Anti-BSG monoclonal antibody, clone OX114 [Biotin]

Alternative feeds comprising only brewer's spent grain (BSG) or distillers dried grain (DDG), both agricultural byproducts, and 50% BSG or 50% DDG mixed with 50% wheat bran (WB) were compared to the standard 100% WB feed provided to Tenebrio molitor larvae to evaluate their effects on the nutritional quality and economic viability of mass-producing this insect. Crude protein content was highest in larvae fed on 100% WB and 100% DDG, and the latter had 2.32 and 1.88 times more essential and non-essential amino acids than the 100% WB group, respectively. Larvae fed on 50% DDG+50% WB had 1.30 times more saturated fatty acids but 1.08 times less unsaturated fatty acids and 1.03-1.23 times less potassium, phosphorus, and magnesium than larvae fed on 100% WB. Traces of mercury were detected in larvae fed on 100% WB and 50% DDG+50% WB, although at levels below the General Food and Feed Standard (Ministry of Food and Drug Safety, Republic of Korea), but neither Escherichia coli or Salmonella spp. were detected in the feeds. Larval and pupal weight, larval development and survival, and pupation rate were higher in larvae fed on 50% BSG or 50% DDG mixed with 50% WB groups than in larvae fed on 100% WB. Therefore, using 50% BSG or 50% DDG mixed with 50% WB as an alternative feed in the mass production of T.molitor provides higher quality larvae at a lower cost than does using the conventional 100% WB feed.

In this work we deal with a biobjective variant of the single container loading problem. The problem consists in packing a set of boxes into a large box or container. In addition to the usual objective related to maximize the volume utilization, we include a second objective consisting on maximizing the total profit (e.g., weight or priority) of the loaded boxes. We propose to adapt bsg, a state-of-the-art single-objective algorithm for solving the biobjective problem. bsg can be seen as an incomplete version of a breadth first search in which each level of the search tree is restricted to a fixed number of promising nodes. In order to select the most promising nodes, the algorithm constructs a solution from them by using a greedy algorithm and evaluates the objectives. To deal with two objectives, we propose to select nodes by using well-known multi-objective criteria based on dominance and crowding distance related to the greedy evaluations. We go a little bit further and orient the greedy algorithm to one objective or the other by using a mechanism which changes the configuration of the heuristic function dynamically. The proposal is compared with bsg in a set of well-known instances reporting a 24% increase in the hypervolume indicator. Compared to other biobjective approaches, the reported results are also promising. Codes and test instances are available in: https://github.com/rilianx/Metasolver#bo-bsg (C) 2020 Elsevier B.V. All rights reserved.