Inulin and maltodextrin can replace fat in baked savoury legume snacks

A baked yellow split pea cracker was developed with fat replacement (0%, 25%, 50%, 75% and 100%) using inulin, hydroxypropyl methylcellulose and maltodextrin. Effects of fat replacement on physical (water activity, moisture content, colour and hardness), nutritional properties and consumer acceptance (nine-point hedonic rating) of snacks were investigated. Water activity (0.15-0.32) and moisture (1.28-3.16%) readings were consistent, and products were considered shelf stable. High levels of fat replacement (100%) were detrimental to snack colour and hardness. Snacks with 75% fat replacement using inulin and maltodextrin received similar mean overall acceptability scores (6.40 ± 1.36 and 6.26 ± 1.37, respectively) to the control and a similar commercial product. These snacks were eligible to claim that they were a 'good source' of protein (requirement; ≥10 g per serve) and an 'excellent source' of dietary fibre (requirement; ≥7 g per serve) while providing 'reduced' fat content (≤25% than reference food) based on the Australian Food Standards Code.

Investigation into the role of potentially contaminated feed as a source of the first-detected outbreaks of porcine epidemic diarrhea in Canada

In January 2014, approximately 9 months following the initial detection of porcine epidemic diarrhea (PED) in the USA, the first case of PED was confirmed in a swine herd in south-western Ontario. A follow-up epidemiological investigation carried out on the initial and 10 subsequent Ontario PED cases pointed to feed as a common risk factor. As a result, several lots of feed and spray-dried porcine plasma (SDPP) used as a feed supplement were tested for the presence of PEDV genome by real-time RT-PCR assay. Several of these tested positive, supporting the notion that contaminated feed may have been responsible for the introduction of PEDV into Canada. These findings led us to conduct a bioassay experiment in which three PEDV-positive SDPP samples (from a single lot) and two PEDV-positive feed samples supplemented with this SDPP were used to orally inoculate 3-week-old piglets. Although the feed-inoculated piglets did not show any significant excretion of PEDV, the SDPP-inoculated piglets shed PEDV at a relatively high level for ≥9 days. Despite the fact that the tested PEDV genome positive feed did not result in obvious piglet infection in our bioassay experiment, contaminated feed cannot be ruled out as a likely source of this introduction in the field where many other variables may play a contributing role.

Metabolic fate (absorption, β-oxidation and deposition) of long-chain n-3 fatty acids is affected by sex and by the oil source (krill oil or fish oil) in the rat

The effects of krill oil as an alternative source of n-3 long-chain PUFA have been investigated recently. There are conflicting results from the few available studies comparing fish oil and krill oil. The aim of this study was to compare the bioavailability and metabolic fate (absorption, β-oxidation and tissue deposition) of n-3 fatty acids originating from krill oil (phospholipid-rich) or fish oil (TAG-rich) in rats of both sexes using the whole-body fatty acid balance method. Sprague-Dawley rats (thirty-six male, thirty-six female) were randomly assigned to be fed either a krill oil diet (EPA+DHA+DPA=1·38 mg/g of diet) or a fish oil diet (EPA+DHA+DPA=1·61 mg/g of diet) to constant ration for 6 weeks. The faeces, whole body and individual tissues were analysed for fatty acid content. Absorption of fatty acids was significantly greater in female rats and was only minimally affected by the oil type. It was estimated that most of EPA (>90 %) and more than half of DHA (>60 %) were β-oxidised in both diet groups. Most of the DPA was β-oxidised (57 and 67 % for female and male rats, respectively) in the fish oil group; however, for the krill oil group, the majority of DPA was deposited (82-83 %). There was a significantly greater deposition of DPA and DHA in rats fed krill oil compared with those fed fish oil, not due to a difference in bioavailability (absorption) but rather due to a difference in metabolic fate (anabolism v. catabolism).

