bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing Botanical Knowledge Graphs with Machine Learning
Authors: Gu Qianqian , Scott Ben , Smith Vincent 
Published: August 2022

Integrating sparse and incomplete biodiversity data into a global, coherent data space and generating machine-readable data infrastructures is a challenge in biodiversity informatics. In recent years, biodiversity data researchers have started proposing Knowledge Graphs (KGs) as one approach to connecting biodiversity data worldwide (Page 2019), representing the connections between the what, when, and where of objects in natural history collections. At the Natural History Museum (NHM) we have constructed a KG of botanical specimens and collectors, encoded into numerical representations, and using a Relational Graph Convolutional Network (RGCN) (Schlichtkrull et al. 2018) to infer gaps in the KG, forging new connections between nodes. The datasets involved in our botanical KG project are NHM Botany Collector database (105,780 entities) and NHM Indian Region Botanical Specimen Dataset (110,043 entities with geographical information).
Our KG with RGCN enables the structured and contextual data to be reasoned across the knowledge content, allowing us to dynamically update its representation according to its closely related neighbours. Our work will explain why and how the KG with RGCN can offer a better way to link digitised botanical data. We use the prototype KG to demonstrate its potential for modelling botanical data and provide a graphical representation for other machine learning applications. For example, the combination of KG with RGCN and Metric Learning (Xing et al. 2002, a form of Machine Learning generally used to automatically construct task-specific distance metrics) supports data completion via entity classification and link prediction for a subset of botanical specimens within a geographic region. These data augmentation models with KGs allow us to identify gaps in specimen provenance, and fill in missing data. After phase one training, our model can achieve 88% accuracy in entity classification and report a reasonable Mean Reciprocal Rank (MRR) in raw ranking link prediction for the Indian Region Botanical Specimen Dataset.
Our research also evaluates the use of the KG and RGCN to improve post-OCR (Optical Character Recognition) correction algorithms as part of automatic specimen digitisation pipelines. This improves the accuracy of entity recognition on specimen label text identification and transcription, as part of machine learning natural language processing and human-in-the-loop transcription. Human-based transcription can be aided and improved by an interpretation recommendation system predicated on the specimen unit’s RGCN-inferred location in the KG. This methodology can also be used to explore the alignment of KGs from different institutions within the global biodiversity network, to identify the relative importance of collectors or determine strengths or gaps in different geographic regions or ecosystems, duplicate items in collections, or objects in collections that have potentially been misidentified.
Connecting the Dots: Joint development of best practices between infrastructures in support of bidirectional data linking
Authors: Addink Wouter , Kyriakopoulou Niki 
Published: August 2022

Working together is key in terms of knowledge exchange and in the Biodiversity Community Integrated Knowledge Library project (BiCIKL), infrastructures involved in the biodiversity data landscape are working together to connect data from their different but related data domains. This will be key to connecting the dots towards the development of global collections and global specimen networks in line with e.g., the Extended Specimens Network (Lendemer et al. 2019), which describes a strategy to enhance US biodiversity collections and promote research and education by enabling seamless data integration, attribution and use tracking. It will enable and improve linkages in the fragmented landscape of literature, specimens, collections, species and sequence data. It is required to reliably connect collection level data and specimen level data with derived and related data served through these infrastructures.
BiCIKL is a project funded by the European Commission that will develop bidirectional data linkages through persistant identifiers between the data so that they become part of a big FAIR (Findable, Accessible, Interoperable, Reusable) data pool available to researchers, public authorities and business to foster innovation in the digital economy and to contribute in solving global environmental challenges. This will enable end-users to seamlessly access a larger pool of enriched data and knowledge, thereby bypassing the traditional barrier of having to search multiple databases and then link up different data types, or to manually extract data from literature.
Two elements are key for development of the data linkages: 1) the global adoption of agreed upon persistent identifiers for digital specimen objects, taxonomic treatments, collections, persons, sequences and taxa across stakeholders, and 2) best practices for the generation, management and curation of the linked data. We will present the best practices that have been jointly developed by the infrastructures in the BiCIKL project for findability, re-use and accessibility. The presentation will focus on the best practices that are essential for reliably linking specimen- and collection-level data with other types of data. Implementing these practices will be an important contribution towards connecting the dots in the biodiversity data landscape and will enrich the information at the data provider level.
NBN Atlas: Making data work for nature
Authors: Ratcliffe Sophia , Manders Jones Helen 
Published: August 2022

