Key factors influencing the sale of bulls in livestock auctions

This research determines which factors most influence the purchase price of bulls in livestock auctions in the State of Rio Grande do Sul, Southern Brazil. Hence, 760 beef bulls sold in eleven different auctions between August and November 2013 were analysed. The data consists of: breed, muscularity (MUSC), frame (FRAME), body condition score (BCS), scrotal circumference (SC) and body weight (BW). Other data such as the animal entry order and the purchase price of the bulls was collected during the auction. A linear generalized model was used to evaluate the interaction of each variable with the purchase price of the bulls. An ANOVA with Tukey post-hoc was used to compare the differences between the categories that influenced the purchase price of bulls and were realized in the software SPSS 20.0. All breeds presented declining pricesfrom the first to the second entry order and increasing purchase prices from the order third to forth. Bulls with large frame received higher purchase prices independent of the auction order, except for the second order of entry, in which medium and small animals were more valued. Angus bulls obtained the highest prices in relation to the breeds Brangus and Hereford. The frame and breed constituted the main phenotypic characteristics that influence in price. In addition, the order of entry of bulls in the ring influence the purchase price

Effect of surgical treatment on the cellular immune response of gastric cancer patients

Patients with gastric cancer have a variety of immunological abnormalities. In the present study the lymphocytes and their subsets were determined in the peripheral blood of patients with gastric cancer (N = 41) both before and after surgical treatment. The percent of helper/inducer CD4 T cells (43.6 ± 8.9) was not different after tumor resection (43.6 ± 8.2). The percent of the cytotoxic CD8+ T cell population decreased significantly, whether patients were treated surgically (27.2 ± 5.8%, N = 20) or not (27.3 ± 7.3%, N = 20) compared to individuals with inflammatory disease (30.9 ± 7.5%) or to healthy individuals (33.2 ± 7.6%). The CD4/CD8 ratio consequently increased in the group of cancer patients. The peripheral blood lymphocytes of gastric cancer patients showed reduced responsiveness to mitogens. The defective blastogenic response of the lymphocytes was not associated with the production of transforming growth factor beta (TGF-ß) since the patients with cancer had reduced production of TGF-ß1 (269 ± 239 pg/ml, N = 20) in comparison to the normal individuals (884 ± 175 pg/ml, N = 20). These results indicate that the immune response of gastric cancer patients was not significantly modified by surgical treatment when evaluated four weeks after surgery and that the immunosuppression observed was not due to an increase in TGF-ß1 production by peripheral leukocytes.33934

Bayesian Nonparametric Inverse Reinforcement Learning

Inverse reinforcement learning (IRL) is the task of learning the reward function of a Markov Decision Process (MDP) given the transition function and a set of observed demonstrations in the form of state-action pairs. Current IRL algorithms attempt to find a single reward function which explains the entire observation set. In practice, this leads to a computationally-costly search over a large (typically infinite) space of complex reward functions. This paper proposes the notion that if the observations can be partitioned into smaller groups, a class of much simpler reward functions can be used to explain each group. The proposed method uses a Bayesian nonparametric mixture model to automatically partition the data and find a set of simple reward functions corresponding to each partition. The simple rewards are interpreted intuitively as subgoals, which can be used to predict actions or analyze which states are important to the demonstrator. Experimental results are given for simple examples showing comparable performance to other IRL algorithms in nominal situations. Moreover, the proposed method handles cyclic tasks (where the agent begins and ends in the same state) that would break existing algorithms without modification. Finally, the new algorithm has a fundamentally different structure than previous methods, making it more computationally efficient in a real-world learning scenario where the state space is large but the demonstration set is small

A prediction algorithm for drug response in patients with mesial temporal lobe epilepsy based on clinical and genetic information

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOMesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide121FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO2013/07559-

Post-harvest quality of fresh-marketed tomatoes as a function of harvest periods

Losses on tomato business chain start at harvest, a two-months period. At the beginning of the harvest, fruits concentrate at the basal part of the plant, then in the middle, and finally at the top, and undergo changes in diameter and maturity indexes as harvest progresses. The aim of this work was to evaluate the impact of handling at three different periods: (I) 15 days, (II) 30 days, and (III) 45 days after the beginning of harvest. Tomatoes were ordinarily grown and harvested in to bamboo baskets, and transferred to plastics boxes. Fruits were classified according to ripening stage and diameter, and evaluated for mechanical damage and external defects caused by harvesting procedures. The time required for the harvest operation was measured; damage to fruits (%) and weight loss (%), caused either in the field and/or during the harvesting process, were taken into consideration and related to the final quality of fruit after storage for 21 days. The same methodology was used all through the production and harvest cycle. The highest % fruit damage occurred during period II, a longer harvest time than the other two periods. Fruits not submitted to handling showed lower weight loss than handled fruits. Fruits harvested in period II and stored for 21 days showed higher losses due to mechanical injury

A Coulomb gas approach to the anisotropic one-dimensional Kondo lattice model at arbitrary filling

We establish a mapping of a general spin-fermion system in one dimension into a classical generalized Coulomb gas. This mapping allows a renormalization group treatment of the anisotropic Kondo chain both at and away from half-filling. We find that the phase diagram contains regions of paramagnetism, partial and full ferromagnetic order. We also use the method to analyze the phases of the Ising-Kondo chain.Comment: 19 pages, 9 figure

Diversity and patterns of marine non‐native species in the archipelagos of Macaronesia

Aims The present study is the first attempt to grasp the scale and richness of marine biological invasions in Macaronesia. We pioneered a comprehensive non-native species (NNS), inventory in the region to determine their diversity patterns and native distribution origins. NNS were defined here as the result of both introductions and range expansions. We also used statistical modelling to examine relationships among NNS richness, anthropogenic activities, demographic and geographical variables across Macaronesia. Location Macaronesia. Methods A comprehensive literature search was conducted for marine NNS records in Macaronesia, registering the first record's location and year from 1884 to 2020. We used univariate and multivariate analyses to evaluate differences and similarities in community composition. By applying a Generalized Linear Model (GLM), we tested hypotheses regarding NNS richness as a function of anthropogenic activities, demographic and geographical variables. Results A total of 144 marine non-native species (NNS) were recorded for the whole of Macaronesia. The highest NNS richness was registered in the Canary Islands (76 NNS), followed by the Azores (66 NNS), Madeira (59 NNS) and finally Cabo Verde (18 NNS). Some differences amongst archipelagos were observed, such as the high number of non-native macroalgae in the Azores, fishes in the Canary Islands and tunicates in Cabo Verde. Overall, macroalgae, tunicates and bryozoans were the predominant taxonomic groups in the Macaronesian archipelagos. Madeira and Canary Islands were the archipelagos with more similarity in marine NNS, and Cabo Verde the most divergent. Finally, GLM suggested that non-native richness patterns across Macaronesia were dependent on the considered archipelago and strongly affected by (1) minimum distance to the mainland, (2) the total number of ports and marinas and (3) total marinas area (km2). Conclusions The model results and NNS listing in the present study will likely raise the awareness and response regarding marine NNS in the whole Macaronesia region, serving as a baseline for future research as well as implementing and enforcing regulations related to the introduction of marine NNS in oceanic islands