Microalbuminuria, arterial hypertension and the cardiovascular risk

Both the Entamoeba histolytica lectin, a virulence factor for the causative agent of amebiasis, and the mammalian hepatic lectin bind to N-acetylgalactosamine (GalNAc) and galactose (Gal) nonreducing termini on oligosaccharides, with preference for GalNAc. Polyvalent GalNAc-derivatized neoglycoproteins have >1000-fold enhanced binding affinity for both lectins (Adler,P., Wood,S.J., Lee,Y.C., Lee,R.T., Petri,W.A.,Jr. and Schnaar,R.L.,1995, J. Biol. Chem ., 270, 5164-5171). Substructural specificity studies revealed that the 3-OH and 4-OH groups of GalNAc were required for binding to both lectins, whereas only the E.histolytica lectin required the 6-OH group. Whereas GalNAc binds with 4-fold lower affinity to the E.histolytica lectin than to the mammalian hepatic lectin, galactosamine and N-benzoyl galactosamine bind with higher affinity to the E. histolytica lectin. Therefore, a synthetic scheme for converting polyamine carriers to poly-N-acyl galactosamine derivatives (linked through the galactosamine primary amino group) was developed to test whether such ligands would bind the E.histolytica lectin with high specificity and high affinity. Contrary to expectations, polyvalent derivatives including GalN6lys5, GalN4desmosine, GalN4StarburstTMdendrimer, and GalN8StarburstTMdendrimer demonstrated highly enhanced binding to the mammalian hepatic lectin but little or no enhancement of binding to the E.histolytica lectin. We propose that the mammalian hepatic lectin binds with greatest affinity to GalNAc "miniclusters," which mimic branched termini of N-linked oligosaccharides, whereas the E.histolytica lectin binds most effectively to "maxiclusters," which may mimic more widely spaced GalNAc residues on intestinal mucins.     

Nonlinear Versus Linear Learning Devices: A Procedural Perspective

We provide a discussion of bounded rationality learning behind traditional learning mechanisms, i.e., Recursive Ordinary Least Squares and Bayesian Learning . These mechanisms lack for many reasons a behavioral interpretation and, following the Simon criticism, they appear to be substantively rational. In this paper, analyzing the Cagan model, we explore two learning mechanisms which appear to be more plausible from a behavioral point of view and somehow procedurally rational: Least Mean Squares learning for linear models and Back Propagation for Artificial Neural Networks . The two algorithms look for a minimum of the variance of the error forecasting by means of a steepest descent gradient procedure. The analysis of the Cagan model shows an interesting result: non-convergence of learning to the Rational Expectations Equilibrium is not due to the restriction to linear learning devices; also Back Propagation learning for Artificial Neural Networks may fail to converge to the Rational Expectations Equilibrium of the model.     

Genetic programming with one-point crossover and subtree mutation for effective problem solving and bloat control

Genetic programming (GP) is one of the most widely used paradigms of evolutionary computation due to its ability to automatically synthesize computer programs and mathematical expressions. However, because GP uses a variable length representation, the individuals within the evolving population tend to grow rapidly without a corresponding return in fitness improvement, a phenomenon known as bloat. In this paper, we present a simple bloat control strategy for standard tree-based GP that achieves a one order of magnitude reduction in bloat when compared with standard GP on benchmark tests, and practically eliminates bloat on two real-world problems. Our proposal is to substitute standard subtree crossover with the one-point crossover (OPX) developed by Poli and Langdon (Second online world conference on soft computing in engineering design and manufacturing, Springer, Berlin (1997)), while maintaining all other GP aspects standard, particularly subtree mutation. OPX was proposed for theoretical purposes related to GP schema theorems, however since it curtails exploration during the search it has never achieved widespread use. In our results, on the other hand, we are able to show that OPX can indeed perform an effective search if it is coupled with subtree mutation, thus combining the bloat control capabilities of OPX with the exploration provided by standard mutation.     

Components meet aspects: Assessing design stability of a software product line

Context

It is important for Product Line Architectures (PLA) to remain stable accommodating evolutionary changes of stakeholder’s requirements. Otherwise, architectural modifications may have to be propagated to products of a product line, thereby increasing maintenance costs. A key challenge is that several features are likely to exert a crosscutting impact on the PLA decomposition, thereby making it more difficult to preserve its stability in the presence of changes. Some researchers claim that the use of aspects can ameliorate instabilities caused by changes in crosscutting features. Hence, it is important to understand which aspect-oriented (AO) and non-aspect-oriented techniques better cope with PLA stability through evolution.

