Collocation analysis for UMLS knowledge-based word sense disambiguation

BACKGROUND: The effectiveness of knowledge-based word sense disambiguation (WSD) approaches depends in part on the information available in the reference knowledge resource. Off the shelf, these resources are not optimized for WSD and might lack terms to model the context properly. In addition, they might include noisy terms which contribute to false positives in the disambiguation results. METHODS: We analyzed some collocation types which could improve the performance of knowledge-based disambiguation methods. Collocations are obtained by extracting candidate collocations from MEDLINE and then assigning them to one of the senses of an ambiguous word. We performed this assignment either using semantic group profiles or a knowledge-based disambiguation method. In addition to collocations, we used second-order features from a previously implemented approach.Specifically, we measured the effect of these collocations in two knowledge-based WSD methods. The first method, AEC, uses the knowledge from the UMLS to collect examples from MEDLINE which are used to train a Naïve Bayes approach. The second method, MRD, builds a profile for each candidate sense based on the UMLS and compares the profile to the context of the ambiguous word.We have used two WSD test sets which contain disambiguation cases which are mapped to UMLS concepts. The first one, the NLM WSD set, was developed manually by several domain experts and contains words with high frequency occurrence in MEDLINE. The second one, the MSH WSD set, was developed automatically using the MeSH indexing in MEDLINE. It contains a larger set of words and covers a larger number of UMLS semantic types. RESULTS: The results indicate an improvement after the use of collocations, although the approaches have different performance depending on the data set. In the NLM WSD set, the improvement is larger for the MRD disambiguation method using second-order features. Assignment of collocations to a candidate sense based on UMLS semantic group profiles is more effective in the AEC method.In the MSH WSD set, the increment in performance is modest for all the methods. Collocations combined with the MRD disambiguation method have the best performance. The MRD disambiguation method and second-order features provide an insignificant change in performance. The AEC disambiguation method gives a modest improvement in performance. Assignment of collocations to a candidate sense based on knowledge-based methods has better performance. CONCLUSIONS: Collocations improve the performance of knowledge-based disambiguation methods, although results vary depending on the test set and method used. Generally, the AEC method is sensitive to query drift. Using AEC, just a few selected terms provide a large improvement in disambiguation performance. The MRD method handles noisy terms better but requires a larger set of terms to improve performance

Capturing the Invisible Wealth in Nonprofits to Overcome Myopic Perceptions

Since nonprofits use third-party funds for their activities, they are often perceived as resource managers or spending units, instead of being considered as social wealth generating entities. The aim of this study is to help to overcome this myopic perception by showing how the invisible wealth generated by these organizations can be made visible. We use the SROI methodology to do so, by identifying stakeholders, outcomes (tangible, intangible) and social impacts in a drug addiction treatment centre. The results show that social impact in monetary terms exceeds that of the inputs used, confirming the idea that addiction-based nonprofits are social wealth generating units. The conclusion drawn is that social impact measurement should be widely used as a management tool and a mechanism for reinforcing the social image of nonprofits

Employment Expectations and Gross Flows by Type of Work Contract

There is growing interest in understanding firms’ temporary and permanent employment practices and how institutional changes shape them. Using data on Spanish establishments, we examine: (a) how employers adjust temporary and permanent job and worker flows to prior employment expectations, and (b) how the 1994 and 1997 labour reforms promoting permanent employment affected establishments’ employment practices. Generally, establishments’ prior employment expectations are realized through changes in all job and worker flows. However, establishments uniquely rely on temporary hires as a buffer to confront diminishing long-run employment expectations. None of the reforms significantly affected establishments’ net temporary or permanent employment flows.http://deepblue.lib.umich.edu/bitstream/2027.42/40032/3/wp646.pd

Analysing the impact of climate change on hydrological ecosystem services in laguna del sauce (Uruguay) using the swat model and remote sensing data

