Big Data approaches as a support for precision livestock farming techniques

With the advent of new technologies it is increasingly easier to find data of different nature from even more accurate sensors that measure the most disparate physical quantities and with different methodologies. The collection of data thus becomes progressively important and takes the form of archiving, cataloging and online and offline consultation of information. Over time, the amount of data collected can become so relevant that it contains information that cannot be easily explored manually or with basic statistical techniques. The use of Big Data therefore becomes the object of more advanced investigation techniques, such as Machine Learning and Deep Learning. In this work some applications in the world of precision zootechnics and heat stress accused by dairy cows are described. Experimental Italian and German stables were involved for the training and testing of the Random Forest algorithm, obtaining a prediction of milk production depending on the microclimatic conditions of the previous days with satisfactory accuracy. Furthermore, in order to identify an objective method for identifying production drops, compared to the Wood model, typically used as an analytical model of the lactation curve, a Robust Statistics technique was used. Its application on some sample lactations and the results obtained allow us to be confident about the use of this method in the future.

A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

A new three phase method (SDP method) for the multi-objective vehicle routing problem with simultaneous delvery and pickup (VRPSDP)

Transportation service operators are witnessing a growing demand for bi-directional movement of goods. Given this, the following thesis considers an extension to the vehicle routing problem (VRP) known as the delivery and pickup transportation problem (DPP), where delivery and pickup demands may occupy the same route. The problem is formulated here as the vehicle routing problem with simultaneous delivery and pickup (VRPSDP), which requires the concurrent service of the demands at the customer location. This formulation provides the greatest opportunity for cost savings for both the service provider and recipient. The aims of this research are to propose a new theoretical design to solve the multi-objective VRPSDP, provide software support for the suggested design and validate the method through a set of experiments. A new real-life based multi-objective VRPSDP is studied here, which requires the minimisation of the often conflicting objectives: operated vehicle fleet size, total routing distance and the maximum variation between route distances (workload variation). The former two objectives are commonly encountered in the domain and the latter is introduced here because it is essential for real-life routing problems. The VRPSDP is defined as a hard combinatorial optimisation problem, therefore an approximation method, Simultaneous Delivery and Pickup method (SDPmethod) is proposed to solve it. The SDPmethod consists of three phases. The first phase constructs a set of diverse partial solutions, where one is expected to form part of the near-optimal solution. The second phase determines assignment possibilities for each sub-problem. The third phase solves the sub-problems using a parallel genetic algorithm. The suggested genetic algorithm is improved by the introduction of a set of tools: genetic operator switching mechanism via diversity thresholds, accuracy analysis tool and a new fitness evaluation mechanism. This three phase method is proposed to address the shortcoming that exists in the domain, where an initial solution is built only then to be completely dismantled and redesigned in the optimisation phase. In addition, a new routing heuristic, RouteAlg, is proposed to solve the VRPSDP sub-problem, the travelling salesman problem with simultaneous delivery and pickup (TSPSDP). The experimental studies are conducted using the well known benchmark Salhi and Nagy (1999) test problems, where the SDPmethod and RouteAlg solutions are compared with the prominent works in the VRPSDP domain. The SDPmethod has demonstrated to be an effective method for solving the multi-objective VRPSDP and the RouteAlg for the TSPSDP.

Hybrid multi-objective optimization and hybridized self-organizing response surface method

Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.

In vitro evaluation of an alternative method to bond molar tubes

Despite the advances in bonding materials, many clinicians today still prefer to place bands on molar teeth. Molar bonding procedures need improvement to be widely accepted clinically. OBJECTIVE: The purpose of this study was to evaluate the shear bond strength when an additional adhesive layer was applied on the occlusal tooth/tube interface to provide reinforcement to molar tubes. MATERIAL AND METHODS: Sixty third molars were selected and allocated to the 3 groups: group 1 received a conventional direct bond followed by the application of an additional layer of adhesive on the occlusal tooth/tube interface, group 2 received a conventional direct bond, and group 3 received a conventional direct bond and an additional cure time of 10 s. The specimens were debonded in a universal testing machine. The results were analyzed statistically by ANOVA and Tukey's test (α=0.05). RESULTS: Group 1 had a significantly higher (p<0.05) shear bond strength compared to groups 2 and 3. No difference was detected between groups 2 and 3 (p>0.05). CONCLUSIONS: The present in vitro findings indicate that the application of an additional layer of adhesive on the tooth/tube interface increased the shear bond strength of the bonded molar tubes.

