Toward eradication of B-vitamin deficiencies : considerations for crop biofortification

'Hidden hunger' involves insufficient intake of micronutrients and is estimated to affect over two billion people on a global scale. Malnutrition of vitamins and minerals is known to cause an alarming number of casualties, even in the developed world. Many staple crops, although serving as the main dietary component for large population groups, deliver inadequate amounts of micronutrients. Biofortification, the augmentation of natural micronutrient levels in crop products through breeding or genetic engineering, is a pivotal tool in the fight against micronutrient malnutrition (MNM). Although these approaches have shown to be successful in several species, a more extensive knowledge of plant metabolism and function of these micronutrients is required to refine and improve biofortification strategies. This review focuses on the relevant B-vitamins (B1, B6, and B9). First, the role of these vitamins in plant physiology is elaborated, as well their biosynthesis. Second, the rationale behind vitamin biofortification is illustrated in view of pathophysiology and epidemiology of the deficiency. Furthermore, advances in biofortification, via metabolic engineering or breeding, are presented. Finally, considerations on B-vitamin multi-biofortified crops are raised, comprising the possible interplay of these vitamins in planta

Analysing how constraints impact architectural decision-making

Architectural design projects are characterised by a high number of constraints. Along with planning, energy performance and fire safety regulations, current designers have to face constraining factors related to budget, acoustics, orientation, wind turbulence, accessibility for the disabled, and so forth. These constraints steer the design process implicitly and explicitly in certain directions as soon as architectural designers aim at satisfying design briefs. We aim in this article at analysing the impact of such constraints on the design process. At this end, we have studied four design sessions in a particular (student) design use case. In analysing these four sessions, we used linkography as a method, because this appeared to be one of the better options to obtain a more quantitative assessment of the design process. The linkography method was combined with an interview of the student design team, in order to check the correctness of our conclusions

Conversation and critique within the architectural design process: a linkograph analysis

Conversation and critique are central to architectural design practice as they function as tools for probing and further improving design ideas. We study the kind of design activities that take place in such conversation and critique within the architectural design process. We use linkographs to characterise the design process taking place during conversation. More precisely, we study conversations between design teachers and design students. In this article, an example design process is considered that takes place via a traditional face-to-face meeting. Using the resulting linkograph, we are able to assess the kind of design activity taking place during such sessions of conversation and critique

Cash transfers in an epidemic context : the interaction of formal and informal support in rural Malawi

This paper investigates the short-run consumption expenditure dynamics and the interaction of public and private arrangements of ultra-poor and labor-constrained households in Malawi using an original dataset from the Mchinjii social cash transfer pilot project (one of the first experiments of social protection policies based on unconditional cash transfers in Sub-Saharan Africa). The authors exploit the unique source of exogenous variation provided by the randomized component of the program in order to isolate the effect of cash transfers on consumption expenditures as well as the net crowding out effect of cash transfers on private arrangements. They find a statistically significant reduction effect on the level of consumption expenditures for those households receiving cash transfers, thus leading to the rejection of the perfect risk sharing hypothesis. Moreover, by looking at the effects of cash transfers on private arrangements in a context characterized by imperfect enforceability of contracts and by a social fabric heavily compromised by high HIV/AIDS rates, the analysis confirms the presence of crowding out effects on private arrangements when looking at gifts and (to a lesser extent) remittances, while informal loans seem to be completely independent from the cash transfer's reception. From a policy perspective, the paper offers a contribution to the evaluation of the very recent wave of social protection policies based on (unconditional) cash transfers in Sub-Saharan Africa, suggesting that there might be an important role for public interventions aimed at helping households to pool risk more effectively.Safety Nets and Transfers,Rural Poverty Reduction,Labor Policies,Services&Transfers to Poor,Debt Markets

A Bayesian model to estimate individual skull conductivity for EEG source imaging

EEG source imaging (ESI) techniques estimate 3D brain activity based on electrical activity measured on the scalp. In a clinical context, these techniques are typically used for the analysis of epileptiform activity. They play a central role in the pre-surgical planning prior to removal of the epileptic seizure focus, needed in about 30% of people with epilepsy [1]. ESI techniques make use of a parametric model of the geometry and electromagnetic properties of the subject’s head. While the geometry can be modelled precisely using an anatomical MR image of the head, there remains high uncertainty in the electrical conductivity of several types of tissue in the head (skull, white and gray matter, scalp etc.). Commonly, these conductivity values are set to a conventional value, based on previous studies. Because individual conductivity values can deviate radically from the conventional values (exceeding an order of magnitude) this can lead to errors that need to be avoided for accurate estimation of the epileptic focus location [2]. In this work, a first Bayesian model is proposed that is able to simultaneously estimate the source location and the subject specific skull conductivity from the measured EEG signals. The expectation-maximization algorithm was used to iteratively update the parameter estimation. As a first proof of concept, we used a three-layered spherical head model and a single dipole source to simulate electrical activity on the scalp, measured at 36 electrode positions, for a range of human skull conductivity values found in literature. We compared the source localization performance with our adaptive conductivity estimation to the performance with several conventional conductivity values used in previous studies. We found that, due to the high variation in individual skull conductivity values, the true source can be located more than 15mm away from the estimated source location using the conventional conductivity. Adaptive estimation of the conductivity with the Bayesian model lowers the maximum location error to only 3mm (see Figure 1). The first proof of concept looks promising and will be further deployed, including better probabilistic models for the variation in measured EEG, variation in dipole location and prior distribution of conductivity values. The final goal of this work is to estimate all tissue conductivity parameters, making the head model truly adaptive to the individual subject. [1] Strobbe G., Carrette E., Lopez J.D., Van Roost D., Meurs E., Vonck K., Boon P., Vandenberghe S., van Mierlo P. (2015) EEG source imaging of interictal spikes using multiple sparse volumetric priors for presurgical focus localization, NeuroImage, in preparation for submission. [2] Kassem A., Jackson D., Baumann S., Williams J., Wilton D., Fink P. and Prasky B. (1998) Effect of Conductivity Uncertainties and Modeling Errors on EEG Source Localization Using a 2-D Model, IEEE Transaction on Biomedical Engineering, vol. 45, no. 9, pp. 1135-114

Automatic learning of user interests for personalized communication services

In view of the overwhelming popularity of user generated content new intelligent services are needed to filter this content based on personal interests. In this paper we present a set of algorithms for retrieving content, based on dynamic user profiles and learning capabilities. To illustrate the approach taken, a rich communication service is presented