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Technological discontinuities and dominant design models are among the most heavily researched topics in the strategy and innovation literature. In this paper, we attempt to illuminate the process of technological progress in the automotive industry, one of the most important contemporary industries. Drawing from a unique and archival database, we offer a comprehensive historical analysis of Ford from 1896 to 1906. Specifically, our study shows that an important catalyst for the emergence of internal combustion engine (ICE) technology as the dominant design in the early automobile industry was Ford's technological experimentation. Accordingly, we provide theoretical contributions to the dominant design literature. [ABSTRACT FROM AUTHOR]

Conditional Spectrum (CS), characterized by a conditional mean and conditional standard deviation, serves as a target spectrum linking seismic hazard information to ground motion selection for seismic demand analysis. Current Ground Motion Selection and Modification (GMSM) methods aim to align with this target spectrum but face challenges due to the limited availability of recorded ground motions and potential modifications, leading to difficulties in ensuring selected ground motions accurately reflect site characteristics. Addressing this issue, the study presents an algorithm to select hazard-consistent CS-based records utilizing a stochastic ground motion model with a dual objective: (1) alleviate the need for scaling during the selection process, and (2) select records consistent with the target hazard and the contributing causal scenarios. To achieve both objectives, the study generates a database of hazard-targeted ground motions utilizing the kriging surrogate with scenarios sampled from the disaggregation matrix. Then, a postprocessing step explicitly considers causative parameters in the selection process. The algorithm's potential to select site-specific ground motions is demonstrated using sites in the Western United States, providing insights into the computational cost and accuracy. Additionally, statistical comparisons are conducted to explore circumstances where similar hazard consistency can be achieved without the postprocessing step, reducing the overall computational cost. Finally, the selected ground motions are favorably compared to those selected through traditional conditional spectrum-based approaches based on their spectral shape and ground motion intensity measures. [ABSTRACT FROM AUTHOR]

The sensitivity of hurricane-driven storm surge in the Houston Ship Channel Industrial Corridor to variations in storm characteristics is studied. Hurricane surge from Hurricane Ike from 2008 was simulated using the Delft3D Flexible Mesh model. Use of the HURDAT2 wind parameter database allowed alteration of relevant hurricane characteristics to develop these alternate scenarios. Moving the actual landfall location of Ike toward the southwest at a distance of 50 km yielded a 123% increase at Manchester relative to observations during the storm. Relocation of the landfall location 200 km further southwest caused a 40% decrease in water level at the Galveston Bay entrance relative to observed values, but with a corresponding 50% water level increase at Manchester. Reduction of the storm forward speed to 25% of the actual speed over the nearshore led to a 25% increase in water level in Manchester over recorded values, while a 57% reduction of the storm forward speed over land increased water levels in Manchester by 30%. Incorporating river flow also identified locations where Galena Park's residual floodwater is likely to remain after flooding. The results of this work can be used to guide modeling efforts of storm impacts on areas with narrow waterways. [ABSTRACT FROM AUTHOR]

The purpose of this scoping review was to highlight the current scientific evidence on eHealth-based information tools for menopause in terms of quality, requirements and previous intervention outcomes. We systematically searched electronic databases (Embase, CINAHL, Cochrane Library, Global Health Database [Ovid], Web of Science, ClinicalTrials.gov [NLM], LIVIVO Search Portal [ZB MED] and Google Scholar) from 1974 to March 2022 for relevant records. Our search yielded 1773 records, of which 28 met our inclusion criteria. Thirteen of 28 selected studies were cross-sectional with qualitative content analysis of websites about menopause; 9 studies were cohort studies examining the impact of an eHealth intervention; two studies were randomized controlled trials comparing eHealth tools with conventional ones; and four studies were non-systematic literature reviews. This scoping review highlights the potential of eHealth-based information tools for the management of menopause and shows that most eHealth-based information tools are inadequate in terms of readability and the balanced view on information. Providers of eHealth-based information tools should pay attention to a participatory design, readability, balance of content and the use of multimedia tools for information delivery to improve understanding. [ABSTRACT FROM AUTHOR]

This study aimed to understand the relationship between course activities and learning progress among students enrolled in the MicroMasters certificate program offered in an affordable MOOC-based learning platform. In order to capture the relationship, the differences between the engagement patterns of learners in the MicroMasters program compared to a non-degree MOOC were examined by utilizing machine-learning (ML) techniques in the clickstream database. The ML analyses revealed discrepancies in activity patterns and progress rates of students enrolled in MicroMaster and MOOC courses. The findings can further support optimizing the program's design to enhance learners' engagement and improve the overall completion rates. [ABSTRACT FROM AUTHOR]

How can an open access database annotating pictures, films, music and texts support adults as existential exemplars? This article explores the opportunities of a Norwegian database called the OE-database. Its target group is all adults who want to become better exemplars for children through encounters with art and conversations in small groups. Educational sources contain many annotations of art and literature for the education of children and youth, but material for adults' self-education, published in databases and thus easily accessible for all, are lacking. The article invites readers to a critical conversation on the purpose and potential of the OE-database and to create similar databases in other languages. The narratives that provide the foundation of the OE-database are influenced by Aristotle, Thomas Aquinas and Søren Kierkegaard. The article highlights Kierkegaard's concept 'upbuilding' (edification) and three stages in a process that encourage adults to let themselves be 'built up' as exemplars. [ABSTRACT FROM AUTHOR]

The diagnosis and recommendation integrated system (DRIS) has such high reliability that it can be used to evaluate many crops. Therefore, in order to have a practical database for these norms, this study was conducted to evaluate the established DRIS norms for plant pineapples (Ananas comosus L.) and to assess their nutrition status in an acid sulfate soil. Healthy and disease-free leaf samples of 8-month-old pineapple plants without fruits were collected from experimental fields with nutritional omission trials and from farmers' fields at four cultivating sites. Nutrient concentrations were analyzed to determine DRIS indices. The result showed that the + 7 leaf was highly reliable to diagnose the macro-nutrition status, while the + 1 leaf and + 3 leaf lacked the nutrient ratios pair to assess P and Mg nutrition status. Based on the average DRIS indices of the four sites, the nutrient surplus was observed in the order P>Mn>Fe>Ca (81.7 > 52.8 > 15.7 > 13.3), while nutrient deficiency varied in the order K>Zn>N>Mg (−88.2<-20.3<-16.4<-10.7) at the + 7 leaf. The DRIS norms needed to be calibrated to obtain nutrient ratio pairs for P in the + 1 leaf, and P and Mg at the + 3 leaf. [ABSTRACT FROM AUTHOR]

