Age-Related Changes in Hippocampal Arc Expression Following Minimal Behavioural Induction

Normal ageing is associated with significant changes in cognitive function, including the decline of some forms of memory. The hippocampal formation is critical to learning and memory function, and plasticity in this region declines with age. Additionally, age-related differences in plasticity are greatest at lower levels of stimulation, thus peri-threshold plasticity may be of the greatest relevance for age-related changes in cognition. Moreover, the hippocampus is prone to changes in the expression of gene products that mediate plasticity with age. The current thesis attempts to link these observations by measuring hippocampal expression of Arc, an immediate-early gene that is critical for both plasticity and memory function, using a behavioural analogue of minimal stimulation. In this paradigm, adult (11 months) and aged (23 months) F344 rats traversed a varying number of laps (i.e., 1, 3, or 5) in a triangular track. To test cholinergic influences on these dynamics, animals were also injected with physostigmine, a cholinergic agonist, which has been shown to modulate hippocampal physiology. Consistent with previous studies, a greater number of laps induced Arc in more cells across the hippocampus. In addition, age altered the Arc expression that followed different stimulation levels, but not in the way hypothesized. Aged animals, in fact, expressed more Arc following fewer laps. Additionally, we did not show any evidence of one-trial learning as has previously been demonstrated. Finally, physostigmine administration significantly increased cellular recruitment selectively in the dorsal regions of the hippocampus. These data suggest that age-related changes in neural activation are present, but complex. Additionally, these data show that physostigmine appears to augment IEG dynamics

TUOTESERTIFIOINTI VENÄJÄLLÄ

Tämän tutkimuksen tarkoituksena on antaa yleiskuva Venäjän tuotesertifioinnista ja kuvata ulkomaisten yritysten toimintatapoja sertifiointiprosessissa. Tutkimuksessa käsitellään Venäjän sertifiointivaatimuksia ja millä tavoin tullauksessa ja kansanvälisessä kaupassa vaadittavat asiakirjat (tuoteturvallisuustodistukset, luvat ja lausunnot) on mahdollista saada. Opinnäytetyön tavoitteena on antaa mahdollisimman selkeät perustiedot Venäjän tuotesertifioinnista vientiä aloitteleville yrityksille tai henkilöille. Kvalitatiivisen tutkimuksen teoreettisessa viitekehyksessä käsiteltiin sertifioinnin prosessia ja siihen liittyvää toimintoja, erilaisia sertifikaatteja, niiden tarkoituksia, sertifiointilainsäädäntöä ja -järjestelmiä. Aihetta koskevat suomenkieliset julkaisut ja seminaarit ovat harvinaisia, joten tiedon lähteinä ne ovat tärkeitä. Raportissa käytetty materiaali perustuu 25.11.2008 SCS Akatemian seminaarista ”Venäjän ja Ukrainan sertifiointi” saatuihin tietoihin. Tässä annetaan käsitys siitä, minkälaisia sertifiointivaatimuksia Venäjällä on ja miten niitä tulee noudattaa. Tutkimuksen empiirinen osa suoritettiin case-yritykseksi valitun OOO Luhta Fashion Groupin työskentelyn kautta. Valitun yrityksen pohjalta käsiteltiin hygienialausunnon, GOST-R-sertifikaatin ja vastaavuusvakuutuksen prosesseja. Saatujen tietojen pohjalta yritykset osaavat varautua tarpeellisiin kuluihin ja aikavieviin sertifiointiprosesseihin

Chromatin from sperm of Bivalvia molluscs Specific features of nucleosomal organization

AbstractIn chromatin from the sperm of two Bivalvia molluscs a highly basic low molecular mass sperm-specific protein (S-protein) has been found in addition to the full complement of histones. It is shown that sperm chromatin preserves nucleosomal organization, some parameters of which are specific: (i) DNase I cuts DNA within the sperm nuclei with dinucleosomal periodicity; (ii) linker DNA of the nucleosome is significantly elongated. The S-protein is shown to be located on the linker DNA

Real-time problem determination in distributed systems using active probing

Abstract We describe algorithms and an architecture for a real-time problem determination system that uses online selection of most-informative measurements -the approach called herein active probing. Probes are end-to-end test transactions which gather information about system components. Active probing allows probes to bc selected and sent on-demand, in response to one's belief about the state of the system. At each step the most informative next probe is computed and sent. As probe results are received, belief about the system state is updated using probabilistic inference. This process continues until the problem is diagnosed. We demonstrate through both analysis and simulation that the active probing scheme greatly reduces both the number of probes and the time needed for localizing the problem when compared with non-active probing schemes

Multi-fault Diagnosis in Dynamic Systems

In this paper, we consider the task of real-time event correlation and problem diagnosis. We present simple, linear-time aproach that extends commonly used diagnostic techniques (such as codebook [2] and active probing [5]) to allow multiple fault diagnosis and change detection in dynamically changing systems (under certain assumptions about the fault occurrences). We demonstrate empirically the advantages of our approach. 1

Active probing strategies for problem diagnosis in distributed systems

We address the task of problem determination in a distributed system using probes, or test transactions, which gather information about system components. Effective probing requires minimizing the cost of probing while maximizing the diagnostic accuracy of the probe set. We show that pre-planning an optimal probe set is NP-hard and present polynomial-time approximation algorithms that perform well. We then implement an active probing strategy which selects probes dynamically and show that it yields a significant reduction in probe set size.

Problem Diagnosis in Distributed Systems using Active Probing

As distributed systems continue to grow in size and complexity, scalable and cost-effective techniques are needed for performing tasks such as problem determination and fault diagnosis. We address these tasks using probes, or end-to-end test transactions, which gather information about system components (e.g., using IBM's EPP technology). Effective probing requires minimizing the cost of probing while maximizing the diagnostic accuracy of the probe set. In this paper we introduce an information-theoretic approach to optimal probe set selection, and combine it with real-time probabilistic diagnosis using Bayesian networks. We show that selecting a pre-planned optimal probe set is NP-hard, but there exist polynomial-time approximation algorithms that perform well. Finally, the main contribution of the paper is a novel approach called active probing that allows adaptive, on-demand selection of most-informative probes, based on the current state of diagnosis. We demonstrate through both analysis and simulation that the active probing scheme can greatly reduce the number of probes (by almost 70% in one of our practical applications) and the time needed for localizing the problem when compared with a non-active probing scheme

Real-time Problem Determination in Distributed Systems using Active Probing

We describe algorithms and an architecture for a real-time problem determination system that uses online selection of most-informative measurements – the approach called herein active probing. Probes are end-to-end test transactions which gather information about system components. Active probing allows probes to be selected and sent on-demand, in response to one’s belief about the state of the system. At each step the most informative next probe is computed and sent. As probe results are received, belief about the system state is updated using probabilistic inference. This process continues until the problem is diagnosed. We demonstrate through both analysis and simulation that the active probing scheme greatly reduces both the number of probes and the time needed for localizing the problem when compared with non-active probing schemes. Keywords self-managing networks, real-time monitoring and problem determination, end-to-end response time measurements, AI techniques/probabilistic inference, information theory 1