Influence of the training set composition on the estimation performance of linear ECG-lead transformations.

Linear ECG-lead transformations (LELTs) are used to estimate unrecorded target leads by applying a number of recorded basis leads to a LELT matrix. Such LELT matrices are commonly developed using training datasets that are composed of ECGs that belong to different diagnostic classes (DCs). The aim of our research was to assess the influence of the training set composition on the estimation performance of LELTs that estimate target leads V1, V3, V4 and V6 from basis leads I, II, V2 and V5 of the 12-lead ECG. Our assessment was performed using ECGs from the three DCs left ventricular hypertrophy, right bundle branch block and normal (ECGs without abnormalities). Training sets with different DC compositions were used for the development of LELT matrices. These matrices were used to estimate the target leads of different test sets. The estimation performance of the developed matrices was quantified using root mean square error values calculated between derived and recorded target leads. Our findings indicate that unbalanced training sets can lead to LELTs that show large estimation performance variability across different DCs. Balanced training sets were found to produce LELTs that performed well across multiple DCs. We recommend balanced training sets for the development of LELTs

Development and Reliability of Countermovement Jump Performance in Youth Athletes at Pre-, Circa- and Post-Peak Height Velocity

The purpose of this study was to establish the intrasession reliability of various outcome, propulsion and braking phase countermovement jump (CMJ) variables and to compare the mean differences in youth athletes at different stages of maturity. Thirty male participants, aged 10-16 years, were grouped as either pre-, circa- or post-peak height velocity (PHV) according to their percentage of predicted adult height. All participants performed 3 CMJ trials on a force plate, sampling at 1000 Hz. A one-way ANOVA identified statistically significant differences between maturity groups for all CMJ variables (P<0.05) excluding propulsion peak rate of force development (RFD), braking peak velocity and countermovement depth. Post-hoc analysis revealed that the significant differences in CMJ variables were between the pre- to post- and circa- to post-PHV groups (P <0.05), with moderate to very large effect sizes. Relative and absolute reliability improved with maturity as the post-PHV group demonstrated superior reliability scores (ICC = 0.627-0.984; CV% = 3.25-21.55) compared to circa- (ICC = 0.570-0.998; CV% = 1.82-20.05) and pre-PHV groups (ICC= 0.851-0.988; CV% = 2.16-14.12). In summary, these results suggest that the biggest differences in CMJ performance are observed between preto post- and circa- to post-PHV, and that careful consideration is warranted when selecting variables in youth athletes at pre- and circa-PHV, given the lower reliability scores observed

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Funder: Critical Ecosystem Partnership Fund; Id: http://dx.doi.org/10.13039/100013724Funder: Global Environment Facility; Id: http://dx.doi.org/10.13039/100011150Funder: Danish International Development Agency; Id: http://dx.doi.org/10.13039/501100011054Funder: Scottish Government’s Rural and Environment Science and Analytical Services DivisionFunder: Finnish International Development AgencyFunder: Leverhulme Trust; Id: http://dx.doi.org/10.13039/501100000275Societal Impact Statement: Large areas of tropical forest are degraded. While global tree cover is being mapped with increasing accuracy from space, much less is known about the quality of that tree cover. Here we present a field protocol for rapid assessments of forest condition. Using extensive field data from Tanzania, we show that a focus on remotely‐sensed deforestation would not detect significant reductions in forest quality. Radar‐based remote sensing of degradation had good agreement with the ground data, but the ground surveys provided more insights into the nature and drivers of degradation. We recommend the combined use of rapid field assessments and remote sensing to provide an early warning, and to allow timely and appropriately targeted conservation and policy responses. Summary: Tropical forest degradation is widely recognised as a driver of biodiversity loss and a major source of carbon emissions. However, in contrast to deforestation, more gradual changes from degradation are challenging to detect, quantify and monitor. Here, we present a field protocol for rapid, area‐standardised quantifications of forest condition, which can also be implemented by non‐specialists. Using the example of threatened high‐biodiversity forests in Tanzania, we analyse and predict degradation based on this method. We also compare the field data to optical and radar remote‐sensing datasets, thereby conducting a large‐scale, independent test of the ability of these products to map degradation in East Africa from space. Our field data consist of 551 ‘degradation’ transects collected between 1996 and 2010, covering >600 ha across 86 forests in the Eastern Arc Mountains and coastal forests. Degradation was widespread, with over one‐third of the study forests—mostly protected areas—having more than 10% of their trees cut. Commonly used optical remote‐sensing maps of complete tree cover loss only detected severe impacts (≥25% of trees cut), that is, a focus on remotely‐sensed deforestation would have significantly underestimated carbon emissions and declines in forest quality. Radar‐based maps detected even low impacts (<5% of trees cut) in ~90% of cases. The field data additionally differentiated types and drivers of harvesting, with spatial patterns suggesting that logging and charcoal production were mainly driven by demand from major cities. Rapid degradation surveys and radar remote sensing can provide an early warning and guide appropriate conservation and policy responses. This is particularly important in areas where forest degradation is more widespread than deforestation, such as in eastern and southern Africa

Environmental correlates of phylogenetic endemism in amphibians and the conservation of refugia in the Coastal Forests of Eastern Africa

Aims To quantify the spatial distribution of amphibian phylogenetic endemism (PE), an indicator of potential refugia, to test PE for correlations with current and historical environmental predictors, and to evaluate the effectiveness of current protected areas at conserving evolutionary history. Location Coastal Forests of Eastern Africa (CFEA) and the adjacent low-elevation Eastern Afromontane (EA). Methods We integrated new and existing spatial and phylogenetic data to map PE for almost the full amphibian assemblage (41 of 55 species), including 35 intraspecific lineages from several species and complexes showing high phylogeographic structure. Using spatial and non-spatial regressive models, we tested whether PE can be predicted by measures of Quaternary climate change, forest stability, topographic heterogeneity and current climate. PE results were intersected with the protected area network to evaluate current conservation effectiveness. Results We detect refugia in Tanzania and coastal Kenya previously identified as CFEA centres of endemism but also new areas (lowland Tanga region and Pangani river, Zaraninge forest, Mafia island, Matumbi hills). Results show that refugia for amphibians (high PE) are located in areas with long-term Quaternary climate stability and benign current climate (high precipitation of driest quarter, high annual precipitation), with climatically unstable areas demonstrating low PE. Conservation analyses revealed that ten PE hotspots account for over 25% of the total PE, but only small parts of these areas are under conservation protection. Main Conclusions Utilizing cryptic diversity from novel phylogeographic data and distribution modelling improves our understanding of endemism patterns, with climate stability being strongly correlated with the distribution of PE. Our analyses point towards high PE areas being refugia, which require an urgent need to consolidate protected areas within centres of endemism in this highly threatened biodiversity hotspot.Humer Foundation via the Centre for African Studies Basel; Stipendienkommission für Nachwuchskräfte; COSTECH, Grant/Award Number: 2013-341-NA-2013-121; Freiwillige Akademische Gesellschaft Basel (FAG); Kenya Wildlife Service, Grant/Award Number: KWS/ BRM/5001. University of Basel Travel Fund. Kenya Forest service permit, MUS/1/KFS/ VOL.II/

A transition solvent strategy to print polymer:fullerene films using halogen-free solvents for solar cell applications

10.1016/j.orgel.2013.10.025Organic Electronics: physics, materials, applications152449-460OERL