Domain Coverage Research Articles

Permutation Coding for Vertex-Blend Attribute Compression

Compression of vertex attributes is crucial to keep bandwidth requirements in real-time rendering low. We present a method that encodes any given number of blend attributes for skinning at a fixed bit rate while keeping the worst-case error small. Our method exploits that the blend weights are sorted. With this knowledge, no information is lost when the weights get shuffled. Our permutation coding thus encodes additional data, e.g. about bone indices, into the order of the weights. We also transform the weights linearly to ensure full coverage of the representable domain. Through a thorough error analysis, we arrive at a nearly optimal quantization scheme. Our method is fast enough to decode blend attributes in a vertex shader and also to encode them at runtime, e.g. in a compute shader. Our open source implementation supports up to 13 weights in up to 64 bits.

Development and validation of the symptom burden questionnaire for long covid (SBQ-LC): Rasch analysis

ObjectiveTo describe the development and validation of a novel patient reported outcome measure for symptom burden from long covid, the symptom burden questionnaire for long covid (SBQ-LC).DesignMultiphase, prospective mixed methods...

Factor Structure and Reliability of A Servant Leader Humility Scale

Humility is a core trait of servant leaders, enabling them to better understand the needs of their workplaces, make optimum decisions, readily accept and use feedback, and effortlessly ask for assistance when the need arises. While several instruments exist for measuring leader humility, their coverage of the humility domain differ. They also seem to conflate (and even confound) the construct with similar but distinct ideas like modesty and honesty. As a contribution towards addressing these issues, the researchers explored the factor structure and reliability of the humility scale from Page and Wong’s (2000) Servant Leadership Profile (SLP). Principal component analysis (PCA) and confirmatory factor analysis (CFA) were performed using JASP on a dataset generated from a sample of 181 academic staff drawn online from the 30 public universities in Saudi Arabia. Contrary to Page and Wong’s (2000) unidimensional structure of the humility scale, the PCA results suggest a two-factor (humbleness factor and self-effacement factor) solution that explains 49% of the cumulative variance. The results from CFA analysis confirm the fit of the model structure (?2/df = 0.863, CFI = 1.000, TLI = 1.011, NFI = 0.954, RMSEA = 0.000, SRMR = 0.051, GFI = 0.974, MFI = 1.010) for the Servant Leader Humility Scale (SLHS). However, while results of reliability analyses indicate that the humbleness factor shows good psychometrics (? = .833, CI = .795–.872; ? = .810, CI = .759–.852), it is not so with the self-effacement factor (? = .685, CI = .614–.756; ? = .671, CI = .588–.741). Accordingly, we recommend that the humbleness factor should be given greater weight in the evaluation of servant leadership qualities.

Scalable Moir\xe9 Lattice with Oriented TMD Monolayers

Moiré lattice in artificially stacked monolayers of two-dimensional (2D) materials effectively modulates the electronic structures of materials, which is widely highlighted. Formation of the electronic Moiré superlattice promises the prospect of uniformity among different moiré cells across the lattice, enabling a new platform for novel properties, such as unconventional superconductivity, and scalable quantum emitters. Recently, epitaxial growth of the monolayer transition metal dichalcogenide (TMD) is achieved on the sapphire substrate by chemical vapor deposition (CVD) to realize scalable growth of highly-oriented monolayers. However, fabrication of the scalable Moiré lattice remains challenging due to the lack of essential manipulation of the well-aligned monolayers for clean interface quality and precise twisting angle control. Here, scalable and highly-oriented monolayers of TMD are realized on the sapphire substrates by using the customized CVD process. Controlled growth of the epitaxial monolayers is achieved by promoting the rotation of the nuclei-like domains in the initial growth stage, enabling aligned domains for further grain growth in the steady-state stage. A full coverage and distribution of the highly-oriented domains are verified by second-harmonic generation (SHG) microscopy. By developing the method for clean monolayer manipulation, hetero-stacked bilayer (epi-WS2/epi-MoS2) is fabricated with the specific angular alignment of the two major oriented monolayers at the edge direction of 0°/ ± 60°. On account of the optimization for scalable Moiré lattice with a high-quality interface, the observation of interlayer exciton at low temperature illustrates the feasibility of scalable Moiré superlattice based on the oriented monolayers.