The National Biodiversity Network (NBN) Atlas is the United Kingdom's (UK) largest repository of publicly available biodiversity data, with more than 200 million records of almost 50,000 species. It is the largest Living Atlas installation and has been customised considerably to meet the needs of the UK biological recording community. The main customisation was the addition of support for Ordnance Survey grid references as the location of the occurrence, which was added to the core Atlas of Living Australia (ALA) code. UK-specific customisations include authorised access to the supplied location of sensitive records in downloads and an updated species search to better implement the UK Species Inventory, which is the taxonomic backbone of the NBN Atlas.
The biggest source of records is from the professionals and volunteers working with the National Recording Schemes and Societies and environmental non-governmental organizations (eNGOs). We also receive a substantial number of records from government agencies, Local Environmental Record Centres, museums, and botanical gardens across the UK. Currently we don’t receive many records from universities or research organisations, however they are one of the biggest consumers of NBN Atlas records across all sectors. We will discuss the challenges of managing record collation from such a broad range of data providers to meet the data requirements of all users, and how we are upgrading the NBN Atlas to the latest version of the ALA platform, whilst maintaining the UK customisations in a separate code layer.
The Australian National Species List steps up for biodiversity conservation
Authors: Fuchs Anne , Cooper Endymion , Whitbread Greg 
Published: August 2022

The Australian National Species List (AuNSL) will bring together authoritative national taxonomies and supporting nomenclatural data for flora, fauna, fungi and algae. These data enable biodiversity infrastructures, such as the Atlas of Living Australia, to store information about taxa against a standard, permanently resolvable taxonomy, and to create linkages between them.
The Biodiversity Data Repository (BDR) is a new Australian government infrastructure supporting environmental assessments under Australia's Environment Protection and Biodiversity Conservation Act. The BDR will bring together biodiversity data assets from a range of sources and enable decision making to be based on a more holistic view of taxa in Australia. To achieve its objectives, the BDR requires the ability to align disparate taxonomies to a national standard. To support the BDR we have restructured and consolidated the constituent datasets of the AuNSL and added a GraphQL interface from which we can provide machine access to the full suite of taxonomic and nomenclatural entities in the data and the linkages between them. Currently we provide a simple name check service for aligning supplied names with the standard AuNSL taxonomy and a full taxonomic backbone extract as a SKOS concept scheme expressed in JSON-LD. We are working towards an expanded set of taxonomic and nomenclatural services and a more generalised and complete graph of the AuNSL taxonomy, which can serve an increasing number of initiatives including the Australian Traits database (AusTraits), the Australian National DNA Library, and sensitive species data exchange mechanisms.
Linking Fennoscandian Species of Two Fungal Genera: A test case for linked open data
Authors: Liljeblad Johan , Lahti Tapani , Sjöro Elisabet , von Bonsdorff-Salminen Tea , Bendiksen Katriina , Skarp Liselott , Döring Markus 
Published: August 2022