Objective

This paper evaluates the positive and negative change impact of component and aspect based design on PLAs. The objective of the evaluation is to assess how aspects and components promote PLA stability in the presence of various types of evolutionary change. To support a broader analysis, we also evaluate the PLA stability of a hybrid approach (i.e. combined use of aspects and components) against the isolated use of component-based, OO, and AO approaches.

Method

An quantitative and qualitative analysis of PLA stability which involved four different implementations of a PLA: (i) an OO implementation, (ii) an AO implementation, (iii) a component-based implementation, and (iv) a hybrid implementation where both components and aspects are employed. Each implementation has eight releases and they are functionally equivalent. We used conventional metrics suites for change impact and modularity to measure the architecture stability evaluation of the 4 implementations.

Results

The combination of aspects and components promotes superior PLA resilience than the other PLAs in most of the circumstances.

Conclusion

It is concluded that the combination of aspects and components supports the design of high cohesive and loosely coupled PLAs. It also contributes to improve modularity by untangling feature implementation.     

A systematic approach to improve multiple Lyapunov function stability and stabilization conditions for fuzzy systems

This paper presents a systematic approach for decreasing conservativeness in stability analysis and control design for Takagi-Sugeno (TS) systems. This approach is based on the idea of multiple Lyapunov functions together with simple techniques for introducing slack matrices. Unlike some previous approaches based on multiple Lyapunov functions, both the stability and the stabilization conditions are written as linear matrix inequality (LMI) problems. The proposed approach reduces the number of inequalities and guarantees extra degrees of freedom to the LMI problems. Numeric examples illustrate the effectiveness of this method.     

Compressed Multiresolution Hierarchies for High‐Quality Precomputed Shadows

The quality of shadow mapping is traditionally limited by texture resolution. We present a novel lossless compression scheme for high‐resolution shadow maps based on precomputed multiresolution hierarchies. Traditional multiresolution trees can compactly represent homogeneous regions of shadow maps at coarser levels, but require many nodes for fine details. By conservatively adapting the depth map, we can significantly reduce the tree complexity. Our proposed method offers high compression rates, avoids quantization errors, exploits coherency along all data dimensions, and is well‐suited for GPU architectures. Our approach can be applied for coherent shadow maps as well, enabling several applications, including high‐quality soft shadows and dynamic lights moving on fixed‐trajectories.     

The shape of feature code: an analysis of twenty C-preprocessor-based systems

Feature annotations (e.g., code fragments guarded by #ifdef C-preprocessor directives) control code extensions related to features. Feature annotations have long been said to be undesirable. When maintaining features that control many annotations, there is a high risk of ripple effects. Also, excessive use of feature annotations leads to code clutter, hinder program comprehension and harden maintenance. To prevent such problems, developers should monitor the use of feature annotations, for example, by setting acceptable thresholds. Interestingly, little is known about how to extract thresholds in practice, and which values are representative for feature-related metrics. To address this issue, we analyze the statistical distribution of three feature-related metrics collected from a corpus of 20 well-known and long-lived C-preprocessor-based systems from different domains. We consider three metrics: scattering degree of feature constants, tangling degree of feature expressions, and nesting depth of preprocessor annotations. Our findings show that feature scattering is highly skewed; in 14 systems (70 %), the scattering distributions match a power law, making averages and standard deviations unreliable limits. Regarding tangling and nesting, the values tend to follow a uniform distribution; although outliers exist, they have little impact on the mean, suggesting that central statistics measures are reliable thresholds for tangling and nesting. Following our findings, we then propose thresholds from our benchmark data, as a basis for further investigations.     

TinyPBC: Pairings for authenticated identity-based non-interactive key distribution in sensor networks

Key distribution in Wireless Sensor Networks (WSNs) is challenging. Symmetric cryptosystems can perform it efficiently, but they often do not provide a perfect trade-off between resilience and storage. Further, even though conventional public key and elliptic curve cryptosystems are computationally feasible on sensor nodes, protocols based on them are not, as they require the exchange and storage of large keys and certificates, which is expensive.Using Pairing-Based Cryptography (PBC) protocols parties can agree on keys without any interaction. In this work, we (i) show how security in WSNs can be bootstrapped using an authenticated identity-based non-interactive protocol and (ii) present TinyPBC, to our knowledge, the most efficient implementation of PBC primitives for 8, 16 and 32-bit processors commonly found in sensor nodes. TinyPBC is able to compute pairings, the most expensive primitive of PBC, in 1.90 s on ATmega128L, 1.27 s on MSP430 and 0.14 s on PXA27x.