Applications of a New Proposal for Solving the "Problem of Time" to Some Simple Quantum Cosmological Models

We apply a recent proposal for defining states and observables in quantum gravity to simple models. First, we consider a Klein-Gordon particle in an ex- ternal potential in Minkowski space and compare our proposal to the theory ob- tained by deparametrizing with respect to a time slicing prior to quantiza- tion. We show explicitly that the dynamics of the deparametrization approach depends on the time slicing. Our proposal yields a dynamics independent of the choice of time slicing at intermediate times but after the potential is turned off, the dynamics does not return to the free particle dynamics. Next we apply our proposal to the closed Robertson-Walker quantum cosmology with a massless scalar field with the size of the universe as our time variable, so the only dynamical variable is the scalar field. We show that the resulting theory has the semi-classical behavior up to the classical turning point from expansion to contraction, i.e., given a classical solution which expands for much longer than the Planck time, there is a quantum state whose dynamical evolution closely approximates this classical solution during the expansion. However, when the "time" gets larger than the classical maximum, the scalar field be- comes "frozen" at its value at the maximum expansion. We also obtain similar results in the Taub model. In an Appendix we derive the form of the Wheeler- DeWitt equation for the Bianchi models by performing a proper quantum reduc- tion of the momentum constraints; this equation differs from the usual one ob- tained by solving the momentum constraints classically, prior to quantization.Comment: 30 pages, LaTeX 3 figures (postscript file or hard copy) available upon request, BUTP-94/1

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Network Intrusion Detection by Combining One-Class Classifiers

Intrusion Detection Systems (IDSs) play an essential role in today’s network security infrastructures. Their main aim is in finding out traces of intrusion attempts alerting the network administrator as soon as possible, so that she can take suitable countermeasures. In this paper we propose a misuse-based Network Intrusion Detection architecture in which we combine multiple one-class classifiers. Each one-class classifier is trained in order to discriminate between a specific attack and all other traffic patterns. As attacks can be grouped in classes according to a taxonomy, for each attack class a number of one-class classifiers are trained, each one specialized to a specific attack. The proposed multiple classifier architecture combine the outputs of one class classifiers to attain an IDS based on generalized attack signatures. The aim is in labelling a pattern either as normal or as belonging to one of the attack classes according to the adopted taxonomy. The potentials and effectiveness of the proposed approach are analysed and discussed

A Modular Multiple Classifier System for the Detection of Intrusions in Computer Networks

Abstract. The security of computer networks plays a strategic role in modern computer systems. In order to enforce high protection levels against threats, a number of software tools have been currently developed. Intrusion Detection Systems aim at detecting intruders who elude “first line ” protection. In this paper, a pattern recognition approach to network intrusion detection based on the fusion of multiple classifiers is proposed. In particular, a modular Multiple Classifier architecture is designed, where each module detects intrusions against one of the services offered by the protected network. Each Multiple Classifier System fuses the information coming from different feature representations of the patterns of network traffic. The potentialities of classifier fusion for the development of effective intrusion detection systems are evaluated and discussed. 1

Immune Modulation to Improve Tissue Engineering Outcomes for Cartilage Repair in the Osteoarthritic Joint

Osteoarthritis (OA), the most common form of arthritis, is a disabling degenerative joint disease affecting synovial joints and is associated with cartilage destruction, inflammation of the synovial membrane, and subchondral bone remodeling. Inflammation of the synovial membrane may arise secondary to degenerative processes in articular cartilage (AC), or may be a primary occurrence in OA pathogenesis. However, synovial inflammation plays a key role in the pathogenesis and disease progression of OA through the production of pro-inflammatory mediators, and is associated with cartilage destruction and pain. The triggers that initiate activation of the immune response in OA are unknown, but crosstalk between osteoarthritic chondrocytes, cartilage degradation products, and the synovium may act to perpetuate this response. Increasing evidence has emerged highlighting an important role for pro-inflammatory mediators and infiltrating inflammatory cell populations in the progression of the disease. Tissue engineering strategies hold great potential for the repair of damaged AC in an osteoarthritic joint. However, an in-depth understanding of how OA-associated inflammation impacts chondrocyte and progenitor cell behavior is required to achieve efficient cartilage regeneration in a catabolic osteoarthritic environment. In this review, we will discuss the role of inflammation in OA, and investigate novel immune modulation strategies that may prevent disease progression and facilitate successful cartilage regeneration for the treatment of OA