Consumer Demand for Healthy Diet: New Evidence from Healthy Eating Index

Replaced with revised version of paper 07/20/10.Food Consumption/Nutrition/Food Safety, Health Economics and Policy,

Inefficient Star Formation In Extremely Metal Poor Galaxies

The first galaxies contain stars born out of gas with little or no metals. The lack of metals is expected to inhibit efficient gas cooling and star formation but this effect has yet to be observed in galaxies with oxygen abundance relative to hydrogen below a tenth of that of the Sun. Extremely metal poor nearby galaxies may be our best local laboratories for studying in detail the conditions that prevailed in low metallicity galaxies at early epochs. Carbon Monoxide (CO) emission is unreliable as tracers of gas at low metallicities, and while dust has been used to trace gas in low-metallicity galaxies, low-spatial resolution in the far-infrared has typically led to large uncertainties. Here we report spatially-resolved infrared observations of two galaxies with oxygen abundances below 10 per cent solar, and show that stars form very inefficiently in seven star-forming clumps of these galaxies. The star formation efficiencies are more than ten times lower than found in normal, metal rich galaxies today, suggesting that star formation may have been very inefficient in the early Universe.Comment: Author's version (10 pages, 4 figures). Published in Natur

The Weak Carbon Monoxide Emission In An Extremely Metal Poor Galaxy, Sextans A

Carbon monoxide (CO) is one of the primary coolants of gas and an easily accessible tracer of molecular gas in spiral galaxies but it is unclear if CO plays a similar role in metal poor dwarfs. We carried out a deep observation with IRAM 30 m to search for CO emission by targeting the brightest far-IR peak in a nearby extremely metal poor galaxy, Sextans A, with 7% Solar metallicity. A weak CO J=1-0 emission is seen, which is already faint enough to place a strong constraint on the conversion factor (a_CO) from the CO luminosity to the molecular gas mass that is derived from the spatially resolved dust mass map. The a_CO is at least seven hundred times the Milky Way value. This indicates that CO emission is exceedingly weak in extremely metal poor galaxies, challenging its role as a coolant in these galaxies.Comment: 4 pages, 1 table, 4 figures. ApJL in pres

Pair-breaking scattering interference as a mechanism for superconducting gap modulation

We propose the "pair-breaking scattering interference" as a general source of coherence peak modulations in superconductors. Assuming this mechanism, we present a simple physical picture for the coherence peak modulations in overdoped cuprate Bi$_2$Sr$_2$Ca$_2$Cu$_3$O$_{10+\delta}$ (Bi-2223), ferromagnetic iron pnictide EuRbFe$_4$As$_4$ (Eu-1144), and kagome metals $A$V$_3$Sb$_5$ ($A=$ K, Rb, and Cs). Specifically, we explain the wavevectors, the particle-hole symmetry, and the dependence on the internal or external Zeeman-field of the coherence peak modulations. This work is intended as a cautious reminder to the scientific community when asserting the existence of a pair density wave phenomenon in the absence of tunneling conductance modulations in the normal state.Comment: 5+6 pages, 3+2 figure

On the use of an explicit chemical mechanism to dissect peroxy acetyl nitrate formation.

Peroxy acetyl nitrate (PAN) is a key component of photochemical smog and plays an important role in atmospheric chemistry. Though it has been known that PAN is produced via reactions of nitrogen oxides (NOx) with some volatile organic compounds (VOCs), it is difficult to quantify the contributions of individual precursor species. Here we use an explicit photochemical model--Master Chemical Mechanism (MCM) model--to dissect PAN formation and identify principal precursors, by analyzing measurements made in Beijing in summer 2008. PAN production was sensitive to both NOx and VOCs. Isoprene was the predominant VOC precursor at suburb with biogenic impact, whilst anthropogenic hydrocarbons dominated at downtown. PAN production was attributable to a relatively small class of compounds including NOx, xylenes, trimethylbenzenes, trans/cis-2-butenes, toluene, and propene. MCM can advance understanding of PAN photochemistry to a species level, and provide more relevant recommendations for mitigating photochemical pollution in large cities

Regression Analysis of Beijing Hotels Customer Satisfaction Based upon Data from TripAdvisor