Radio frequency energy harvesting from a feeding source in a passive deep brain stimulation device for murine preclinical research

This paper presents the development of an energy harvesting circuit for use with a head-mountable deep brain stimulation (DBS) device. It consists of a circular planar inverted-F antenna (PIFA) and a Schottky diode-based Cockcroft-Walton 4-voltage rectifier. The PIFA has the volume of π × 10(2) × 1.5 mm(3), resonance frequency of 915 MHz, and bandwidth of 16 MHz (909-925 MHz) at a return loss of -10 dB. The rectifier offers maximum efficiency of 78% for the input power of -5 dBm at a 5 kΩ load resistance. The developed rectenna operates efficiently at 915 MHz for the input power within -15 dBm to +5 dBm. For operating a DBS device, the DC voltage of 2 V is recorded from the rectenna terminal at a distance of 55 cm away from a 26.77 dBm transmitter in free space. An in-vitro test of the DBS device is presented.

Satellite imagery as a single source of predictor variables for habitat suitability modelling: how Landsat can inform the conservation of a critically endangered lemur

1. Statistical modelling of habitat suitability is an important tool for planning conservation interventions, particularly for areas where species distribution data are expensive or hard to collect. Sometimes however the predictor variables typically used in habitat suitability modelling are themselves difficult to obtain or not meaningful at the geographical extent of the study, as is the case for the Alaotran gentle lemur Hapalemur alaotrensis, a critically endangered lemur confined to the marshes of Lake Alaotra in Madagascar.2. We developed a habitat suitability model where all predictor variables, including vegetation indices and image texture measures at different scales (as surrogates for habitat structure), were derived from Landsat7 satellite imagery. Using relatively few presence records, the maximum entropy (Maxent) approach and AUC were used to assess the performance of candidate predictor variables, for studying the effect of scale, model selection and mapping suitable habitat.3. This study demonstrated the utility of satellite imagery as a single source of predictor variables for a Maxent habitat suitability model at the landscape level, within a restricted geographical extent and with a fine grain, in a case where predictor variables typically used at the macro-scale level (e.g. climatic and topographic) were not applicable.4. In the case of H. alaotrensis, the methodology generated a habitat suitability map to inform conservation management in Lake Alaotra and a replicable protocol to allow rapid updates to habitat suitability maps in the future. The exploration of candidate predictor variables allowed the identification of scales that appear ecologically relevant for the species.5. Synthesis and applications. This study presents a cost-effective combination of maximum entropy habitat suitability modelling and satellite imagery, where all predictor variables are derived solely from Landsat7 images. With a habitat modelling method like Maxent that shows good performance with few presence samples and Landsat images now freely available, the methodology can play an important role in rapid assessments of the status of species at the landscape level in data-poor regions, when typical macro-scale environmental predictors are of little use or difficult to obtain.

Sturnus vulgaris, mitochondrial selection, MATLAB code and microsatellite data

Here we provide MATLAB code used to simulate drift and selection between and within individuals, which has been used to investigate mitochondrial haplotype frequency shifts in Sturnus vulgaris. Also provided is a microsatellite data set used to assess whether empirical allele frequency shifts were likely to be caused by admixture. These files support and upcoming publication, which concludes that within-individuals selection on mitochondrial DNA best explains empirical data.

A convex geometry-based blind source separation method for separating nonnegative sources

This paper presents a convex geometry (CG)-based method for blind separation of nonnegative sources. First, the unaccessible source matrix is normalized to be column-sum-to-one by mapping the available observation matrix. Then, its zero-samples are found by searching the facets of the convex hull spanned by the mapped observations. Considering these zero-samples, a quadratic cost function with respect to each row of the unmixing matrix, together with a linear constraint in relation to the involved variables, is proposed. Upon which, an algorithm is presented to estimate the unmixing matrix by solving a classical convex optimization problem. Unlike the traditional blind source separation (BSS) methods, the CG-based method does not require the independence assumption, nor the uncorrelation assumption. Compared with the BSS methods that are specifically designed to distinguish between nonnegative sources, the proposed method requires a weaker sparsity condition. Provided simulation results illustrate the performance of our method.