Physics-aware learning and domain-specific loss design in ophthalmology.

The human cataract, a developing opacification of the human eye lens, currently constitutes the world's most frequent cause for blindness. As a result, cataract surgery has become the most frequently performed ophthalmic surgery in the world. By removing the human lens and replacing it with an artificial intraocular lens (IOL), the optical system of the eye is restored. In order to receive a good refractive result, the IOL specifications, especially the refractive power, have to be determined precisely prior to surgery. In the last years, there has been a body of work to perform this prediction by using biometric information extracted from OCT imaging data, recently also by machine learning (ML) methods. Approaches so far consider only biometric information or physical modelling, but provide no effective combination, while often also neglecting IOL geometry. Additionally, ML on small data sets without sufficient domain coverage can be challenging. To solve these issues, we propose OpticNet, a novel optical refraction network based on an unsupervised, domain-specific loss function that explicitly incorporates physical information into the network. By providing a precise and differentiable light propagation eye model, physical gradients following the eye optics are backpropagated into the network. We further propose a new transfer learning procedure, which allows the unsupervised pre-training on the optical model and fine-tuning of the network on small amounts of surgical patient data. We show that our method outperforms the current state of the art on five OCT-image based data sets, provides better domain coverage within its predictions, and achieves better physical consistency.

Evaluation of Community Medicine Postgraduate Theory Examination to Measure the Content and Cognitive Domain CoverageA Retrospective Analysis

Introduction: Assessment is a critical step in learning process. Postgraduate theory examination ideally should assess higher levels of cognition. In order to maintain high standard of public health the postgraduates of the specialty should be certified properly using the appropriate assessment methods. Since the assessment drives learning, ideally it should be aimed at judging a learner’s attainment of curriculum outcomes. Aim: To evaluate the postgraduate theory exam question papers from 2014 to 2018 in Community Medicine (CM) of various South Indian Universities and to measure the actual content coverage as stated in National Medical Commission (NMC) curriculum and cognitive domain coverage as per Bloom’s taxonomy. Materials and Methods: The present retrospective analytical study was conducted from April 2019 to July 2019 to asses the question papers from 2014-2018 in community medicine. Sixty theory exam question papers (20 per University) of last 5 years of three South Indian Universities namely Pondicherry (PU), Tamil Nadu (TN), and Kerala (KR) of CM subject were analysed for content coverage and to categorise the level of knowledge assessed as per Bloom’s taxonomy. The significance of difference between the data of various years was tested using Chi-square test. Results: Questions testing higher cognitive domain was found only in 15%, 3.75% and 2.5% of PU, TN and KR universities, respectively. Epidemiology of communicable and noncommunicable diseases was the content that received maximum coverage of total marks, 25%, 21.25% and 18.5% in PU, TN and KR universities respectively. Certain topics were not covered in many papers. There was no statistical difference in distribution of marks among various Universities in South India. Conclusion: Findings of this study may be used to redefine the distribution of contents and cognitive domain tested across universities ensuring the validity and reliability of the assessment.

Space-Based Global Maritime Surveillance. Part II: Artificial Intelligence and Data Fusion Techniques

Maritime surveillance (MS) is of paramount importance for search and rescue operations, fishery monitoring, pollution control, law enforcement, migration monitoring, and national security policies. Since ground-based radars and automatic identification system (AIS) do not always provide a comprehensive and seamless coverage of the entire maritime domain, the use of space-based sensors is crucial to complement them. We reviewed space-based technologies for MS in the first part of this work, titled "Space-based Global Maritime Surveillance. Part I: Satellite Technologies" [1]. However, future MS systems combining multiple terrestrial and space-based sensors with additional information sources will require dedicated artificial intelligence and data fusion techniques for the processing of raw satellite images and fuse heterogeneous information. The second part of our work focuses on the most promising artificial intelligence and data fusion techniques for MS using space-based sensors.

