Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

Innovative approaches For enhancing the flow of funds into the Benefit Sharing Fund of the International Treaty on Plant Genetic Resources for Food and Agriculture: an evaluation of options

This report assesses the implications and revenue-generating potential of options for reform of the International Treaty on Plant Genetic Resources for Food and Agriculture in the context of the structure of the global seed industry and the emerging landscape of plant variety innovation for different crops. The implementation of these options would require modifications of Treaty and provisions of the Standard Material Transfer Agreements to alter the nature of payment obligations related to different categories of products, the payment rates under different options and the coverage of crops in Annex-I to the Treaty.

Fat and fatty acid composition of cooked meat from UK retail chickens labelled as from organic and non-organic production systems

This study compared fat and fatty acids in cooked retail chicken meat from conventional and organic systems. Fat contents were 1.7, 5.2, 7.1 and 12.9 g/100 g cooked weight in skinless breast, breast with skin, skinless leg and leg with skin respectively, with organic meat containing less fat overall (P < 0.01). Meat was rich in cis-monounsaturated fatty acids, although organic meat contained less than did conventional meat (1850 vs. 2538 mg/100 g; P < 0.001). Organic meat was also lower (P < 0.001) in 18:3 n−3 (115 vs. 180 mg/100 g) and, whilst it contained more (P < 0.001) docosahexaenoic acid (30.9 vs. 13.7 mg/100 g), this was due to the large effect of one supermarket. This system by supermarket interaction suggests that poultry meat labelled as organic is not a guarantee of higher long chain n−3 fatty acids. Overall there were few major differences in fatty acid contents/profiles between organic and conventional meat that were consistent across all supermarkets.

Formulaic sequences in native and non-native argumentative writing in German

Whereas there is substantial scholarship on formulaic language in L1 and L2 English, there is less research on formulaicity in other languages. The aim of this paper is to contribute to learner corpus research into formulaic language in native and non-native German. To this effect, a corpus of argumentative essays written by advanced British students of German (WHiG) was compared with a corpus of argumentative essays written by German native speakers (Falko-L1). A corpus-driven analysis reveals a larger number of 3-grams in WHiG than in Falko-L1, which suggests that British advanced learners of German are more likely to use formulaic language in argumentative writing than their native-speaker counterparts. Secondly, by classifying the formulaic sequences according to their functions, this study finds that native speakers of German prefer discourse-structuring devices to stance expressions, whilst British advanced learners display the opposite preferences. Thirdly, the results show that learners of German make greater use of macro-discourse-structuring devices and cautious language, whereas native speakers favour micro-discourse structuring devices and tend to use more direct language. This study increases our understanding of formulaic language typical of British advanced learners of German and reveals how diverging cultural paradigms can shape written native speaker and learner output.

Preferred response of the East Asian summer monsoon to local and non-local anthropogenic sulphur dioxide emissions

In this study, the atmospheric component of a state-of-the-art climate model (HadGEM2-ES) that includes earth system components such as interactive chemistry and eight species of tropospheric aerosols considering aerosol direct, indirect, and semi-direct effects, has been used to investigate the impacts of local and non-local emissions of anthropogenic sulphur dioxide on the East Asian summer monsoon (EASM). The study focuses on the fast responses (including land surface feedbacks, but without sea surface temperature feedbacks) to sudden changes in emissions from Asia and Europe. The initial responses, over days 1–40, to Asian and European emissions show large differences. The response to Asian emissions involves a direct impact on the sulphate burden over Asia, with immediate consequences for the shortwave energy budget through aerosol–radiation and aerosol–cloud interactions. These changes lead to cooling of East Asia and a weakening of the EASM. In contrast, European emissions have no significant impact on the sulphate burden over Asia, but they induce mid-tropospheric cooling and drying over the European sector. Subsequently, however, this cold and dry anomaly is advected into Asia, where it induces atmospheric and surface feedbacks over Asia and the Western North Pacific (WNP), which also weaken the EASM. In spite of very different perturbations to the local aerosol burden in response to Asian and European sulphur dioxide emissions, the large scale pattern of changes in land–sea thermal contrast, atmospheric circulation and local precipitation over East Asia from days 40 onward exhibits similar structures, indicating a preferred response, and suggesting that emissions from both regions likely contributed to the observed weakening of the EASM. Cooling and drying of the troposphere over Asia, together with warming and moistening over the WNP, reduces the land–sea thermal contrast between the Asian continent and surrounding oceans. This leads to high sea level pressure (SLP) anomalies over Asia and low SLP anomalies over the WNP, associated with a weakened EASM. In response to emissions from both regions warming and moistening over the WNP plays an important role and determines the time scale of the response.