Big data is being used by many organizations to make decisions about the efficiency and effectiveness of their operation. One of the data sets that are used most frequently is TripAdvisor. This article explores the advantages and disadvantages of using such a data set. The case study chosen was the hotel services in Beijing, China. A new approach is being proposed in which baseline information is used on a regional basis to establish the uniqueness of a region. Many times the data does not give the proper perspective because it incorporates the larger perspective and does not provide for regional differences. The other dimension developed in the article is a statistical approach that tries to define a better understanding instead of using a descriptive method. Keywords: Big data, TripAdvisor, Beijing, Statistical analysi

Variance-Preserving-Based Interpolation Diffusion Models for Speech Enhancement

The goal of this study is to implement diffusion models for speech enhancement (SE). The first step is to emphasize the theoretical foundation of variance-preserving (VP)-based interpolation diffusion under continuous conditions. Subsequently, we present a more concise framework that encapsulates both the VP- and variance-exploding (VE)-based interpolation diffusion methods. We demonstrate that these two methods are special cases of the proposed framework. Additionally, we provide a practical example of VP-based interpolation diffusion for the SE task. To improve performance and ease model training, we analyze the common difficulties encountered in diffusion models and suggest amenable hyper-parameters. Finally, we evaluate our model against several methods using a public benchmark to showcase the effectiveness of our approac

Genomic and biologic comparisons of cyprinid herpesvirus 3 strains

Cyprinid herpesvirus 3 (CyHV-3) is the archetypal fish alloherpesvirus and the etiologic agent of a lethal disease in common and koi carp. To date, the genome sequences of only four CyHV-3 isolates have been published, but no comparisons of the biologic properties of these strains have been reported. We have sequenced the genomes of a further seven strains from various geographical sources, and have compared their growth in vitro and virulence in vivo. The major findings were: (i) the existence of the two genetic lineages previously described as European and Asian was confirmed, but inconsistencies between the geographic origin and genotype of some strains were revealed; (ii) potential inter-lineage recombination was detected in one strain, which also suggested the existence of a third, as yet unidentified lineage; (iii) analysis of genetic disruptions led to the identification of non-essential genes and their potential role in virulence; (iv) comparison of the in vitro and in vivo properties of strains belonging to the two lineages revealed that inter-lineage polymorphisms do not contribute to the differences in viral fitness observed; and (v) a negative correlation was observed among strains between viral growth in vitro and virulence in vivo. This study illustrates the importance of coupling genomic and biologic comparisons of viral strains in order to enhance understanding of viral evolution and pathogenesis

Rethinking solar photovoltaic parameter estimation: global optimality analysis and a simple efficient differential evolution method

Accurate, fast, and reliable parameter estimation is crucial for modeling, control, and optimization of solar photovoltaic (PV) systems. In this paper, we focus on the two most widely used benchmark datasets and try to answer (i) whether the global minimum in terms of root mean square error (RMSE) has already been reached; and (ii) whether a significantly simpler metaheuristic, in contrast to currently sophisticated ones, is capable of identifying PV parameters with comparable performance, e.g., attaining the same RMSE. We address the former using an interval analysis based branch and bound algorithm and certify the global minimum rigorously for the single diode model (SDM) as well as locating a fairly tight upper bound for the double diode model (DDM) on both datasets. These obtained values will serve as useful references for metaheuristic methods, since none of them can guarantee or recognize the global minimum even if they have literally discovered it. However, this algorithm is excessively slow and unsuitable for time-sensitive applications (despite the great insights on RMSE that it yields). Regarding the second question, extensive examination and comparison reveal that, perhaps surprisingly, a classic and remarkably simple differential evolution (DE) algorithm can consistently achieve the certified global minimum for the SDM and obtain the best known result for the DDM on both datasets. Thanks to its extreme simplicity, the DE algorithm takes only a fraction of the running time required by other contemporary metaheuristics and is thus preferable in real-time scenarios. This unusual (and certainly notable) finding also indicates that the employment of increasingly complicated metaheuristics might possibly be somewhat overkill for regular PV parameter estimation. Finally, we discuss the implications of these results and suggest promising directions for future development.Comment: v2, see source code at https://github.com/ShuhuaGao/rePVes