Ranked choice voting for representative transcripts with TRaCE.

SummaryGenome sequencing projects annotate protein-coding gene models with multiple transcripts, aiming to represent all of the available transcript evidence. However, downstream analyses often operate on only one representative transcript per gene locus, sometimes known as the canonical transcript. To choose canonical transcripts, Transcript Ranking and Canonical Election (TRaCE) holds an ‘election’ in which a set of RNA-seq samples rank transcripts by annotation edit distance. These sample-specific votes are tallied along with other criteria such as protein length and InterPro domain coverage. The winner is selected as the canonical transcript, but the election proceeds through multiple rounds of voting to order all the transcripts by relevance. Based on the set of expression data provided, TRaCE can identify the most common isoforms from a broad expression atlas or prioritize alternative transcripts expressed in specific contexts.Availability and implementationTranscript ranking code can be found on GitHub at {{https://github.com/warelab/TRaCE}}.Supplementary information Supplementary data are available at Bioinformatics online.

Buckling-resistant topological design using sensitivities to variations in localised nominal stiffness

Thin-walled structures are extensively used in aerospace, automotive and mechanical engineering applications due to their high strength- and stiffness-to-weight ratios. However, the performance of these structures tends to be heavily influenced by localised features such as manufacturing defects or design details included for non-structural reasons, e.g. inspection cut-outs. Understanding the sensitivity of structural performance to these nominal stiffness variations, and especially their spatial distribution through the volume of the structure, is important to the designer. We propose a new methodology, the Localised Nominal Stiffness method, to quantify the sensitivity of buckling performance to the distribution of nominal stiffness variations across the structure. The underpinning idea involves reducing the stiffness in small localised regions of the structure and quantifying the ensuing variation in linear buckling capacity before returning the stiffness to its original value. The process is repeated for all locations ensuring coverage of the entire structural domain, which leads to a sensitivity map. In practice, each location corresponds to an element in a finite element mesh. Focusing on structures subject to buckling constraints, and with the aim of using highly efficient structural analysis, we identify sensitivities using the hierarchical Unified Formulation. The resulting sensitivity contour maps can be used to identify regions of the structure where defects or removal of material (for lightweighting) would not significantly affect buckling and post-buckling performance. The effectiveness of the method is tested through three examples: a simply-supported plate; a simply-supported, thin-walled box-section column; and a thin shell with simply-supported and clamped boundary conditions. In all cases, the buckling performance of structures can be maintained with reduced structural weight.

AOP Report: Inhibition of Chitin Synthase 1 Leading to Increased Mortality in Arthropods.

AOP Report: Inhibition of Chitin Synthase 1 Leading to Increased Mortality in Arthropods.

Representation of Music Creators on Wikipedia, Differences in Gender and Genre

Wikipedia is not only the world’s largest online encyclopedia and among the most frequented websites, but provides important data leveraged by many popular services and products. Since Wikipedia data is ubiquitously encountered, it is important to evaluate its coverage of content and identify data gaps that may exist. Here, we evaluate Wikipedia’s coverage of the music domain, which is one of the most popular topics.Particularly, we compile the most prominent 50,000 music artists (by streaming popularity on a large online streaming platform) and determine whether each artist has a Wikipedia page. We first show that streaming popularity correlates with Wikipedia representation – while 90% of the top one thousand most popularly streamed artists are on Wikipedia, the chance of being on Wikipedia drops to 50% after the ten thousandth artist. Next, we examine the Wikipedia coverage of artists of different gender and genre, while controlling for popularity.We also examine, for artists that are on Wikipedia, the amount of content, frequency of edits, and Pagerank for their pages.We uncover large differences in representation for artists of different genres; for the same popularity level ,hiphop, latin, and dance/electronic artists are most lacking in representation while rock artists have approximately twice as much representation. With respect to gender, while female artists are under represented in the top of the music industry itself, male artists were less likely represented on Wikipedia relative to the female artists in this study’s top sample, suggesting inter-action with genre and visibility of select superstars.

