Fatty acids are very important biological substances due to their metabolic, structural and signal- ing functions. Omega-3 has different beneficial, harmful and neutral effects on adipokines. Adi- pokines have autocrine, paracrine and endocrine effects on metabolism. In the study 54 German Fawn x Hair crossbred goats were synchronized using intravaginal sponges. During the first pe- riod (mating-75 days), all animals were fed a diet supplemented with protected fat and during the second period of pregnancy (76 days-kidding), one of the groups was fed a diet supplemented with fish oil and other was fed a diet supplemented with protected fat. Serum leptin, ghrelin, adi- ponektin and omentin levels were measured by ELISA system. Distributed fed (roughage and concentrate) were sampled and dry matter, crude protein, fat, and ash were determined by AOAC (1988) analysis methods. The Acid Detergent Fiber (ADF) and Neutral Detergent Fiber (NDF) analysis were conducted using heat stable α-amylase and sodium sulphite. Fat source (fish oil or protected fat) affected feed consumption and the highest feed consumption was found in the group fed with protected oil first half of the pregnancy and with fish oil in the second half of the pregnancy and in the fish oil group during the pregnancy. It was determined that the use of fish oil during pregnancy did not affect ghrelin, leptin and omentin concentrations in serum. Adipokine levels of fish oil fed animals during any period of pregnancy were found to be high and it was also found that serum adiponectin levels in goats fed with diet containing fish oil in the first half of pregnancy and protected fat in the second half were statistically significantly high in adipokines.

Mn-Al alloys are important alloys due to their magnetic properties and have been identified as permanent magnets. This alloy possesses magnetic properties and can be manufactured at a relatively low cost. Mn-Al alloys could be an alternative to rare earth magnets and hard ferrites and have a promising future. In this study, the effects of sintering temperature, holding time and pressure on densification, average grain size and magnetic properties of the SPS-ed Mn-Al alloys were observed. However, with the different sintering parameters, the magnetic phase τ phase could be achieved. To obtain the τ phase, different annealing methods were tried, yet samples heated to 650°C and air cooled exhibited magnetic properties. This sample was selected from various sintering parameters due to its high density of 99% N6 (800°C – 300 sec – 60 MPa) and has an average grain size of 137±18.1 µm. The uniqueness of this work is that statistical approaches such as Taguchi design of experiment (DOE) and regression were used for optimization of the manufacturing process.

This paper describes the p-diagram (parameter-diagram) and its application in planning a DoE (Design of Experiments). A case study describing an actual problem from industry is presented where the planning phase started to go wrong as difficulties in selecting the right variables for the DoE were discovered. Furthermore, running these experiments became prohibitively expensive, due to the large number of such experiments that would be needed, and though the exploitation of a p-diagram it was then possible to come up with a feasible DoE.

Optimal parameters setting of injection moulding (IM) machine critically effects productivity, quality, and cost production of end products in manufacturing industries. Previously, trial and error method were the most common method for the production engineers to meet the optimal process injection moulding parameter setting. Inappropriate injection moulding machine parameter settings can lead to poor production and quality of a product. Therefore, this study was purposefully carried out to overcome those uncertainty. This paper presents a statistical technique on the optimization of injection moulding process parameters through central composite design (CCD). In this study, an understanding of the injection moulding process and consequently its optimization is carried out by CCD based on three parameters (melt temperature, packing pressure, and cooling time) which influence the shrinkage and tensile strength of rice husk (RH) reinforced low density polyethylene (LDPE) composites. Statistical results and analysis are used to provide better interpretation of the experiment. The models are form from analysis of variance (ANOVA) method and the model passed the tests for normality and independence assumptions.

The paper presents the method of simplified parametric analysis of the sensitivity of a pre-tensioned concrete beam. The presented approach is based on the DOE (design of experiments) data collection which is simulation technique allowing for identification of variables deciding about the effectiveness and costs of designed structures. Additionally, application of the hyper-surface of the construction response allows designers to the development of multi-dimensional trade-off graphs to facilitate, the assessment of the scope of changes in random state variables permitted due to the adequate criteria and selection of their values close to optimum. Design basics, procedures and results of the presented considerations of sensitivity assessment and reliability of the structure has been shown on the example of a pre-stressed concrete beam designed in accordance with the requirements and procedures of Eurocode 2.