Similarity of point patterns is critical to geographic information retrieval. Many methods depend on measuring the similarity between point patterns within the spatial database. However, previous researches mainly focus on point density which is only one aspect of point patterns. A point distribution can be complex by its numerous alignments of point groups, which usually imply different geographical meanings in reality. In this paper, we propose a new method that uses image analysis techniques to comprehensively consider the characteristics of a point pattern. Specifically, given a set of point datasets falling in the same region, our method first generates the point intensity surfaces to transform the original vector space to raster space; then, the method constructs a matrix to describe all the pattern-related information. Finally, the point pattern similarity is calculated by decomposing this matrix into the lower-order representation and the factorized basis features. Due to the use of matrix decomposition, the proposed method has the merits that it can eliminate noises from the original data and assess the similarity of two patterns with emphasis on their major features. As a case study, our method is effective in discovering regularity from the taxi pick-up/drop-off point datasets. [ABSTRACT FROM AUTHOR]

Objective: Patients with triple-class refractory (TCR) multiple myeloma (MM) have limited treatment options and poor prognoses. This high unmet need has prompted the development of new therapies allowing for improved outcomes for these patients. Recently, new targeted therapies for the treatment of patients with relapsed or refractory MM have been approved based on single-arm clinical trial results. Real-world (RW) data enable a better understanding of the effectiveness of new therapies in clinical practice and provide external controls for single-arm studies. However, using RW data to identify patients with TCR MM is challenging and subject to limitations. Methods: In this retrospective cohort study of an analysis of the COTA electronic health record (EHR) database, we used four algorithms to define refractory status and created four groups of patients with TCR MM initiating post-TCR therapy. Each algorithm relied on slightly different criteria to identify TCR patients, but all were based on the International Myeloma Working Group (IMWG)-derived and/or healthcare provider (HCP)-reported progressions within the database. Results: A total of 3815 patients with newly diagnosed MM met the eligibility criteria for this study. The choice of the algorithm did not impact the characteristics of identified patients with TCR MM (Algorithm 1 [n = 404], Algorithm 2 [n = 123], Algorithm 3 [n = 404], and Algorithm 4 [n = 375]), including their demographic and disease characteristics, MM treatment history, or treatment patterns received after becoming TCR. However, identifying TCR MM using a combination of IMWG-derived and HCP-reported progressions allowed up to a 70% increase in the size of the identified group of patients compared with using only IMWG-derived progressions. Conclusion: In RW settings, progressions from both IMWG-derived data and physician reports may be used to identify patients with TCR MM. [ABSTRACT FROM AUTHOR]

The review had two purposes. The first was to examine the nature and extent of published literature on student loan and the second was to systematically review the literature on student loans and mental health. Data from academic databases (1900–2019) were analyzed using two methods. First, topic modeling (a text-mining tool that utilized Bayesian statistics to extract hidden patterns in large volumes of texts) was used to understand the topical coverage in peer-reviewed abstracts (n = 988) on student debt. Second, using PRISMA guidelines, 46 manuscripts were systematically reviewed to synthesize literature linking student debt and mental health. A model with 10 topics was selected for parsimony and more accurate clustered representation of the patterns. Certain topics have received less attention, including mental health and wellbeing. In the systematic review, themes derived were categorized into two life trajectories: before and during repayment. Whereas stress, anxiety, and depression dominated the literature, the review demonstrated that the consequences of student loans extend beyond mental health and negatively affect a person's wellbeing. Self-efficacy emerged as a potential solution. Across countries and samples, the results are uniform and show that student loan burdens certain vulnerable groups more. Findings indicate diversity in mental health measures has resulted into a lack of a unified theoretical framework. Better scales and consensus on commonly used terms will strengthen the literature. Some areas, such as impact of student loans on graduate students or consumers repaying their loans, warrant attention in future research. [ABSTRACT FROM AUTHOR]

This paper estimates a correlation model and joint distribution model of spectral accelerations of vertical ground motions based on the NGA-West2 ground motion database. The correlation model calculated via BC16 vertical GMPE in this study is compared with those published models via other vertical NGA-West2 GMPEs. It is verified that the calculated residuals of vertical ground motions at multiple periods follow the multivariate normal distributions via both a qualitative validation method and a set of quantitative validation methods. The correlation model and the joint distribution model of vertical spectral accelerations are the theoretical basis for research on the joint occurrence of spectral accelerations of vertical ground motions, and an example of applied research on joint occurrence of spectral accelerations of vertical ground motions is studied: the conditional mean spectrum of vertical ground motions. Finally, the effects of different vertical correlation models and ground motion prediction equations on vertical conditional spectra are investigated for wide application of the correlation model and the joint distribution model of spectral accelerations of vertical ground motions. [ABSTRACT FROM AUTHOR]

Benthic protist communities, including sand-dwelling dinoflagellates, are still poorly characterized worldwide and there is a lack of knowledge on their diversity and spatiotemporal dynamics. In this study, sediments were obtained from several coastal locations of the German Wadden Sea during the summer months of 2017 and 2018 to determine the diversity and spatiotemporal distribution of sand-dwelling dinoflagellates. The analyses consisted of light microscopy and the metabarcoding of small subunit (SSU) rRNA gene V4 region amplicons. Additionally, SSU rRNA sequences were newly obtained for 15 observed taxa included in a reference database and were used to taxonomically assign the obtained amplicon sequence variants (ASVs). The combination of morphological and molecular approaches allowed a deep characterization of dinoflagellate communities. Seventy-three morphospecies were detected by microscopy, while metabarcoding ASVs (amplicon sequence variants) were assigned to 116 species, resulting in a more comprehensive biodiversity inventory than achieved with either method alone. Pfiesteriaceae, Togula compacta and Thecadinium yashimaense predominated in the different sampling locations. Communities from Wilhelmshaven diverged from the others, consistent with its muddier sediment. A high level of resemblance was determined for the communities from each location, regardless of the sampling month and year, indicating a high summertime stability of benthic communities. Further efforts will be needed to characterize benthic protist diversity, as a first step in obtaining a complete picture of the habitat characteristics and physico-chemical conditions that influence benthic community composition. Metabarcoding and microscopy observations provide complementary results. Much of the diversity of sand-dwelling dinoflagellates is uncharacterized. Benthic dinoflagellate communities were stable at each location in summer. [ABSTRACT FROM AUTHOR]

