Effects of weekly feeding frequency and previous ration restriction on the compensatory growth and body composition of Nile tilapia fingerlings

[EN] The effect of different weekly feeding frequencies on Nile tilapia fingerlings of 2.02 g, was determined during 12 weeks. This was done by feeding the fish 7 days/week, 6 days/week or 5 days/week. After this restriction feeding period, all fish were fed as the control group (7 days/week) during 26 days to study the capability of the fish to compensate the growth during this re-feeding period. At the end of the feeding restriction period, there were significant differences in weights among the different treatments, although the significance was detected only at 7 days/week level, which presented the highest final body weight compared with the other 2 treatments. The daily feed intake and the feed conversion and protein efficiency ratios did not present significant differences. Crude protein efficiency (CPE) and gross energy efficiency (GEE) were affected by the feeding frequency, presenting high values in fish fed 7 days/week. Growth results obtained during this re-feeding period indicate that weight gain (WG) and specific growth rate (SGR) presented a linear increase from 7 to 5 days/week, i.e. with increasing feed deprivation period the fish could compensate the growth effectively, trying to reach to the weight as those of the control group.El Sayed Aly Hassan, T.; Martínez Llorens, S.; Moñino López, AV.; Jover Cerdá, M.; Tomás Vidal, A. (2016). Effects of weekly feeding frequency and previous ration restriction on the compensatory growth and body composition of Nile tilapia fingerlings. Egyptian Journal of Aquatic Research. 42:357-363. doi:10.1016/j.ejar.2016.06.004S3573634

The Role of the Novel Exopolyphosphatase MT0516 in Mycobacterium tuberculosis Drug Tolerance and Persistence

Inorganic polyphosphate (poly P) has been postulated to play a regulatory role in the transition to bacterial persistence. In bacteria, poly P balance in the cell is maintained by the hydrolysis activity of the exopolyphosphatase PPX. However, the Mycobacterium tuberculosis PPX has not been characterized previously. Here we show that recombinant MT0516 hydrolyzes poly P, and an MT0516-deficient M. tuberculosis mutant exhibits elevated intracellular levels of poly P and increased expression of the genes mprB, sigE, and rel relative to the isogenic wild-type strain, indicating poly P-mediated signaling. Deficiency of MT0516 resulted in decelerated growth during logarithmic-phase in axenic cultures, and tolerance to the cell wall-active drug isoniazid. The MT0516-deficient mutant showed a significant survival defect in activated human macrophages and reduced persistence in the lungs of guinea pigs. We conclude that exopolyphosphatase is required for long-term survival of M. tuberculosis in necrotic lung lesions

JPN Guidelines for the management of acute pancreatitis: severity assessment of acute pancreatitis

This article addresses the criteria for severity assessment and the severity scoring system of the Ministry of Health and Welfare of Japan; now the Japanese Ministry of Health, Labour, and Welfare (the JPN score). It also presents data comparing the JPN score with the Acute Physiology and Chronic Health Evaluation (APACHE) II score and the Ranson score, which are the major measuring scales used in the United States and Europe. The goal of investigating these scoring systems is the achievement of earlier diagnosis and more appropriate and successful treatment of severe or moderate acute pancreatitis, which has a high mortality rate. This article makes the following recommendations in terms of assessing the severity of acute pancreatitis

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Bayesian Optimization Under Uncertainty for Chance Constrained Problems

International audienceChance constraint is an important tool for modeling the reliability on decision making in thepresence of uncertainties. Indeed, the chance constraint enforces that the constraint is satisfiedwith probability1−α(0< α <1) at least. In addition, we consider that the objective func-tion is affected by uncertainties. This problem is challenging since modeling a complex systemunder uncertainty can be expensive and for most real-world stochastic optimization will not becomputationally viable.In this talk, we propose a Bayesian methodology to efficiently solve such class of problems.The central idea is to use Gaussian Process (GP) models [1] together with appropriate acquisi-tion functions to guide the search for an optimal solution. We first show that by specifying aGP prior to the objective function, the loss function becomes tractable [2]. Similarly, using GPmodels for the constraints, the probability satisfaction can be efficiently approximated. Sub-sequently, we introduce new acquisition functions to iteratively select the points to query theexpensive objective and constraint functions. Finally, we present numerical examples to validateour approach compared to benchmark results

Estimation of the Pumping Pressure from Concrete Composition Based on the Identified Tribological Parameters

A new method is proposed to estimate pumping pressure based on concrete composition without experimental measurements. Previous studies show that the pumping pressure depends on the interface friction between concrete and the wall of the pumping pipes. This friction is determined by the thickness and the rheology of the boundary layer formed at the interface. The latter is mainly formed by water, cement, and fine sand particles which come from concrete. Hence, interface parameters, which are the viscous constant and the interface yield stress, are directly related to concrete composition. In this work, at the first time the interface yield stress model is suggested and validated thanks to an experimental database also carried out in this study with a precision of around 13%. Then, the pressure estimation method is proposed using the two models to calculate the interface parameters. The validation of the method is carried out basing on the comparison with real measurements on the building site. This method enables the calculation of the pumping pressure with a precision of around 15%

Coupling constraints in Bayesian optimization with uncertainties

International audienc

Sampling Criteria for Constrained Bayesian Optimization under Uncertainty

International audienceWe consider the problem of chance constrained optimization where the objective and the constraint functions are affected by uncertainties and are computationally costly. Bayesian optimization is an appropriate family of methods to address such problems. We first propose a two-step acquisition criterion defined in the joint space of optimization variables and uncertain parameters. The objective and the constraints are aggregated through a feasible improvement measure and the two steps consist in the optimization of the expectation and the one-step-ahead variance of this criterion. To ease the computational burden, an analytical approximation to the one-step-ahead variance is proposed. Additionally, we also account for the possible correlation between the constraints. This is done by considering a vector-valued "input as output" joined Gaussian process which improves the constraints modeling accuracy and consequently the optimization procedure. The correlations between the constraints are further exploited by allowing each constraint to be evaluated for different uncertain parameters and by optimally selecting a subset of constraints to be evaluated at each iteration, thus avoiding unnecessary computations. Numerical tests confirm the applicability and potential gains brought by these methods, such a faster convergence speed and better scaling with respect to the number of constraints if compared to alternative optimization methods