In Norway, Sweden and Finland, we all have our own taxonomy initiatives, mapping our biodiversity (Lahti and Skarp 2019, Sjödin Skarp 2019, Skarp et al. 2019). Together these countries make up most of Fennoscandia, sharing a large part of the fauna, flora and fungi. It was only natural for us to start cooperating through a Nordic Taxonomy Initiative, sharing expertise and knowledge. Our implementation of Linked Open Data (LOD) is a first step toward automated sharing of information about Fennoscandian species. By linking taxon concepts, we can share observations and facilitate our efforts to combat invasive alien species, as well as assessing conservation status of our native species (Liljeblad and Lahti 2019a, Liljeblad and Lahti 2019b).
We picked the fungal genera Hygrophorus Fr. and Tricholoma (Fr.) Staude (Basiciomycetes: Agaricales) as test cases for matching species concepts between our countries. We downloaded lists of species from Checklistbank as a starting point, including synonym names and documenting the specific versions. However, the identifiers for these taxa are not independent of name and concept changes here, so this backbone was imported into taxonid.org. A spreadsheet with these taxa was then complemented with taxa from the three respective countries’ taxonomic databases.
In Hygrophorus, there were 35 species with 28 present in Finland, 33 in Norway and 34 in Sweden. The mycologists among us discussed the full list during a virtual workshop and agreed upon how to interpret their respective taxonomies compared to the list at taxonid.org. Next, we copied the identifier for each species in taxonid.org to our respective national databases.
Matching up all species of Hygrophorus took about 3 hours for 3 people, making for a total of 9 hours of effort excluding things such as exporting and preparing checklists for comparison. Adding the identifiers from taxonid.org into the respective national databases was a simple import of a maximum one hour each. We then did the same for the more species-rich genus Tricholoma.
In the process, besides the links, we have established closer personal contact, synced our views on the taxonomy and had a chance to tidy up the nomenclature. When attempting to share more than taxonomic information, we have come to realize how our countries differ in usage of standard terms documenting residency, reproductive status as well as that of establishment means. For now, we will have to make do with a simple absence/presence, but having the actual taxon links is the prerequisite we are now starting to fulfill.
Essential Biodiversity Variables: extracting plant phenological data from specimen labels using machine learning
Authors: Mora-Cross Maria , Morales-Carmiol Adriana , Chen-Huang Te , Barquero-Pérez María 
Published: August 2022

Essential Biodiversity Variables (EBVs) make it possible to evaluate and monitor the state of biodiversity over time at different spatial scales. Its development is led by the Group on Earth Observations Biodiversity Observation Network (GEO BON) to harmonize, consolidate and standardize biodiversity data from varied biodiversity sources. This document presents a mechanism to obtain baseline data to feed the Species Traits Variable Phenology or other biodiversity indicators by extracting species characters and structure names from morphological descriptions of specimens and classifying such descriptions using machine learning (ML).
A workflow that performs Named Entity Recognition (NER) and Classification of morphological descriptions using ML algorithms was evaluated with excellent results. It was implemented using Python, Pytorch, Scikit-Learn, Pomegranate, Python-crfsuite, and other libraries applied to 106,804 herbarium records from the National Biodiversity Institute of Costa Rica (INBio). The text classification results were almost excellent (F1 score between 96% and 99%) using three traditional ML methods: Multinomial Naive Bayes (NB), Linear Support Vector Classification (SVC), and Logistic Regression (LR). Furthermore, results extracting names of species morphological structures (e.g., leaves, trichomes, flowers, petals, sepals) and character names (e.g., length, width, pigmentation patterns, and smell) using NER algorithms were competitive (F1 score between 95% and 98%) using Hidden Markov Models (HMM), Conditional Random Fields (CRFs), and Bidirectional Long Short Term Memory Networks with CRF (BI-LSTM-CRF).
Bacteriological profile and antibiogram of blood culture isolates from bloodstream infections in a rural tertiary hospital in Nigeria
Authors: Oyekale Oluwalana T. , Ojo Bola O. , Olajide Adewale T. , Oyekale Oluwatoyin I. 
Published: August 2022