Accumulating evidence suggests that non-genetic factors have important etiologic roles in amyotrophic lateral sclerosis (ALS), yet identification of specific culprit factors has been challenging. Many medications target biological pathways implicated in ALS pathogenesis, and screening large pharmacologic datasets for signals could greatly accelerate the identification of risk-modulating pharmacologic factors for ALS. We conducted a high-dimensional screening of patients' history of medication use and ALS risk using an advanced machine learning approach based on gradient-boosted decision trees coupled with Bayesian model optimization and repeated data sampling. Clinical and medication dispensing data were obtained from a large Israeli health fund for 501 ALS cases and 4,998 matched controls using a lag period of 3 or 5 years prior to ALS diagnosis for ascertaining medication exposure. Of over 1,000 different medication classes, we identified 8 classes that were consistently associated with increased ALS risk across independently trained models, where most are indicated for control of symptoms implicated in ALS. Some suggestive protective effects were also observed, notably for vitamin E. Our results indicate that use of certain medications well before the typically recognized prodromal period was associated with ALS risk. This could result because these medications increase ALS risk or could indicate that ALS symptoms can manifest well before suggested prodromal periods. The results also provide further evidence that vitamin E may be a protective factor for ALS. Targeted studies should be performed to elucidate the possible pathophysiological mechanisms while providing insights for therapeutics design. [ABSTRACT FROM AUTHOR]

To predict ALS progression with varying observation and prediction window lengths, using machine learning (ML). We used demographic, clinical, and laboratory parameters from 5030 patients in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to model ALS disease progression as fast (at least 1.5 points decline in ALS Functional Rating Scale-Revised (ALSFRS-R) per month) or non-fast, using Extreme Gradient Boosting (XGBoost) and Bayesian Long Short Term Memory (BLSTM). XGBoost identified predictors of progression while BLSTM provided a confidence level for each prediction. ML models achieved area under receiver-operating-characteristics curve (AUROC) of 0.570-0.748 and were non-inferior to clinician assessments. Performance was similar with observation lengths of a single visit, 3, 6, or 12 months and on a holdout validation dataset, but was better for longer prediction lengths. 21 important predictors were identified, with the top 3 being days since disease onset, past ALSFRS-R and forced vital capacity. Nonstandard predictors included phosphorus, chloride and albumin. BLSTM demonstrated higher performance for the samples about which it was most confident. Patient screening by models may reduce hypothetical Phase II/III clinical trial sizes by 18.3%. Similar accuracies across ML models using different observation lengths suggest that a clinical trial observation period could be shortened to a single visit and clinical trial sizes reduced. Confidence levels provided by BLSTM gave additional information on the trustworthiness of predictions, which could aid decision-making. The identified predictors of ALS progression are potential biomarkers and therapeutic targets for further research. [ABSTRACT FROM AUTHOR]

This work introduces the use of convolutional neural network (CNN) in combination with advanced structural theories for the damage detection of multi-component and composite structures. Well-established component-wise (CW) models based on the Carrera Unified Formulation (CUF) are developed first to demonstrate the effect of localized damages on the mechanical performance of thin-walled beams and laminates. Finite element Monte Carlo simulations of randomly damaged structures are then used to generate a large database of full-field displacement and strain images. These images are lately feed into a dedicated CNN for training purpose and for the prediction of location and intensity of structural damages occurring in unseen scenarios. The results demonstrate the validity of the present approach and suggest the importance of adopting opportune structural models to carry out localized damage detection by image-driven AI. Overall, the research provides good confidence for future investigation and experimental testing. [ABSTRACT FROM AUTHOR]

While scholars of activism have begun to unfold the dynamics of the 'contentious politics of data', less explored are the forms of appropriation of algorithms to pursue political objectives by social movements. This article fills this gap by offering a novel theoretical framework, a conceptual vocabulary, and a typology to foreground and articulate algorithmic activism as a subset of algorithmic politics. It starts discussing why an excessive focus on the power of platforms risks disregarding the exploration of agency and provides the definitions of algorithmic agency and politics. Subsequently, it centres on algorithmic activism and demonstrates that algorithms have become the latest addition to the contention repertoire of social movements. Drawing on a heterogeneous set of examples and case studies (including our own research and a database of 250 articles), we propose and examine a typology of three dynamics of algorithmic activism, i.e. algorithmic amplification, evasion, and hijacking. We show that the struggle for visibility (either to achieve it or deny it) lies at the centre of all these types of activism. In the conclusions, we reflect on the key takeaways of our work, clarifying that algorithmic activism (1) exceeds the notion of 'hashtag activism' (2) constitutes an agnostic concept (3) is part of an incessant political struggle between algorithmic strategies and tactics. [ABSTRACT FROM AUTHOR]

Language technology tools provide a promising way to teach, share, retain, and curate under-resourced language learning materials in community. The inclusion of language teachers working with communities increases the potential for designed tools to be adopted by those groups. However, there is little research concerning the adaptation of tools designed with one community to other languages. To identify the implications for such scalability, we ran workshops with the ‘Record and Write’ tool, developed as a versatile format for collection, curation, and use of under-resourced language learning materials in community. The process enabled teachers of languages with varying availability of teaching materials to reflect on some of the embedded complexities of adapting the tool to their context. This paper critically reflects on the design process of the tool and design lessons learned relating to language governance, the reflection of culture in database tools, conversational learning support, and differentiated needs for grammatical accuracy and annotation. Methodologically, the paper proposes a reflexive lens on co-design in cross-cultural contexts, identifying some of the latent assumptions embedded in technologies that emerge when tools are transposed to different language and learning contexts. [ABSTRACT FROM AUTHOR]

Impressive progress has been made in developing companion Socially Interactive Agents (SIAs) that provide companionship and reduce loneliness. However, recent works focus on analyzing multimodal feedback in Answer part but ignore Question part. Furthermore, research on SIAs is primarily based on English, which poses a challenge for Chinese SIAs because of cultural differences between English and Chinese. Therefore, we introduce a Chinese Natural Audiovisual Multimodal Database (CNAMD) corpus, the first and largest freely available Chinese multimodal database for multi-person interaction, containing 48 hours of videos and annotations across eight modalities. Using CNAMD, we analyze the characteristics of vocal-verbal, audio, behavioral, and multimodal combinations during questioning, test the performance of six baselines on three tasks, and propose improvements for processing daily Chinese data. The present findings will help designers consider Chinese customs and language when designing Chinese SIAs, making them more suitable for the Chinese cultural context and users. [ABSTRACT FROM AUTHOR]

