Late Quaternary palaeoenvironmental reconstruction from Lakes Ohrid and Prespa (Macedonia/Albania border) using stable isotopes

Abstract. Here we present stable isotope data from three sediment records from lakes that lie along the Macedonian- Albanian border (Lake Prespa: 1 core, and Lake Ohrid: 2 cores). The records only overlap for the last 40 kyr, although the longest record contains the MIS 5/6 transition (Lake Ohrid). The sedimentary characteristics of both lakes differ significantly between the glacial and interglacial phases. At the end of MIS 6 Lake Ohrid’s water level was low (high �18Ocalcite) and, although productivity was increasing (high calcite content), the carbon supply was mainly from inorganic catchment rock sources (high �13Ccarb). During the last interglacial, calcite and TOC production and preservation increased, progressively lower �18Ocalcite suggest increase in humidity and lake levels until around 115 ka. During ca. 80 ka to 11 ka the lake records suggest cold conditions as indicated by negligible calcite precipitation and low organic matter content. In Lake Ohrid, �13Corg are complacent; in contrast, Lake Prespa shows consistently higher �13Corg suggesting a low oxidation of 13C-depleted organic matter in agreement with a general deterioration of climate conditions during the glacial. From 15 ka to the onset of the Holocene, calcite and TOC begin to increase, suggesting lake levels were probably low (high �18Ocalcite). In the Holocene (11 ka to present) enhanced productivity is manifested by high calcite and organic matter content. All three cores show an early Holocene characterised by low �18Ocalcite, apart from the very early Holocene phase in Prespa where the lowest �18Ocalcite occurs at ca. 7.5 ka, suggesting a phase of higher lake level only in (the more sensitive) Lake Prespa. From 6 ka, �18Ocalcite suggest progressive aridification, in agreement with many other records in the Mediterranean, although the uppermost sediments in one core records low �18Ocalcite which we interpret as a result of human activity. Overall, the isotope data present here confirm that these two big lakes have captured the large scale, low frequency palaeoclimate variation that is seen in Mediterranean lakes, although in detail there is much palaeoclimate information that could be gained, especially small scale, high frequency differences between this region and the Mediterranean.

A Texture-based land cover classification for the delineation of a shifting cultivation landscape in the Lao PDR using landscape metrics

The delineation of shifting cultivation landscapes using remote sensing in mountainous regions is challenging. On the one hand, there are difficulties related to the distinction of forest and fallow forest classes as occurring in a shifting cultivation landscape in mountainous regions. On the other hand, the dynamic nature of the shifting cultivation system poses problems to the delineation of landscapes where shifting cultivation occurs. We present a two-step approach based on an object-oriented classification of Advanced Land Observing Satellite, Advanced Visible and Near-Infrared Spectrometer (ALOS AVNIR) and Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM) data and landscape metrics. When including texture measures in the object-oriented classification, the accuracy of forest and fallow forest classes could be increased substantially. Based on such a classification, landscape metrics in the form of land cover class ratios enabled the identification of crop-fallow rotation characteristics of the shifting cultivation land use practice. By classifying and combining these landscape metrics, shifting cultivation landscapes could be delineated using a single land cover dataset.

Eco-evolutionary Dynamics of Individual-Based Food Webs

The past decade has seen the rise of high resolution datasets. One of the main surprises of analysing such data has been the discovery of a large genetic, phenotypic and behavioural variation and heterogeneous metabolic rates among individuals within natural populations. A parallel discovery from theory and experiments has shown a strong temporal convergence between evolutionary and ecological dynamics, but a general framework to analyse from individual-level processes the convergence between ecological and evolutionary dynamics and its implications for patterns of biodiversity in food webs has been particularly lacking. Here, as a first approximation to take into account intraspecific variability and the convergence between the ecological and evolutionary dynamics in large food webs, we develop a model from population genomics and microevolutionary processes that uses sexual reproduction, genetic-distance-based speciation and trophic interactions. We confront the model with the prey consumption per individual predator, species-level connectance and prey–predator diversity in several environmental situations using a large food web with approximately 25,000 sampled prey and predator individuals. We show higher than expected diversity of abundant species in heterogeneous environmental conditions and strong deviations from the observed distribution of individual prey consumption (i.e. individual connectivity per predator) in all the environmental conditions. The observed large variance in individual prey consumption regardless of the environmental variability collapsed species-level connectance after small increases in sampling effort. These results suggest (1) intraspecific variance in prey–predator interactions has a strong effect on the macroscopic properties of food webs and (2) intraspecific variance is a potential driver regulating the speed of the convergence between ecological and evolutionary dynamics in species-rich food webs. These results also suggest that genetic–ecological drift driven by sexual reproduction, equal feeding rate among predator individuals, mutations and genetic-distance-based speciation can be used as a neutral food web dynamics test to detect the ecological and microevolutionary processes underlying the observed patterns of individual and species-based food webs at local and macroecological scales.

