Application of ipil- ipil leaf meal (IILM) as feed Ingredient for Monosex tilapia fry (oreochronis niioticus) : In terms of growth and economics

The Ipil-ipil (Leucaena leucocephal) leaf analyzed for crude protein (CP), fat, crude fibre (CF), ash content, moisture content and nitrogen free extract (NFE). The CP 23± 0.12 % , fat 8 ± 0.11 %, CF 18 ± 0.15 % , ash 10 ± 0.13 %, moisture 14. ± .16% and NFE 29.± 1.10 % were recorded. A twenty one days experiment was conduced to assess the response of juvenile monosex tilapia with different iso-nitrogenous formulated diets for find out the feasibility study of using ipil-ipil leaf meals as feed ingredient for juvenile tilapia. Three experimental diets were formulated by using fish meal, soybean meal, rice bran and ipil ipil leaf meal. One control diet was formulated by using fish meal, soybean meal and rice bran. Considering the high demand, limited availability of fish meal and soybean meal, ipil ipil leaf meal was incorporated in juvenile tilapia feed. Among plant protein ingredients ipil ipil leaf meal was considered as the most nutritive plant protein source after soybean meal. However, high concentration of toxic element limited the incorporation level of ipil ipil leaf meal in fish feed. Use of 15 % ipil ipil leaf meal in fish feed was more significant from the view of growth performance and economics. The higher Absolute Growth was 1119.26 gm, higher Specific Growth Rate was 6.52% /day higher Feed Conversion Efficiency was 41.23% , higher Protein Efficiency Ratio was 1.178 and higher Average Daily Growth rate was 14.00% recorded in diet-4 ( which contained 15% IILM). The lower Feed Conversion Ratio 2.42 and lower cost for per unit production 34.65 taka/kg were recorded in diet-4. The higher cost for per unit fish production 45.6 tk./kg was recorded for diet-1 where no ipil ipil leaf meal.. The results suggest that tree legumes Ipil-ipil (Leucaena leucocephal) leaf has potential and excellent source of feed ingredients as protein supplements for juvenile monosex

Postantifungal Effect of Micafungin against the Species Complexes of Candida albicans and Candida parapsilosis

Micafungin is an effective antifungal agent useful for the therapy of invasive candidiasis. Candida albicans is the most common cause of invasive candidiasis; however, infections due to non-C. albicans species, such as Candida parapsilosis, are rising. Killing and postantifungal effects (PAFE) are important factors in both dose interval choice and infection outcome. The aim of this study was to determinate the micafungin PAFE against 7 C. albicans strains, 5 Candida dubliniensis, 2 Candida Africana, 3 C. parapsilosis, 2 Candida metapsilosis and 2 Candida orthopsilosis. For PAFE studies, cells were exposed to micafungin for 1 h at concentrations ranging from 0.12 to 8 mu g/ml. Time-kill experiments (TK) were conducted at the same concentrations. Samples were removed at each time point (0-48 h) and viable counts determined. Micafungin (2 mu g/ml) was fungicidal (>= 3 log(10) reduction) in TK against 5 out of 14 (36%) strains of C. albicans complex. In PAFE experiments, fungicidal endpoint was achieved against 2 out of 14 strains (14%). In TK against C. parapsilosis, 8 mu g/ml of micafungin turned out to be fungicidal against 4 out 7 (57%) strains. Conversely, fungicidal endpoint was not achieved in PAFE studies. PAFE results for C. albicans complex (41.83 +/- 2.18 h) differed from C. parapsilosis complex (8.07 +/- 4.2 h) at the highest tested concentration of micafungin. In conclusion, micafungin showed significant differences in PAFE against C. albicans and C. parapsilosis complexes, being PAFE for the C. albicans complex longer than for the C. parapsilosis complex.

On-line learning of mutually orthogonal subspaces for face recognition by image sets.

We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by subspace-to-subspace matching. In this paper, 1) a new discriminative method that maximises orthogonality between subspaces is proposed. The method improves the discrimination power of the subspace angle based face recognition method by maximizing the angles between different classes. 2) We propose a method for on-line updating the discriminative subspaces as a mechanism for continuously improving recognition accuracy. 3) A further enhancement called locally orthogonal subspace method is presented to maximise the orthogonality between competing classes. Experiments using 700 face image sets have shown that the proposed method outperforms relevant prior art and effectively boosts its accuracy by online learning. It is shown that the method for online learning delivers the same solution as the batch computation at far lower computational cost and the locally orthogonal method exhibits improved accuracy. We also demonstrate the merit of the proposed face recognition method on portal scenarios of multiple biometric grand challenge.