Total content and dialyzable iron and zinc in foods from northern and Southern Mexico

Developing countries diets are based on a variety of plant foods that often are the main suppliers of important amounts of iron (Fe) and zinc (Zn). The objectives of this study were 1) to measure the total and dialyzable amounts of Fe and Zn in foods from Northern Mexico (Sonora) and from Southern Mexico (Oaxaca) and 2) to evaluate the effect of meat content of diets on the dialyzable amount of Fe and Zn. Methods to calculate the total dialyzable amount of Fe and Zn, were those of the AOAC and of Shen et al. Total Fe in e northern Mexican foods went from 0.78 +/- 0.0 to 11.59 +/- to 0.03 mg/ 100g (dry weight, DW); in southern Mexican foods the same micronutrient amounts were 0.86 +/- 0.18 to 8.8 +/- 0.57 mg/100 g (BS). Total Zn values were 0.91 +/- 0.00 to 13.58 +/- 0.05 mg/100 g (DW) in Sonora, and 0.64 +/- 0.18 to 20.80 +/- 0.33 mg/100 g (DW) in Oaxaca. In northern Mexico, foods dialyzable Fe had values from 0.1 +/- 0.04% to 10.6 +/- 0.36% and for Zn from 4.0 +/- 0.21% to 55.32 +/- 0.14%. Meanwhile, the range of values of dialyzable Fe for foods from Oaxaca were from 0.22 +/- 0.06% to 9.40 +/- 0.14% for and from 2.41 +/- 0.26% to 54.27 +/- 1.49% for dialyzable Zn. The average value for dialyzable Fe was higher in the foods that contained meat or meat products (p= 0.001).     

First Identification of a Putative Sex Pheromone in a Praying Mantid

Praying mantids are models for a wide variety of behavioral, physiological, and ecological studies, and sex pheromones have been assumed to be important components of their biology. However, no mantid pheromone has ever been identified. We collected volatiles emitted by females of the mantid, Sphodromantis lineola, via solid phase microextraction (SPME). Mass spectral analysis revealed the collected volatiles to be a mixture of pentadecanal and tetradecanal. We prepared a synthetic mixture of these compounds, and found that males were both attracted to this mixture and stimulated to exhibit typical precopulatory behavior. We then examined male antennae with scanning electron microscopy, and confirmed the presence of porous antennal sensilla typical of insect pheromone receptors, i.e., that male mantids are equipped with the appropriate morphological apparatus to receive volatile chemical signals. Pheromones, in conjunction with visual and tactile cues, are thus an important feature of the reproductive biology of this, and undoubtedly other species of mantids. In addition to adding a crucial aspect of behavioral biology to our knowledge of this group, identification and synthesis of mantid pheromones may be a first step in attracting and aggregating these generalist predators for use in pest control.     

Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease

Amnestic mild cognitive impairment (aMCI) often is an early stage of Alzheimer's disease (AD). MCI is characterized by cognitive decline departing from normal cognitive aging but that does not significantly interfere with daily activities. This study explores the potential of scalp EEG for early detection of alterations from cognitively normal status of older adults signifying MCI and AD. Resting 32-channel EEG records from 48 age-matched participants (mean age 75.7 years)—15 normal controls (NC), 16 early MCI, and 17 early stage AD—are examined. Regional spectral and complexity features are computed and used in a support vector machine model to discriminate between groups. Analyses based on three-way classifications demonstrate overall discrimination accuracies of 83.3%, 85.4%, and 79.2% for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. These results demonstrate the great promise for scalp EEG spectral and complexity features as noninvasive biomarkers for detection of MCI and early AD.     

Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control

Introduction

Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal.

Method

A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750 g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (S_I) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort.

Results

Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in S_I of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient S_I deviation 13.7%. In virtual trials, 87–93% of recommended insulin rates were equal or slightly reduced (Δ < 0.16 mU/h) under the head circumference method, while glycaemic control outcomes showed little change.

Conclusion

The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants.     

The annual cycle of Flehmen in black-tailed deer (Odocoileus hemionus columbianus)

Flehmen is a stereotyped response of ungulates and other mammals to urine. In black-tailed deer, Flehmen occurs typically in males (rarely in females), and its frequency shows an annual cycle. Flehmen in response to female urine was most frequent in November, and to male urine in January. The response minimum to both types of urine occurred in May. Fifty-five to 100% of initial responses to female urine resulted in Flehmen. The deer responded more often to female urine, and the difference between the responses to female and male urine increased from May to November. A male's own urine released Flehmen more often than did urine of other males. The response intensity varied with the spatial orientation of the male to the urinating female, and responses were usually limited to distances of 15 m or less.     

