Simulated and Applied Precision Feeding System of High and Low Forage Diets with Different Fat Sources and Sequences of Dietary Fat Concentration in In-Vitro and In-Vivo Studies

Controlling dry matter intake (DMI) is one strategy to meet the animal’s requirements while reducing feed costs and increasing feed efficiency. Controlling intake through precision-feeding provides a more nutrient-dense diet, allowing an increase in energy and nutrient utilization efficiency while decreasing nutrient loss. The literature about precision feeding has provided information regarding optimal N intake and different dietary fiber proportions, but more information needs to be addressed. This is one of the first attempts to further our knowledge through the use of fat inclusion. In the present dissertation, a total of 4 in-vitro and in-vivo experiments were conducted. Simulated and applied precision feeding with different forage to concentrate (F:C) ratios and fat sources inclusion were used to determine the effect on Holstein and Jersey dairy heifer’s digestibility and fermentation.An introduction to the importance of investigating strategies to fat supplementation in precision feeding for dairy heifers is presented in Chapter 1. Background information and justification of the current dissertation is presented in the systematic Literature Review in Chapter 2. The objective of the first experiment presented in Chapter 3 was to screen the effects of including different types of fat to different F:C ratio on digestibility and in-vitro gas production (GP). Treatments included either low forage (LF; 35%) or high forage (HF; 70%) with 2 dietary fat concentrations (6 or 9% DM) screening for 6 different fat sources plus control (CON). The CON diet had a basal fat concentration in the diet [3% fat (0% fat inclusion); and fat sources were added to attain 6% or 9% fat and consisted of Coconut oil, CO; Poultry fat, PF; Palm oil, PO; Palm kernel oil, PKO; Ca Salts, MEG; Soybean oil, SOY]. Modules were randomly assigned to treatments in a 2×2×7 factorial design and incubated for four 24 h runs. The CO-fed module had the highest DM apparent digestibility (AD), followed by SOY and PF. The true DM digestibility (IVTDMD) and OM AD were the highest in CO than the other types of fat. The AD for DM, OM, NDF, ADF, and IVTDMD was higher in LF. Total VFA was lower in modules fed different fat types than the CON and acetate, while propionate was the lowest for the CON, which increased the A:P ratio. These results suggested that LF diets with high fat concentration can be used under a precision feeding system, and different types of fat sources may improve DM and fiber digestibility. The second experiment\u27s objective presented in Chapter 4 was to evaluate the effects of fermentation and digestion of including different fat sources when high concentrate diets with high-fat inclusion are used to simulate precision feeding in continuous culture. Four treatments were randomly assigned to 8 continuous cultures in a randomized complete block design and ran for 2 periods of 10 d. Diets included high concentrate (HC; 65%) with high fat inclusion starting with a basal level of fat as CON [3% fat (0% fat inclusion); 9% fat (6% PF; CO; SO inclusion)]. The DM, OM, NDF, ADF, and hemicellulose digestibility coefficients (dC) were higher for PF-fed fermenter, and CO followed by SO and then CON. Total VFA was higher for CON, and there was a reduction in acetate and propionate with different fat treatments. These results suggest that simulated precision feeding with HC and high fat supplementation can improve digestibility. Chapter 5 presents the third experiment to determine the effects of simulated precision feeding of different PF levels at different F:C ratios on digestibility and fermentation in continuous culture. Treatments included 2 forage combinations, low (LF; 35% forage), and high (HF; 70% forage) and 4 levels of PF starting with a basal level of fat in the diet [3% fat (0% PF); 5% fat (2% PF); 7% fat (4% PF); and 9% fat (6% PF)]. Treatments were randomly assigned to 8 fermenters in a 2×4 factorial design and ran for 4, 10 d periods. The LF-fed fermenter had higher DM, OM, N, starch, and NFC dC than HF. Nutrients digestibility increased linearly with PF inclusion. Bacterial efficiency was decreased with PF inclusion. Total VFA was higher for LF, and there was a reduction in acetate with LF. The PF inclusion had a linear increase in total VFA, a linear reduction in acetate, and a linear increase in propionate. The A:P ratio decreased linearly in both LF and HF as PF increased. These results suggest that increasing PF in precision fed LF or HF can alter rumen fermentation and improve digestibility. Finally, the last experiment\u27s objective in Chapter 6 was to evaluate the effects on nutrient digestion and rumen fermentation of including different levels of PF in precision fed Holstein and Jersey dairy heifers. Four Holstein and 4 Jersey cannulated heifers were randomly assigned to 4 treatments, included a 55% forage diet with 4 increasing PF inclusion starting with a basal concentration of fat in the diet [3% fat (0% PF); 5% fat (2% PF); 7% fat (4% PF); and 9% fat (6% PF)]. Treatments were administered according to a split-plot, 4×4 Latin square design for 4 periods of 21 d. Holstein-group had a lower DM, OM, NDF, ADF, and NFC AD than Jersey-group. The inclusion of PF did not affect AD. However, starch AD increased linearly as PF increased, whereas NFC AD decreased linearly. Manure output was higher for Holstein, and the PF inclusion showed a linear decrease in manure output. Total VFA, acetate decreased linearly as PF increased. Concurrently there was a linear increase in propionate, resulting in a linear reduction in the A:P ratio. These results suggest that Jerseys utilized nutrients more efficiently than Holsteins. Dietary PF inclusion up to 6% in the rations can further reduce DMI in precision feeding programs without compromising total-tract digestibility. Overall, these studie’s results indicate that PF can be used as a replacement for corn in precision-fed Holstein and Jersey dairy heifer diets up to 6% DM. Other fat sources with different characteristics can be utilized with relative success, but further research is needed. Incorporation of supplemental fat to controlled intake strategies such as precision-feeding can reduce feed intake for optimal growth, promising impacts on costs. Furthermore, nutrient digestibility, rumen fermentation, and animal performance can be enhanced with positive effects on environmental impact