The ammonia spectrum is revisited in the important 1.6 µm atmospheric transparency window between 5650 and 6350 cm $ ^{-1} $ − 1 on the basis of recently recorded high-resolution Fourier transform spectra. These spectra offer an improved frequency sampling and better traceability of the measurement conditions compared to previously studied Kitt Peak spectra (Cacciani et al. J. Quant Spectrosc Radiat Transf 2021; 258:107334. https://doi.org/10.1016/j.jqsrt.2020.107334). Overall, 4812 $ ^{14} $ 14 NH $ _3 $ 3 lines were measured in the 5650–6350 cm $ ^{-1} $ − 1 region corresponding to 4866 transitions including 2066 new ones compared with our previous study, included in the HITRAN2020 database. The energy of 1023 upper state levels (including 107 new ones) was derived from 2608 assigned transitions. Independently, ammonia spectra recorded in a supersonic jet expansion using a tunable extended cavity diode laser allow us to check the absolute transition energies in the 5980–6080 cm $ ^{-1} $ − 1 range. Accurate jet spectra calibration was achieved using CH $ _4 $ 4 reference line positions known with kHz accuracy. The position agreement with the FTS data is within the $ 4\times 10^{-4} $ 4 × 10 − 4 cm $ ^{-1} $ − 1 uncertainty of the positions measured in the jet expansion. A recommended line list of 5620 transitions is provided for $ ^{14} $ 14 NH $ _3 $ 3 in the considered 5650–6350 cm $ ^{-1} $ − 1 region. [ABSTRACT FROM AUTHOR]

To facilitate the data analysis of current and future high-resolution space telescope missions, we adopt 'Best Theory + Reliable High-resolution Experiment' (BTRHE) strategy to develop highly accurate infrared line lists for nitrous oxide (N2O). The 'Ames-1' potential energy surface (PES) is a CCSD(T)/aug-cc-pVQZ PES refined using selected HITRAN experimental data, with σrms = 0.02–0.03 cm-1 for five isotopologues. The 'Ames-1' dipole moment surface (DMS) is fitted from CCSD(T)/aug-cc-pV(T,Q,5)Z dipoles extrapolated to one electron basis set limit. Using the Ames-1 PES and DMS, Ames-296K line lists are computed in the full range of 0–15,000 cm-1 for 12 N2O isotopologues, with S296K ≥ 10−31 cm-1/molecule.cm-2. The reliability and consistency of Ames-296K intensity predictions (SAmes) are demonstrated through comparisons with HITRAN (SHITRAN), NOSL-296 (SNOSL), recent observed intensities (Sobs) and Effective Dipole Model (EDM) intensities (SEDM). Agreements and discrepancies are discussed, along with preliminary uncertainty estimate for SAmes. The SAmes provides a good constraint to prevent substantial errors in intensity predictions (e.g. for weak bands and minor isotopologues) and can be further improved. Ames-296K and NOSL-296 may complement each other to provide improved input for future database updates, combining the strengths of EH/EDM and BTRHE approaches. Data available at and https://doi.org/10.48667/9kmk-0334. [ABSTRACT FROM AUTHOR]

Created by the NIH in 2015, the Common Data Elements (CDE) Repository provides free online access to search and use Common Data Elements. This tool helps to ensure consistent data collection, saves time and resources, and ultimately improves the accuracy of and interoperability among datasets. The purpose of this column is to provide an overview of the database, discuss why it is important for researchers and relevant for health sciences librarians, and review the basic layout of the website, including sample searches that will demonstrate how it can be used. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine the accuracy of indexing for "Appalachian Region"[Mesh]. Researchers performed a search in PubMed for articles published in 2019 using "Appalachian Region"[Mesh] or "Appalachia" or "Appalachian" in the title or abstract. Only 17.88% of the articles retrieved by the search were about Appalachia according to the ARC definition. Most articles retrieved appeared because they were indexed with state terms that were included as part of the mesh term. Database indexing and searching transparency is of growing importance as indexers rely increasingly on automated systems to catalog information and publications. [ABSTRACT FROM AUTHOR]

This article explores major findings and evolutions in understandings of transboundary water conflict and cooperation over the last three decades, focusing on the trends emerging from the Transboundary Freshwater Diplomacy Database. It is found that since the 1940s, countries tend to cooperate over shared water resources, in contrast to media portrayals of 'water wars'. Water conflicts, which have increased slightly since 2000, are mostly fuelled by water quantity disputes or unilateral infrastructure developments. Institutions play a role in facilitating cooperation and reducing conflict over shared waters, but their growth and adoption have slowed over the last few decades. [ABSTRACT FROM AUTHOR]

The present study models potential regions for Argan tree plantations in Algeria using the MaxEnt approach, taking into account the sites of successful plantations at national level. There has been exhaustive sampling of 45 sites of plantations, with results collected over three years, 2021, 2022 and 2023. Current climate data were used from the Worldclim database (version 2.0). The results obtained indicate that the north-western regions of the country, the eastern and central coasts, are highly suitable (≥75%), but the desert and steppe regions are weakly suitable (<25%). Therefore, a suitable bioclimatic environment for planting argan trees (with at least 50% probability) depends on a minimum temperature of 2.5 to 6.5°C and annual precipitation of 160 to 1,400 mm. [ABSTRACT FROM AUTHOR]

Confined masonry (CM) buildings experienced some major damages in past earthquakes. Numerous studies have investigated various strengthening techniques to improve the seismic performance of CM walls. A state of the art for strengthening CM structures using externally bonded reinforced cementitious composites, subjected to inplane loads is presented. A database of previous test results was used to evaluate the effectiveness of the strengthening applications. The capacity prediction of strengthened CM walls was performed using available analytical models. A modification of the existing model is proposed by studying the correlation between the experimental parameters and the effective stress. [ABSTRACT FROM AUTHOR]

A scoping review of peer-reviewed academic literature on career interest measures for the African adolescents was conducted. The aim was to determine current knowledge and future research. Measuring learners' career interests during high school is imperative to promote a positive start to their career trajectory. A sample of 10 articles (2012–2022) from four databases was analysed. The results indicate that research is lacking and conducted mainly by one author utilising the Career Interest Profile, Maree Career Matrix and Career Adapt-Abilities Scale – South African Form. Integrative approaches, mixing methodologies and referencing the unique African context in measurement were common characteristics of studies. It is concluded that more research should be conducted on African adolescents to develop context-sensitive career interest measures. [ABSTRACT FROM AUTHOR]