Electrophoretic deposition of carbon nanotubes

Electrophoretic deposition (EPD) has been gaining increasing interest as an economical and versatile processing technique for the production of novel coatings or films of carbon nanotubes (CNTs) on conductive substrates. The purpose of the paper is to present an up-to-date comprehensive overview of current research progress in the field of EPD of CNTs. The paper specifically reviews the preparation and characterisation of stable CNT suspensions, and the mechanism of the EPD process; it includes discussion of pure CNT coatings and CNT/nanoparticle composite films. A complete discussion of the EPD parameters is presented, including electrode materials, deposition time, electrode separation, deposition voltage and resultant electric field. The paper highlights potential applications of the resulting CNT and CNT/composite structures, in areas such as field emission devices, fuel cells, and supercapacitors.     

Void formation in a filled SBR rubber determined by small-angle X-ray scattering

Two commercial styrene-butadiene (SBR) latexes were used to prepare a model filled material consisting of glassy SBR filler particles about 1000 Å in diameter embedded in a rubbery SBR matrix crosslinked by γ-radiation. When transparent specimens of this material were extended, voiding occurred, as evidenced by stress whitening and greatly enhanced X-ray scattering intensity. More voids were formed at higher rates of extension, but voids disappeared when specimens were relaxed. The effects of filler content and cure time of the matrix on the size and number of voids formed were determined by low-angle X-ray scattering for a constant extension rate and a constant extension ratio λ = 1.6. The number of voids measured by X-ray scattering intensity decreased rapidly with time over the 3-h period of measurement. The number of voids remaining 1 h after extension increased about 40 times as filler content was increased from 15% to 50%. Increasing the cure time from 24 to 96 h increased the number of voids about four times. In contrast, the radius of gyration of the voids formed (250–350 Å) did not depend strongly on time, nor did it depend strongly on the filler content or the cure time of the matrix. Stress relaxation measurements made under the same conditions as X-ray scattering measurements showed effects typical of filled materials. However, the relaxation of stress (which followed a power law decay) was much slower than the decay of the number of voids as measured by X-ray scattering intensity.     

Hybrid clustering solution selection strategy

Cluster ensemble approaches make use of a set of clustering solutions which are derived from different data sources to gain a more comprehensive and significant clustering result over conventional single clustering approaches. Unfortunately, not all the clustering solutions in the ensemble contribute to the final result. In this paper, we focus on the clustering solution selection strategy in the cluster ensemble, and propose to view clustering solutions as features such that suitable feature selection techniques can be used to perform clustering solution selection. Furthermore, a hybrid clustering solution selection strategy (HCSS) is designed based on a proposed weighting function, which combines several feature selection techniques for the refinement of clustering solutions in the ensemble. Finally, a new measure is designed to evaluate the effectiveness of clustering solution selection strategies. The experimental results on both UCI machine learning datasets and cancer gene expression profiles demonstrate that HCSS works well on most of the datasets, obtains more desirable final results, and outperforms most of the state-of-the-art clustering solution selection strategies.     

Image clustering based on sparse patch alignment framework

Image clustering methods are efficient tools for applications such as content-based image retrieval and image annotation. Recently, graph based manifold learning methods have shown promising performance in extracting features for image clustering. Typical manifold learning methods adopt appropriate neighborhood size to construct the neighborhood graph, which captures local geometry of data distribution. Because the density of data points’ distribution may be different in different regions of the manifold, a fixed neighborhood size may be inappropriate in building the manifold. In this paper, we propose a novel algorithm, named sparse patch alignment framework, for the embedding of data lying in multiple manifolds. Specifically, we assume that for each data point there exists a small neighborhood in which only the points that come from the same manifold lie approximately in a low-dimensional affine subspace. Based on the patch alignment framework, we propose an optimization strategy for constructing local patches, which adopt sparse representation to select a few neighbors of each data point that span a low-dimensional affine subspace passing near that point. After that, the whole alignment strategy is utilized to build the manifold. Experiments are conducted on four real-world datasets, and the results demonstrate the effectiveness of the proposed method.     

Observability Analysis of Continuous‐Time LTI Systems with Limited Derivative Data

We consider continuous‐time LTI systems with either unknown‐input or with lack of information about the input and output derivatives. We compute the unknown‐input observability subspace and the observability subspace with unknown derivatives of input and output. We first formulate the unknown‐input observability subspace via projection matrices, then show that through having the unknown‐input observability subspace, one can easily evaluate the effect of known input and output signals but unknown derivatives on the observability subspace. Our method is demonstrated on the dynamics of a longitudinal aircraft in steady‐state flight.