Dissociation Strategies to Maximize Coverage of α-Helical Domains in Top-Down Mass Spectrometry of Integral Membrane Proteins.

Transmembrane α-helical domains of membrane proteins tend to remain structured in the gas phase, presenting a challenge for efficient electron capture/transfer dissociation during top-down dissociation mass spectrometry (MS) experiments. In this study, we compare results from different dissociation modes on a modern Orbitrap platform applied to a model integral membrane protein containing two transmembrane helices, the c-subunit of the Fo domain of the chloroplast ATP synthase. Using commercially available options, we compare collisionally activated dissociation (CAD) with the related variant higher-energy collisional dissociation (HCD) and with electron transfer dissociation (ETD). HCD performed better than CAD and ETD. A combined method utilizing both ETD and HCD (EThcD) demonstrates significant synergy over HCD or ETD alone, representing a robust option analogous to activated ion electron capture dissociation, whereby an infrared laser was used to heat the protein ion alongside electron bombardment. Ultraviolet photodissociation at 213 nm displays at least three backbone dissociation mechanisms and covered nearly 100% of backbone bonds, suggesting significant potential for this technique.

Coordinating assessment of spiritual needs: a cross-walk of narrative and psychometric assessment tools used in palliative care

Addressing spiritual needs of patients in healthcare settings improves patient experiences and clinical outcomes; however, non-chaplain providers typically assess spiritual needs differently (quantitative psychometric) than healthcare chaplains (long form narrative) and thus there is little shared language or cross-disciplinary evaluation frameworks across disciplines. This discrepancy impedes the provision of both team-based and patient-centered care. This paper used scoping review methodology to illustrate the overlap between narrative and psychometric assessment tools, comparing four narrative tools against eight psychometric tools. The SpNQ-120 and Brief RCOPE demonstrated consistent domain coverage across the four chaplain narrative tools. This work provides preliminary resources to aid clinicians and researchers in choosing an appropriate tool. Additionally, for those who do not work closely with chaplains, it provides a sense of what domains chaplains prioritize, from their professional and lived experience, in assessing the spiritual life of the patient. This improves interdisciplinary communication, and therefore, patient care.

STO: Stroke Ontology for Accelerating Translational Stroke Research.

IntroductionOntology-based annotation of evidence, using disease-specific ontologies, can accelerate analysis and interpretation of the knowledge domain of diseases. Although many domain-specific disease ontologies have been developed so far, in the area of cardiovascular diseases, there is a lack of ontological representation of the disease knowledge domain of stroke.MethodsThe stroke ontology (STO) was created on the basis of the ontology development life cycle and was built using Protégé ontology editor in the ontology web language format. The ontology was evaluated in terms of structural and functional features, expert evaluation, and competency questions.ResultsThe stroke ontology covers a broad range of major biomedical and risk factor concepts. The majority of concepts are enriched by synonyms, definitions, and references. The ontology attempts to incorporate different users’ views on the stroke domain such as neuroscientists, molecular biologists, and clinicians. Evaluation of the ontology based on natural language processing showed a high precision (0.94), recall (0.80), and F-score (0.78) values, indicating that STO has an acceptable coverage of the stroke knowledge domain. Performance evaluation using competency questions designed by a clinician showed that the ontology can be used to answer expert questions in light of published evidence.ConclusionsThe stroke ontology is the first, multiple-view ontology in the domain of brain stroke that can be used as a tool for representation, formalization, and standardization of the heterogeneous data related to the stroke domain. Since this is a draft version of the ontology, the contribution of the stroke scientific community can help to improve the usability of the current version.

Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data

Benchmarking unsupervised outlier detection is difficult. Outliers are rare, and existing benchmark data contains outliers with various and unknown characteristics. Fully synthetic data usually consists of outliers and regular instances with clear characteristics and thus allows for a more meaningful evaluation of detection methods in principle. Nonetheless, there have only been few attempts to include synthetic data in benchmarks for outlier detection. This might be due to the imprecise notion of outliers or to the difficulty to arrive at a good coverage of different domains with synthetic data. In this work, we propose a generic process for the generation of datasets for such benchmarking. The core idea is to reconstruct regular instances from existing real-world benchmark data while generating outliers so that they exhibit insightful characteristics. We propose and describe a generic process for the benchmarking of unsupervised outlier detection, as sketched so far. We then describe three instantiations of this generic process that generate outliers with specific characteristics, like local outliers. To validate our process, we perform a benchmark with state-of-the-art detection methods and carry out experiments to study the quality of data reconstructed in this way. Next to showcasing the workflow, this confirms the usefulness of our proposed process. In particular, our process yields regular instances close to the ones from real data. Summing up, we propose and validate a new and practical process for the benchmarking of unsupervised outlier detection.

Development and validation of a patient-report measure of safety climate for general practice.

Patients remain an under-utilized source of information on patient safety, as reflected by the dearth of patient-report measures of safety climate, particularly for use in general practice settings. Extant measures are marked by poor coverage of safety climate domains, inadequate psychometric properties and/or lack of consideration of usability. To develop a novel patient-report measure of safety climate specifically for completion by general practice patients, and to establish the validity, reliability and usability of this measure. An iterative process was used to develop the safety climate measure, with patient and general practitioner input. A cross-sectional design was employed to examine the validity (content, construct and convergent), reliability (internal consistency), and usability (readability and burden) of the measure. A total of 584 general practice patients completed the measure. The exploratory factor analysis identified five factors pertaining to safety climate in general practice: Feeling of Safety with GP; Practice Staff Efficiency and Teamwork; Staff Stress and Workload; Patient Knowledge and Accountability, and; Safety Systems and Behaviours. These factors strongly correlated with two global safety measures, demonstrating convergent validity. The measure showed strong internal consistency, and was considered usable for patients as indicated by readability and duration of completion. Our novel measure of safety climate for use in general practice demonstrates favourable markers of validity, reliability and usability. This measure will provide a mechanism for the patient voice to be heard in patient safety measurement, and to be used to improve patient safety in general practice.

Comparison of Two 16S rRNA Primers (V3-V4 and V4-V5) for Studies of Arctic Microbial Communities.

Microbial communities of the Arctic Ocean are poorly characterized in comparison to other aquatic environments as to their horizontal, vertical, and temporal turnover. Yet, recent studies showed that the Arctic marine ecosystem harbors unique microbial community members that are adapted to harsh environmental conditions, such as near-freezing temperatures and extreme seasonality. The gene for the small ribosomal subunit (16S rRNA) is commonly used to study the taxonomic composition of microbial communities in their natural environment. Several primer sets for this marker gene have been extensively tested across various sample sets, but these typically originated from low-latitude environments. An explicit evaluation of primer-set performances in representing the microbial communities of the Arctic Ocean is currently lacking. To select a suitable primer set for studying microbiomes of various Arctic marine habitats (sea ice, surface water, marine snow, deep ocean basin, and deep-sea sediment), we have conducted a performance comparison between two widely used primer sets, targeting different hypervariable regions of the 16S rRNA gene (V3–V4 and V4–V5). We observed that both primer sets were highly similar in representing the total microbial community composition down to genus rank, which was also confirmed independently by subgroup-specific catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) counts. Each primer set revealed higher internal diversity within certain bacterial taxonomic groups (e.g., the class Bacteroidia by V3–V4, and the phylum Planctomycetes by V4–V5). However, the V4–V5 primer set provides concurrent coverage of the archaeal domain, a relevant component comprising 10–20% of the community in Arctic deep waters and the sediment. Although both primer sets perform similarly, we suggest the use of the V4–V5 primer set for the integration of both bacterial and archaeal community dynamics in the Arctic marine environment.

