Missing lithotroph identified as new planctomycete

With the increased use of chemical fertilizers in agriculture, many densely populated countries face environmental problems associated with high ammonia emissions. The process of anaerobic ammonia oxidation ('anammox') is one of the most innovative technological advances in the removal of ammonia nitrogen from waste water. This new process combines ammonia and nitrite directly into dinitrogen gas. Until now, bacteria capable of anaerobically oxidizing ammonia had never been found and were known as "lithotrophs missing from nature". Here we report the discovery of this missing lithotroph and its identification as a new, autotrophic member of the order Planctomycetales, one of the major distinct divisions of the Bacteria. The new planctomycete grows extremely slowly, dividing only once every two weeks. At present, it cannot be cultivated by conventional microbiological techniques. The identification of this bacterium as the one responsible for anaerobic oxidation of ammonia makes an important contribution to the problem of unculturability

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It is a standard practice to test for the signature of homologous recombination in studies examining the genetic diversity of bacterial populations. Although it has emerged that homologous recombination rates can vary widely between species, comparing the results from different studies is made difficult by the diversity of estimation methods used. Here, Multi Locus Sequence Typing (MLST) datasets from a wide variety of bacteria and archaea are analyzed using the ClonalFrame method. This enables a direct comparison between species and allows for a first exploration of the question whether phylogeny or ecology is the primary determinant of homologous recombination rate

Note--A Note on "Lot Size Scheduling on a Single Machine for Stochastic Demand" by Goyal

A Note on "Lot Size Scheduling on a Single Machine for Stochastic Demand" by Goyal (Goyal, S. K. 1973. Lot size scheduling on a single machine for stochastic demand. Management Sci. 19 1322-1325).

Scheduling Maintenance and Determining Crew Size for Stochastically Failing Equipment

Past treatment of the single machine maintenance problem has shown that preventive maintenance may be desirable for equipment for which failures are caused at least partially by wear-out factors. In all previous treatment, however, the size of the maintenance-repair crew has been held constant and the optimal maintenance period has then been determined. This paper develops a simultaneous solution for the maintenance-repair crew size and the optimal maintenance period. The optimal maintenance period is seen to shift as the size of the maintenance-repair crew varies. For the multi-machine maintenance problem, the sharing of the maintenance-repair crew creates a queuing system. Because of its complexity, an analytical solution of this multi-machine maintenance queuing system is not feasible. A simulation model was used to develop a set of general rules for scheduling maintenance for the multi-machine case.

A Cluster-Analytic Approach to Facility Layout

Due to the combinatorial nature of the facility layout problem, current heuristic computer procedures do not always provide better solutions than visual methods. A new algorithm, FLAC (Facility Layout by Analysis of Clusters), is described which emulates the visual methods used by industrial engineers in solving facility layout problems. Initially side-stepping the combinatorial nature of the problem, FLAC is found to perform well in problems with high as well as low flow dominance, and in the presence and absence of line dominance. Computation time is attractive, especially on larger problems.facilities/equipment planning: layout, statistics: cluster analysis, networks/graphs: flow algorithms

Comparison of Computer Algorithms and Visual Based Methods for Plant Layout

Increasing emphasis on the reduction of materials handling costs in the modern plant has led to research into new methods of planning the process type layout in such a way as to minimize these costs. This project compares the performances of three highly rated computer algorithms prescribed for the solution of the plant layout problem with the performances of selected human subjects using the manual and visual methods still used and recommended by industrial engineers for plant layout design. The objective of this comparison is to determine whether there is in fact an advantage to using one of the available computer programs to solve the problem, instead of designing the layout by traditional visual-based methods. These tests, performed under the control of a computer system which accurately recorded the solutions achieved by each subject, show not only that the computer algorithms do not perform better than selected human subjects in the design of plant layouts, but that the human subjects, without the benefit of any prescriptive help from a computer, actually achieve layouts which are stochastically better than those produced by the computer programs.