REMEDIATION OF TETRACYCLINE FROM WATER SOURCES USING VETIVER GRASS (Chrysopogon zizanioides L. Nash) AND TETRACYCLINE-TOLERANT ROOT-ASSOCIATED BACTERIA

Antibiotics are emerging contaminants worldwide. Due to insufficient policy regulations, public awareness, and the constant exposure of the environment to antibiotic sources has created a major environmental concern. Wastewater treatment plants (WWTP) are not equipped to filter-out these compounds before the discharge of the disinfected effluent into water sources (e.g., lakes and streams) and current available technologies are not equipped to remediate these compounds from environmental sources. Hence, the challenge remains to establish a biological system to remove these antibiotics from wastewater. An invitro hydroponic remediation system was developed using vetiver grass (Chrysopogon zizanioides L. Nash) to remediate tetracycline (TC) from water. Comparative metabolomics studies were conducted to investigate the metabolites/pathways associated with tetracycline metabolism in plants and TC-degrading bacteria. The results show that vetiver plants effectively uptake tetracycline from water sources. Vetiver root-associated bacteria recovered during the hydroponic remediation trial were highly tolerant to TC (as high as 600 ppm) and could use TC as a sole carbon and energy source. Growth conditions (pH, temperature, and oxygen requirement) for TC-tolerant bacteria were optimized for higher TC remediation capability from water sources. The plant (roots and shoots) and bacterial species were further characterized for the metabolites produced during the TC degradation process using GC-MS to identify the possible biochemical mechanism involved. Also, the plant root zone was screened for metabolites/enzymes that were secreted during antibiotic degradation and could potentially enhance the degradation process. The root zone was selected for this analysis because this region of the plant has shown a greater capacity for antibiotic degradation compared to the shoot zone. The role of antioxidant enzymes in TC degradation process revealed glutathione-S-transferase (GSTs) as an important group of enzymes in both plant and bacteria potentially involved in TC degradation process. Metabolomics results also suggest potential GST activity in the TC remediation/ transformation process used by plants. This information could be useful in gaining insights for the application of biological remediation systems for the mitigation of antibiotics from waste-water.

Strengthening a Traditional Fire Protection Course by Using Fault Trees

Traditional courses and textbooks in occupational safety emphasize rules, standards, and guidelines. This paper describes the early stage of a project to upgrade a traditional college course on fire protection by incorporating learning materials to develop the higher-level cognitive ability known as synthesis. Students will be challenged to synthesize textbook information into fault tree diagrams. The paper explains the place of synthesis in Bloom’s taxonomy of cognitive abilities and the utility of fault trees diagrams as a tool for synthesis. The intended benefits for students are: improved abilities to synthesize, a deeper understanding of fire protection practices, ability to construct fault trees for a wide range of undesired occurrences, and perhaps recognition that heavy reliance on memorization is the hard way to learn occupational safety and health.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.