The specification logic νZ

This paper introduces a wide-spectrum specification logic νZ. The minimal core logic is extended to a more expressive specification logic which includes a schema calculus similar (but not equivalent) to Z, new additional schema operators, and extensions to programming and program development logics.     

Adherence to pharmacologic management of hypertension

Adherence to pharmacologic therapy of hypertension is low (in the range of 50-70%) and has important implications both for blood pressure control and cardiovascular complications. Based on a review of the literature using the levels of evidence grading technique, determinants of adherence to the pharmacologic therapy of hypertension have been assessed. Additionally, interventions to improve compliance were evaluated. Patient-centred, health care provider-centred and drug-specific factors have all been shown to affect adherence rates. We conclude that the extent of adherence to pharmacologic therapy is modifiable. Measurable improvements in adherence can be obtained from simplified medication regimens and a combination of behaviour strategies, including the tailoring of pill-taking to patients' daily habits and rituals, the advocacy of self-monitoring of pills and blood pressure, and the institution of reward systems.     

Moment arms and lengths of human upper limb muscles as functions of joint angles

Modeling of musculoskeletal structures requires accurate data on anatomical parameters such as muscle lengths (MLs), moment arms (MAs) and those describing the upper limb position. Using a geometrical model of planar arm movements with three degrees of freedom, we present, in an analytical form, the available information on the relationship between MAs and MLs and joint angles for thirteen human upper limb muscles. The degrees of freedom included are shoulder flexion/extension, elbow flexion/extension, and either wrist flexion/extension (the forearm in supination) or radial/ulnar deviation (the forearm in mid-pronation). Previously published MA/angle curves were approximated by polynomials. ML/angle curves were obtained by combining the constant values of MLs (defined by the distance between the origin and insertion points for a specific upper limb position) with a variable part obtained by multiplying the MA (joint radius) and the joint angle. The MAs of the prime wrist movers in radial/ulnar deviation were linear functions of the joint angle (R2 > or = 0.9954), while quadratic polynomials accurately described their MAs during wrist flexion/extensions. The relationship between MAs and the elbow angle was described by 2nd, 3rd or 5th-order polynomials (R2 > or = 0.9904), with a lesser quality of fit for the anconeus (R2 = 0.9349). In the full range of angular displacements, the length of wrist, elbow and shoulder muscles can change by 8.5, 55 and 200%, respectively.     

Learning to Predict Non-Deterministically Generated Strings

In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.     

Learning Automata from Ordered Examples

Connectionist learning models have had considerable empirical success, but it is hard to characterize exactly what they learn. The learning of finite-state languages (FSL) from example strings is a domain which has been extensively studied and might provide an opportunity to help understand connectionist learning. A major problem is that traditional FSL learning assumes the storage of all examples and thus violates connectionist principles. This paper presents a provably correct algorithm for inferring any minimum-state deterministic finite-state automata (FSA) from a complete ordered sample using limited total storage and without storing example strings. The algorithm is an iterative strategy that uses at each stage a current encoding of the data considered so far, and one single sample string. One of the crucial advantages of our algorithm is that the total amount of space used in the course of learning for encoding any finite prefix of the sample is polynomial in the size of the inferred minimum state deterministic FSA. The algorithm is also relatively efficient in time and has been implemented. More importantly, there is a connectionist version of the algorithm that preserves these properties. The connectionist version requires much more structure than the usual models and has been implemented using the Rochester Connectionist Simulator. We also show that no machine with finite working storage can iteratively identify the FSL from arbitrary presentations.     

Optimal techniques for arterial gene transfer

Cardiovascular gene therapy is becoming a clinical reality due to improved vectors, delivery systems and careful experimental validation studies. Nearly all cardiovascular diseases are amenable to gene therapy, but the optimal combination of vector, delivery system and therapeutic gene is likely to be unique to each application. Currently, the most efficient vectors available are replication-defective adenoviral vectors, but transgene expression is limited in time due to a strong immune response. Conversely, non-viral vectors or plasmid DNA may be used safely but have very limited efficiency. Percutaneous, catheter-based delivery is feasible for most applications. The ultimate issues that will decide of the future of gene therapy are safety of the transfer and delivery techniques as well as cost/effectiveness comparisons with alternative therapies, including local delivery of drugs, proteins and/or mechanical devices.     

Evolution of multiprotocol label switching

Multiprotocol label switching (MPLS) is rapidly emerging as an Internet Engineering Task Force (IETF) standard intended to enhance the speed, scalability, and service provisioning capabilities in the Internet. MPLS uses the technique of packet forwarding based on labels, to enable the implementation of a simpler high-performance packet forwarding engine. This also decouples packet forwarding from routing, facilitating the provision of varied routing services independent of the packet forwarding paradigm. The authors track the evolution of this technology in relation to other existing technologies. Then an overview of the MPLS architecture and design is provided. In addition, some of the work that was a precursor to MPLS is discussed, as well as related issues and debates