Cassava root peel as a replacement for maize in diets for growing pigs: effects on energy and nutrient digestibility, performance and carcass characteristics

Two experiments were conducted to evaluate cassava root peel (CRP) as diet component for fattening pigs. In the first experiment, ten male pigs were used to investigate the nutrient digestibility and the nutritive value of CRP as replacement for maize in the diet at 0 %, 30 %, 40 %, 50 % and 60 %, while supplementing free amino acids (fAA). During two experimental periods, faeces were quantitatively collected and analysed for chemical composition. In the second experiment, 40 pigs received the same diets as in Experiment 1, and daily feed intake and weekly weight changes were recorded. Four pigs per diet were slaughtered at 70 kg body weight to evaluate carcass traits. Digestibility of dry and organic matter, crude protein, acid detergent fibre and gross energy were depressed (p<0.05) at 60 % CRP; digestible energy content (MJ kg^(−1) DM) was 15.4 at 0 % CRP and 12.7 at 60 % CRP. In the second experiment, CRP inclusion had only a small impact on feed intake, weight gain and feed conversion ratio (p>0.05) as well as on the length of the small intestine and the Longissimus dorsi muscle area. The missing correlation of daily weight gain and feed-to-gain ratio up to a CRP inclusion of 40 % indicates that negative effects of CRP on pig growth can be avoided by respecting upper feeding limits. Hence, a combined use of CRP and fAA can reduce feeding costs for small-scale pig farmers in countries where this crop-by product is available in large amounts.

Evaluation of two soil carbon models using two Kenyan long term experimental datasets

RothC and Century are two of the most widely used soil organic matter (SOM) models. However there are few examples of specific parameterisation of these models for environmental conditions in East Africa. The aim of this study was therefore, to evaluate the ability of RothC and the Century to estimate changes in soil organic carbon (SOC) resulting from varying land use/management practices for the climate and soil conditions found in Kenya. The study used climate, soils and crop data from a long term experiment (1976-2001) carried out at The Kabete site at The Kenya National Agricultural Research Laboratories (NARL, located in a semi-humid region) and data from a 13 year experiment carried out in Machang'a (Embu District, located in a semi-arid region). The NARL experiment included various fertiliser (0, 60 and 120 kg of N and P2O5 ha(-1)), farmyard manure (FYM - 5 and 10 t ha(-1)) and plant residue treatments, in a variety of combinations. The Machang'a experiment involved a fertiliser (51 kg N ha(-1)) and a FYM (0, 5 and 10 t ha(-1)) treatment with both monocropping and intercropping. At Kabete both models showed a fair to good fit to measured data, although Century simulations for treatments with high levels of FYM were better than those without. At the Machang'a site with monocrops, both models showed a fair to good fit to measured data for all treatments. However, the fit of both models (especially RothC) to measured data for intercropping treatments at Machang'a was much poorer. Further model development for intercrop systems is recommended. Both models can be useful tools in soil C Predictions, provided time series of measured soil C and crop production data are available for validating model performance against local or regional agricultural crops. (C) 2007 Elsevier B.V. All rights reserved.

Negative correlations between control performance and verbalizable knowledge: indicators for implicit learning in process control tasks?

Negative correlations between task performance in dynamic control tasks and verbalizable knowledge, as assessed by a post-task questionnaire, have been interpreted as dissociations that indicate two antagonistic modes of learning, one being “explicit”, the other “implicit”. This paper views the control tasks as finite-state automata and offers an alternative interpretation of these negative correlations. It is argued that “good controllers” observe fewer different state transitions and, consequently, can answer fewer post-task questions about system transitions than can “bad controllers”. Two experiments demonstrate the validity of the argument by showing the predicted negative relationship between control performance and the number of explored state transitions, and the predicted positive relationship between the number of explored state transitions and questionnaire scores. However, the experiments also elucidate important boundary conditions for the critical effects. We discuss the implications of these findings, and of other problems arising from the process control paradigm, for conclusions about implicit versus explicit learning processes.

