Towards a Perfect CMOS CCII

DC offset and inaccurate voltage follower action betweenterminals Y and X, the relatively highimpedance seen at terminal X and inaccurate currentfollower action between terminals X and Zplague simple circuit realizations of the CCII. This paper summarizesthe methods employed and compares the improvement of the CCIIcharacteristics achieved by a variety of published circuits,with emphasis laid on CMOS realizations. In these comparisons,the conventionally employed but inaccurate current mirror outputstages were replaced by a circuit employing current isolationand thereby providing accurate current follower action betweenterminals X and Z. Furthermore, twonovel realizations of a differential CCII – basedtransconductance amplifier are described, which can also be employedas input stage of an instrumentation voltage amplifier exhibitingan exceptionally high CMRR and excellent frequency response.Finally, a current fan out circuit for cascode CCII –swill be introduced, whose transfer function value is electronicallyadjustable.     

Photosensitizedcis-trans isomerization of jojoba wax

Jojoba wax solutions were irradiated at wavelengths longer than 366 nm, in the presence of sensitizers, at room temperature.Cis-trans isomerization took place only with sensitizers with triplet energy greater than 68 kcal/mol. Quantum yields were low and a conversion of up to 25% of thetrans isomer was achieved at the photostationary state.     

Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping

Semi-automated geomorphological mapping techniques are gradually replacing classical techniques due to increasing availability of high-quality digital topographic data. In order to efficiently analyze such large amounts of data, there is a need for optimizing the processing of automated mapping techniques. In this context, we present a novel approach to semi-automatically map alpine geomorphology using stratified object-based image analysis. We used a 1 m Digital Terrain Model (DTM) derived from laser altimetry data from a mountainous catchment from which we calculated various Land-Surface Parameters (LSPs). The LSPs ‘slope angle’ and ‘topographic openness’ have been combined into a single composite layer for selecting reference material and delineating training samples. We developed a novel method to semi-automatically assess segmentation results by comparing 2D frequency distribution matrices of training samples and image objects. The segmentation accuracy assessment allowed us to automate optimization of the scale parameter and LSPs used for segmentation. We concluded that different geomorphological feature types have different sets of optimal segmentation parameters. The feature-dependent parameters were used in a new approach of stratified feature extraction for classifying karst, glacial, fluvial and denudational landforms. In this way, we have used stratified object-based image analysis to semi-automatically extract contrasting geomorphological features from high-resolution digital terrain data. A further step would be to also automate the optimization of classification rules. We would then be able to create a library of feature characteristics that could be transferred and applied to other mountain regions and further automate geomorphological mapping strategies.     

On the consistency, expressiveness, and precision of partial modeling formalisms

Partial transition systems support abstract model checking of complex temporal properties by combining both over- and under-approximating abstractions into a single model. Over the years, three families of such modeling formalisms have emerged, represented by (1) Kripke Modal Transition Systems (KMTSs), with restrictions on necessary and possible behaviors; (2) Mixed Transition Systems (MixTSs), with relaxation on these restrictions; and (3) Generalized Kripke MTSs (GKMTSs), with hyper-transitions, respectively. In this paper, we investigate these formalisms based on two fundamental ways of using partial transition systems (PTSs) - as objects for abstracting concrete systems (and thus, a PTS is semantically consistent if it abstracts at least one concrete system) and as models for checking temporal properties (and thus, a PTS is logically consistent if it gives consistent interpretation to all temporal logic formulas). We study the connection between semantic and logical consistency of PTSs, compare the three families w.r.t. their expressive power (i.e., what can be modeled, what abstractions can be captured using them), and discuss the analysis power of these formalisms, i.e., the cost and precision of model checking.Specifically, we identify a class of PTSs for which semantic and logical consistency coincide and define a necessary and sufficient structural condition to guarantee consistency. We also show that all three families of PTSs have the same expressive power (but do differ in succinctness). However, GKMTSs are more precise (i.e., can establish more properties) for model checking than the other two families. The direct use of GKMTSs in practice has been hampered by the difficulty of encoding them symbolically. We address this problem by developing a new semantics for temporal logic of PTSs that makes the MixTS family as precise for model checking as the GKMTS family. The outcome is a symbolic model checking algorithm that combines the efficient encoding of MixTSs with the model checking precision of GKMTSs. Our preliminary experiments indicate that the new algorithm is a good match for predicate-abstraction-based model checkers.     