Metadata is vital for information storage and retrieval from a database or repository. In the case of Research Data Repositories (RDRs), metadata can be a potent tool for describing and identifying data. Further, producing the metadata is indispensable for fostering data reuse. A filtered view of the registry of research data repositories, re3data.org, depicts no uniform patterns or standards for metadata in the case of RDRs, and the metadata elements and practices differ from RDR to RDR. The present study describes the features of a select number of RDRs and analyzes their metadata practices: Harvard Dataverse, Dryad, Figshare, Zenodo, and the Open Science Framework (OSF). It further examines the total number of metadata elements, common metadata elements, required metadata elements, and item-level metadata. Results indicate that even though Harvard Dataverse has the most metadata elements, Dryad provides rich metadata concerning item level. This study suggests a common metadata framework, richer metadata elements, and more features to make the research data's interoperability possible from one RDR to another. [ABSTRACT FROM AUTHOR]

The poor grade subarachnoid haemorrhage patients represent a unique cohort with lack of clear treatment protocol. Most neurosurgical units in the UK will manage them at local hospital until they make a significant recovery, this period can put them at higher risk of rebleed while with aggressive treatment a significant subset can achieve a favourable outcome. Identification of this subset is difficult and decision to treat them is associated with significant commitment of neurosurgical and ITU resources. Recent paper by Szklener has come up with a scale for prognostication in this subgroup of patients. We wanted to check the validity of this scale in our patient population and see if this scale can be used to guide early patient transfer and aggressive management at the Neurosurgical unit. We retrospectively reviewed our referral database for all poor grade subarachnoid patients referred over 2 years. Demographic information, Fisher and WFNS scores, admitting leucocyte count and outcome information as per MRS were obtained. These were scored as per the scale suggested by Szklener. A total of 115 poor grade subarachnoid patients were referred over the study time frame. 47 of them were accepted for admission. 18/47 patients achieved a favourable outcome (GOS4-5). Only 1 patient managed in peripheral hospital had a good outcome. There was a significant association between Szklener's score and achieving a favourable outcome p = 0.002. A selective admission policy could work specially with current economic climate, achieving outcomes comparable to admit-all. However, to optimise outcomes for all patients an aggressive standardised management at peripheral hospitals and a uniform admission policy assisted by Szklener score may be adopted. Szklener's model predicts the outcome better than WFNS and age but more validation is needed. [ABSTRACT FROM AUTHOR]

Illegal structures, which are structures illegally built on land or buildings, are common in Taiwan. Urban residents frequently inform authorities of illegal roofs, a type of illegal structure, because of the potential fire hazards they pose. However, the government does not conduct timely inspection on illegal roofs because this process requires additional human resources. Therefore, developing an efficient and correct method for inspecting and reporting illegal structures is necessary. In this study, unmanned aerial vehicles (UAVs) were used to rapidly capture images, which were then used to generate orthophotos, a 3D building model, a digital surface model (DSM), and a data set containing 400 images of illegal roofs and 400 images of legal roofs. The data set was then used in a convolutional neural network (CNN) to train and evaluate image classification. The results revealed an illegal roof classification accuracy of 96.0%, with a loss of 0.09. In addition, You Only Look Once v3 (YOLOv3) was used to detect illegal buildings, and DSMs higher than 9 m were overlaid to improve the accuracy of the illegal roof identification model. Overall, the study results can help inspectors build a comprehensive database of illegal roofs, which can serve as a reference for budgeting demolition costs and human resources. [ABSTRACT FROM AUTHOR]

To determine whether the Angelo Bruno Business Library was meeting the needs of business faculty in the College of Business (COB) at The University of Alabama, and to measure the frequency of publishing via Open Access (OA) journals, a comprehensive citation analysis of business faculty (tenured/tenure-track/non-tenure track/clinical/instructor/etc.) publications was conducted for the years 2019 - 2020. There are other reasons, as well, for considering the exercise of a citation analysis. The following data were collected from Scopus: all citations from works listed by each faculty member per the COB Faculty and Staff Directory (each department in the COB was included), title of reference, authors, year of publication, source title, volume/issue, and publication type. The results were analyzed collectively as well as for each department. This study also determined how often OA journal titles were chosen as the outlet for publication. Only 24% of published works by COB authors during this time frame are OA. This research also revealed the dismal results that none of the 100 most-cited journals were OA. It is to libraries' financial advantage that more authors use OA publishing for their works as well as their places for cited research. [ABSTRACT FROM AUTHOR]

The prevalence of hepatitis C (HCV) among psychiatric patients is elevated compared to the background population in many studies, but the prevalence among Danish psychiatric patients is unknown. The aim of the study was to determine the HCV prevalence and the proportion of the psychiatric patient population that remains to be diagnosed and treated in a Danish setting. During a 5-month period, patients attending the psychiatric emergency room in Vejle, Denmark, were offered point-of-care anti-HCV testing. Previous hepatitis C tests for all patients attending the Psychiatric Department in the study period were extracted from the national laboratory database (DANVIR). We combined the survey and register data in a capture–recapture estimate of undiagnosed patients with HCV. During the study 24.9% (589 of 2364) patients seen at the psychiatric department attended the emergency room. The prevalence of anti-HCV among those tested in the emergency room was 1.6%. The laboratory register identified 595/2364 patients previously tested for anti-HCV with a positive prevalence of 6.1%. The undiagnosed anti-HCV positives among the 1483 never tested was estimated to 1.1%. Thus the total estimated prevalence of anti-HCV was 2.3% (54/2364, 95% CI 1.7%–3.0%) in the population, of whom 70.4% had been diagnosed, and 72.2% of diagnosed patients had received treatment or cleared HCV. Combining survey and register data showed that the WHO target of 90% diagnosed and 80% treated was not met. To eliminate HCV in the psychiatric population, both undiagnosed and untreated patients must be targeted. [ABSTRACT FROM AUTHOR]

