Nano Aerosol Chamber for In-Vitro Toxicity (NACIVT) studies.

Abstract Inhalation of ambient air particles or engineered nanoparticles (NP) handled as powders, dispersions or sprays in industrial processes and contained in consumer products pose a potential and largely unknown risk for incidental exposure. For efficient, economical and ethically sound evaluation of health hazards by inhaled nanomaterials, animal-free and realistic in vitro test systems are desirable. The new Nano Aerosol Chamber for in-vitro Toxicity studies (NACIVT) has been developed and fully characterized regarding its performance. NACIVT features a computer-controlled temperature and humidity conditioning, preventing cellular stress during exposure and allowing long-term exposures. Airborne NP are deposited out of a continuous air stream simultaneously on up to 24 cell cultures on Transwell® inserts, allowing high-throughput screening. In NACIVT, polystyrene as well as silver particles were deposited uniformly and efficiently on all 24 Transwell® inserts. Particle-cell interaction studies confirmed that deposited particles reach the cell surface and can be taken up by cells. As demonstrated in control experiments, there was no evidence for any adverse effects on human bronchial epithelial cells (BEAS-2B) due to the exposure treatment in NACIVT. The new, fully integrated and transportable deposition chamber NACIVT provides a promising tool for reliable, acute and sub-acute dose-response studies of (nano)particles in air-exposed tissues cultured at the air-liquid interface.

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.