How Sustainable Are North American Wood Supplies?

This paper analyzes the current wood supply estimates for North America. The result of the analysis casts doubts whether the North American supplies are sustainable. It is obvious that current estimates do not consider many of the aspects of sustainable forest management but are based on a concept of the availability of timber. It can be concluded that there is a lack of consistent national projections in both the USA and Canada. The North American analyses do not take into account that the wood supply issue is driven by the political economy and not only by the market economy. North America has a lot to gain if future analyses of the supply would be carried out based on a political economic concept

Peculiar Velocities of Galaxy Clusters

We investigate the peculiar velocities predicted for galaxy clusters by theories in the cold dark matter family. A widely used hypothesis identifies rich clusters with high peaks of a suitably smoothed version of the linear density fluctuation field. Their peculiar velocities are then obtained by extrapolating the similarly smoothed linear peculiar velocities at the positions of these peaks. We test these ideas using large high resolution N-body simulations carried out within the Virgo supercomputing consortium. We find that at early times the barycentre of the material which ends up in a rich cluster is generally very close to a high peak of the initial density field. Furthermore the mean peculiar velocity of this material agrees well with the linear value at the peak. The late-time growth of peculiar velocities is, however, systematically underestimated by linear theory. At the time clusters are identified we find their rms peculiar velocity to be about 40% larger than predicted. Nonlinear effects are particularly important in superclusters. These systematics must be borne in mind when using cluster peculiar velocities to estimate the parameter combination $\sigma_8\Omega^{0.6}$.Comment: 8 pages, 4 figures; submitted to MNRA

Filaments in observed and mock galaxy catalogues

Context. The main feature of the spatial large-scale galaxy distribution is an intricate network of galaxy filaments. Although many attempts have been made to quantify this network, there is no unique and satisfactory recipe for that yet. Aims. The present paper compares the filaments in the real data and in the numerical models, to see if our best models reproduce statistically the filamentary network of galaxies. Methods. We apply an object point process with interactions (the Bisous process) to trace and describe the filamentary network both in the observed samples (the 2dFGRS catalogue) and in the numerical models that have been prepared to mimic the data.We compare the networks. Results. We find that the properties of filaments in numerical models (mock samples) have a large variance. A few mock samples display filaments that resemble the observed filaments, but usually the model filaments are much shorter and do not form an extended network. Conclusions. We conclude that although we can build numerical models that are similar to observations in many respects, they may fail yet to explain the filamentary structure seen in the data. The Bisous-built filaments are a good test for such a structure.Comment: 13 pages, accepted for publication in Astronomy and Astrophysic

Walking-Induced Fatigue Leads to Increased Risk in Older Adults

Background- For older adults, falls are a serious health problem, with more than 30% of people older than 65 suffering a fall at least once a year. One element often overlooked in the assessment of falls is whether a person\u27s balance, walking ability, and overall falls risk is affected by performing activities of daily living such as walking. Objective- This study assessed the immediate impact of incline walking at a moderate pace on falls risk, leg strength, reaction time, gait, and balance in 75 healthy adults from 30 to 79 years of age. Subjects were subdivided into 5 equal groups based on their age (group 1, 30-39 years; group 2, 40-49 years; group 3, 50-59 years; group 4, 60-69 years; group 5, 70-79 years). Methods- Each person\u27s falls risk (using the Physiological Profile Assessment), simple reaction time, leg strength, walking ability, and standing balance were assessed before and after a period of incline walking on an automated treadmill. The walking task consisted of three 5-minute trials at a faster than preferred pace. Fatigue during walking was elicited by increasing the treadmill incline in increments of 2 degrees (from level) every minute to a maximum of 8 degrees. Results- As predicted, significant age-related differences were observed before the walking activity. In general, increasing age was associated with declines in gait speed, lower limb strength, slower reaction times, and increases in overall falls risk. Following the treadmill task, older adults exhibited increased sway (path length 60-69 years; 10.2 ± 0.7 to 12.1 ± 0.7 cm: 70-79 years; 12.8 ± 1.1 to 15.1 ± 0.8 cm), slower reaction times (70-79 years; 256 ± 6 to 287 ± 8 ms), and declines in lower limb strength (60-69 years; 36 ± 2 to 31 ± 1 kg: 70-79 years; 32.3 ± 2 to 27 ± 1 kg). However, a significant increase in overall falls risk (pre; 0.51 ± 0.17: post; 1.01 ± 0.18) was only seen in the oldest group (70-79 years). For all other persons (30-69 years), changes resulting from the treadmill-walking task did not lead to a significant increase in falls risk. Conclusions: As most falls occur when an individual is moving and/or fatigued, assessing functional properties related to balance, gait, strength, and falls risk in older adults both at rest and following activity may provide additional insight