Microleakage in conservative cavities varying the preparation method and surface treatment

OBJECTIVE: To assess microleakage in conservative class V cavities prepared with aluminum-oxide air abrasion or turbine and restored with self-etching or etch-and-rinse adhesive systems. Materials and Methods: Forty premolars were randomly assigned to 4 groups (I and II: air abrasion; III and IV: turbine) and class V cavities were prepared on the buccal surfaces. Conditioning approaches were: groups I/III - 37% phosphoric acid; groups II/IV - self-priming etchant (Tyrian-SPE). Cavities were restored with One Step Plus/Filtek Z250. After finishing, specimens were thermocycled, immersed in 50% silver nitrate, and serially sectioned. Microleakage at the occlusal and cervical interfaces was measured in mm and calculated by a software. Data were subjected to ANOVA and Tukey's test (α=0.05). RESULTS: Marginal seal provided by air abrasion was similar to high-speed handpiece, except for group I. There was SIGNIFICANT difference between enamel and dentin/cementum margins for to group I and II: air abrasion. The etch-and-rinse adhesive system promoted a better marginal seal. At enamel and dentin/cementum margins, the highest microleakage values were found in cavities treated with the self-etching adhesive system. At dentin/cementum margins, high-speed handpiece preparations associated with etch-and-rinse system provided the least dye penetration. CONCLUSION: Marginal seal of cavities prepared with aluminum-oxide air abrasion was different from that of conventionally prepared cavities, and the etch-and-rinse system promoted higher marginal seal at both enamel and dentin margins.

Development and validation of a fast RP-HPLC method to determine the analogue of the thyroid hormone, 3,5,3 '-triiodothyroacetic acid (TRIAC), in polymeric nanoparticles

The objective of this work was to develop and validate a rapid Reversed-Phase High-Performance Liquid Chromatography method for the quantification of 3,5,3 '-triiodothyroacetic acid (TRIAC) in nanoparticles delivery system prepared in different polymeric matrices. Special attention was given to developing a reliable reproductive technique for the pretreatment of the samples. Chromatographic runs were performed on an Agilent 1200 Series HPLC with a RP Phenomenex (R) Gemini C18 (150 x 4, 6 mm i.d., 5 mu m) column using acetonitrile and triethylamine buffer 0.1% (TEA) (40 : 60 v/v) as a mobile phase in an isocratic elution, pH 5.6 at a flow rate of 1 ml min(-1). TRIAC was detected at a wavelength of 220 nm. The injection volume was 20 mu l and the column temperature was maintained at 35 degrees C. The validation characteristics included accuracy, precision, specificity, linearity, recovery, and robustness. The standard curve was found to have a linear relationship (r(2) - 0.9996) over the analytical range of 5-100 mu g ml(-1) . The detection and quantitation limits were 1.3 and 3.8 mu g ml(-1), respectively. The recovery and loaded TRIAC in colloidal system delivery was nearly 100% and 98%, respectively. The method was successfully applied in polycaprolactone, polyhydroxybutyrate, and polymethylmethacrylate nanoparticles.

Efficient method for obtaining Lep(ob)/Lep(ob)-derived animal models using adipose tissue transplantations

Background: Leptin-deficient mice (Lep(ob)/Lep(ob), also known as ob/ob) are of great importance for studies of obesity, diabetes and other correlated pathologies. Thus, generation of animals carrying the Lep(ob) gene mutation as well as additional genomic modifications has been used to associate genes with metabolic diseases. However, the infertility of Lep(ob)/Lep(ob) mice impairs this kind of breeding experiment. Objective: To propose a new method for production of Lep(ob)/Lep(ob) animals and Lep(ob)/Lep(ob)-derived animal models by restoring the fertility of Lep(ob)/Lep(ob) mice in a stable way through white adipose tissue transplantations. Methods: For this purpose, 1 g of peri-gonadal adipose tissue from lean donors was used in subcutaneous transplantations of Lep(ob)/Lep(ob) animals and a crossing strategy was established to generate Lep(ob)/Lep(ob)-derived mice. Results: The presented method reduced by four times the number of animals used to generate double transgenic models (from about 20 to 5 animals per double mutant produced) and minimized the number of genotyping steps (from 3 to 1 genotyping step, reducing the number of Lep gene genotyping assays from 83 to 6). Conclusion: The application of the adipose transplantation technique drastically improves both the production of Lep(ob)/Lep(ob) animals and the generation of Lep(ob)/Lep(ob)-derived animal models. International Journal of Obesity (2009) 33, 938-944; doi: 10.1038/ijo.2009.95; published online 16 June 2009

MULTIVARIATE STATISTICAL METHOD IN OPTIMIZATION OF PROTEIN EXTRACTION FROM SOYBEAN FLOUR WITH DAIRY WHEY

The aim objective of this project was to evaluate the protein extraction of soybean flour in dairy whey, by the multivariate statistical method with 2(3) experiments. Influence of three variables were considered: temperature, pH and percentage of sodium chloride against the process specific variable ( percentage of protein extraction). It was observed that, during the protein extraction against time and temperature, the treatments at 80 degrees C for 2h presented great values of total protein (5.99%). The increasing for the percentage of protein extraction was major according to the heating time. Therefore, the maximum point from the function that represents the protein extraction was analysed by factorial experiment 2(3). By the results, it was noted that all the variables were important to extraction. After the statistical analyses, was observed that the parameters as pH, temperature, and percentage of sodium chloride, did not sufficient for the extraction process, since did not possible to obtain the inflection point from mathematical function, however, by the other hand, the mathematical model was significant, as well as, predictive.