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005 2009 and 2010 2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.This work has received funding from the European Union’s Horizon 2020 research and innovation programme within the framework of the project SMARTLAGOON under grant agreement No. 101017861. This study was also supported by the State Research Agency of Spain through the excellence certification María de Maeztu (Ref. MDM-2017-0714). Celina Aznarez was supported by the Doctoral INPhINIT–INCOMING program, fellowship code (LCF/BQ/DI20/11780004), from “la Caixa” Foundation (ID 100010434). Javier Senent-Aparicio was supported by the training grant (21201/EE/19) awarded by the Séneca Foundation in the framework of the Jimenez de la Espada Mobility, Cooperation and Internationalization Program. Adrián López-Ballesteros was supported by the Spanish Ministerio de Educación, Cultura y Deporte with an FPU grant (FPU17/00923). Juan Pablo Pacheco was supported by the Sino-Danish Center–Aarhus University, the University of the Chinese Academy of Sciences and the University of the Republic, Uruguay. This work has received funding from the European Union?s Horizon 2020 research and innovation programme within the framework of the project SMARTLAGOON under grant agreement No. 101017861. This study was also supported by the State Research Agency of Spain through the excellence certification Mar?a de Maeztu (Ref. MDM-2017-0714). Celina Aznarez was supported by the Doctoral INPhINIT?INCOMING program, fellowship code (LCF/BQ/DI20/11780004), from ?la Caixa? Foundation (ID 100010434). Javier Senent-Aparicio was supported by the training grant (21201/EE/19) awarded by the S?neca Foundation in the framework of the Jimenez de la Espada Mobility, Cooperation and Internationalization Program. Adri?n L?pez-Ballesteros was supported by the Spanish Ministerio de Educaci?n, Cultura y Deporte with an FPU grant (FPU17/00923). Juan Pablo Pacheco was supported by the Sino-Danish Center?Aarhus University, the University of the Chinese Academy of Sciences and the University of the Republic, Uruguay. The authors acknowledge Paper Check Proofreading and Editing Services for proofreading the manuscript

Exploiting MeSH indexing in MEDLINE to generate a data set for word sense disambiguation

<p>Abstract</p> <p>Background</p> <p>Evaluation of Word Sense Disambiguation (WSD) methods in the biomedical domain is difficult because the available resources are either too small or too focused on specific types of entities (e.g. diseases or genes). We present a method that can be used to automatically develop a WSD test collection using the Unified Medical Language System (UMLS) Metathesaurus and the manual MeSH indexing of MEDLINE. We demonstrate the use of this method by developing such a data set, called MSH WSD.</p> <p>Methods</p> <p>In our method, the Metathesaurus is first screened to identify ambiguous terms whose possible senses consist of two or more MeSH headings. We then use each ambiguous term and its corresponding MeSH heading to extract MEDLINE citations where the term and only one of the MeSH headings co-occur. The term found in the MEDLINE citation is automatically assigned the UMLS CUI linked to the MeSH heading. Each instance has been assigned a UMLS Concept Unique Identifier (CUI). We compare the characteristics of the MSH WSD data set to the previously existing NLM WSD data set.</p> <p>Results</p> <p>The resulting MSH WSD data set consists of 106 ambiguous abbreviations, 88 ambiguous terms and 9 which are a combination of both, for a total of 203 ambiguous entities. For each ambiguous term/abbreviation, the data set contains a maximum of 100 instances per sense obtained from MEDLINE.</p> <p>We evaluated the reliability of the MSH WSD data set using existing knowledge-based methods and compared their performance to that of the results previously obtained by these algorithms on the pre-existing data set, NLM WSD. We show that the knowledge-based methods achieve different results but keep their relative performance except for the Journal Descriptor Indexing (JDI) method, whose performance is below the other methods.</p> <p>Conclusions</p> <p>The MSH WSD data set allows the evaluation of WSD algorithms in the biomedical domain. Compared to previously existing data sets, MSH WSD contains a larger number of biomedical terms/abbreviations and covers the largest set of UMLS Semantic Types. Furthermore, the MSH WSD data set has been generated automatically reusing already existing annotations and, therefore, can be regenerated from subsequent UMLS versions.</p

Multitasking Compensatory Saccadic Training Program for Hemianopia Patients: A New Approach With 3-Dimensional Real-World Objects