An Ontology-Based Approach to Automated Test Case Generation

Software testing is as old as software itself. However, the techniques, tools, and processes used by researchers to ensure product quality are constantly evolving. Application of knowledge management technologies in automated test case generation is one of them. This paper addressed the issue of ontology-based automated test case generation in the case of black box testing. In this context, several challenges are present in existing literature. The prime challenges among are (1) major approaches are confined to a specific domain, (2) least consideration about modified domain knowledge, (3) lack of methodology for auto-identification of pre-conditions and different combinations among test input data and (4) poor requirements and domain coverage. The proposed methodology, in this paper, is aimed to resolve these issues by devising a rule-based reasoner that can auto generate the test cases. The proposed method takes an ontology-based requirements specification as an input. The novelty of the proposed method is the specification of domain independent inference rules based on which the devised reasoner can generate test cases for different domains and systems automatically. This contribution of the proposed work facilitates in improving both user’s requirements coverage and domain coverage. The devised reasoned, in this paper, is implemented in Apache Jena (Apache Jena, https://jena.apache.org ., Accessed 2020/09/04). In addition, the usability of the proposed work is illustrated using a suitable case study.

AgentDSM-Eval: A framework for the evaluation of domain-specific modeling languages for multi-agent systems

Software development required for constructing multi-agent systems (MAS) usually becomes challenging and time-consuming due to the properties of autonomy, distributedness, and openness of these systems in addition to the complicated nature of internal agent behaviors and agent interactions. To facilitate MAS development, the researchers propose various domain-specific modeling languages (DSMLs) by enriching MAS metamodels with a defined syntax and semantics. Although the descriptions of these languages are given in the related studies with the examples of their use, unfortunately, many are not evaluated in terms of either the usability (being hard to learn, understand and use) or the quality of the generated artifacts. Hence, in this paper, we introduce an evaluation framework, called AgentDSM-Eval, with its supporting tool which can be used to evaluate MAS DSMLs systematically according to various quantitative and qualitative aspects of agent software development. The empirical evaluation, presented by the AgentDSM-Eval framework, was successfully applied for one of the well-known MAS DSMLs. The assessment showed that both MAS domain coverage of DSMLs and the agent developers’ adoption of modeling elements can be determined with this framework. Moreover, the tool's quantitative results can assess MAS DSML's performance on the development time and throughput. AgentDSM-Eval also enables the qualitative assessment of MAS DSML features according to novel quality characteristics and measures, which it defines specifically for the MAS domain.

Teleneuropsychology practice survey during COVID-19 within the United States

Objective Identify factors influencing service delivery changes during COVID-19 and examine barriers and provider satisfaction with teleneuropsychology (teleNP). Method Licensed clinical neuropsychologists within the United States recruited via neuropsychology-specific listservs (July–August 2020) to complete an online survey. Results A total of 261 individuals completed the survey. Most (76%) reported delivering in-person testing in some capacity at the time of our survey. Relatively more private practitioners identified concerns with privacy/confidentiality (45.2% vs. 17.9%; χ 2(2) = 6.99, p < 0.05), legal issues (47.6% vs. 17.9%; χ 2(2) = 8.06, p < 0.05), and an undesirable precedent for legal/forensic cases (59.5% vs. 15.4%; χ 2(2) = 17.54, p < 0.001) compared to hospital or other medical (non-VA) practitioners. Multiple resources informed teleNP protocols, such as organization guidelines (87.6%), literature review (75.9%), webinars (72.4%), and consultation (68%). Several factors influenced test selection, including availability of normative data (70.1%), test familiarity (66.4%), administration time (63.5%), and evidence base (60.6%). Reported barriers to continuing teleNP after COVID-19 included need for improved teleNP norms (85.9%), domain coverage (84.7%), improved patient access to technology (74.1%) and further validation studies (84.1%). Conclusion TeleNP may not be feasible in all settings and/or referrals. Respondents employed multiple resources in aggregating teleNP protocols and considered several factors when selecting tests. Results highlight the complex and varied decision-making processes utilized by respondents to adapt to service delivery changes. Considering the many benefits of teleNP, future research addressing some of the potentially modifiable factors (e.g., technology access, attitudes regarding teleNP) and significant development needs for teleNP itself (i.e., improved teleNP norms, further validation studies, etc.) is warranted.