Inverse Volume-of-Fluid Meshless Method for Efficient Non-Destructive Thermographic Evaluation

A novel computational tool based in the Localized Radial-basis Function (RBF) Collocation (LRC) Meshless method coupled with a Volume-of-Fluid (VoF) scheme capable of accurately and efficiently solving transient multi-dimensional heat conduction problems in composite and heterogeneous media is formulated and implemented. While the LRC Meshless method lends its inherent advantages of spectral convergence and ease of automation, the VoF scheme allows to effectively and efficiently simulate the location, size, and shape of cavities, voids, inclusions, defects, or de-attachments in the conducting media without the need to regenerate point distributions, boundaries, or interpolation matrices. To this end, the Inverse Geometric problem of Cavity Detection can be formulated as an optimization problem that minimizes an objective function that computes the deviation of measured temperatures at accessible locations to those generated by the LRC-VoF Meshless method. The LRC-VoF Meshless algorithms will be driven by an optimization code based on the Genetic Algorithms technique which can efficiently search for the optimal set of design parameters (location size, shape, etc.) within a predefined design space. Initial guesses to the search algorithm will be provided by the classical 1D semi-infinite composite analytical solution which can predict the approximate location of the cavity. The LRC-VoF formulation is tested and validated through a series of controlled numerical experiments. This approach will allow solving the onerous computational inverse problem in a very efficient and robust manner while affording its implementation in modest computational platforms, thereby realizing the disruptive potential of the multi-dimensional high-fidelity non-destructive evaluation (NDE) method

Biomass Characterization and Insulation Optimization Studies

This study indicates how biomass materials can be effectively used as naturally sustainable alternatives to insulation materials. Barley grains and oak leaves, straw, and jute are collected, and crushed into powders/ chopped pieces. The physical characteristics are measured to characterize each powder. The biomass powder reinforced composites are manufactured in varying weight ratios. The density and thermal conductivity of composite materials are measured. The properties of composites compared to those of commercial insulation materials are found to be close to them. Furthermore, genetic algorithms (GA) can be used to achieve multi-objective optimization entailing maximizing insulation (minimizing heat transfer) and simultaneously maximizing sustainability (minimizing carbon footprint) of a designed insulation structure. The two resulting nonlinear competing objective functions will be maximized by means of evolutionary optimization techniques within a defined design space. The multi-objective optimization is achieved by building a Pareto front and determining the points of best compromise between the two objectives

Determinants and Consequences of Knowledge Sharing Among Employees in a UAE National Oil and Gas Company

This dissertation investigates the determinants and consequences of knowledge sharing among members of technical teams at a UAE national oil company. The research aims to identify some of the key factors that encourage knowledge sharing between members of the technical teams and the link between knowledge sharing and individual job performance. Drawing on earlier research, an integrated theoretical model linking the antecedents and outcomes of knowledge sharing was developed. A Partial Least Square (PLS-SEM) technique was used to analyze the data collected from 357 engineers in various divisions in the largest business unit of the organization in question. Results suggest that management support, task-interdependence, individual attitude towards knowledge sharing, self-efficacy and the perceived usefulness of the knowledge itself play an important role in encouraging employees to share knowledge. Furthermore, the study suggests that knowledge sharing influences individual job performance by enhancing their innovative and task-focused organizational behaviors. This research contributes to the current literature on knowledge sharing and has done so by empirically testing the relationship between the antecedents and outcomes of knowledge sharing within new cultural and industrial contexts. Additionally, it addresses a gap in the extant literature where the focus has traditionally been on the macro-organizational outcomes of knowledge sharing, e.g. innovation, financial performance and operational efficiency, and not on micro-organizational factors such as individual job performance

Explicit upper bound for the function of sum of divisors

we developed the result proved by A.Eviwhere he proved the following  theore