Alternative plant protein sources for pigs and chickens in the tropics – nutritional value and constraints: a review

In the tropics, a large number of smallholder farms contribute significantly to food security by raising pigs and poultry for domestic consumption and for sale on local markets. The high cost and, sometimes, the lack of availability of commercial protein supplements is one of the main limitations to efficient animal production by smallholders. Locally-grown forages and grain legumes offer ecological benefits such as nitrogen fixation, soil improvement, and erosion control which contribute to improve cropping efficiency. Besides these agronomical assets, they can be used as animal feeds in mixed farming systems. In this paper we review options to include locally-grown forages and grain legumes as alternative protein sources in the diets of pigs and poultry in order to reduce farmers’ dependence on externally-purchased protein concentrates. The potential nutritive value of a wide range of forages and grain legumes is presented and discussed. The influence of dietary fibre and plant secondary metabolites contents and their antinutritive consequences on feed intake, digestive processes and animal performances are considered according to the varying composition in those compounds of the different plant species and cultivars covered in this review. Finally, methods to overcome the antinutritive attributes of the plant secondary metabolites using heat, chemical or biological treatment are reviewed regarding their efficiency and their suitability in low input farming systems.

Contradictions within the Modern Food System: Nutritional Disbalance across the Globe, Its Main Drivers and Possible Ways Out

Contemporary food production, given the degree of technology being applied in it and the present state of scientific knowledge, should be able to feed the world. Corresponding statistics show that in fact the volumes of modern food production confirm this statement. Yet, the present nutritional situation across the globe leaves much to be desired: on the one hand the numbers of undernourished and malnourished people are still high and even growing in some regions, and on the other hand there is an increasing number of overweight and obese people who are experiencing (or are at risk of) adverse health impacts as consequences. The question arises how this situation is possible given the present state of food production and knowledge, and also in terms of nutrition basics when talking about the latter. When arguing about the main causes of the present situation with nutrition across the globe, it is the modern food system with its distortions that is often criticised with emphasis placed on inappropriate food distribution as one of the key problems. However it is not only food distribution that shapes inequalities in terms of food availability and accessibility – there is a number of other factors contributing to this situation including political influences. Each of the drivers of the present situation might affect more than one part and have outcomes in different dimensions. Therefore it makes sense to apply a holistic approach when viewing the modern food system, embracing all the elements and existing relationships between them for this will facilitate taking appropriate actions in order to target the desired outcome in the best possible way. Applying a systematic approach and linking various elements with corresponding interactions among them allows for picturing all the possible outcomes and hence finding the way for a better solution on global level – a solution to the present problem with nutritional disbalance across the globe.

Enlarging a training set for genomic selction by imputation of un-genotyped animals in populations of varying genetic architecture

Background: The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. ----- Methods: Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. ----- Results: Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. ----- Conclusions: Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.

Diversity and nutritional properties of Pakistani dates: implications for sustainable value chain and decent living perspectives of rural households

Date palm (Phoenix dactylifera L.) occupies almost three percent of the total worldwide cultivated area, with an annual production of seven million tonnes (t). Pakistan is an ideal place for the cultivation of date palm due to its sandy loam soil and semi-arid climate. In 2012, Pakistan produced 600,000 t of dates, on an area of 95,000 ha. Baluchistan province is the country’s top date producer, followed by Sindh, Punjab and Khyber Pakhtunkhwa (KPK) provinces. More than 300 date varieties are known to exist in Pakistan and some commercially important cultivars are: Karbalaen, Aseel, Muzawati, Fasli, Begum Jhangi, Hillawi, Dashtiari, Sabzo, Koharaba, Jaan Swore, Rabai and Dhakki. Six districts from the four provinces of Pakistan (Jhang, Muzaffargarh and Bahawalpur (Punjab), Dera Ismail Khan (KPK), Khairpur (Sindh) and Panjgur (Baluchistan)) with largest area under date palm cultivation were selected to conduct socio-economic surveys including the income sources of date palm growers. A structured questionnaire with open-ended and closed questions was used for face-to-face interviews of 170 date palm growers. At each location after selection of a first farmer through a local guide, the former was requested to provide names and addresses of three other date growers in his area. From these three names, one was randomly selected for the next sampling. Additionally, date palm fronds and fruits of all available cultivars were collected for morphological and nutritional analyses. Soil samples were collected from the groves for subsequent chemical and physical analyses. Almost all farmers used dates as a food item for their families and some were using low quality dates as a feed for their livestock. Apart from dates, other date palm components (trunk, spadix, frond, inflorescence and seed) were used by date palm growers as a raw material for making many by-products for their families. Date palm had a major contribution in the income of households, 24% received 91-100% of their income from date palms. More than half of the surveyed farmers had date palm groves, but scattered plantations, home gardens and intercropping systems with cereal and other fruits were also present. Dhakki, Muzawati, Aseel, and Karbalaen were the most important commercial cultivars grown in the provinces of KPK, Baluchistan, and Sindh. Aseel, Karoch, Haleni, Karbalaen, and Muzawati cultivars had the most firm fruit and good total soluble sugar, calcium and magnesium contents. The amount of magnesium found in dates of studied cultivars ranged from 0.143 to 0.876 mg g-1. A great variation in frond morphology was recorded among the cultivars. Fruit length and fruit weight was highest in Dhakki date, making it visually more attractive for customers in addition to its good nutritional properties. The seed weight of the studied cultivars ranged from 0.7-2.0 g, while Desi dates had largest seed, making them less attractive for marketing. However, in terms of nutritional value and fruit size, most of the investigated varieties can compete with globally important commercial dates.