Background: Bloodstream infections (BSIs) are a cause of significant morbidity and mortality requiring urgent antibiotic treatment. However, there is widespread antibiotic-resistance from the bacterial causes, necessitating regular surveillance for drug-resistant bacteria and their antibiograms.Objective: This study isolated and identified various bacterial causes of BSIs, determined their antibiotic susceptibility patterns, and determined the best empirical treatment for cases of BSI in the setting.Methods: A cross-sectional study was carried out at the Federal Teaching Hospital, Ido-Ekiti, Nigeria between June 2020 and February 2021 on 177 blood culture samples from cases of BSI. Identification of isolated bacteria and antibiotic susceptibility testing of the isolates were carried out following the standard protocol.Results: Culture positivity in this study was 19.2%. No significant difference was seen in culture positivity between male and female participants (p = 0.97). Gram-negative enteric bacteria were predominantly isolated (67.6%), including Escherichia coli (29.4%) and Klebsiella aerogenes (20.6%). Staphylococcus aureus was the most common Gram-positive bacterium isolated (23.5%). Three (37.5%) S. aureus isolates were methicillin-resistant. All isolates were sensitive to meropenem, and 97.1% were sensitive to imipenem; other sensitivity patterns were: ceftazidime (85.3%), ciprofloxacin (79.4%), ofloxacin (79.4%), and gentamicin (76.5%). There was low sensitivity to ampicillin (32.4%) and cotrimoxazole (38.2%). All Gram-positive isolates, including methicillin-resistant S. aureus, were sensitive to vancomycin.Conclusion: Regular surveillance of isolate sensitivity patterns, formulation of hospital antibiotic policies based on existing data and compliance with treatment guidelines will promote rational antibiotic use and reduce resistance among bacteria.
Hypertensive patients’ knowledge and practices on lifestyle modification in Extension 6, Middelburg
Authors: Rahimi Amir , Nkombua Lushiku 
Published: August 2022

Background: Hypertension (HTN) is one of the most common chronic diseases affecting the majority of patients worldwide, including in South Africa. The control of HTN and prevention of complications are major challenges for patients and healthcare workers. The proper control of the disease requires a multifactorial approach consisting of medical treatment, as well as lifestyle modification, with the assistance of healthcare workers. Addressing patients’ beliefs, the practice of lifestyle and acceptance of change are some of the ways of aiding control.Methods: The researchers used a cross-sectional and descriptive survey to establish the knowledge and practices of lifestyle modifications in patients with hypertension. A validated questionnaire was adopted. A total of 250 participants from the Extension 6 Clinic in Middelburg, Mpumalanga, constituted the study population.Results: Most of the participants had borderline high blood pressure (37.2%) or uncontrolled high blood pressure (46%). The participants’ knowledge of HTN and its complications was not adequate. The study established that increased age and long duration of HTN were associated with high numbers of uncontrolled HTN. Most of the participants (88.8%) had difficulty exercising. Also, most of the participants (90.8%) did not have a place or facility for exercises. Fifty per cent of the participants were unable to maintain a balanced healthy diet which included fruits and vegetables.Conclusion: The study explored the participants’ knowledge and practice of lifestyle modification. The participants lacked knowledge regarding the definition of HTN and the meaning of controlled HTN. To assist the patients and improve on the identified pitfalls, each consultation session should include some methods of education, and motivation for healthy behaviours and lifestyle modification. This should be extended to all the people visiting the health facilities for them to adopt a healthier diet, greater intake of vegetables and availability of fitness facilities for the community.
COVID-19 vaccine acceptance and associated factors among people living with HIV in the Middle East and North Africa region
Authors: Mohamed Rahma , White Trenton M. , Lazarus Jeffrey V. , Salem Amany , Kaki Reham , Marrakchi Wafa , M Kheir Sara G. , Amer Ibrahim , M Ahmed Fida , A Khayat Maie , Al-Abdullah Nabeela , Ali Batool , Sultan Roaa , Alamri Bandar , Abdulmajid Anouf , Kooli Ikbal , Chakroun Mohamed , Madani Tariq A. , Esmat Gamal , Cordie Ahmed 
Published: August 2022

