Adaptive input shaping for single-link flexible manipulators using an algebraic identification

This work proposes an adaptive control scheme applied to single link-flexible manipulators, which combines a feedback controller of the joint angle with an adaptive input shaper updated by an algebraic non-asymptotic identification. The feedback controller is designed to guarantee trajectory tracking of the joint angle, simplifying thus the input shaper, which can be designed for the arm dynamics only. The input shaper is updated by an algebraic identification of the natural frequency corresponding to the first vibration mode of the arm. In addition, the influence of the assumptions adopted to derive the algebraic identification on the performance of the estimation is studied. Finally, the proposed adaptive control strategy is implemented in practice.     

Current concepts: tissue engineering and regenerative medicine applications in the ankle joint

Tissue engineering and regenerative medicine (TERM) has caused a revolution in present and future trends of medicine and surgery. In different tissues, advanced TERM approaches bring new therapeutic possibilities in general population as well as in young patients and high-level athletes, improving restoration of biological functions and rehabilitation. The mainstream components required to obtain a functional regeneration of tissues may include biodegradable scaffolds, drugs or growth factors and different cell types (either autologous or heterologous) that can be cultured in bioreactor systems (in vitro) prior to implantation into the patient. Particularly in the ankle, which is subject to many different injuries (e.g. acute, chronic, traumatic and degenerative), there is still no definitive and feasible answer to ‘conventional’ methods. This review aims to provide current concepts of TERM applications to ankle injuries under preclinical and/or clinical research applied to skin, tendon, bone and cartilage problems. A particular attention has been given to biomaterial design and scaffold processing with potential use in osteochondral ankle lesions.     

Analytical Tools Used to Distinguish Chemical Profiles of Plants Widely Consumed as Infusions and Dietary Supplements: Artichoke,Milk Thistle,and Borututu

Artichoke, borututu, and milk thistle are three medicinal plants widely consumed as infusions or included in dietary supplements (e.g., pills and syrups). Despite the high consumption of these plants, studies on their nutritional value and primary metabolites are scarce, with their composition in secondary metabolites such as phenolic compounds being only reported. Therefore, their nutritional value was assessed, and analytical tools (liquid and gas chromatography coupled to different detectors) were used to distinguish their chemical profiles according to their hydrophilic (sugars and organic acids) and lipophilic (fatty acids and tocopherols) components. Chromatographic techniques are important analytical tools used in the identification and quantification of several molecules, also being a standard requirement to distinguish different profiles. Borututu gave the highest energetic value with the highest content of carbohydrates and fat, sucrose and total sugars, shikimic and citric acids, and α-, β-, δ-, and total tocopherols. Artichoke had the highest ash and protein contents, oxalic acid, SFA (mainly palmitic acid), and γ-tocopherol, and also the best n-6/n-3 ratio. Milk thistle showed the highest levels of fructose and glucose, quinic acid and total organic acids, and PUFA, mainly linoleic acid, and the best PUFA/SFA ratio. The hydrophilic compounds identified in the studied plants, mostly sugars, are responsible for the energy contribution of their widely consumed infusions. Otherwise, the bioactivity of lipophilic compounds, namely, unsaturated fatty acids and tocopherols, is lost in those preparations but can be recovered in dietary supplements based on the plants. As far as we know, this is the first report on the detailed composition of the three plants regarding their nutritional features.     

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from ?0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.     

Modelling group processes and effort estimation in project management using the Choquet integral: An MCDM approach

We investigate the group processes involved in effort estimation in the context of project management. The groups considered are formed by “experts” (people with specific technical competence) and “non-experts” (people with less specific technical competence, usually experts in related fields), because the typically complementary bias of the two classes contribute to a more balanced estimate. In this paper we exploit further the synergies between experts and non-experts in an MCDM framework, aggregating the individual estimates by means of non-additive Choquet integration, and representing the complementary bias by the multiagent interaction structure underlying the capacity. We present some examples and computer simulations whose aggregation results outperform those of the classical weighted mean (additive case), showing lower MMRE (mean magnitude of the relative error between the central estimate and the actual value) and higher HitRate (at which the interval estimate contains the actual value).     

Characterizing landscape changes in central Rondonia using Landsat TM imagery

An analysis of landscape changes in a region of pioneer settlements in central Rondonia, western Brazilian Amazon, was derived from Landsat TM data. Total deforested area increased from 206 x 103 ha in 1977, to 565 x 103 ha in 1985 and to 1210 x 103 ha, or 35.5% of the region, in 1995. Eighty-one per cent of the total 1995 deforestation had occurred in regions within 12.5km from areas of pioneer colonization deforested by 1977. Deforested area exceeded 79% in regions within 12.5km from the region's first road.     

Combination of Reaction and Separation in Heterogeneous Catalytic Hydrogenation of Ethylformate

Continuous hydrogenation reaction of ethyl benzoylformate was studied over a (–)‐cinchonidine (CD)‐modified Pt/Al₂O₃ catalyst. The catalyst showed a good stability, and high enantioselectivity was achieved in the fixed‐bed reactor. Chromatographic separation of (R)‐ and (S)‐ethyl mandelate originating from a post‐continuous hydrogenation reaction of ethyl benzoylformate over the (–)‐CD‐modified Pt/Al₂O₃ catalyst was investigated in the same reaction mixture. A commercial column filled with a chiral selector resin was chosen as a perspective preparative‐scale adsorbent. Since adsorption equilibrium isotherms were linear within the entire investigated range of concentrations, they were determined by pulse experiments for the isomers present in a post‐reaction mixture. Breakthrough curves were measured and described successfully by the dispersive plug‐flow model with linear driving force approximation.     

FeO0.7F1.3/C Nanocomposite as a High‐Capacity Cathode Material for Sodium‐Ion Batteries

Searching high capacity cathode materials is one of the most important fields of the research and development of sodium‐ion batteries (SIBs). Here, we report a FeO_0.7F_1.3/C nanocomposite synthesized via a solution process as a new cathode material for SIBs. This material exhibits a high initial discharge capacity of 496 mAh g^?1 in a sodium cell at 50 °C. From the 3^rd to 50^th cycle, the capacity fading is only 0.14% per cycle (from 388 mAh g^?1 at 3^rd the cycle to 360 mAh g^?1 at the 50^th cycle), demonstrating superior cyclability. A high energy density of 650 Wh kg^?1 is obtained at the material level. The reaction mechanism studies of FeO_0.7F_1.3/C with sodium show a hybridized mechanism of both intercalation and conversion reaction.     

Improvement of mead fermentation by honey‐must supplementation

Through honey's fermentation, diverse beverages can be obtained, among which is mead, an alcoholic drink with 8 to 18% of ethanol (v/v). Since honey is a matrix with a low nutrient concentration and other unfavourable growth conditions, several problems are usually encountered, namely delayed or arrested fermentations, unsatisfactory quality parameters and lack of uniformity of the final product, as well as unpleasant sensory properties. In this context, the aim of this work was to optimize mead production through honey‐must supplementation with (a) salts, (b) vitamins or (c) salts + vitamins. The effects of the honey‐must formulation on the fermentation kinetics, growth profile and physicochemical characteristics of final meads were evaluated. The results showed minor differences in the fermentation profile and time between fermentations with the different formulations. The growth profile was influenced more by the yeast strain than by the supplements added to the honey‐must. In general, the honey‐must composition did not influence meads’ final characteristics, except regarding the SO₂ concentration of the meads produced using the strain QA23. In summary, the addition of salts and/or vitamins to honey‐must had no positive effects on the fermentation, growth profile or characteristics of the final products. Copyright © 2015 The Institute of Brewing & Distilling