Structural Appraisal of the Florentine Gothic Construction System

The nave of Santa Maria Novella, a Dominican church in Florence Italy is representative of a Florentine Gothic system of construction. This system, consisting of domical rib vaults on square nave bays, high side aisles, and crypto-buttressing, differs substantially from the French high Gothic system of even-level-crown rib vaults on rectangular bays, with flying buttresses over relatively low aisles. An investigation into the structural aspects of the Florentine Gothic construction system reveals that the domical vaults increase the longitudinal thrust and reduce the transverse thrust, which may require additional precautions to be taken during construction, but entails a less elaborate buttressing system. The domical vaults are found to perform well structurally, with an absence of tensile stresses, and are more suitable for a square bay. In general, the structural system of the nave of Santa Maria Novella is found to be the product of carefully considered structural design, which may be accepted as an alternative to the French Gothic construction system.     

Relationship between the binding sites for an alpha-conotoxin and snake venom neurotoxins in the nicotinic acetylcholine receptor from Torpedo californica

Photoinduced cross-links between the iodinated Lys26-p-azidobenzoyl derivative of neurotoxin II from Naja naja oxiana cobra venom and nicotinic acetylcholine receptor from Torpedo californica (AChR) have been studied in the presence of alpha-conotoxin GI from the marine snail C. geographus. Preincubation of the AChR-enriched membranes with increasing concentrations of alpha-conotoxin GI protects first the gamma subunit from photolabelling and then the delta subunit, the IC50 values being 0.76 and 5.01 microM, respectively. The results obtained, in view of the relevant data in literature, demonstrate that the (alpha + gamma) site, which is the high affinity site for d-tubocurarine, has also a higher affinity for an alpha-conotoxin than the (alpha + delta) containing site. The latter has a somewhat higher affinity than the (alpha + gamma) site towards some naturally occurring snake venom alpha-neurotoxins or their derivatives.     

Serum enzyme abnormalities in protein energy malnutrition

A semi-quantitative right coronary artery score (RCA score) was derived from the ratio of the number of the major left ventricular branches of the right coronary artery to the total of the right coronary and left circumflex arteries, to stratify the extent of perfusion in patients with right coronary artery dominance. Thirty-seven patients with one-vessel coronary disease involving a dominant right coronary artery proximal to the left ventricular branches were selected for study. Thallium scintigraphy was performed after right intracoronary injection in 11 patients, and 26 patients underwent conventional stress thallium scintigraphy (24 exercise thallium and two dipyridamole thallium scintigraphy). Thallium scores of perfusion region size after right intracoronary thallium injection and perfusion defect size in stress thallium studies were quantitated from planar thallium images. Both the RCA score and the regional thallium scores spanned over a wide range. The RCA score (range 0.23-0.85) correlated best with the posterior (70 degrees left anterior oblique view) plus lateral segment (40 degrees left anterior oblique view) thallium score (r = 0.88 and 0.53 for intracoronary and stress thallium studies respectively). It also correlated with the summed thallium scores in the posterior, lateral, apical and inferior segments (r = 0.73 and 0.54 respectively) but not with thallium scores in the apex or inferior segment alone. The proposed RCA score quantitates the variable posterolateral perfusion territory of the right coronary artery, and could stratify the area of myocardium at risk from coronary stenosis in the majority of patients with right coronary dominance.     

Information cut for clustering using a gradient descent approach

We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between probability density functions. We propose to optimize the Information Cut using a gradient descent-based approach. Our algorithm has several advantages compared to many other graph-based methods in terms of determining an appropriate affinity measure, computational complexity, memory requirements and coping with different data scales. We show that our method may produce clustering and image segmentation results comparable or better than the state-of-the art graph-based methods.     

Crystal structure of TNF-alpha mutant R31D with greater affinity for receptor R1 compared with R2

Crystal structures have been determined of recombinant human tumor necrosis factor-alpha (TNF-alpha) and its R31D mutant that preferentially binds to TNF receptor R1 with more than seven times the relative affinity of binding to receptor R2. Crystals of the wild-type TNF were of space group P4(1)2(1)2 and had unit cell dimensions of a = b = 94.7 and c = 117.4 A. Refinement of the structure gave an R-factor of 22.3% at 2.5 A resolution. The crystals of TNF R31D mutant diffracted to 2.3 A resolution, and were of identical space group to the wild type with unit cell dimensions of a = b = 95.4 and c = 116.2 A, and the structure was refined to an R-factor of 21.8%. The trimer structures of the wild-type and mutant TNF were similar with a root mean square (r.m.s.) deviation of 0.56 A for Calpha atoms; however, the subunits within each trimer were more variable with an average r.m.s. deviation of 1.00 A on Calpha atoms for pairwise comparison of subunits. Model complexes of TNF with receptors R1 and R2 have been used to predict TNF-receptor interactions. Arg31 in all three subunits of wild-type TNF is predicted to form an ionic interaction with the equivalent glutamic acid in both receptors R1 and R2. Asp31 of the TNF R31D mutant is predicted to interact differently with the two receptors. The side chain of Asp31 in two subunits of the TNF mutant is predicted to form hydrogen bond interactions with Ser59 or Cys70 of R1, while it has no predicted interactions with R2. The loss of three strong ionic interactions of Arg31 and the electrostatic repulsion of Asp31 with Glu in the receptors is consistent with the reduced binding of the R31D mutant to both receptors relative to wild-type TNF. The replacement of these ionic interactions by two weaker hydrogen bond interactions between Asp31 of the R31D mutant and R1, compared with no interactions with R2, is in agreement with the observed preferential binding of the R31D mutant to R1 over R2. Analysis of the structure and function of receptor-discriminating mutants of TNF will help understand the biological role of TNF and facilitate its use as an antitumor agent.      

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Diversity and Software Development

Scott E. Page's diversity framework provides useful insights regarding software engineering research, practice, and education. This editorial discusses the concepts and implications of diversity in this context.     

Perturbation-Based Eigenvector Updates for On-Line Principal Components Analysis and Canonical Correlation Analysis

Principal components analysis is an important and well-studied subject in statistics and signal processing. Several algorithms for solving this problem exist, and could be mostly grouped into one of the following three approaches: adaptation based on Hebbian updates and deflation, optimization of a second order statistical criterion (like reconstruction error or output variance), and fixed point update rules with deflation. In this study, we propose an alternate approach that avoids deflation and gradient-search techniques. The proposed method is an on-line procedure based on recursively updating the eigenvector and eigenvalue matrices with every new sample such that the estimates approximately track their true values as would be calculated analytically from the current sample estimate of the data covariance matrix. The perturbation technique is theoretically shown to be applicable for recursive canonical correlation analysis, as well. The performance of this algorithm is compared with that of a structurally similar matrix perturbation-based method and also with a few other traditional methods like Sanger’s rule and APEX.

---

     

Generalized information potential criterion for adaptive system training

We have previously proposed the quadratic Renyi's error entropy as an alternative cost function for supervised adaptive system training. An entropy criterion instructs the minimization of the average information content of the error signal rather than merely trying to minimize its energy. In this paper, we propose a generalization of the error entropy criterion that enables the use of any order of Renyi's entropy and any suitable kernel function in density estimation. It is shown that the proposed entropy estimator preserves the global minimum of actual entropy. The equivalence between global optimization by convolution smoothing and the convolution by the kernel in Parzen windowing is also discussed. Simulation results are presented for time-series prediction and classification where experimental demonstration of all the theoretical concepts is presented.