Institutionalizing Intensive Family Preservation Services: A Strategy for Creating Staffing Standards Based on Projections of At-Risk Children from Referral Sources

In spite of new legislation and much public and professional interest, intensive family preservation service (IFPS) remains in a vulnerable position as compared to other child welfare services. This article details a method to project ideal IFPS caseloads as a function of children who are at-risk for placement by various referral sources. Using this approach, resource allocation for IFPS can be more nearly on equal ground with the traditional child welfare functions and help IFPS to assume its needed place as a core service in the child welfare continuum.

Dietary Intakes of Children From Food Insecure Households

The objective of this cross-sectional study is to compare the dietary behaviors of children from low food secure (LFS) households with children from very low food secure (VLFS) households over an entire day, and during meals specifically consumed at home —breakfast, snack, and dinner. Parents of the recruited children completed a demographic questionnaire, along with USDA's 6-item short form food security questionnaire. Children completed 24-hour dietary recalls in person. Complete data from 102 children 9 to 12 years old were used. Using ANOVA to assess the differences among groups in intakes over an entire day and during meals consumed at home, no significant differences were found, except for vitamin C intake during breakfast. Based on the definitions of LFS and VLFS, it was hypothesized that children from VLFS group would have lower dietary intakes compared to children from the LFS group. However, this study found little difference. Speculations have been made for these findings and implications for research have been presented.

Food Insecurity and the Behavioral and Intellectual Development of Children: A Review of the Evidence

Background: Given that an alarming 1 in 5 children in the USA are at risk of hunger (1 in 3 among black and Latino children), and that 3.9 million households with children are food insecure, it is crucial to understand how household food insecurity (HFI) affects the present and future well-being of our children. Purpose: The objectives of this review article are to: (i) examine the association between HFI and child intellectual, behavioral and psycho-emotional development, controlling for socio-economic indicators; (ii) review the hypothesis that HFI is indeed a mediator of the relationship between poverty and poor child development outcomes; (iii) examine if the potential impact of HFI on caregivers’ mental health well-being mediates the relationship between HFI and child development outcomes. Methods: Pubmed search using the key words “food insecurity children.” For articles to be included they had to: (i) be based on studies measuring HFI using an experience-based scale, (ii) be peer reviewed, and (iii) include child intellectual, behavioral and/or socio-emotional development outcomes. Studies were also selected based on backward and forward Pubmed searches, and from the authors’ files. After reviewing the abstracts based on inclusion criteria a total of 26 studies were selected. Results: HFI represents not only a biological but also a psycho-emotional and developmental challenge to children exposed to it. Children exposed to HFI are more likely to internalize or externalize problems, as compared to children not exposed to HFI. This in turn is likely to translate into poor academic/cognitive performance and intellectual achievement later on in life. A pathway through which HFI may affect child development is possibly mediated by caregivers’ mental health status, especially parental stress and depression. Thus, HFI is likely to foster dysfunctional family environments. Conclusion: Findings indicate that food insecure households may require continued food assistance and psycho-emotional support until they transition to a “stable” food secure situation. This approach will require a much better integration of social policies and access to programs offering food assistance and mental health services to those in need. Findings also fully justify increased access of vulnerable children to programs that promote early in life improved nutrition as well as early psycho-social and cognitive stimulation opportunities.

