Bench Test of a Hydraulic Biofluid Based on Refined Pomace Oil

This paper aims at investigating the possibility of replacing conventional hydraulic fluids with refined olive pomace oil added with a common food grade antioxidant, as hydraulic fluid for agricultural machinery. The fluid efficiency test is carried out using an experimental test rig based on a hydraulic system designed to apply severe work cycles (pressure values up to 40 MPa; temperatures up to 100 °C) to small oil volumes with the aim of strongly accelerating the ageing of the tested fluid. The fluid, added with 2 g kg⁻¹ of antioxidant, apparently does not undergo any changes in chemical-physical properties and maintains stable the technical performance of the test equipment during 530 h work cycle. This research has four different goals: i) to contribute to the circular economy, by using olive oil byproducts in agricultural environment; ii) to contribute to the reduction of environmental contamination by substituting petroleum products with natural biodegradable ones; iii) to contribute to avoid the presence of mineral products (such as saturated hydrocarbons, which could accumulate in human organs, and aromatic hydrocarbons, which are potentially genotoxic), as a residue in food products and in vegetable oils. iv) to identify alternative market possibilities for such a by-product. Practical applications : The results of the study seem to indicate the possibility of using the olive pomace oil as hydraulic fluid, for example, in agricultural machinery, opening new market perspectives which would increase its added value.     

A market-driven algorithm for the assessment of promising bio-based chemicals

Actors willing to participate in biomass-based value chains need to screen through a vast number of product options to identify the most promising ones. This is challenging as (a) processes for biomass-based chemicals/materials are still in development stage, thus do not perform well in techno-economic evaluations, (b) factors as which and how many links of the value chain should be uptaken, are not fully addressed by techno-economic analysis. Inspired by the Five Forces framework for industry analysis, this work presents an algorithm-like approach for assessing the attractiveness of biomass-based products. The algorithm relies on market data to classify the different sources as posing a low, medium, or high threat to the profit of a company that is considering production of a certain chemical/material. The approach is exemplified by analyzing the attractiveness of the biomass-lactic acid-polylactic acid route in the context of defining pathways for development of a biomass-based industry in Uruguay.     

Effects of altering the ratio of dietary n-6 to n-3 fatty acids on spontaneous luteolysis in lactating dairy cows

Objectives were to evaluate the effects of altering the dietary ratio of omega-6 (n-6) to omega-3 (n-3) fatty acids on the profile of fatty acids and expression of genes related to the prostaglandin biosynthesis on endometrial tissue, uterine secretion of PGF_2α, and timing of spontaneous luteolysis in dairy cows. Multiparous lactating Holstein cows (n = 45) were blocked based on milk yield and, within each block, assigned randomly to 1 of 3 dietary treatments at 14 d postpartum for 90 d. Diets were supplemented with a mixture of Ca salts of fish, safflower, and palm oils to create 3 different ratios of n-6 to n-3 fatty acids, namely R4, R5, and R6, which resulted in 3.9, 4.9, and 5.9 parts of n-6 to 1 part of n-3 fatty acids, respectively. Blood was sampled every 2 h from d 16 to 23 of the estrous cycle and assayed for concentrations of progesterone and the PGF_2α metabolite 13,14-dihydro-15-keto-PGF_2α (PGFM). In a subsequent estrous cycle, endometrial tissue was collected for biopsy on d 8 and endometrial fatty acids profile and gene expression were quantified. The proportion of arachidonic acid of the endometrial fatty acids increased as the dietary ratio n-6 to n-3 fatty acids increased (R4 = 9.05, R5 = 11.64, and R6 = 13.41%). On the other hand, proportions of eicosapentaenoic (R4 = 2.85, R5 = 2.14, and R6 = 2.02%) and docosahexaenoic (R4 = 3.30, R5 = 1.57, and R6 = 1.08%) decreased as the ratio of n-6 to n-3 fatty acids in the diet increased. Increasing the ratio of dietary n-6 to n-3 fatty acids increased mRNA expression of estrogen receptor 1, oxytocin receptor, cyclooxygenase 2, prostaglandin E and F synthases, and steroidogenic acute regulatory protein in endometrium, but decreased expression of peroxisome proliferator-activated receptor gamma and insulin-like growth factor-1. The changes in endometrium gene expression caused by dietary treatments were associated with changes in the ratio of n-6 to n-3 fatty acids in the endometrium. As the ratio increased from R4 to R6, the number of PGFM pulses (R4 = 5.6, R5 = 4.3, and R6 = 3.8 ± 0.6 pulses; least squares means ± standard error of the means) decreased, but the amplitude of the greatest PGFM pulse increased (R4 = 226, R5 = 267, and R6 = 369 ± 38 pg/mL). Luteolysis by d 23 of the estrous cycle was observed in 79.6% of the cows (R4 = 11/14; R5 = 13/15; and R6 = 11/15) and day of spontaneous luteolysis did not differ among treatments (R4 = 20.8; R5 = 21.1; and R6 = 21.0 ± 0.4). Three pulses of PGFM was the best predictor of luteolysis in dairy cows. Collectively, supplying the same quantity of fatty acids in the diet of lactating dairy cows, but altering the ratio of n-6 to n-3 fatty acids, influenced the endometrial fatty acids profile and gene expression and altered the pattern of prostaglandin synthesis; however, the changes were not sufficient to alter the length of the estrous cycle.     