Aerobic training increases skin perfusion by a nitric oxide mechanism in type 2 diabetes

It is well known that a number of locally released vasodilatory and vasoconstrictive compounds can affect skin perfusion. This study investigated the effects of aerobic training on the contribution of nitric oxide (NO), prostaglandins (PG), and endothelial-derived hyperpolarizing factor (EDHF) in stimulated dorsal foot skin perfusion in individuals with type 2 diabetes (T2DM). Ten previously sedentary, older individuals with T2DM (57.0 ± 3.1 years) and nine sedentary controls (53.5 ± 3.2 years) were tested before and after undertaking six months of moderate aerobic training three times weekly in a supervised setting. All subjects underwent measurement of baseline (32°C) and heat-stimulated (40°C and 44°C) dorsal foot skin perfusion starting one hour after ingestion of a single, oral 325 mg dose of aspirin, a known inhibitor of PG synthesis. Before aspirin ingestion, a subcutaneous microdialysis probe was inserted into each foot dorsum to administer either saline (PG pathway only blocked by aspirin in the left foot) or L-NAME (N(G)-nitro-l-arginine methyl ester; thereby inhibiting both PG and NO pathways in the right foot). Normative data collected previously on subjects undergoing saline administration via microdialysis without aspirin ingestion served as a control group. Significantly lower responsiveness of maximal perfusion was found with the EDHF pathway alone unblocked compared with NO and EDHF unblocked after training. Maximal suppression attributable directly to NO, PG, and EDHF was not significantly different when examined by subject group and training status. However, contributions of NO, PG, and EDHF to maximal perfusion were significantly increased, decreased, and unchanged by aerobic training, respectively, with diabetic and control subjects combined due to nonsignificant differences between groups. Improvements in maximally stimulated dorsal foot skin perfusion resulting from six months of aerobic training appear to have primarily an NO basis, with lesser contributions from PG following training, regardless of diabetes status

Development and Validation of a Predictive Model of Acute Glucose Response to Exercise in Individuals With Type 2 Diabetes

Background: Our purpose was to develop and test a predictive model of the acute glucose response to exercise in individuals with type 2 diabetes. Design and methods: Data from three previous exercise studies (56 subjects, 488 exercise sessions) were combined and used as a development dataset. A mixed-effects Least Absolute Shrinkage Selection Operator (LASSO) was used to select predictors among 12 potential predictors. Tests of the relative importance of each predictor were conducted using the Lindemann Merenda and Gold (LMG) algorithm. Model structure was tested using likelihood ratio tests. Model accuracy in the development dataset was assessed by leave-one-out cross-validation. Prospectively captured data (47 individuals, 436 sessions) was used as a test dataset. Model accuracy was calculated as the percentage of predictions within measurement error. Overall model utility was assessed as the number of subjects with ≤ 1 model error after the third exercise session. Model accuracy across individuals was assessed graphically. In a post-hoc analysis, a mixed-effects logistic regression tested the association of individuals\u27 attributes with model error. Results: Minutes since eating, a non-linear transformation of minutes since eating, post-prandial state, hemoglobin A1c, sulfonylurea status, age, and exercise session number were identified as novel predictors. Minutes since eating, its transformations, and hemoglobin A1c combined to account for 19.6% of the variance in glucose response. Sulfonylurea status, age, and exercise session each accounted for \u3c1.0% of the variance. In the development dataset, a model with random slopes for pre-exercise glucose improved fit over a model with random intercepts only (likelihood ratio 34.5, p \u3c 0.001). Cross-validated model accuracy was 83.3%. In the test dataset, overall accuracy was 80.2%. The model was more accurate in pre-prandial than postprandial exercise (83.6% vs. 74.5% accuracy respectively). 31/47 subjects had ≤1 model error after the third exercise session. Model error varied across individuals and was weakly associated with within-subject variability in pre-exercise glucose (Odds ratio 1.49, 95% Confidence interval 1.23-1.75). Conclusions: The preliminary development and test of a predictive model of acute glucose response to exercise is presented. Further work to improve this model is discussed