Förderung des kritischen Denkens thailändischer Deutschlernender durch Training des kritischen Lesens im Deutschunterricht

Die vorliegende Dissertation untersucht das Leseverhalten thailändischer Deutschlernender mit dem Ziel, ihre Fähigkeit zum kritischen Lesen unter Anwendung des MURDER-Schemas im fremdsprachlichen Deutschunterricht zu fördern. Neben der Lesefertigkeit soll aufgrund der bestehenden Zusammenhänge zusätzlich das kritische Denken der Lernenden gefördert werden.

Rotation Invariant Object Recognition from One Training Example

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. Such a descriptor--based on a set of oriented Gaussian derivative filters-- is used in our recognition system. We report here an evaluation of several techniques for orientation estimation to achieve rotation invariance of the descriptor. We also describe feature selection based on a single training image. Virtual images are generated by rotating and rescaling the image and robust features are selected. The results confirm robust performance in cluttered scenes, in the presence of partial occlusions, and when the object is embedded in different backgrounds.

Support Vector Machines: Training and Applications

The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique for Polynomial, Radial Basis Function and Multi-Layer Perceptron classifiers. An interesting property of this approach is that it is an approximate implementation of the Structural Risk Minimization (SRM) induction principle. The derivation of Support Vector Machines, its relationship with SRM, and its geometrical insight, are discussed in this paper. Training a SVM is equivalent to solve a quadratic programming problem with linear and box constraints in a number of variables equal to the number of data points. When the number of data points exceeds few thousands the problem is very challenging, because the quadratic form is completely dense, so the memory needed to store the problem grows with the square of the number of data points. Therefore, training problems arising in some real applications with large data sets are impossible to load into memory, and cannot be solved using standard non-linear constrained optimization algorithms. We present a decomposition algorithm that can be used to train SVM's over large data sets. The main idea behind the decomposition is the iterative solution of sub-problems and the evaluation of, and also establish the stopping criteria for the algorithm. We present previous approaches, as well as results and important details of our implementation of the algorithm using a second-order variant of the Reduced Gradient Method as the solver of the sub-problems. As an application of SVM's, we present preliminary results we obtained applying SVM to the problem of detecting frontal human faces in real images.

Validating Co-Training Models for Web Image Classification

Co-training is a semi-supervised learning method that is designed to take advantage of the redundancy that is present when the object to be identified has multiple descriptions. Co-training is known to work well when the multiple descriptions are conditional independent given the class of the object. The presence of multiple descriptions of objects in the form of text, images, audio and video in multimedia applications appears to provide redundancy in the form that may be suitable for co-training. In this paper, we investigate the suitability of utilizing text and image data from the Web for co-training. We perform measurements to find indications of conditional independence in the texts and images obtained from the Web. Our measurements suggest that conditional independence is likely to be present in the data. Our experiments, within a relevance feedback framework to test whether a method that exploits the conditional independence outperforms methods that do not, also indicate that better performance can indeed be obtained by designing algorithms that exploit this form of the redundancy when it is present.

Implementation of training programs in self-regulated learning strategies in Moodle format : Results of a experience in higher education

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How to improve the formal analytic reasoning and scientific motivation in the intellectual training of medical students

A review article of the The New England Journal of Medicine refers that almost a century ago, Abraham Flexner, a research scholar at the Carnegie Foundation for the Advancement of Teaching, undertook an assessment of medical education in 155 medical schools in operation in the United States and Canada. Flexner’s report emphasized the nonscientific approach of American medical schools to preparation for the profession, which contrasted with the university-based system of medical education in Germany. At the core of Flexner’s view was the notion that formal analytic reasoning, the kind of thinking integral to the natural sciences, should hold pride of place in the intellectual training of physicians. This idea was pioneered at Harvard University, the University of Michigan, and the University of Pennsylvania in the 1880s, but was most fully expressed in the educational program at Johns Hopkins University, which Flexner regarded as the ideal for medical education. (...)

Attention training in Attention Deficit Hyperactivity Disorder

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Training and pre-decisional bias in a multiattribute decision task. 'Formaci??n y sesgo pre-decisional en una tarea de decisi??n multiatributiva'

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Inputs for the incorporation of the UNESCO guidelines on ICT competency standards for teachers : the training of teachers of mathematics in Central America

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Teacher Training Videos

Free online training resources on using web 2.0 tools for busy lecturers. - 'Outstanding ICT initiative of the year' winner of the JISC award is commended for 'commitment to open access to online content' A wealth of openly available multimedia content won the JISC/Times Higher Award. Created by University of Westminster lecturer Russell Stannard's websites build upon pioneering work using video to mark students' work. Using screen recording software, Stannard recorded himself walking through various Web 2.0 technologies with a voice-over, which were then uploaded to a website - www.teachertrainingvideos.com. The site quickly proved popular and rapidly built into a bank of over 30 videos.

Multimedia Training Videos

Multimedia Training Videos is a series of free learning videos to show anyone interested in learning packages like Flash, Director and Photoshop.