81 research outputs found

    TreeGrad: Transferring Tree Ensembles to Neural Networks

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    Gradient Boosting Decision Tree (GBDT) are popular machine learning algorithms with implementations such as LightGBM and in popular machine learning toolkits like Scikit-Learn. Many implementations can only produce trees in an offline manner and in a greedy manner. We explore ways to convert existing GBDT implementations to known neural network architectures with minimal performance loss in order to allow decision splits to be updated in an online manner and provide extensions to allow splits points to be altered as a neural architecture search problem. We provide learning bounds for our neural network.Comment: Technical Report on Implementation of Deep Neural Decision Forests Algorithm. To accompany implementation here: https://github.com/chappers/TreeGrad. Update: Please cite as: Siu, C. (2019). "Transferring Tree Ensembles to Neural Networks". International Conference on Neural Information Processing. Springer, 2019. arXiv admin note: text overlap with arXiv:1909.1179

    Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

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    Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets

    Excision of HIV-1 Proviral DNA by Recombinant Cell Permeable Tre-Recombinase

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    Over the previous years, comprehensive studies on antiretroviral drugs resulted in the successful introduction of highly active antiretroviral therapy (HAART) into clinical practice for treatment of HIV/AIDS. However, there is still need for new therapeutic approaches, since HAART cannot eradicate HIV-1 from the infected organism and, unfortunately, can be associated with long-term toxicity and the development of drug resistance. In contrast, novel gene therapy strategies may have the potential to reverse the infection by eradicating HIV-1. For example, expression of long terminal repeat (LTR)-specific recombinase (Tre-recombinase) has been shown to result in chromosomal excision of proviral DNA and, in consequence, in the eradication of HIV-1 from infected cell cultures. However, the delivery of Tre-recombinase currently depends on the genetic manipulation of target cells, a process that is complicating such therapeutic approaches and, thus, might be undesirable in a clinical setting. In this report we demonstrate that E.coli expressed Tre-recombinases, tagged either with the protein transduction domain (PTD) from the HIV-1 Tat trans-activator or the translocation motif (TLM) of the Hepatitis B virus PreS2 protein, were able to translocate efficiently into cells and showed significant recombination activity on HIV-1 LTR sequences. Tre activity was observed using episomal and stable integrated reporter constructs in transfected HeLa cells. Furthermore, the TLM-tagged enzyme was able to excise the full-length proviral DNA from chromosomal integration sites of HIV-1-infected HeLa and CEM-SS cells. The presented data confirm Tre-recombinase activity on integrated HIV-1 and provide the basis for the non-genetic transient application of engineered recombinases, which may be a valuable component of future HIV eradication strategies

    The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project

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    Background The voluntary carbon market is a new and growing market that is increasingly important to consider in managing forestland. Monitoring, reporting, and verifying carbon stocks and fluxes at a project level is the single largest direct cost of a forest carbon offset project. There are now many methods for estimating forest stocks with high accuracy that use both Airborne Laser Scanning (ALS) and high-resolution optical remote sensing data. However, many of these methods are not appropriate for use under existing carbon offset standards and most have not been field tested. Results This paper presents a pixel-based forest stratification method that uses both ALS and optical remote sensing data to optimally partition the variability across an ~10,000 ha forest ownership in Mendocino County, CA, USA. This new stratification approach improved the accuracy of the forest inventory, reduced the cost of field-based inventory, and provides a powerful tool for future management planning. This approach also details a method of determining the optimum pixel size to best partition a forest. Conclusions The use of ALS and optical remote sensing data can help reduce the cost of field inventory and can help to locate areas that need the most intensive inventory effort. This pixel-based stratification method may provide a cost-effective approach to reducing inventory costs over larger areas when the remote sensing data acquisition costs can be kept low on a per acre basis

    High prevalence and diversity of HIV-1 non-B genetic forms due to immigration in southern Spain: A phylogeographic approach

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    Phylogenetic studies are a valuable tool to understand viral transmission patterns and the role of immigration in HIV-1 spread. We analyzed the spatio-temporal relationship of different HIV-1 non-B subtype variants over time using phylogenetic analysis techniques. We collected 693 pol (PR+RT) sequences that were sampled from 2005 to 2012 from naïve patients in different hospitals in southern Spain. We used REGA v3.0 to classify them into subtypes and recombinant forms, which were confirmed by phylogenetic analysis through maximum likelihood (ML) using RAxML. For the main HIV-1 non-B variants, publicly available, genetically similar sequences were sought using HIV-BLAST. The presence of HIV-1 lineages circulating in our study population was established using ML and Bayesian inference (BEAST v1.7.5) and transmission networks were identified. We detected 165 (23.4%) patients infected with HIV-1 non-B variants: 104 (63%) with recombinant viruses in pol: CRF02_AG (71, 43%), CRF14_BG (8, 4.8%), CRF06_cpx (5, 3%) and nine other recombinant forms (11, 6.7%) and unique recombinants (9, 5.5%). The rest (61, 37%) were infected with non-recombinant subtypes: A1 (30, 18.2%), C (7, [4.2%]), D (3, [1.8%]), F1 (9, 5.5%) and G (12, 7.3%). Most patients infected with HIV-1 non-B variants were men (63%, p < 0.001) aged over 35 (73.5%, p < 0.001), heterosexuals (92.2%, p < 0.001), from Africa (59.5%, p < 0.001) and living in the El Ejido area (62.4%, p<0.001). We found lineages of epidemiological relevance (mainly within Subtype A1), imported primarily through female sex workers from East Europe. We detected 11 transmission clusters of HIV-1 non-B Subtypes, which included patients born in Spain in half of them. We present the phylogenetic profiles of the HIV-1 non-B variants detected in southern Spain, and explore their putative geographical origins. Our data reveals a high HIV-1 genetic diversity likely due to the import of viral lineages that circulate in other countries. The highly immigrated El Ejido area acts as a gateway through which different subtypes are introduced into other regions, hence the importance of setting up epidemiological control measures to prevent future outbreaks
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