Background: Identifying coronavirus disease 2019 (COVID-19) vaccine acceptance and associated factors among people living with HIV (PLHIV) in the Middle East and North Africa region is important to meet the need for broad-scale vaccination against COVID-19.Objectives: To investigate the COVID-19 vaccine acceptance rate and factors among PLHIV in the Middle East and North Africa region.Method: An online cross-sectional survey was conducted among PLHIV currently living in Egypt, Tunisia and Saudi Arabia between March 2021 and August 2021.Results: Of the 540 respondents, 19.3% reported already being vaccinated against COVID-19 (n = 104), 32.0% responded ‘definitely yes’ (n = 173), and 13.3% responded ‘probably yes’ (n = 72) for intention to receive a COVID-19 vaccine, with an overall COVID-19 vaccine acceptance rate of 64.6% among PLHIV in the region. The most significant predictors of COVID-19 vaccine acceptance included feeling less worried about COVID-19 transmission post-vaccination (221.0% higher odds), and believing the disease is vaccine-preventable (160.0% higher odds). Reported barriers to COVID-19 vaccine acceptance include concerns about vaccine effectiveness and belief that HIV medications protect against COVID-19 transmission, living in a rural area and reporting less-frequent engagement with HIV care. Nine out of 10 participants reported that the chances of them getting COVID-19 vaccine would increase if given adequate information and if their doctor recommended it.Conclusion: Findings of the study can help researchers, health officials, and other health system actors understand the predictors and barriers to COVID-19 vaccine acceptance reported by PLHIV. This understanding could inform the future planning of interventions tailored to PLHIV.
Echocardiographic Evaluation of Right Ventricular Function in Patients Presenting with Acute ST-Elevation Myocardial Infarction
Authors: Gupta Rajeev Kumar , Shahi Ram Gopal Singh , Calton Rajneesh Kumar 
Published: August 2022

Background:
To evaluate the effect of different infarction sites on the right ventricular (RV) function by echocardiography in patients presenting with acute ST-elevation myocardial infarction (STEMI) and to correlate it with in-hospital morbidity and mortality.

Materials and Methods:
The present study was a descriptive cross-sectional study conducted in a tertiary care hospital involving 55 patients of anterior wall myocardial infarction (AWMI), 25 patients of inferior wall myocardial infarction (IWMI), and 20 patients of IWMI + RVMI. Among them, 55% of patients were males with a M: F ratio of 1.22:1. M-mode, two-dimensional, and Doppler echocardiographic evaluation of both RV and left ventricular (LV) function (tricuspid annular plane systolic excursion/RV fractional area change/right ventricular index of myocardial performance and LV ejection fraction [LVEF]) were done in all patients within 48 h of admission along with the assessment of arrhythmias, heart failure (HF), cardiogenic shock (CS), and complete heart block (CHB). All the four echocardiographic parameters were deranged in 30 (54.5%) patients of AWMI and 14 (70%) patients of IWMI with RVMI. However, derangement in at least one echocardiographic parameter of RV dysfunction was observed in 50 (90.9%) patients of AWMI, 11 (44%) patients of IWMI, and 20 (100%) patients of IWMI+RVMI, respectively. LVEF was significantly reduced in patients with AWMI (40.4 ± 11.2%) as compared to patients with IWMI and IWMI+RVMI, respectively (46.4 ± 10.3% and 46.5 ± 7.6%). Cardiovascular complications (ventricular tachycardia, ventricular fibrillation, atrial fibrillation, CS, and HF) were more in the AWMI patients with RV dysfunction. HF was specifically more in the patients of AWMI (81.8%) than IWMI (28%) and IWMI+RVMI (20%). CHB was frequently seen in IWMI (20%) and IWMI+RVMI (20%) patients.

Conclusion:
RV dysfunction is not only common in RVMI but also in AWMI and IWMI, and complications of STEMI are also more frequently seen in patients with RV dysfunction.