Deadwood Characteristics in Mature and Old-Growth Birch Stands and Their Implications for Carbon Storage

As one of the most abundant tree species in the hemiboreal zone, birch is important from both commercial and biodiversity perspectives. While old-growth deciduous stands are important for biodiversity conservation with an emphasis on deadwood availability, the role that deadwood in these stands plays in carbon sequestration remains unclear. We studied mature (71–110 years old) and old-growth (121–150 years old) birch stands on fertile mineral soils. The marginal mean deadwood volume was 43.5 ± 6.4 m3 ha−1 in all mature stands, 51.3 ± 7.1 m3 ha−1 in recently unmanaged mature stands, and 54.4 ± 4.4 m3 ha−1 in old-growth stands; the marginal mean deadwood carbon pool for each stand type was 5.4 ± 0.8 t·ha−1, 6.3 ± 0.9 t·ha−1, and 7.9 ± 0.6 t·ha−1, respectively. Deadwood volume was not related to stand productivity in terms of stand basal area, stand height, or stand age. The difference between mature and old-growth stands remained non-significant (p < 0.05). A high volume of deadwood was almost continuously present throughout the landscape in assessed unmanaged sites; moreover, 88% of sample plots in old-growth stands and 63% of sample plots in mature stands had a deadwood volume higher than 20 m3·ha−1. Old-growth stands had a slightly greater volume of large deadwood than unmanaged mature stands; in both, almost half of the deadwood was more than 30 cm in diameter and approximately one-fifth had a diameter greater than 40 cm. Both groups of stands had similar proportions of coniferous and deciduous deadwood and lying and standing deadwood. Old-growth stands had a higher volume of recently and weakly decayed wood, indicating increased dieback during recent years.

Natural course of scoliosis and lifetime risk of scoliosis surgery in spinal muscular atrophy

ObjectiveTo investigate the natural course of scoliosis and to estimate lifetime probability of scoliosis surgery in spinal muscular atrophy (SMA).MethodsWe analyzed cross-sectional data from 283 patients from our population-based cohort study. Additional longitudinal data on scoliosis progression and spinal surgery were collected from 36 consecutive patients who received scoliosis surgery at our center.ResultsThe lifetime probability of receiving scoliosis surgery was ≈80% in SMA types 1c and 2. Patients with type 2 who only learned to sit (type 2a) were significantly younger at time of surgery than those who learned to sit and stand (type 2b). The lifetime risk of surgery was lower in type 3a (40%) and strongly associated with age at loss of ambulation: 71% in patients losing ambulation before 10 years of age vs 22% losing ambulation after the age of 10 years (p = 0.005). In type 3a, preserving the ability to walk 1 year longer corresponded to a 15% decrease in lifetime risk of scoliosis surgery (hazard ratio 0.852, p = 0.017). Scoliosis development was characterized by initial slow progression, followed by acceleration in the 1.5- to 2-year period before surgery.ConclusionThe lifetime probability of scoliosis surgery is high in SMA types 1c and 2 and depends on age at loss of ambulation in type 3. Motor milestones such as standing that are not part of the standard classification system are of additional predictive value. Our data may act as a reference to assess long-term effects of new SMA-specific therapies.

Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development

The rapid increase in the quantity of customer data has promoted the necessity to analyse these data. Recent progress in text mining has enabled analysis of unstructured text data such as customer suggestions, customer complaints and customer feedback. Much research has been attempted to use insights gained from text mining to identify customer needs to guide development of market-oriented products. However, the previous research has a drawback that identifies limited customer needs based on product features. To overcome the limitation, this paper presents application of text mining analysis of customer complaints to identify customers’ true needs by using the Outcome-Driven Innovation (ODI) method. This paper provides a method to analyse customer complaints by using the concept of job. The ODI-based analysis contributes to identification of customer latent needs during the pre-execution and post-execution steps of product use by customers that previous methods cannot discover. To explain how the proposed method can identify customer requirements, we present a case study of stand-type air conditioners. The analysis identified two needs that experts had not identified but regarded as important. This research helps to identify requirements of all the points at which customers want to obtain help from the product.