A new accuracy measure based on bounded relative error for time series forecasting

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred

History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity.

Background:Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods:Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results:Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions:The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling

Brain resting-state functional MRI connectivity: Morphological foundation and plasticity

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From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Microstructures and resistivity of cuprate/manganite bilayer deposited on SrTiO3 substrate

Thin Yba[SUB2]Cu[SUB3]O[SUB7-δ/La[SUB0.67]Ca[SUB0.33]MnO[SUB3] (YBCO/LCMO) films were grown on SrTiO[SUB3](STO)substrates by magnetron sputtering technique. The microstructures of the bilayers were characterized and a standard four-probe technique was applied to measure the resistivity of the samples. The interdiffusions at the YBCO/LCMO and LCMO/STO interfaces formed two transient layers with the thickness of about 3 and 2 nm, respectively. All the bilayers were well textured along the c axis. At low temperature, the superconductivity can only be observed when the thickness of YBCO is more than 25 nm. When the thickness of YBCO is less than 8 nm, the bilayers show only ferromagnetism. The superconductivity and ferromagnetism perhaps coexist in the bilayer with the YBCO thickness of 12.5 nm. These interesting properties are related to the interaction between spin polarized electrons in the manganites and the cooper pairs in the cuprates. © 2003 American Institute of Physics.published_or_final_versio

Characteristics of C-4 photosynthesis in stems and petioles of C-3 flowering plants

Most plants are known as C-3 plants because the first product of photosynthetic CO2 fixation is a three-carbon compound. C-4 plants, which use an alternative pathway in which the first product is a four-carbon compound, have evolved independently many times and are found in at least 18 families. In addition to differences in their biochemistry, photosynthetic organs of C-4 plants show alterations in their anatomy and ultrastructure. Little is known about whether the biochemical or anatomical characteristics of C-4 photosynthesis evolved first. Here we report that tobacco, a typical C-3 plant, shows characteristics of C-4 photosynthesis in cells of stems and petioles that surround the xylem and phloem, and that these cells are supplied with carbon for photosynthesis from the vascular system and not from stomata. These photosynthetic cells possess high activities of enzymes characteristic of C-4 photosynthesis, which allow the decarboxylation of four-carbon organic acids from the xylem and phloem, thus releasing CO2 for photosynthesis. These biochemical characteristics of C-4 photosynthesis in cells around the vascular bundles of stems of C-3 plants might explain why C-4 photosynthesis has evolved independently many times

Resting-state fMRI using passband balanced steady-state free precession

OBJECTIVE: Resting-state functional MRI (rsfMRI) has been increasingly used for understanding brain functional architecture. To date, most rsfMRI studies have exploited blood oxygenation level-dependent (BOLD) contrast using gradient-echo (GE) echo planar imaging (EPI), which can suffer from image distortion and signal dropout due to magnetic susceptibility and inherent long echo time. In this study, the feasibility of passband balanced steady-state free precession (bSSFP) imaging for distortion-free and high-resolution rsfMRI was investigated. METHODS: rsfMRI was performed in humans at 3 T and in rats at 7 T using bSSFP with short repetition time (TR = 4/2.5 ms respectively) in comparison with conventional GE-EPI. Resting-state networks (RSNs) were detected using independent component analysis. RESULTS AND SIGNIFICANCE: RSNs derived from bSSFP images were shown to be spatially and spectrally comparable to those derived from GE-EPI images with considerable intra- and inter-subject reproducibility. High-resolution bSSFP images corresponded well to the anatomical images, with RSNs exquisitely co-localized to the gray matter. Furthermore, RSNs at areas of severe susceptibility such as human anterior prefrontal cortex and rat piriform cortex were proved accessible. These findings demonstrated for the first time that passband bSSFP approach can be a promising alternative to GE-EPI for rsfMRI. It offers distortion-free and high-resolution RSNs and is potentially suited for high field studies.published_or_final_versio

State Transfer Between a Mechanical Oscillator and Microwave Fields in the Quantum Regime

Recently, macroscopic mechanical oscillators have been coaxed into a regime of quantum behavior, by direct refrigeration [1] or a combination of refrigeration and laser-like cooling [2, 3]. This exciting result has encouraged notions that mechanical oscillators may perform useful functions in the processing of quantum information with superconducting circuits [1, 4-7], either by serving as a quantum memory for the ephemeral state of a microwave field or by providing a quantum interface between otherwise incompatible systems [8, 9]. As yet, the transfer of an itinerant state or propagating mode of a microwave field to and from a mechanical oscillator has not been demonstrated owing to the inability to agilely turn on and off the interaction between microwave electricity and mechanical motion. Here we demonstrate that the state of an itinerant microwave field can be coherently transferred into, stored in, and retrieved from a mechanical oscillator with amplitudes at the single quanta level. Crucially, the time to capture and to retrieve the microwave state is shorter than the quantum state lifetime of the mechanical oscillator. In this quantum regime, the mechanical oscillator can both store and transduce quantum information