Kaularankamurtumien esiintyvyys ja hoito Tampereen yliopistollisessa sairaalassa vuosina 1987-1996

Johdanto: Kaularankamurtumat ovat henkeä uhkaavia vammoja. Niiden seurauksena potilaalle voi jäädä pysyviä toimintakykyä heikentäviä neurologisia oireita. Tämän tutkimuksen tarkoituksena on selvittää kaularankamurtumien esiintyvyyttä ja hoitokäytäntöjä sekä niiden muutosta Tampereen yliopistollisessa sairaalassa vuosien 1987 ja 1996 välillä. Aineisto: Tutkimus on retrospektiivinen potilasasiakirjoihin perustuva tutkimus. Potilaat kerättiin Tampereen yliopistollisen sairaalan potilasarkistoista. Tutkimuksessa tarkasteltiin ainoastaan tapa-turmaisia kaularankamurtumia 1987-1996 välillä. Tiedot kerättiin vuosi tapaturmasta eteenpäin. Tulokset: Tutkimuksen kriteerit täytti 329 potilastapausta. Näistä 71,8 % (234/326) oli miehiä. Tut-kimus populaation mediaani ikä oli 40,5 vuotta (11 kuukautta-88 vuotta). Auto-onnettomuudet olivat yleisin vammamekanismi 40,5 % (132/326). Kaikista kaularankamurtumista 26,0 % (85/326) tapahtui päihtyneenä. Yleisin murtuman taso oli C2 29,1 % (112/326). Selkäydinvaurion sai 13,5 % (44/326) potilaista. Sairaalahoitopäiviä oli keskimäärin 13,9 (95% luottamusväli11,7-16,2) ja operatiivisen hoidon sai 28,5 % (93/326) potilaista. Johtopäätökset: Kaularankamurtumien hoito on muuttunut vuosien 1987 ja 1996 välillä huomattavasti. Operatiiviset menetelmät ovat lisääntyneet. Halovest-hoidon käyttö on seuranta-aikana vähentynyt. Nuorten miesten joukossa auto-onnettomuudet ja päihtyneenä syntyneet vammat ovat hyvin yleisiä

Ontology-based negotiation and enforcement of privacy constraints in collaborative knowledge discovery

Many people could benefit from collecting and analyzing their own personal digital data, but most do not possess the necessary expertise to do so. Remote collaboration with knowledge discovery experts who do possess this expertise is a possible solution to this conundrum but raises a number of issues of its own, one of which is preserving the data owner's privacy. It is up to the data owner to decide how much data to share with a data analyst, but withholding too much will make the analyst unable to help the data owner effectively, so it is necessary to find a trade-off between these two conflicting interests. We propose a solution whereby the data requirements imposed by analysis tasks and the access restrictions imposed by privacy constraints are encoded formally using an ontology, enabling automatic detection of conflicts. Once a conflict has been identified, the data owner and the data analyst can negotiate a resolution, possibly by transforming the data using a method that makes it no longer sensitive from the data owner's perspective while sufficiently preserving its utility from the data analyst's perspective. Using such an ontology, data owners and data analysts tap into a knowledge base of privacy-preserving data transformations, each with known effects on the utility of the transformed data for analysis. This makes it easier to find an acceptable trade-off between privacy and utility in future collaborations

Semi-automatic Maintenance of Regression Models: an Application in the Steel Industry

Software applications used in the controlling and planning of production processes commonly make use of predictive statistical models. Changes in the process involve a more or less regular need for updating the prediction models on which the operational software applications are based. The objective of this article is • to provide information which helps to design semiautomatic systems for the maintenance of statistical prediction models and • to describe a proof-of-concept implementation in an industrial application. The system developed processes the production data and provides an easy-to-use interface to construct updated models and introduce them into a software application. The article presents the architecture of the maintenance system, with a description of the algorithms that cause the system’s functionality. The system developed was implemented for keeping up-to-date prediction models which are in everyday use in a steel plate mill in the planning of the mechanical properties of steel products. The conclusion of the results is that the semi-automatic approach proposed is competitive with fully automatic and manual approaches. The benefits include good prediction accuracy and decreased workload of the deployment of updated model versions