Producción CientíficaPurpose: To examinewhether a noncomputerized multitasking compensatory saccadic training program (MCSTP) for patients with hemianopia, based on a reading regimen and eight exercises that recreate everyday visuomotor activities using threedimensional (3D) real-world objects, improves the visual ability/function, quality of life (QL), and functional independence (FI). Methods: The 3D-MCSTP included four in-office visits and two customized homebased daily training sessions over 12weeks. A quasiexperimental, pretest/posttest study designwas carried out with an intervention group (IG) (n = 20) and a no-training group (NTG) (n = 20) matched for age, hemianopia type, and brain injury duration. Results: The groups were comparable for the main baseline variables and all participants (n = 40) completed the study. The IGmainly showed significant improvements in visual-processing speed (57.34% ± 19.28%; P < 0.0001) and visual attention/retention ability (26.67% ± 19.21%; P < 0.0001), which also were significantly greater (P < 0.05) than in the NTG. Moreover, the IG showed large effect sizes (Cohen’s d) in 75% of the totalQL and FI dimensions analyzed; in contrast to the NTGthat showed negligiblemean effect sizes in 96% of these dimensions. Conclusions: The customized 3D-MCSTP was associated with a satisfactory response in the IG for improving complex visual processing, QL, and FI. Translational Relevance: Neurovisual rehabilitation of patientswith hemianopia seems more efficient when programs combine in-office visits and customized home-based training sessions based on real objects and simulating real-life conditions, than no treatment or previously reported computer-screen approaches, probably because of better stimulation of patients´ motivation and visual-processing speed brain mechanisms

Wavelength-shifter coated polystyrene as an easy-to-build and low-cost plastic scintillator detector

We studied the light yield of a pure polystyrene slide coated with wavelength-shifter molecules, coupled to a photomultiplier, using beta particles from a 90-Sr source, as a possible easy-to-build, low-cost plastic scintillator detector. Comparison measurements were performed with an uncoated polystyrene slide as well as with uncoated and coated PMMA slides, the latter which can only produce Cherenkov light when being traversed by charged particles. The results with the single (double) coated polystyrene slides show about 4.9 (6.3) times higher detected photon yield compared to the uncoated slide. For comparison, the light yield of a polystyrene-based extruded plastic scintillator material doped with PTP and POPOP was measured as well. The absolute detected light yield motivates future studies for developing easy-to-build, low-cost polystyrene-based plastic scintillator detectors.Comment: 20 pages, 13 figure

Engineering a two-helix bundle protein for folding studies

The SAP domain from the Saccharomyces cerevisiae THO1 protein contains a hydrophobic core and just two α-helices. It could provide a system for studying protein folding that bridges the gap between studies on isolated helices and those on larger protein domains. We have engineered the SAP domain for protein folding studies by inserting a tryptophan residue into the hydrophobic core (L31W) and solved its structure. The helical regions had a backbone root mean-squared deviation of 0.9 Å from those of wild type. The mutation L31W destabilised wild type by 0.8 ± 0.1 kcal mol−1. The mutant folded in a reversible, apparent two-state manner with a microscopic folding rate constant of around 3700 s−1 and is suitable for extended studies of folding

Knowledge-based biomedical word sense disambiguation: comparison of approaches

<p>Abstract</p> <p>Background</p> <p>Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature. Statistical learning approaches have produced good results, but the size of the UMLS makes the production of training data infeasible to cover all the domain.</p> <p>Methods</p> <p>We present research on existing WSD approaches based on knowledge bases, which complement the studies performed on statistical learning. We compare four approaches which rely on the UMLS Metathesaurus as the source of knowledge. The first approach compares the overlap of the context of the ambiguous word to the candidate senses based on a representation built out of the definitions, synonyms and related terms. The second approach collects training data for each of the candidate senses to perform WSD based on queries built using monosemous synonyms and related terms. These queries are used to retrieve MEDLINE citations. Then, a machine learning approach is trained on this corpus. The third approach is a graph-based method which exploits the structure of the Metathesaurus network of relations to perform unsupervised WSD. This approach ranks nodes in the graph according to their relative structural importance. The last approach uses the semantic types assigned to the concepts in the Metathesaurus to perform WSD. The context of the ambiguous word and semantic types of the candidate concepts are mapped to Journal Descriptors. These mappings are compared to decide among the candidate concepts. Results are provided estimating accuracy of the different methods on the WSD test collection available from the NLM.</p> <p>Conclusions</p> <p>We have found that the last approach achieves better results compared to the other methods. The graph-based approach, using the structure of the Metathesaurus network to estimate the relevance of the Metathesaurus concepts, does not perform well compared to the first two methods. In addition, the combination of methods improves the performance over the individual approaches. On the other hand, the performance is still below statistical learning trained on manually produced data and below the maximum frequency sense baseline. Finally, we propose several directions to improve the existing methods and to improve the Metathesaurus to be more effective in WSD.</p