PROGRESSIVE AND SUSTAINED SCHOOL REFORMS: FRAMING AND COALITION BUILDING IN SWISS CITIES

ABSTRACT: Urban politics in the early 21st century is structured by conflicts over social cohesion and economic competitiveness. Education policy takes center stage in this struggle as schools are institutions of both social and economic reproduction. I draw on arguments of urban regime and policy frame analysis to examine the politics of urban school reform in two Swiss cities. Empirically, I analyze neighborhood‐embedded bottom‐up school reforms committed to social cohesion. The paths these reforms eventually take were shaped by different coalitions geared around specific school policy frames. Frames indeed play a crucial role in building a coalition toward progressive school reforms. In addition, their sustainability in a political environment, increasingly shifting toward development policies, hinges on the dominant frame underlying the reforms as well as the properties of the network advancing them.     

Multidrug-Resistant Transport Proteins in Yeast: Complete Inventory and Phylogenetic Characterization of Yeast Open Reading Frames within the Major Facilitator Superfamily

Screening of the complete genome sequence from the yeast Saccharomyces cerevisiae reveals that 28 open reading frames (ORFs) are homologous to each other and to established bacterial members of the drug-resistant subfamily of the major facilitator superfamily. The phylogenesis of these protein sequences shows that they fall into three major clusters. Cluster I contains 12 ORFs, cluster II contains ten ORFs and cluster III contains six ORFs. Hydropathy analyses indicate that in clusters II and III ORFs, 14 transmembrane spans are predicted whereas only 12 transmembrane spans are predicted in cluster I ORFs. Three ORFs that have known functions as multidrug-resistance pumps in other yeast species such as Schizosaccharomyces pombe (CAR1), Candida albicans (BMRP) or C. maltosa (CYHR), also fall into cluster I. Two S. cerevisiae ORFs of known multidrug-resistance function (ATR1, SGE1) fall into cluster II. Cluster III consists exclusively of ORFs of unknown function but binary sequence comparisons show homology to ORFs from cluster II. Analysis of the multiple alignment for these proteins leads to the identification of characteristic signature sequences for each of the three clusters. © 1997 by John Wiley & Sons, Ltd.     

Alfalfa Proteins: Isolation and Partial Characterization of the Major Component — Fraction I Protein

Fraction I protein was extracted from fresh alfalfa (Medicago sativa) leaves and purified by ammonium sulfate fractionation, DEAE-cellulose and Sephadex G-200 chromatography. The isolate possessed a specific activity for ribulosebisphosphate carboxylase EC 4.1.1.39) of 1.01 units/mg protein. An approximate molecular weight of 573,000 was determined from values of S^o_20,w (18.7) and D^o_20,w (2.97). The protein contained 26 disulfide and 37 sulfhydryl groups—only one of which was titratable in the undenatured protein complex. It migrated as a single boundry by Tiselius electrophoresis and as a dense zone in polyacrylamide gels (disc). In the presence of SDS, two principal subunits of ～52,000 and ～12,500 daltons were revealed. Based on the FAO/WHO (1973) provisional pattern for essential amino acids, the protein was slightly deficient in sulfur-containing residues.     

Multi-agent approach and stochastic optimization: random events in manufacturing systems

We propose a method to solve industrial problems and to take into account random events. It is called the triple coupling. It is based on stochastic algorithms, a simulation model and the multi-agents model of artificial intelligence. The method we propose is easy to use and allows us to take into account most of the constraints found in manufacturing systems. Experts look for solutions to increasing the capacity of production. But the production can be disturbed by random events experienced by the system. Industrial experts need schedules which prevent the consequences of random events. Minimizing such consequences is very important to increasing system delivery. Capital investment is often very high in factories and the cost of the investment goes on regardless of whether the resources are running or not. The multi-agent approach is used to determine schedules for which the consequences of random events are low, and a stochastic algorithm is proposed which permits us to optimize a random variable. We prove that this algorithm finds, with probability one, the schedule of the production for which the consequences of random events are the lowest. We propose to measure the consequences of random events using an influence ratio. Our approach has been used to study the consequences of random events in Peugeot sand foundries of Sept-Fons (France). A benchmark test is presented to prove the efficiency of our solution. For the Peugeot sand foundry of Sept-Fond, random events increase the production time by about 20% compared with the production time without any random events occurring. We have determined schedules of production for which the consequences of random events are about 0.5%.     

BULK MECHANICAL BEHAVIOR OF COMMERCIAL PARTICLE FOOD FOAMS

The texture of 10 commercial cereal foam products, of different composition and shape, has been evaluated through the measurement of its bulk mechanical properties using a Kramer shear cell. Force–displacement curves led to repeatable measurements, characterized by low standard deviations. Discrimination among samples and relevant mechanical variables were determined by the PCA of these curves. Most of the variability in the force–displacement curves (97%) and mechanical variables (93%) were contained in the two PC1s, and the mechanical behavior of this large variety of cereal foams texture could be explained by two variables: the energy needed for crushing (area under the force–displacement curve) and the slope ratio of the curve. These variables were then respectively related to bulk density, which increased with sugar content, and to the shape factor, evaluated through geometric approximation.

PRACTICAL APPLICATIONS

The contribution of this work to the characterization of cereal foam product texture is first, to extend the validation of the Kramer shear cell for assessing the bulk behavior of real products of irregular shape. Low standard deviation and product differentiation among 10 commercial samples shows that this method is reliable enough for quality control of cereal particle foams. Then, by its ability to determine the two most relevant variables from the texture profiles, it allows a deeper look on the relationships between mechanical properties and multi-scale structure, as shown by the relation with apparent bulk density and particle shape, and the role of sugar content. Finally, the relation with former works on cornflakes also suggests the use of these variables for assessing sample crispness.