Spatially varying peatland initiation, Holocene development, carbon accumulation patterns and radiative forcing within a subarctic fen

High latitude peatlands act as globally important carbon (C) sinks and are in constant interaction with the atmosphere. Their C storage formed during the Holocene. In the course of time, the aggregate effect of the C fluxes on radiative forcing (RF) typically changes from warming to cooling, but the timing of this shift varies among different peatlands. Here we investigated Holocene peatland development, including vegetation history, vertical peat growth and the lateral expansion of a patterned subarctic fen in northern Finland by means of multiple sampling points. We modelled the Holocene RF by combining knowledge on past vegetation communities based on plant macrofossil stratigraphies and present in situ C flux measurements. The peatland initiated at ca. 9500 calibrated years Before Present (cal yr BP), and its lateral expansion was greatest between ca. 9000 and 7000 cal yr BP. After the early expansion, vertical peat growth proceeded very differently in different parts of the peatland, regulated by internal and external factors. The pronounced surface microtopography, with high strings and wet (larks, started to form only after ca. 1000 cal yr BP. C accumulation within the peatland recorded a high degree of spatial variability throughout its history, including the recent past. We applied two flux scenarios with different interpretation of the initial peatland development phases to estimate the RF induced by C fluxes of the fen. After ca. 4000 cal yr BP, at the latest, the peatland RF has been negative (cooling), mainly driven by C uptake and biomass production, while methane emissions had a lesser role in the total RF. Interestingly, these scenarios suggest that the greatest cooling effect took place around ca. 1000 cal yr BP, after which the surface microtopography established. The study demonstrated that despite the high spatial heterogeneity and idiosyncratic behaviour of the peatland, the RF of the studied fen followed the general development pattern of more southern peatlands. Holocene climate variations and warm phases did not seem to induce any distinctive and consistent peatland-scale patterns in C accumulation, whereas our data suggests that the changes in vegetation related to autogenic succession were reflected in the C accumulation patterns and RF more clearly. (C) 2020 Elsevier Ltd. All rights reserved.Peer reviewe

The effect of rainfall amount and timing on annual transpiration in a grazed savanna grassland

The role of precipitation (P) variability with respect to evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E), from savannas continues to draw significant research interest given its relevance to a number of ecohydrological applications. Our study reports on 6 years of measured ET and estimated T and E from a grazed savanna grassland at Welgegund, South Africa. Annual P varied significantly with respect to amount (508 to 672 mm yr(-1)), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy-covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T for the 4 wet years with frequent early wet-season rainfall was nearly constant, 326 +/- 19 mm yr(-1) (T/ET=0.51), but was lower and more variable between the 2 dry years (255 and 154 mm yr(-1), respectively). Annual T and T/ET were linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grasses as well as trees' ability to use water from deeper layers. During extreme drought, grasses respond to water availability with a dieback-regrowth pattern, reducing leaf area and transpiration and, thus, increasing the proportion of transpiration contributed by trees. The works suggest that the early-season P distribution explains the interannual variability in T, which should be considered when managing grazing and fodder production in these grasslands.Peer reviewe

Meteorological responses of carbon dioxide and methane fluxes in the terrestrial and aquatic ecosystems of a subarctic landscape