The effect of supplementing maize stover with cowpea (Vigna unguiculata) haulms on the intake and growth performance of Ethiopian sheep

This study compared the effect of supplementing maize stover (MS) with cowpea (Vigna unguiculata) haulms or commercial concentrate (CC) on feed intake, nutrient digestibility, live weight gain and carcass yield of male Ethiopian Highland sheep. Two cowpea genotypes, 12688 (forage) and IT96D-774 (dual-purpose), were used. A randomised block design was applied with groups of eight sheep, blocked by weight, allocated to one of six treatments; MS ad libitum either unsupplemented or supplemented daily with 150 or 300g dry matter (DM) of either cowpea or CC. MS contained more neutral detergent fibre (NDF), acid detergent fibre (ADF) and lignin than either cowpeas or CC Crude protein (CP) content of the forage-type cowpeas was higher than either dual-purpose or CC, while MS had the lowest CP content Relative to the negative control group, cowpea at either level significantly (P < 0.01) increased both MS intake and total NDF and lignin. Supplementation significantly (P < 0.01) increased nitrogen (N) intakes relative to the negative control, with N intake for CC and dual-purpose cowpea (high level) being similar to the intakes for cowpeas at 150g. N intake with the forage-type cowpea offered at higher levels was significantly (P < 0.01) greater than the other groups. No significant differences (P > 0.01) in MS intake were identified between cowpeas at either level or CC and, although intake level of CC increased, it did not differ significantly from the negative control group. Supplementation significantly (P < 0.01) improved average daily gain, with the negative control group losing weight over the experimental period, and increased final live weight, carcass cold weight and dressing percentage. Supplementation significantly improved the apparent digestibility of DM, organic matter and NDF, with no significant difference found between cowpeas at either level. N retention was negative for sheep offered only MS, but positive with all supplements, with cowpeas improving N retention to a greater extent than CC. Interestingly, N retention/N intake was higher with cowpeas offered at the lower level suggesting an improvement in utilisation efficiency. The results indicate that the supplementation of MS with cowpea enhanced ruminant production through improvements in digestibility and intake. Further, as production improvements associated with the two levels of supplementation did not differ significantly, it is suggested that where limited quantities of cowpea are available, it may be of greater nutritional benefit to offer smaller quantities over an increased number of animal days.

Effect of type and timing of oil supplements to sows during pregnancy on the growth performance and endocrine profile of low and normal birth weight offspring

Eighty-eight multiparous sows were used to evaluate whether type and timing of oil supplementation during gestation influences the incidence of low birth weight (LBW). Sows were allocated (eight per treatment) commercial sow pellets (3 kg/d; control diet) or an experimental diet consisting of control diet plus 10 % extra energy in the form of excess pellets, palm oil, olive oil (OO), sunflower oil (SO) or fish oil; experimental diets were fed during either the first half (G1) or second half (G2) of gestation. Growth performance and endocrine profile of LBW ( < 1·09 kg) and normal birth weight (NBW; 1·46–1·64 kg) offspring were compared. Maternal dietary supplementation altered the distribution curve for piglet birth weight. SOG1 sows had a greater proportion of LBW piglets (P < 0·05), whilst it was reduced in the OOG1 group (P < 0·05). Growth rate of LBW piglets was lower compared with their NBW siblings (P < 0·05) when dietary supplementation was offered in G2 but were similar for G1. At birth, LBW offspring of supplemented animals possessed more fat compared with the control group (P < 0·05); LBW offspring of control animals exhibited a more rapid decline in fat free mass/kg prior to weaning. Plasma metabolites and insulin concentrations were influenced by maternal diet and birth weight. In conclusion, maternal dietary supplementation altered the distribution of piglet birth weights and improved the energy status of LBW piglets. Supplementation with MUFA during G1 reduced the incidence of LBW, whereas PUFA had the reverse effect.

Effect of damper and heat source on wind catcher natural ventilation performance

Experimental wind tunnel and smoke visualisation testing and CFD modelling were conducted to investigate the effect of air flow control mechanism and heat source inside rooms on wind catchers/towers performance. For this purpose, a full-scale wind catcher was connected to a test room and positioned centrally in an open boundary wind tunnel. Pressure coefficients (C-p's) around the wind catcher and air flow into the test room were established. The performance of the wind catcher depends greatly on the wind speed and direction. The incorporation of dampers and egg crate grille at ceiling level reduces and regulates the air flow rate with an average pressure loss coefficient of 0.01. The operation of the wind catcher in the presence of heat sources will potentially lower the internal temperatures in line with the external temperatures.

Age and flexible thinking: an experimental demonstration of the beneficial effects of increased cognitively stimulating activity on fluid intelligence in healthy older adults

The disuse hypothesis of cognitive aging attributes decrements in fluid intelligence in older adults to reduced cognitively stimulating activity. This study experimentally tested the hypothesis that a period of increased mentally stimulating activities thus would enhance older adults' fluid intelligence performance. Participants (N = 44, mean age 67.82) were administered pre- and post-test measures, including the fluid intelligence measure, Cattell's Culture Fair (CCF) test. Experimental participants engaged in diverse, novel, mentally stimulating activities for 10-12 weeks and were compared to a control condition. Results supported the hypothesis; the experimental group showed greater pre- to post-CCF gain than did controls (effect size d = 0.56), with a similar gain on a spatial-perceptual task (WAIS-R Blocks). Even brief periods of increased cognitive stimulation can improve older adults' problem solving and flexible thinking.