There is limited research on the factors that contribute to suicides among farm and agriculture workers. The purpose of this analysis was to examine the socio-demographic characteristics and circumstances that may increase risk of suicide for a farm worker by using the detailed data from the Kansas Violent Death Reporting System (KS-VDRS). KS-VDRS is a state-based system and was used to look at suicides among farm and agricultural workers that occurred in Kansas from 2016 to 2020. Frequencies, percentages, and age-adjusted rates were calculated to compare trends between farm/agriculture workers and other major occupational groups (non-farm/agriculture). Females were not included in this analysis due to low counts in the occupational group. In Kansas, male farm and agriculture workers die by suicide at a rate of 147.5 per 100,000 population, which is 3 times that of the average male workers (45.2 per 100,000 population). Male suicide decedents in farming and agriculture-related occupations were older with a mean age of 54 years and less educated (73% had a high school diploma or less) than their non-agriculture counterparts (mean age 44 years, and 57% had a high school diploma or less). Common circumstances around time of death were current depressed mood (58.6%), current mental health problem (41.4%), and physical health problem (31.4%). KSVDRS provides valuable information on the circumstances surrounding suicides, and this can inform prevention efforts within and across states. Numerous factors may contribute to the increased risk of suicide among farmers and those who work in agriculture. Physical health problems, family relationship problems, and financial problems are more commonly reported among this population compared to other male workers. Findings from this report highlight the complexity of suicide risk within the farm and agriculture industry in Kansas and reinforce the need for state-specific data and tailored prevention efforts. [ABSTRACT FROM AUTHOR]

Farming is one of the top industries in Michigan and has the highest fatality rate. National sources of non-fatal farm injuries underestimate the burden, especially among children. In this paper, we provide a more accurate estimate of non-fatal farm injuries in Michigan by using an ongoing multi-source surveillance system. Michigan's farm-injury surveillance system includes abstractions of hospital-based medical records, poison control center calls, ambulance runs, and workers' compensation claims for individuals with a farm-related injury. For this analysis, injury onset occurred in 2015 to 2021 and included all injuries regardless of age or occupation. We identified 4,306 injuries in adults and 336 injuries in youth. For those 0–13 years of age all but two were family members. For those 14–15 and 16–17 years of age, 19% and 45%, respectively were hired hands. For adults, 51% were owner/operators, 43% were hired hands, and 5% were family members. For all ages, the most frequent injury source was cattle. Lacerations/cuts/punctures were the most common type of injury for those < 14 years of age while for older individuals it was contusions/bruises. The plurality of injuries occurred in the summer months. Children working on a farm are in unique situation and tracking injuries and identifying injury sources provide necessary information to protect their health and well-being. Michigan's farm-injury surveillance system will continue to provide a comprehensive count of work-related injuries among Michigan's farming population. The information is used to direct public health intervention both at the individual and population level. [ABSTRACT FROM AUTHOR]

Agriculture is one of the most important and also hazardous industries in Australia. Having a sound knowledge and understanding of the circumstance of injury events is critical to developing evidence-based intervention programs. This paper aims to provide a brief historical snapshot of the development of data systems underpinning the assessment of fatal farm injury in Australia and how it has impacted on safety policy and practice. The first Australian studies used coronial information to explore agricultural fatalities, these studies reviewed paper-based records (in-situ) and collected the information for analysis and reporting. This task was laborious and costly. When the National Coronial Information System (NCIS) was established in 2000, this allowed access to coronial records online. Information provided about the deceased includes demographics, contextual details on the nature of the fatality and autopsy, toxicology, and police reports, as-well-as the coroner's finding. Information from the NCIS, along with media reports, have been used to develop the farm fatality database. This information has been used to inform the safety goals and targets for farm commodity groups, identify key risks, provide long-term benchmark indicators and underpin the development of prevention materials and training resources. Without accurate, timely, concise and relevant data about injury occurring on farms, there is no evidence to drive policy and practice or to evaluate programs of work. As such, the continued utilization and extension of the NCIS data will prove crucial to further reducing the burden of preventable fatal injuries on Australian farms. [ABSTRACT FROM AUTHOR]

Data is a basic production factor in the digital economy era, and it creates value in the processes of flow, sharing, and processing. However, there are different attitudes toward data flow, and less attention has been paid to the impact of data flow provisions on international trade. Based on the Trade Agreements Provisions on Electronic-commerce and Data (TAPED) database, we evaluate the impact of data flow provisions on trade in goods and services. Our results show that the signing of provisions on the free flow of data plays a more significant role in promoting trade in services. This finding is robust to a wide range of tests, including parallel trend test, lagging one period, and placebo tests. Mechanism analysis shows that signing provisions on the free flow of data can promote the growth of goods trade by breaking through distance restrictions. From the perspective of trade in services, the effect of signing data free flow provisions varies according to the degree of Internet access in the destination country. In addition, data flow provisions have heterogeneous effects on international trade at the national and industry levels. [ABSTRACT FROM AUTHOR]

The rapid enhancement in social media over the internet generates massive information in real-time scenarios, which has a striking impact on big data analysis. It resulted in the elevated usage of emotions and sentiments in social media. This paper proffers a proficient sentiment analysis technique in Twitter data. The Twitter database is preprocessed includes, stemming, tokenisation, number removal and stop word removal, etc. The preprocessed words are then passed into the HDFS (Hadoop Distributed File System) to reduce the repeated words and are eliminated using the MapReduce technique. The emoticons and the non-emoticons are extorted as features. The resulted features are ranked with their intended meaning. Then, the classification is performed utilising the DLMNN (Deep Learning Modified Neural Network). The experimental results were examined by using the output parameter such as Accuracy, Recall, Precision, F-Score and Execution Time with other conventional techniques such as ANN, SVM, K-Means and DCNN to show the greatest outcome of the proposed model. Evaluation result shows that DLMNN achieved the greatest performance in terms of precision (95.78%), Recall (95.84%), F-Score (95.87%) and Accuracy (91.65%) when compared with the existing models. [ABSTRACT FROM AUTHOR]

What is geopolitical risk to multinational enterprises in a world flooded with geopolitical changes? Does such risk impact foreign direct investment flows? To answer these questions, we attempt to develop the concept of comprehensive geopolitical risk by expanding the border of geopolitical risk in the literature to include both implicit and explicit risks that overseas investors face in host countries. We further construct an index by mining big data from a news report database, which we use to examine how comprehensive geopolitical risk impacts FDI outflows from China to 154 host countries between 2003 and 2020. Our findings indicate that comprehensive geopolitical risk does negatively impact FDI outflows, especially in the energy sector. Implicit geopolitical risk also significantly deters FDI outflows. [ABSTRACT FROM AUTHOR]