Specifying model transformations by direct manipulation using concrete visual notations and interactive recommendations

Model transformations are a crucial part of Model-Driven Engineering (MDE) technologies but are usually hard to specify and maintain for many engineers. Most current approaches use meta-model-driven transformation specification via textual scripting languages. These are often hard to specify, understand and maintain. We present a novel approach that instead allows domain experts to discover and specify transformation correspondences using concrete visualizations of example source and target models. From these example model correspondences, complex model transformation implementations are automatically generated. We also introduce a recommender system that helps domain experts and novice users find possible correspondences between large source and target model visualization elements. Correspondences are then specified by directly interacting with suggested recommendations or drag and drop of visual notational elements of source and target visualizations. We have implemented this approach in our prototype tool-set, CONVErT, and applied it to a variety of model transformation examples. Our evaluation of this approach includes a detailed user study of our tool and a quantitative analysis of the recommender system.

Dimensions and metrics for evaluating recommendation systems

Recommendation systems support users and developers of various computer and software systems to overcome information overload, perform information discovery tasks, and approximate computation, among others. They have recently become popular and have attracted a wide variety of application scenarios ranging from business process modeling to source code manipulation. Due to this wide variety of application domains, different approaches and metrics have been adopted for their evaluation. In this chapter, we review a range of evaluation metrics and measures as well as some approaches used for evaluating recommendation systems. The metrics presented in this chapter are grouped under sixteen different dimensions, e.g., correctness, novelty, coverage. We review these metrics according to the dimensions to which they correspond. A brief overview of approaches to comprehensive evaluation using collections of recommendation system dimensions and associated metrics is presented. We also provide suggestions for key future research and practice directions.

K-Center: an approach on the multi-source identification of information diffusion

The global diffusion of epidemics, computer viruses, and rumors causes great damage to our society. It is critical to identify the diffusion sources and timely quarantine them. However, most methods proposed so far are unsuitable for diffusion with multiple sources because of the high computational cost and the complex spatiotemporal diffusion processes. In this paper, based on the knowledge of infected nodes and their connections, we propose a novel method to identify multiple diffusion sources, which can address three main issues in this area: 1) how many sources are there? 2) where did the diffusion emerge? and 3) when did the diffusion break out? We first derive an optimization formulation for multi-source identification problem. This is based on altering the original network into a new network concerning two key elements: 1) propagation probability and 2) the number of hops between nodes. Experiments demonstrate that the altered network can accurately reflect the complex diffusion processes with multiple sources. Second, we derive a fast method to optimize the formulation. It has been proved that the proposed method is convergent and the computational complexity is O(mn log α) , where α = α (m,n) is the slowly growing inverse-Ackermann function, n is the number of infected nodes, and m is the number of edges connecting them. Finally, we introduce an efficient algorithm to estimate the spreading time and the number of diffusion sources. To evaluate the proposed method, we compare the proposed method with many competing methods in various real-world network topologies. Our method shows significant advantages in the estimation of multiple sources and the prediction of spreading time.

Haptically-enabled dance visualisation framework for deafblind-folded audience and artists

In this paper we propose a framework for communicating performance art to deaf, blind and deafblind audiences and artists haptically through the sense of touch. This research opens doors for novel artistic trends relying mainly on the sense of touch. The paper investigates the design considerations dictated by solo and group dances as well as stage setup. Implementation scenarios for deafblind audiences and performers are also discussed.

Defence against code injection attacks

Code injection attacks are considered serious threats to the Internet users. In this type of attack the attacker injects malicious codes in the user programs to change or divert the execution flows. In this paper we explore the contemporary defence strategies against code injection attacks (CIAs) and underline their limitations. To overcome these limitations, we suggest a number of countermeasure mechanisms for protecting from CIAs. Our key idea relies on the multiplexing technique to preserve the exact return code to ensure the integrity of program execution trace of shell code. This technique also maintains a FIFO (first in first out) queue to defeat the conflict state when multiple caller method makes a call simultaneously. Finally, our technique can provide better performance, in terms of protection and speed, in some point compared to the CFI (control flow integrity) as well as CPM (code pointer masking) techniques.