Thermal Character of Geopolymers Synthesized from Class F Fly Ash Containing High Concentrations of Iron and α-Quartz

This article reports the thermal characteristics of geopolymers prepared with a class F fly ash containing 15 wt% iron oxide and 20 wt%α-quartz. The characterization techniques used included dilatometry, TGA, DTA, XRD, and SEM. Geopolymer specimens were prepared with nominal ratios of Si:Al=2.3 and Na:Al=0.85. Iron oxide in the fly ash precursor was found to play a critical role in the thermal expansion and morphology of geopolymers at temperatures >500°C. Volume changes of quartz on either side of the α–β phase transition cause only minor variations in thermal expansion.     

Determination of the reactive component of fly ashes for geopolymer production using XRF and XRD

Geopolymers are a class of versatile materials that have the potential for utilisation as a cement replacement, fireproof barriers, materials for high temperatures, and biological implant applications. This study investigated methods for determining the formulation for manufacturing geopolymers made with fly ash from coal-fired power stations. The accepted method of determining the formulation of geopolymers to get the desired matrix chemistry uses the bulk composition of the feedstock materials. This formulation method is widely used in investigations using feedstock materials that almost completely react during processing. It is widely considered that amorphous components of fly ash are the reactive components in the geopolymerisation reaction. However, quantification of the amorphous components is challenging and generally avoided with the concomitant problem that the formulation is far from optimum. For the work presented here, the composition of the amorphous part is determined accurately and this information utilised to synthesise geopolymers. The bulk composition is first determined using X-ray fluorescence spectroscopy (XRF) and then the amorphous composition determined using XRF and quantitative X-ray diffraction (QXRD). Formulating the mixture based on amorphous composition produced samples with a significantly higher compressive strength than those formulated using the bulk composition. Using the amorphous composition of fly ash produced geopolymers with similar physical properties to that of metakaolin geopolymers with the same targeted composition. We demonstrated a new quantitative formulation method that is superior to the accepted method.     

Multiple-wavelength quasi-phase-matched nonlinear interactions

Quasi-phase-matching allows one to arbitrarily phase match a single interaction by periodic modulation of the material nonlinear coefficient. A partial extension is obtained by Fibonacci-based quasi-periodic modulation of the nonlinear coefficient. These Fibonacci-based structures allow for simultaneously phase matching two interactions, provided that their wavevector mismatch ratio obeys selection rules, which are governed by the golden ratio τ=(1+√5)/2. In this paper, we present a novel method for simultaneously phase matching any two nonlinear interactions by general quasi-periodic modulation of the nonlinear coefficient. These quasi-periodic structures, which also include the Fibonacci-based structures as a subgroup, provide greater design flexibility. Our method can be useful for various nonlinear devices, such as multiple-peak frequency doublers, frequency triplers, and frequency quadruplers. We show for two specific devices that similar efficiency, compared to a cascaded device, can be obtained. Furthermore, in contrast to some cascaded devices, these structures can be used in double-pass and standing-wave configurations, since they operate with the same efficiency in both directions of propagation     

Improved Algorithms for Some Competitive Location Centroid Problems on Paths, Trees and Graphs

We consider a common scenario in competitive location, where two competitors (providers) place their facilities (servers) on a network, and the users, which are modeled by the nodes of the network, can choose between the providers. We assume that each user has an inelastic demand, specified by a positive real weight. A user is fully served by a closest facility. The benefit (gain) of a competitor is his market share, i.e., the total weight (demand) of the users served at his facilities. In our scenario the two providers, called the leader and the follower, sequentially place p and r servers, respectively. After the leader selects the locations for his p servers, the follower will determine the optimal locations for his r servers, that maximize his benefit. An (r,p)-centroid is a set of locations for the p servers of the leader, that will minimize the maximum gain of the follower who can establish r servers. In this paper we focus mainly on the cases where either the leader or the follower can establish only one facility, i.e., either p=1, or r=1. We consider two versions of the model. In the discrete case the facilities can be established only at the nodes, while in the absolute case they can be established anywhere on the network. For the (r,1)-centroid problem, we show that it is strongly NP-hard for a general graph, but can be approximated within a factor e/(e?1). On the other hand, when the graph is a tree, we provide strongly polynomial algorithms for the (r,p)-centroid model, whenever p is fixed. For the (1,1)-centroid problem on a general graph, we improve upon known results, and give the first strongly polynomial algorithm. The discrete (1,p)-centroid problem has been known to be NP-hard even for a subclass of series-parallel graphs with pathwidth bounded by 6. In view of this result, we consider the discrete and absolute (1,p) centroid models on a tree, and present the first strongly polynomial algorithms. Further improvements are shown when the tree is a path.     

A lean specification for GADTs: system F with first-class equality proofs

Generalized Algebraic Data Types are a generalization of Algebraic Data Types with additional type equality constraints. These found their use in many functional programs, including the development of embedded domain specific programming languages and generic programming.