The year 2020 marked the 25th anniversary of the Barcelona Process, an initiative which is celebrated as the beginning of a quarter of a century of dialogue and cooperation between the EU and its South Mediterranean partners. This article offers the first systematic analysis of the scholarly debate about the EU's action in the Southern Mediterranean by using bibliometric data of studies from 1995 until 2020 from the Scopus database. The analysis reveals the following findings: first, regardless of the presence of several research networks, studies about Euro-Mediterranean relations remain mainly an individual enterprise. Second, after the Barcelona Process, the literature was marked by a creative synthesis between area studies and EU-wide trends leading to distinctive typologies of Euro-Mediterranean relations. Third, although there is a consensus among scholars about the EU's Eurocentric approach towards Euro-Mediterranean relations, a social network analysis of the literature shows that scientific cooperation remains extremely Eurocentric. Fourth, despite the important contribution of women in this field, the discipline suffers from a significant gender gap. [ABSTRACT FROM AUTHOR]

The prosperity of urban life is dependent on its infrastructure. Urban underground infrastructure components (assets) are aging and need regular monitoring, maintenance and rehabilitation. These assets are often placed under pavements and in close vicinity to each other. Managing them in a coordinated way is rational considering costs and disruption of services and communities caused by each intervention on the different assets. Recently, interest in practice as well as in research has grown to manage urban infrastructures in a coordinated way. This article reviews journal articles and grey literature to evaluate managing these infrastructures in an integrated way (i.e. the highest level of coordination) and describe possible obstacles for doing so. This article identifies seven main challenges of integrated multi-infrastructure asset management (IMAM) that need to be addressed by practitioners and researchers. These challenges are related to: (i) dependencies and interdependencies, (ii) data quality, availability and interoperability, (iii) uncertainties in modelling and decision-making, (iv) comparability, (v) problems of scale, (vi) problems of fit and (vii) problems of interplay. This article provides details on these challenges and discusses future research and practical directions. [ABSTRACT FROM AUTHOR]

Are secessionisms from and within the EU comparable? What motivates them and to what extent do they pose similar challenges to EU territorial governance? This article addresses these questions by comparing the framing of the British Leave campaign and the Catalan independence movement. Drawing on the FraTerr database and method, the analysis suggests that secessionism from the EU and secessionism within the EU are different political phenomena despite sharing an emphasis on sovereignty and the common goal of breaking-up from an existing polity. Secessionism from the EU is primarily a call for the recovery of lost sovereignty and of classical functions of the state such as border control. Secessionism within the EU invokes sovereignty as the right to external self-determination and adds narratives around a better future and greater democratic quality and social justice. These two types of secessionism pose different challenges to EU territorial governance because the first entails a full rejection of the European project while the latter calls for a review of European multi-level governance. [ABSTRACT FROM AUTHOR]

An updated strong-motion database of the Iranian earthquakes has been used to propose empirical equations for the prediction of peak ground velocity (PGV), peak ground acceleration (PGA), and 5%-damped Spectral Accelerations (SA) up to0.0 s for geometric mean of horizontal components. Some records from the NGA-West2 are added to the database to enrich it at near source distances for large magnitude events. Lack of data in the near source distances causes less accuracy in previous Iranian Ground Motion Models (GMMs) in comparison with the current study. In this work, the regression analyses have been performed on a truncated database which causes to obtain unbiased results. We used 3015 acceleration time series from 594 earthquakes after truncation of data to develop a new GMM. The provided model is valid for Joyner-Boore distances ranging from 0 km to80 km and magnitudes ranging from 4 to 7.9 and Vs30 ranging from50 m/s to500 m/s. [ABSTRACT FROM AUTHOR]

The compilation of a database of 225 strain/stress tensors (accounting for ~ 4000 fault-striae data pairs) combined with evidence of syntectonic strata, and a seismotectonic appraisal along the Patagonian Andes (39°-50° S; South America), leads us to assess typical features of Mesozoic to current faulting in this segment of the Andean orogen. At the orogen scale, the fault-slip and focal mechanism database show the prevalence of strike-slip faulting, challenging the classic proposal for the Andean orogen of alternating extensional and contractional deformation phases. However, the wrenching tectonism in Cenozoic times may be explained through a strain partitioning model in the North Patagonian Andes by re-activating a large-scale, inherited anisotropy within the basement (namely the Liquiñe-Ofqui fault system), which is currently the locus of significant seismicity. On the other hand, a non-partitioned context allows explaining the Cenozoic patterns of brittle deformation the South Patagonian Andes. Our results highlight that the classifications of Andean-type orogens should integrate both inherited anisotropies and the heterogeneous distribution of strain across the upper plate in order to address complex patterns of deformation. [ABSTRACT FROM AUTHOR]

To explore a noninvasive method for diagnosis of SEA-thalassemia and to investigate whether the regional factors affect the accuracy of this method. The method involved using a public database and bioinformatics software to construct parental haplotypes for proband and predicting fetal genotypes using relative haplotype dosage. We screened and downloaded sequencing data of couples who were both SEA-thalassemia carriers from the China National Genebank public data platform, and matched the sequencing data format with that of the reference panel using Ubuntu system tools. We then used Beagle software to construct parental haplotypes, predicted fetal haplotypes by relative haplotype dosage. Finally, we used Hidden Markov Model and Viterbi algorithm to determine fetal pathogenic haplotypes. All noninvasive fetal genotype diagnosis results were compared with gold standard gap-PCR electrophoresis results. Our method was successful in diagnosing 13 families with SEA-thalassemia carriers. The best diagnostic results were obtained when Southern Chinese Han was used as the reference panel, and 10 families showed full agreement between our noninvasive diagnostic results and the gap-PCR electrophoresis results. The accuracy of our method was higher when using a Chinese Han as the reference panel for haplotype construction in the Southern Chinese Han region as opposed to Beijing Chinese region. The combined use of public databases and relative haplotype dosage for diagnosing SEA-thalassemia is a feasible approach. Our method produces the best noninvasive diagnostic results when the test samples and population reference panel are closely matched in both ethnicity and geography. When constructing parental haplotypes with our method, it is important to consider the effect of region in addition to population background alone. [ABSTRACT FROM AUTHOR]