How is the balance of a forecast ensemble affected by adaptive and non-adaptive localization schemes?

This paper investigates the effect on balance of a number of Schur product-type localization schemes which have been designed with the primary function of reducing spurious far-field correlations in forecast error statistics. The localization schemes studied comprise a non-adaptive scheme (where the moderation matrix is decomposed in a spectral basis), and two adaptive schemes, namely a simplified version of SENCORP (Smoothed ENsemble COrrelations Raised to a Power) and ECO-RAP (Ensemble COrrelations Raised to A Power). The paper shows, we believe for the first time, how the degree of balance (geostrophic and hydrostatic) implied by the error covariance matrices localized by these schemes can be diagnosed. Here it is considered that an effective localization scheme is one that reduces spurious correlations adequately but also minimizes disruption of balance (where the 'correct' degree of balance or imbalance is assumed to be possessed by the unlocalized ensemble). By varying free parameters that describe each scheme (e.g. the degree of truncation in the schemes that use the spectral basis, the 'order' of each scheme, and the degree of ensemble smoothing), it is found that a particular configuration of the ECO-RAP scheme is best suited to the convective-scale system studied. According to our diagnostics this ECO-RAP configuration still weakens geostrophic and hydrostatic balance, but overall this is less so than for other schemes.

Freezing skeletal muscle tissue does not affect its decomposition in soil: Evidence from temporal changes in tissue mass, microbial activity and soil chemistry based on excised samples

The study of decaying organisms and death assemblages is referred to as forensic taphonomy, or more simply the study of graves. This field is dominated by the fields of entomology, anthropology and archaeology. Forensic taphonomy also includes the study of the ecology and chemistry of the burial environment. Studies in forensic taphonomy often require the use of analogues for human cadavers or their component parts. These might include animal cadavers or skeletal muscle tissue. However, sufficient supplies of cadavers or analogues may require periodic freezing of test material prior to experimental inhumation in the soil. This study was carried out to ascertain the effect of freezing on skeletal muscle tissue prior to inhumation and decomposition in a soil environment under controlled laboratory conditions. Changes in soil chemistry were also measured. In order to test the impact of freezing, skeletal muscle tissue (Sus scrofa) was frozen (−20 °C) or refrigerated (4 °C). Portions of skeletal muscle tissue (∼1.5 g) were interred in microcosms (72 mm diameter × 120 mm height) containing sieved (2 mm) soil (sand) adjusted to 50% water holding capacity. The experiment had three treatments: control with no skeletal muscle tissue, microcosms containing frozen skeletal muscle tissue and those containing refrigerated tissue. The microcosms were destructively harvested at sequential periods of 2, 4, 6, 8, 12, 16, 23, 30 and 37 days after interment of skeletal muscle tissue. These harvests were replicated 6 times for each treatment. Microbial activity (carbon dioxide respiration) was monitored throughout the experiment. At harvest the skeletal muscle tissue was removed and the detritosphere soil was sampled for chemical analysis. Freezing was found to have no significant impact on decomposition or soil chemistry compared to unfrozen samples in the current study using skeletal muscle tissue. However, the interment of skeletal muscle tissue had a significant impact on the microbial activity (carbon dioxide respiration) and chemistry of the surrounding soil including: pH, electroconductivity, ammonium, nitrate, phosphate and potassium. This is the first laboratory controlled study to measure changes in inorganic chemistry in soil associated with the decomposition of skeletal muscle tissue in combination with microbial activity.

