Vedegenskaper i härskande och behärskade granar vid Remingstorp : Wood properties in dominant and sub-dominant trees of Norway spruce at Remingstorp

Variation in wood properties for Picea abies trees and logs of different dimensions has been studied at two sites in southern Sweden of different site quality class. Trees have been classified as dominant or sub-dominant, according to their height. Log and board grades were classified and strength grade of boards, basic density and annual ring width measured. A similar study made on four northern sites was used as reference material.Sub-dominant trees were of superior quality in comparison to dominant trees, when classified by log and board grades or strength grading. Differences were accentuated for the second log where the sub-dominant trees had superior strength and low amount of boards with coarse branches. The results correspond well to those from the northern region, Jämtland. The classifica¬tion of boards as well as bending strength indicated superior properties on timber from northern sites even though the basic density was similar.

Development of a molecular test to determine the vitality status of Norway spruce (Picea abies) seedlings during frozen storage

In boreal forest regions, a great portion of forest tree seedlings are stored indoors in late autumn to prevent seedlings from outdoor winter damage. For seedlings to be able to survive in storage it is crucial that they store well and can cope with the dark and cold storage environment. The aim of this study was to search for genes that can determine the vitality status of Norway spruce (Picea abies (L.) Karst.) seedlings during frozen storage. Furthermore, the sensitivity of the ColdNSure (TM) test, a gene activity test that predicts storability was assessed. The storability of seedlings was tested biweekly by evaluating damage with the gene activity test and the electrolyte leakage test after freezing seedlings to -25 A degrees C (the SELdiff-25 method). In parallel, seedlings were frozen stored at -3 A degrees C. According to both methods, seedlings were considered storable from week 41. This also corresponded to the post storage results determined at the end of the storage period. In order to identify vitality indicators, Next Generation Sequencing (NGS) was performed on bud samples collected during storage. Comparing physiological post storage data to gene analysis data revealed numerous vitality related genes. To validate the results, a second trial was performed. In this trial, gene activity was better in predicting seedling storability than the conventional freezing test; this indicates a high sensitivity level of this molecular assay. For multiple indicators a clear switch between damaged and vital seedlings was observed. A collection of indicators will be used in the future development of a commercial vitality test.

Nordic Journal of English Studies : Irish Studies in the Nordic Countries

This special issue of Nordic Journal of English Studies is devoted to the research in Irish Studies being carried out in Scandinavia by a group of scholars based in Denmark, Norway and Sweden, as well as scholars associated—in one way or another—with Scandinavia. Denmark is represented by the University of Aalborg; Norway, by scholars affiliated to the Universities of Agder, the Artic University of Norway, Bergen, and Stavanger; and Sweden is represented by scholars from the universities of Dalarna, Göteborg, Stockholm, Södertörn and Umeå. Included also in this special issue is the work of two former students, who completed their Masters’ degree in Irish literature at DUCIS (Dalarna University Centre for Irish Studies), Sweden—from Norway and China respectively. The collection also contains an article by Dara Waldron, Limerick Institute of Technology, Ireland, whof recently presented his research at the Higher Seminar in Dalarna. Contributions by the Irish poet, Mary O’Donnell, who participated in the Nordic Irish Studies Network (NISN) conference, hosted by DUCIS in December 2012, are also included.

Pedal : identification of models for duodenal administration of levodopa

Backgound and aims: The main purpose of the PEDAL study is to identify and estimate sample individual pharmacokinetic- pharmacodynamic (PK/PD) models for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Other objectives are to study the absorption of Duodopa® and to form a basis for power calculation for a future larger study. PK/PD based on oral levodopa is problematic because of irregular gastric emptying. Preliminary work with data from [Gundert-Remy U et al. Eur J Clin Pharmacol 1983;25:69-72] suggested that levodopa infusion pharmacokinetics can be described by a two-compartment model. Background research led to a hypothesis for an effect model incorporating concentration-unrelated fluctuations, more complex than standard E-max models. Methods: PEDAL involved a few patients already on Duodopa®. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Data collection continued until the clinical effect was back at baseline. The procedure was repeated on two non-consecutive days per patient. The following data were collected in 5 to 15 minutes intervals: i) Accelerometer data. ii) Three e-diary questions about ability to walk, feelings of “off” and “dyskinesia”. iii) Clinical assessment of motor function by a physician. iv) Plasma concentrations of levodopa, carbidopa and the metabolite 3-O-methyldopa. The main effect variable will be the clinical assessment. Results: At date of abstract submission, lab analyses were currently being performed. Modelling results, simulation experiments and conclusions will be presented in our poster.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.