Definition of priority areas for forest conservation through the ordered weighted averaging method

The general objective of this study was to evaluate the ordered weighted averaging (OWA) method, integrated to a geographic information systems (GIS), in the definition of priority areas for forest conservation in a Brazilian river basin, aiming at to increase the regional biodiversity. We demonstrated how one could obtain a range of alternatives by applying OWA, including the one obtained by the weighted linear combination method and, also the use of the analytic hierarchy process (AHP) to structure the decision problem and to assign the importance to each criterion. The criteria considered important to this study were: proximity to forest patches; proximity among forest patches with larger core area; proximity to surface water; distance from roads: distance from urban areas; and vulnerability to erosion. OWA requires two sets of criteria weights: the weights of relative criterion importance and the order weights. Thus, Participatory Technique was used to define the criteria set and the criterion importance (based in AHP). In order to obtain the second set of weights we considered the influence of each criterion, as well as the importance of each one, on this decision-making process. The sensitivity analysis indicated coherence among the criterion importance weights, the order weights, and the solution. According to this analysis, only the proximity to surface water criterion is not important to identify priority areas for forest conservation. Finally, we can highlight that the OWA method is flexible, easy to be implemented and, mainly, it facilitates a better understanding of the alternative land-use suitability patterns. (C) 2008 Elsevier B.V. All rights reserved.

Effectiveness of the standard evaluation method for hydraulic nozzles employed in stored grain protection trials

In stored grains, smaller depositions and great variation with respect to theoretical insecticide doses are frequently found. The objective of this work was to study the effectiveness of the standard method (ISO 5682/1-1996) employed to evaluate hydraulic nozzles used in stored corn and wheat grain protection experiments. The transversal volumetric distribution and droplet spectrum of a model TJ-60 8002EVS nozzle were determined in order to calibrate a spraying system for an application rate of 5 L/t and to obtain theoretical concentrations of 10 and 0.5 mg/kg of fenitrothion and esfenvalerate, respectively. After treatment, the corn and wheat grains were processed and deposition was analyzed by gas chromatography. The type of grain did not have any influence on insecticide deposition and was dependent upon insecticide only. The insecticide deposits on the grains only reached 42.1 and 38.2% of the intended theoretical values for fenitrothion and esfenvalerate concentrations, respectively. These results demonstrate the ineffectiveness of the standard evaluation method for hydraulic nozzles employed in stored grain protection experiments.

A Validated Reverse-phase HPLC Analytical Method for the Quantification of Phenolic Compounds in Baccharis dracunculifolia

Introduction - Baccharis dracunculifolia, which has great potential for the development of new phytotherapeutic medicines, is the most important botanical source of the southeastern Brazilian propolis, known as green propolis on account of its color. Objective - To develop a reliable reverse-phase HPLC chromatographic method for the analysis of phenolic compounds in both B. dracunculifolia raw material and its hydroalcoholic extracts. Methodology - The method utilised a C(18) CLC-ODS (M) (4.6 x 250 mm) column with nonlinear gradient elution and UV detection at 280 nm. A procedure for the extraction of phenolic compounds using aqueous ethanol 90%, with the addition of veratraldehyde as the internal standard, was developed allowing the quantification of 10 compounds: caffeic acid, coumaric acid, ferulic acid, cinnamic acid, aromadendrin-4`-methyl ether, isosakuranetin, drupanin, artepillin C, baccharin and 2,2-dimethyl-6-carboxyethenyl-2H-1-benzopyran acid. Results - The developed method gave a good detection response with linearity in the range 20.83-800 mu g/mL and recovery in the range 81.25-93.20%, allowing the quantification of the analysed standards. Conclusion - The method presented good results for the following parameters: selectivity, linearity, accuracy, precision, robustness, as well as limit of detection and limit of quantitation. Therefore, this method could be considered as an analytical tool for the quality control of B. dracunculifolia raw material and its products in both cosmetic and pharmaceutical companies. Copyright (C) 2008 John Wiley & Sons, Ltd.

A hybrid planning method for transmission networks in a deregulated environment

The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.