Space-conserving agglomerative algorithms

This paper evaluates a general, infinite family of clustering algorithms, called the Lance and Williams algorithms, with respect to the space-conserving criterion. An admissible clustering criterion is defined using the space conserving idea. Necessary and sufficient conditions for Lance and Williams clustering algorithms to satisfy space-conserving admissibility are provided. Space-dilating, space-contracting, and well-structured clustering algorithms are also discussed.The work of J. Van Ness was supported by NSF Grant #DMS 9201075.     

Regulatory peptide immunocytochemistry at light- and electron microscopical levels

Summary Immunocytochemical techniques applied at both light- and electron microscopical levels are valuable in the study of regulatory peptide distribution in normal and diseased tissue, whether in the form of sections or whole cell preparations. Successful immunolocalisation depends on 1) adequate preservation of the peptide antigen and the tissue structure in which it resides; 2) a suitably specific and sensitive labelled antibody detecting system. In general, peptides are stable molecules, most of which retain their antigenicity after conventional cross-linking fixation and tissue processing, allowing standard immunocytochemical methods to be used for light- and electron microscopy. Regulatory peptides are derived from precursor molecules and several families of structurally similar peptides are now generally recognised. Region-specific antibodies may be needed to overcome problems of cross-reactivity or to identify a bioactive form in the presence of its precursor. Multiple co-localisation of different related and unrelated peptides in the same cell or even storage granule is now recognised and can be identified by immunocytochemistry.     

A recombinant dromedary antibody fragment (VHH or nanobody) directed against human Duffy antigen receptor for chemokines

Fy blood group antigens are carried by the Duffy antigen receptor for chemokines (DARC), a red cells receptor for Plasmodium vivax broadly implicated in human health and diseases. Recombinant VHHs, or nanobodies, the smallest intact antigen binding fragment derivative from the heavy chain-only antibodies present in camelids, were prepared from a dromedary immunized against DARC N-terminal extracellular domain and selected for DARC binding. A described VHH, CA52, does recognize native DARC on cells. It inhibits P. vivax invasion of erythrocytes and displaces interleukin-8 bound to DARC. The targeted epitope overlaps the well-defined DARC Fy6 epitope. K _D of CA52?CDARC equilibrium is sub-nanomolar, hence ideal to develop diagnostic or therapeutic compounds. Immunocapture by immobilized CA52 yielded highly purified DARC from engineered K562 cells. This first report on a VHH with specificity for a red blood cell protein exemplifies VHHs?? potentialities to target, to purify, and to modulate the function of cellular markers.     

Skewed superstatistical distributions from a Langevin and Fokker-Planck approach

The superstatistics concept is a useful statistical method to describe inhomogeneous complex systems for which a system parameter βfluctuatesonalargespatio-temporal scale. Inthispaper weanalyze ameasuredtimeseriesofwindspeed fluctuationsandextract the superstatistical distribution function f(β) directly from the data. We construct suitable Langevin and Fokker-Planck models with a position dependent β-field and show that they reduce to standard type of superstatistics in the overdamped limit.     

Genetic analysis of the rare species Salix arizonica (Salicacea) and associated willows in Arizona and Utah

Management decisions affecting the rare plant Arizona willow ( Salix arizonica ) will be aided by understanding genetic similarities among populations of this species. Random Amplified Polymorphic DNA (RAPD) analysis was conducted on 20 populations of S. arizonica , 12 populations of 5 congeners, and 2 samples of outgroup, Populus tremuloides . A phenogram based on DNA markers shows clear separation of populations of S. arizonica from those of co-occurring willow species, but similarity is low (～ 37%) between Utah and Arizona populations of S. arizonica . Evaluation of the relationship of habitat characteristics and geographic distance to genetic similarity reveals that environment and genetic similarity are poorly correlated. Considering Arizona versus Utah populations, we found a significant negative relationship between geographic distance and genetic similarity ( r = 0.936), but no significant relationship between interpopulation distance and genetic similarity within Arizona or Utah. The wide geographic disjunction of S. arizonica populations in Utah and Arizona appears to have existed for a long period during which genetic drift, random mutations, and selection for somewhat different habitats have pushed the 2 regional complexes along separate evolutionary trajectories. Preservation of genetic variation within S. arizonica will require protection of multiple populations in Arizona and Utah.     

In Between Us: On the Transparency and Opacity of Technological Mediation

In recent years several approaches??philosophical, sociological, psychological??have been developed to come to grips with our profoundly technologically mediated world. However, notwithstanding the vast merit of each, they illuminate only certain aspects of technological mediation. This paper is a preliminary attempt at a philosophical reflection on technological mediation as such??deploying the concepts of ??transparency?? and ??opacity?? as heuristic instruments. Hence, we locate a ??theory of transparency?? within several theoretical frameworks??respectively classic phenomenology, media theory, Actor Network Theory, postphenomenology, several ethnographical, psychological, and sociological perspectives, and finally, the ??Critical Theory of Technology.?? Subsequently, we render a general, systematic overview of these theories, thereby conjecturing what a broad analysis of technological mediation in and of itself might look like??finding, at last, an essential contradiction between transparency of ??use?? and transparency of social origins and effects.     

Size matters: Pitch dimensions constrain interactive team behaviour in soccer

Pitch size varies in official soccer matches and differently sized pitches are adopted for tactical purposes in small-sided training games. Since interactive team behaviour emerges under constraints, the authors evaluate the effect of pitch size (task) manipulations on interactive team behaviour in small-sided soccer games. Four 4-a-side (plus goalkeepers) small-sided games were played: a reference game (30×20 m), length manipulation (24×20 m), width manipulation (30×16 m), and a combination (24×16 m). Using position data (100Hz), three measures quantifying the teams’ interaction were calculated: longitudinal inter-team distance, lateral inter-team distance, and surface area difference. Means and standard deviations, correlations and coupling values were calculated. Running correlations were calculated over a 3-s window to evaluate interaction patterns. As expected, a shorter pitch results in smaller longitudinal inter-team distance, lateral inter-team distance decreased for narrow pitches, and smaller total playing area resulted in decreased surface area. Unanticipated, a crossover effect was present; length and width manipulations also triggered changes in lateral and longitudinal direction respectively. Inter-team distances and surface area difference differed significantly across conditions. Interaction patterns differed across conditions for all measures. So, highly tactically relevant, soccer teams seem to adapt their interactive behaviour according to pitch size in small-sided games.     

Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model

This paper compares various ways of extracting macroeconomic information from a data‐rich environment for forecasting the yield curve using the Nelson–Siegel model. Five issues in extracting factors from a large panel of macro variables are addressed; namely, selection of a subset of the available information, incorporation of the forecast objective in constructing factors, specification of a multivariate forecast objective, data grouping before constructing factors, and selection of the number of factors in a data‐driven way. Our empirical results show that each of these features helps to improve forecast accuracy, especially for the shortest and longest maturities. Factor‐augmented methods perform well in relatively volatile periods, including the crisis period in 2008–9, when simpler models do not suffice. The macroeconomic information is exploited best by partial least squares methods, with principal component methods ranking second best. Reductions of mean squared prediction errors of 20–30% are attained, compared to the Nelson–Siegel model without macro factors. Copyright © 2011 John Wiley & Sons, Ltd.