Exploring the Association Between Household Food Insecurity, Parental Self-Efficacy, and Fruit and Vegetable Parenting Practices Among Parents of 5- to 8-Year-Old Overweight Children

Background: Food insecurity may negatively impact children’s nutritional status by affecting parenting quality. Because parents have a strong influence on their children’s eating and food choices, examining the effects of food insecurity on parenting may provide important insights into obesity prevention efforts. Objectives: This study explored whether food insecurity was associated with parental self-efficacy and parenting practices related to fruit and vegetable consumption. Methods: Secondary analysis was performed using baseline data from 31 mothers of 5-8 year old overweight or obese children who had participated in a pilot obesity treatment program. Household food security status, fruit and vegetable parental self-efficacy (modeling/socialization, planning/encouraging and availability/accessibility) and fruit and vegetable parenting practices (structure, responsiveness, non-directive control, and external control) were assessed using validated measures. Students' t-test investigated differences in subscales by food security status. Results: There were no significant differences in fruit and vegetable parenting practices and parental self-efficacy between food secure and insecure groups. There was a trend towards a decrease in parental self-efficacy for making fruit and vegetables available in the home among food insecure parents (p=.06). Conclusions: In this small sample no significant associations were found between food insecurity and fruit and vegetable parenting practices and parental self-efficacy. However, the trend observed in this exploratory analysis supports further hypothesis-driven research with a larger sample size able to detect more subtle differences.

Chapter Six – Individual Trait Variation and Diversity in Food Webs

In recent years, there has been a renewed interest in the ecological consequences of individual trait variation within populations. Given that individual variability arises from evolutionary dynamics, to fully understand eco-evolutionary feedback loops, we need to pay special attention to how standing trait variability affects ecological dynamics. There is mounting empirical evidence that intra-specific phenotypic variation can exceed species-level means, but theoretical models of multi-trophic species coexistence typically neglect individual-level trait variability. What is needed are multispecies datasets that are resolved at the individual level that can be used to discriminate among alternative models of resource selection and species coexistence in food webs. Here, using one the largest individual-based datasets of a food web compiled to date, along with an individual trait-based stochastic model that incorporates Approximate Bayesian computation methods, we document intra-population variation in the strength of prey selection by different classes or predator phenotypes which could potentially alter the diversity and coexistence patterns of food webs. In particular, we found that strongly connected individual predators preferentially consumed common prey, whereas weakly connected predators preferentially selected rare prey. Such patterns suggest that food web diversity may be governed by the distribution of predator connectivity and individual trait variation in prey selection. We discuss the consequences of intra-specific variation in prey selection to assess fitness differences among predator classes (or phenotypes) and track longer term food web patterns of coexistence accounting for several phenotypes within each prey and predator species.

Nebulizing poractant alfa versus conventional instillation: Ultrastructural appearance and preservation of surface activity.

BACKGROUND Nebulized surfactant therapy has been proposed as an alternative method of surfactant administration. The use of a perforated vibrating membrane nebulizer provides a variety of advantages over conventional nebulizers. We investigated the molecular structure and integrity of poractant alfa pre- and post-nebulization. METHOD Curosurf® was nebulized using an Investigational eFlow® Nebulizer System. Non-nebulized surfactant ("NN"), recollected surfactant droplets from nebulization through an endotracheal tube ("NT") and nebulization of surfactant directly onto a surface ("ND") were investigated by transmission electron microscopy. Biophysical characteristics were assessed by the Langmuir-Wilhelmy balance and the Captive Bubble Surfactometer. RESULTS Volume densities of lamellar body-like forms (LBL) and multi-lamellar forms (ML) were high for "NN" and "NT" samples (38.8% vs. 47.7% for LBL and 58.2% vs. 47.8% for ML). In the "ND" sample, we found virtually no LBL's, ML's (72.6%) as well as uni-lamellar forms (16.4%) and a new structure, the "garland-like" forms (9.4%). Surface tension for "NN" and "NT" was 23.33 ± 0.29 and 25.77 ± 1.12 mN/m, respectively. Dynamic compression-expansion cycling minimum surface tensions were between 0.91 and 1.77 mN/m. CONCLUSION The similarity of surfactant characteristics of nebulized surfactant via a tube and the non-nebulized surfactant suggests that vibrating membrane nebulizers are suitable for surfactant nebulization. Alterations in surfactant morphology and characteristics after nebulization were transient. A new structural subtype of surfactant was identified. Pediatr Pulmonol. 2014; 49:348-356. © 2013 Wiley Periodicals, Inc.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

Segmentation and Recognition of Multi-Food Meal Images for Carbohydrate Counting

In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

Food Volume Computation for Self Dietary Assessment Applications

There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.