The subarctic landscape consists of a mosaic of forest, peatland, and aquatic ecosystems and their ecotones. The carbon (C) exchange between ecosystems and the atmosphere through carbon dioxide (CO2) and methane (CH4) fluxes varies spatially and temporally among these ecosystems. Our study area in Kaamanen in northern Finland covered 7 km2 of boreal subarctic landscape with upland forest, open peatland, pine bogs, and lakes. We measured the CO2 and CH4 fluxes with eddy covariance and chambers between June 2017 and June 2019 and studied the C flux responses to varying meteorological conditions. The landscape area was an annual CO2 sink of −45 ± 22 and −33 ± 23 g C m−2 and a CH4 source of 3.0 ± 0.2 and 2.7 ± 0.2 g C m−2 during the first and second study years, respectively. The pine forest had the largest contribution to the landscape-level CO2 sink, −126 ± 21 and −101 ± 19 g C m−2, and the fen to the CH4 emissions, 7.8 ± 0.2 and 6.3 ± 0.3 g C m−2, during the first and second study years, respectively. The lakes within the area acted as CO2 and CH4 sources to the atmosphere throughout the measurement period, and a lake located downstream from the fen with organic sediment showed 4-fold fluxes compared to a mineral sediment lake. The annual C balances were affected most by the rainy peak growing season in 2017, the warm summer in 2018, and a heatwave and drought event in July 2018. The rainy period increased ecosystem respiration (ER) in the pine forest due to continuously high soil moisture content, and ER was on a level similar to the following, notably warmer, summer. A corresponding ER response to abundant precipitation was not observed for the fen ecosystem, which is adapted to high water table levels, and thus a higher ER sum was observed during the warm summer 2018. During the heatwave and drought period, similar responses were observed for all terrestrial ecosystems, with decreased gross primary productivity and net CO2 uptake, caused by the unfavourable growing conditions and plant stress due to the soil moisture and vapour pressure deficits. Additionally, the CH4 emissions from the fen decreased during and after the drought. However, the timing and duration of drought effects varied between the fen and forest ecosystems, as C fluxes were affected sooner and had a shorter post-drought recovery time in the fen than forest. The differing CO2 flux response to weather variations showed that terrestrial ecosystems can have a contrasting impact on the landscape-level C balance in a changing climate, even if they function similarly most of the time

Sampling Rate Effects on Resting State fMRI Metrics

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning

Towards a concentration closure of sub-6 nm aerosol particles and sub-3 nm atmospheric clusters

Atmospheric clusters play a key role in atmospheric new particle formation and they are a sensitive indicator for atmospheric chemistry. Both the formation and loss of atmospheric clusters include a complex set of interlinked physical and chemical processes, and therefore their dynamics is highly non-linear. Here we derive a set of simple equations to estimate the atmospheric cluster concentrations in size ranges of 1.5–2 nm and 2–3 nm as well as 3–6 nm aerosol particles. We compared the estimated concentrations with measured ones both in a boreal forest site (the SMEAR II station in Hyytiälä, Finland) and in an urban site (the AHL/BUCT station in Beijing, China). We made this comparison first for 3–6 nm particles, since in this size range observations are more reliable than at smaller sizes, and then repeated it for the 2–3 nm size range. Finally, we estimated cluster concentrations in the 1.5–2 nm size range. Our main finding is that the present observations are able to detect a major fraction of existing atmospheric clusters.Atmospheric clusters play a key role in atmospheric new particle formation and they are a sensitive indicator for atmospheric chemistry. Both the formation and loss of atmospheric clusters include a complex set of interlinked physical and chemical processes, and therefore their dynamics is highly non-linear. Here we derive a set of simple equations to estimate the atmospheric cluster concentrations in size ranges of 1.5–2 nm and 2–3 nm as well as 3–6 nm aerosol particles. We compared the estimated concentrations with measured ones both in a boreal forest site (the SMEAR II station in Hyytiälä, Finland) and in an urban site (the AHL/BUCT station in Beijing, China). We made this comparison first for 3–6 nm particles, since in this size range observations are more reliable than at smaller sizes, and then repeated it for the 2–3 nm size range. Finally, we estimated cluster concentrations in the 1.5–2 nm size range. Our main finding is that the present observations are able to detect a major fraction of existing atmospheric clusters.Peer reviewe

Search for Microscopic Black Hole Signatures at the Large Hadron Collider

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Measurement of W-gamma and Z-gamma production in pp collisions at sqrt(s) = 7 TeV

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