Using hot-vapor bypass for pressure control in distillation columns

Distillation column control is widely explored in literature due to its complexity and importance in chemical and petrochemical industries.In this process,pressure represents one of the most important variables to be controlled.However,there are few studies about how pressure affects the dynamic behavior of distillation columns and most research on distillation column control involve direct manipulation of cooling fluid through the condenser.Nevertheless,such an approach demands constant changes in cooling fluid flowrates that are commonly by the order of tons per hour,which can be difficult to work or even unfeasible in a real plant.Furthermore,this strategy is usually avoided,as it can cause fouling and corrosion acceleration.The hot-vapor bypass strategy fits well as a solution for these issues,eliminating the need to dynamically manipulate cooling fluid flowrates in the condensation unit.This work presents the modeling and simulation of a conventional distillation column for the separation of water and ethanol,in which a comparative study between a conventional pressure control and a control using hot-vapor bypass was performed.The main results were obtained through dynamic simulations which considered various disturbances in the feed stream,and demonstrated superior performance by the hot-vapor bypass system over the usual scheme proposed in literature,while evaluating the Integral Absolute Error (IAE) norm as the control performance index.     

A cross-domain framework for designing healthcare mobile applications mining social networks to generate recommendations of training and nutrition planning

Nowadays, people are practicing physical exercise in order to maintain good health conditions. Such physical workouts are required by a plan, which should be designed and supervised by sport specialists and medical assistants. Thus, the exercise sessions shall start with consultation of a coach, doctor and dietician; however, many times this scenario is not presented. In typical activities such as running, cycling and fitness, people use health mobile apps with their smartphones, which offer support for these activities. Nevertheless, the functionality and operation of these applications are isolated, because many and long questionnaires are performed. Additionally, the physical and health state of a user is not considered. These issues would be taken into account for determining recommendations about the time for doing exercise and the kind of activity for each person. In this work, a social semantic mobile framework to generate recommendations where a mobile application allows sensing the physical performance, taking into consideration medical criteria with smartphones is proposed. The approach includes a semantic cross-information that comes from social network and official data as well as sport activities and medical knowledge. This knowledge is translated into application ontologies related directly to health, nutrition and training domains. The methodology also covers physical fitness tests and a monitoring tool for evaluating the nutrition plan and the correct execution of the training. As case study, the mobile application offers to evaluate the physical and health conditions of a runner, automatically generate a nutrition plan and training, monitor plans and recomputed them if users make changes in their routines. The data provided from the social network are used as feedback in the application, in order to make the training and nutrition plans more flexible by applying spatio-temporal analysis based on machine learning. Finally, the generated training and nutrition plans were validated by specialists, they have demonstrated 82% of effectiveness rate in exercise training routines and 86% in nutrition plans. In addition, the results were compared with isolated approaches and manual recommendations made by specialists, the obtained overall performance was 81%.