Fine-scale population structure analysis of seven local Swiss sheep breeds using genome-wide SNP data

As part of the global sheep Hapmap project, 24 individuals from each of seven indigenous Swiss sheep breeds (Bundner Oberländer sheep (BOS), Engadine Red sheep (ERS), Swiss Black-Brown Mountain sheep (SBS), Swiss Mirror sheep (SMS), Swiss White Alpine (SWA) sheep, Valais Blacknose sheep (VBS) and Valais Red sheep (VRS)), were genotyped using Illumina’s Ovine SNP50 BeadChip. In total, 167 animals were subjected to a detailed analysis for genetic diversity using 45 193 informative single nucleotide polymorphisms. The results of the phylogenetic analyses supported the known proximity between populations such as VBS and VRS or SMS and SWA. Average genomic relatedness within a breed was found to be 12 percent (BOS), 5 percent (ERS), 9 percent (SBS), 10 percent (SMS), 9 percent (SWA), 12 percent (VBS) and 20 percent (VRS). Furthermore, genomic relationships between breeds were found for single individuals from SWA and SMS, VRS and VBS as well as VRS and BOS. In addition, seven out of 40 indicated parent–offspring pairs could not be confirmed. These results were further supported by results from the genome-wide population cluster analysis. This study provides a better understanding of fine-scale population structures within and between Swiss sheep breeds. This relevant information will help to increase the conservation activities of the local Swiss sheep breeds.

Estimating Diagnostic Test Accuracies for Brachyspira hyodysenteriae Accounting for the Complexities of Population Structure in Food Animals

For swine dysentery, which is caused by Brachyspira hyodysenteriae infection and is an economically important disease in intensive pig production systems worldwide, a perfect or error-free diagnostic test ("gold standard") is not available. In the absence of a gold standard, Bayesian latent class modelling is a well-established methodology for robust diagnostic test evaluation. In contrast to risk factor studies in food animals, where adjustment for within group correlations is both usual and required for good statistical practice, diagnostic test evaluation studies rarely take such clustering aspects into account, which can result in misleading results. The aim of the present study was to estimate test accuracies of a PCR originally designed for use as a confirmatory test, displaying a high diagnostic specificity, and cultural examination for B. hyodysenteriae. This estimation was conducted based on results of 239 samples from 103 herds originating from routine diagnostic sampling. Using Bayesian latent class modelling comprising of a hierarchical beta-binomial approach (which allowed prevalence across individual herds to vary as herd level random effect), robust estimates for the sensitivities of PCR and culture, as well as for the specificity of PCR, were obtained. The estimated diagnostic sensitivity of PCR (95% CI) and culture were 73.2% (62.3; 82.9) and 88.6% (74.9; 99.3), respectively. The estimated specificity of the PCR was 96.2% (90.9; 99.8). For test evaluation studies, a Bayesian latent class approach is well suited for addressing the considerable complexities of population structure in food animals.

Characterization of eosinophilic esophagitis murine models using optical coherence tomography.

Pre-clinical studies using murine models are critical for understanding the pathophysiological mechanisms underlying immune-mediated disorders such as Eosinophilic esophagitis (EoE). In this study, an optical coherence tomography (OCT) system capable of providing three-dimensional images with axial and transverse resolutions of 5 µm and 10 µm, respectively, was utilized to obtain esophageal images from a murine model of EoE-like disease ex vivo. Structural changes in the esophagus of wild-type (Tslpr(+/+) ) and mutant (Tslpr(-/-) ) mice with EoE-like disease were quantitatively evaluated and food impaction sites in the esophagus of diseased mice were monitored using OCT. Here, the capability of OCT as a label-free imaging tool devoid of tissue-processing artifacts to effectively characterize murine EoE-like disease models has been demonstrated.