The objective of this study is to propose a knowledge organization system (KOS) for the ethnic groups of Laos by utilizing linked open data (LOD) to standardize the metadata. Data of 49 Laos ethnic groups and the techniques of Linked Open Data were used. Linked data of ethnic groups in Lao PDR from other external standardized data sources, including DBpedia and Wikidata, was found. The results indicate that there is limited an information on the ethnic groups of Laos in online databases. This study aims to link and improve data on Laos ethnic groups by utilizing ontology and reconciliation techniques to link incomplete or outdated data, as well as using OpenRefine and RDF extension to link the source database. Although the country has implemented policies to promote the national identity and the tourism economy, much of the related information remains inaccessible to the public as it is only available in official documents. The available information in the online database system would be compared to foreign languages like Vietnamese, Thai, etc., because these areas and ethnic groups were close to each other, and the languages were in the same family. [ABSTRACT FROM AUTHOR]

The COVID-19 Epidemiological Investigation Support System (EISS) is a digital epidemiological tool, which utilizes location data from cellular base stations, credit card transactions records, and QR codes. It is a mass surveillance system that uses big data to track the entire infected population, featuring an extensive, automated, and speedy processing of data on personal location and the linkage of multiple databases from various governmental agencies. Based on interviews with people who have developed Korean digital epidemiology systems, this paper explores the technical, infrastructural, social, and institutional factors that have shaped Korean digital epidemiology since the 2014 avian flu crisis and examines the essential conditions of big data for digital epidemiology. The main findings are as follows: The feasibility of EISS goes beyond the matter of privacy; it is closely connected to technological infrastructures such as a high density of cellular base stations and private cloud systems; people's behavior such as a high rate of smartphone and credit card usage; and new forms of governance and institutions for speedy data processing. Multiple database linkage would develop EISS into a big data surveillance system that enables the prediction of risk-prone groups in a more preemptive manner. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has achieved a remarkable place in solving complex problems in almost all disciplines. Based on the recent notable performances of machine learning and deep learning techniques for rapid and automatic landslide identifcation, it is observed that availability of quality training data, proper model training and associated cost are crucial for developing such frameworks. Therefore, the primary objective of the study is to propose a novel empirical algorithm, DvD, for rapid landslide identification using Sentinel-2 imagery and comparatively evaluate its performance to a deep learning architecture popularly used in feature extraction problems, binary semantic segmentation U-NET (BSS-UNET) framework. The empirical method has been investigated over a dataset diverse in topography and land cover to evaluate its efficacy. The proposed BSS-UNET framework is trained on the landslide database provided by the Institute of Advance Research in Artificial Intelligence (IARAI) in Landslide4Sense 2022 challenge which achieved a high mIoU value of 0.78 with 84.23% precision, 65% recall and 73.32 F1-score. The DvD algorithm outperformed the BSS-UNET framework and achieved 0.80 mIoU when applied to the IARAI dataset. The proposed empirical method has the potential to serve as large-scale rapid landslide inventory preparation subject to the availability of cloud-free satellite imagery. [ABSTRACT FROM AUTHOR]

This paper investigates the biological, socio-economic, and institutional factors shaping the individual risk of death during a major pre-industrial epidemic. We use a micro-demographic database for an Italian city (Carmagnola) during the 1630 plague to explore in detail the survival dynamics of the population admitted to the isolation hospital (lazzaretto). We develop a theoretical model of admissions to the lazzaretto, for better interpretation of the observational data. We explore how age and sex shaped the individual risk of death, and we provide a one-of-a-kind study of the impact of socio-economic status. We report an inversion of the normal mortality gradient by status for those interned at the lazzaretto. The rich enjoyed a greater ability to make decisions about their hospitalization, but this backfired. Instead, the poor sent to the lazzaretto faced a relatively low risk of death because they enjoyed better conditions than they would have experienced outside the hospital. [ABSTRACT FROM AUTHOR]

Despite the development of alternative modes of urban transport, the private car is still the most popular transport option in many regions around the world. Various spatial and socio-economic characteristics of metropolitan areas (MAs) seem to be generally correlated with levels of car use, and thus with car dependency. In this research, we study car dependency in a subgroup of global MAs, that are characterized profiles of car dependency, and are therefore considered outliers. Drawing on data that are available from the Mobility in Cities Database (MCD), we consider 56 MAs and use Mahalanobis distance to identify 7 outlier MAs that are either more, or less car dependent than anticipated by the regression model. We investigate the driving forces behind unpredicted levels of car use and position the outlier MAs in a catalogue of mobility profiles. A combination of urban form, convenience of car use, availability of alternative modes to car and car ownership characteristics were found to contribute to the level of car dependency in these MAs. [ABSTRACT FROM AUTHOR]

The benefits of research data sharing abound in the literature. However, some factors define how researchers and clinicians approach the challenges surrounding sharing human movement health research data. To describe the perceptions of human movement researchers and clinicians on the barriers and facilitators to research data sharing in Africa. A qualitative descriptive design with a purposive sampling method was used. In-depth interviews with human movement researchers and clinicians across Africa were conducted online via Microsoft Teams. Sixteen (n = 16) participants took part in this study. This sample size was representative of East, West, Northern, and Southern Africa. Efforts made to engage with participants in Central Africa were unsuccessful. Five themes emerged: 1) the researcher-clinician gap; 2) technological pros and cons in Africa; 3) cost matters; 4) bureaucracy and ethical factors; and 5) the unique African perspective. Mainly, barriers rather than facilitators to data sharing exist among African human movement researchers and clinicians. There needs to be a societal and psychological shift through reorientation to encourage data sharing among African human movement researchers and clinicians. [ABSTRACT FROM AUTHOR]

In this study, a methodology is proposed, combining ligand- and structure-based virtual screening tools, for the identification of phosphorus-containing compounds as inhibitors of zinc metalloproteases. First, we use Dragon molecular descriptors to develop a Linear Discriminant Analysis classification model, which is widely validated according to the OECD principles. This model is simple, robust, stable and has good discriminating power. Furthermore, it has a defined applicability domain and it is used for virtual screening of the DrugBank database. Second, docking experiments are carried out on the identified compounds that showed good binding energies to the enzyme thermolysin. Considering the potential toxicity of phosphorus-containing compounds, their toxicological profile is evaluated according to Protox II. Of the five molecules evaluated, two show carcinogenic and mutagenic potential at small LD50, not recommended as drugs, while three of them are classified as non-toxic, and could constitute a starting point for the development of new vasoactive metalloprotease inhibitor drugs. According to molecular dynamics simulation, two of them show stable interactions with the active site maintaining coordination with the metal. A high agreement is evident between QSAR, docking and molecular dynamics results, demonstrating the potentialities of the combination of these tools. [ABSTRACT FROM AUTHOR]