having established that a "training set" of potential markers can be constructed, more work would be required to further test the specificity and sensitivity of the assay in a "testing set". Based on these promising results, further studies are being performed using blood samples from infected sheep to assess the potential use of SELDI-TOF as a pre-mortem blood based diagnostic.https://doi.org/10.1186/1471-2334-9-1889pubpub