Translation practices in political institutions: a comparison of national, supranational, and non-governmental organisations

This paper explores the settings and practices of translation at three types of political institutions, i.e. national, supranational, and non-governmental organisations. The three institutions are the translation service of the German Foreign Office, the translation department of the European Central Bank, and translation provision by the non-governmental organisation Amnesty International. The three case studies describe the specific translation practices in place at these institutions and illustrate some characteristic translation strategies. In this way, we reflect on how different translation practices can impact on translation agency and how these practices in turn are influenced by the type of institution and its organisational structure. The article also aims to explore to which extent the characteristics of collectivity, anonymity and standardisation, and of institutional translation as self-translation are applicable to the institutions under discussion.

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Morphology of polymer networks formed in the chiral and non chiral phases of an anti-ferroelectric liquid crystal

We introduced photo-polymer networks into the various liquid crystalline phases of the antiferroelectric liquid crystal AS612 and studied the effects of these networks by measuring the temperature dependence of the Bragg wavelengths selectively reflected. After polymerization, the decrease in Bragg wavelengths with respect to the original values is consistent with a shorter helical pitch due to polymer network shrinkage. Also, by removing the liquid crystalline material, we are able to image the residual polymer network using scanning electron microscopy and polarized light microscopy. The polymer strands are a few microns thick and the networks show both chiral and non-chiral features.

Joint use of attribute importance rankings and non-attendance data in choice experiments

The joint and alternative uses of attribute non-attendance and importance ranking data within discrete choice experiments are investigated using data from Lebanon examining consumers’ preferences for safety certification in food. We find that both types of information; attribute non-attendance and importance rankings, improve estimates of respondent utility. We introduce a method of integrating both types of information simultaneously and find that this outperforms models where either importance ranking or non-attendance data are used alone. As in previous studies, stated non-attendance of attributes was not found to be consistent with respondents having zero marginal utility for those attributes

English compound and non-compound processing in bilingual and multilingual speakers: effects of dominance and sequential multilingualism

This article reports on a study investigating the relative influence of the first and dominant language on L2 and L3 morpho-lexical processing. A lexical decision task compared the responses to English NV-er compounds (e.g., taxi driver) and non-compounds provided by a group of native speakers and three groups of learners at various levels of English proficiency: L1 Spanish-L2 English sequential bilinguals and two groups of early Spanish-Basque bilinguals with English as their L3. Crucially, the two trilingual groups differed in their first and dominant language (i.e., L1 Spanish-L2 Basque vs. L1 Basque-L2 Spanish). Our materials exploit an (a)symmetry between these languages: while Basque and English pattern together in the basic structure of (productive) NV-er compounds, Spanish presents a construction that differs in directionality as well as inflection of the verbal element (V[3SG] + N). Results show between and within group differences in accuracy and response times that may be ascribable to two factors besides proficiency: the number of languages spoken by a given participant and their dominant language. An examination of response bias reveals an influence of the participants' first and dominant language on the processing of NV-er compounds. Our data suggest that morphological information in the nonnative lexicon may extend beyond morphemic structure and that, similarly to bilingualism, there are costs to sequential multilingualism in lexical retrieval.

Tensor LRR and sparse coding-based subspace clustering

Subspace clustering groups a set of samples from a union of several linear subspaces into clusters, so that the samples in the same cluster are drawn from the same linear subspace. In the majority of the existing work on subspace clustering, clusters are built based on feature information, while sample correlations in their original spatial structure are simply ignored. Besides, original high-dimensional feature vector contains noisy/redundant information, and the time complexity grows exponentially with the number of dimensions. To address these issues, we propose a tensor low-rank representation (TLRR) and sparse coding-based (TLRRSC) subspace clustering method by simultaneously considering feature information and spatial structures. TLRR seeks the lowest rank representation over original spatial structures along all spatial directions. Sparse coding learns a dictionary along feature spaces, so that each sample can be represented by a few atoms of the learned dictionary. The affinity matrix used for spectral clustering is built from the joint similarities in both spatial and feature spaces. TLRRSC can well capture the global structure and inherent feature information of data, and provide a robust subspace segmentation from corrupted data. Experimental results on both synthetic and real-world data sets show that TLRRSC outperforms several established state-of-the-art methods.