Deficient acquisition and consolidation: intertrial free recall performance in Alzheimer's disease and mild cognitive impairment

Previous research demonstrates that dementia of the Alzheimer type (DAT) is characterised by deficits of episodic memory, especially in the acquisition of new material. As well as this deficit in acquisition, some researchers have also argued for a deficit in consolidation in DAT. We examined acquisition and consolidation by measuring the intertrial gained and lost access in DAT, Mild Cognitive Impairment (MCI) and controls. We report findings from a study of clinical data based on assessment of patients using three free recall trials of a word list. We found that both DAT and MCI groups showed a deficit in acquisition and consolidation of items between trials relative to controls. Moreover, the DAT group was significantly impaired relative to the MCI group for both acquisition and consolidation. Correlations within each group showed that there were strong relationships between intertrial measures and standard measures of memory function. Importantly in no group was there a significant correlation between our measures of acquisition and consolidation: we argue that these measures reflect different underlying processes, and the failure to consolidate in DAT and MCI is not related to the deficit in acquisition. Finally, we showed strong correlations between our measure and dementia severity, suggesting that acquisition and consolidation both get worse as the dementia progresses.

A little learning is a dangerous thing: an experimental demonstration of ignorance-driven inference

Studies of ignorance-driven decision making have been employed to analyse when ignorance should prove advantageous on theoretical grounds or else they have been employed to examine whether human behaviour is consistent with an ignorance-driven inference strategy (e. g., the recognition heuristic). In the current study we examine whether-under conditions where such inferences might be expected-the advantages that theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgements, participants reliably use recognition as a basis for their judgements. Their wealth judgements under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all of the names (a "less-is-more effect"). These results are consistent across a number of variations: the number of options given to participants and the nature of the wealth judgement. A basic model of recognition-based inference predicts these effects.

A novel two pass hexagonal search algorithm for motion estimation

This paper presents a novel two-pass algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS). compensation. for block base motion On the basis of research from previous algorithms, especially an on-the-edge motion estimation algorithm called hexagonal search (HEXBS), we propose the LHMEA and the Two-Pass Algorithm (TPA). We introduce hashtable into video compression. In this paper we employ LHMEA for the first-pass search in all the Macroblocks (MB) in the picture. Motion Vectors (MV) are then generated from the first-pass and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of MBs. The evaluation of the algorithm considers the three important metrics being time, compression rate and PSNR. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms. Experimental results show that the proposed algorithm can offer the same compression rate as the Full Search. LHMEA with TPA has significant improvement on HEXBS and shows a direction for improving other fast motion estimation algorithms, for example Diamond Search.

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design

The note proposes an efficient nonlinear identification algorithm by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximized model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious model with excellent generalization performance. The D-optimality design criterion further enhances the model efficiency and robustness. An added advantage is that the user only needs to specify a weighting for the D-optimality cost in the combined model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

On improving the performance in robust controllers for robot manipulators with parametric disturbances

This paper presents a new strategy for controlling rigid-robot manipulators in the presence of parametric uncertainties or un-modelled dynamics. The strategy combines an adaptation law with a well known robust controller proposed by Spong, which is derived using Lyapunov's direct method. Although the tracking problem of manipulators has been successfully solved with different strategies, there are some conditions under which their efficiency is limited. Specifically, their performance decreases when unknown loading masses or model disturbances are introduced. The aim of this work is to show that the proposed strategy performs better than existing algorithms, as verified with real-time experimental results with a Puma-560 robot. (c) 2006 Elsevier Ltd. All rights reserved.

Linear algorithm and hexagonal search based two-pass algorithm for motion estimation

This paper presents a novel two-pass algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for block base motion compensation. On the basis of research from previous algorithms, especially an on-the-edge motion estimation algorithm called hexagonal search (HEXBS), we propose the LHMEA and the Two-Pass Algorithm (TPA). We introduced hashtable into video compression. In this paper we employ LHMEA for the first-pass search in all the Macroblocks (MB) in the picture. Motion Vectors (MV) are then generated from the first-pass and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of MBs. The evaluation of the algorithm considers the three important metrics being time, compression rate and PSNR. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms, Experimental results show that the proposed algorithm can offer the same compression rate as the Full Search. LHMEA with TPA has significant improvement on HEXBS and shows a direction for improving other fast motion estimation algorithms, for example Diamond Search.