Enhancing Tree Species Identification in Forestry and Urban Forests through Light Detection and Ranging Point Cloud Structural Features and Machine Learning

As remote sensing transforms forest and urban tree management, automating tree species classification is now a major challenge to harness these advances for forestry and urban management. This study investigated the use of structural bark features from terrestrial laser scanner point cloud data for tree species identification. It presents a novel mathematical approach for describing bark characteristics, which have traditionally been used by experts for the visual identification of tree species. These features were used to train four machine learning algorithms (decision trees, random forests, XGBoost, and support vector machines). These methods achieved high classification accuracies between 83% (decision tree) and 96% (XGBoost) with a data set of 85 trees of four species collected near Krakow, Poland. The results suggest that bark features from point cloud data could significantly aid species identification, potentially reducing the amount of training data required by leveraging centuries of botanical knowledge. This computationally efficient approach might allow for real-time species classification

Design and Implementation of an Ultrasonic Localization System for Wireless Sensor Networks using Angle-of-Arrival and Distance Measurement

AbstractThis paper presents a localization system for Wireless Sensor Networks (WSN) based on ultrasonic (US) Time-of-Flight (ToF) measurements. The participants send out US pulses while a central localization unit measures the Time-Difference-of-Arrival (TDoA) between four US sensors to calculate the Angle-of-Arrival (AoA). The radio frequency (RF) transceiver of the sensor nodes enables distance measurements using TDoA (US vs. RF) in addition. This improves the localization accuracy significantly since the estimated distance from triangulation suffers excessively from even small angle errors. Several filter stages including Kalman-filtering minimize the number of outliers and fluctuations of the calculated distances and angles. Those computed polar coordinates (angle/distance) are converted into a Cartesian form and forwarded to a base station which is connected to a PC. The mean error and standard deviation of the angle and distance measurements (1.36 ¡ ± 0.39 ¡ / 1.00cm ± 0.14cm) lead to a small mean localization error of 4.21cm and a standard deviation of 0.57cm

The motion of trees in the wind : a data synthesis

Interactions between wind and trees control energy exchanges between the atmosphere and forest canopies. This energy exchange can lead to the widespread damage of trees, and wind is a key disturbance agent in many of the world’s forests. However, most research on this topic has focused on conifer plantations, where risk management is economically important, rather than broadleaf forests, which dominate the forest carbon cycle. This study brings together tree motion time-series data to systematically evaluate the factors influencing tree responses to wind loading, including data from both broadleaf and coniferous trees in forests and open environments. Wefoundthatthetwomostdescriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a tree sways and is strongly related to tree height, and (b) the slope of the power spectrum, which is related to the efficiency of energy transfer from wind to trees. Intriguingly, the slope of the power spectrum was found to remain constant from medium to high wind speeds for all trees in this study. This suggests that, contrary to some predictions, damping or amplification mechanisms do not change dramatically at high wind speeds, and therefore wind damage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of their response to wind loading. Specifically, the fundamental frequency of forest conifers was related to their size according to the cantilever beam model (i.e. vertically distributed mass), whereas broadleaves were better approximated by the simple pendulum model (i.e. dominated by the crown). Forest conifers also had a steeper slope of the power spectrum. We interpret these finding as being strongly related to tree architecture; i.e. conifers generally have a simple shape due to their apical dominance, whereas broadleaves exhibit a much wider range of architectures with more dominant crowns

A Novel murine model identifies cooperating mutations and therapeutic targets critical for chronic myeloid leukemia progression

The introduction of highly selective ABL-tyrosine kinase inhibitors (TKIs) has revolutionized therapy for chronic myeloid leukemia (CML). However, TKIs are only efficacious in the chronic phase of the disease and effective therapies for TKI-refractory CML, or after progression to blast crisis (BC), are lacking. Whereas the chronic phase of CML is dependent on BCR-ABL, additional mutations are required for progression to BC. However, the identity of these mutations and the pathways they affect are poorly understood, hampering our ability to identify therapeutic targets and improve outcomes. Here, we describe a novel mouse model that allows identification of mechanisms of BC progression in an unbiased and tractable manner, using transposon-based insertional mutagenesis on the background of chronic phase CML. Our BC model is the first to faithfully recapitulate the phenotype, cellular and molecular biology of human CML progression. We report a heterogeneous and unique pattern of insertions identifying known and novel candidate genes and demonstrate that these pathways drive disease progression and provide potential targets for novel therapeutic strategies. Our model greatly informs the biology of CML progression and provides a potent resource for the development of candidate therapies to improve the dismal outcomes in this highly aggressive disease.Work in the Huntly laboratory is funded by CRUK, The European Research Council (ERC), Leukaemia Lymphoma Research, the Kay Kendall Leukaemia Fund, Wellcome Trust, the Medical Research Council (UK), the Leukemia Lymphoma Society America and the Cambridge NIHR Biomedical Research centre. David Adams is funded by Cancer Research UK and Wellcome Trust. Steffen Koschmieder has received funding from Deutsche José Carreras Leukämie-Stiftung (DJCLS; grant 10/23).This is the final published version. It first appeared at http://dx.doi.org/10.1084/jem.2014166

Immigration, Acculturation and Chronic Back and Neck Problems Among Latino-Americans

Higher acculturation is associated with increased obesity and depression among Latino-Americans, but not much is known about how acculturation is related to their prevalence of back and neck problems. This study examines whether acculturation is associated with the 12-month prevalence of self-reported chronic back or neck problems among US-born and immigrant Latinos. We performed multivariable logistic regression analysis of data from 2,553 noninstitutionalized Latino adults from the 2002–2003 National Latino and Asian American Survey (NLAAS). After adjusting for demographic, physical and mental health indicators, English proficiency, nativity and higher generational status were all significantly positively associated with the report of chronic back or neck problems. Among immigrants, the proportion of lifetime in the US was not significantly associated. Our findings suggest that the report of chronic back or neck problems is higher among more acculturated Latino-Americans independent of health status, obesity, and the presence of depression

COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access

Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative ‘coordination of standards in metabolomics’ (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities’ participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards

Performance of the RADPHI Detector and Trigger in a High Rate Tagged Photon Beam

We describe the design and operation of a detector system for measuring all-photon decays of mesons photoproduced in a tagged photon beam with energies between 4.3 and 5.4 GeV and a flux of 5×107 tagged photons per second. Photons from meson decays were detected with a lead-glass calorimeter with an energy resolution of 11% at 1 GeV. Various veto and trigger components were also present. Final states with as many as six photons were successfully detected and reconstructed

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe