Consistent Interpretation Research Articles

The rise of artificial intelligence reading of chest X-rays for enhanced TB diagnosis and elimination.

We provide an overview of the latest evidence on computer-aided detection (CAD) software for automated interpretation of chest radiographs (CXRs) for TB detection. CAD is a useful tool that can assist in rapid and consistent CXR interpretation for TB. CAD can achieve high sensitivity TB detection among people seeking care with symptoms of TB and in population-based screening, has accuracy on-par with human readers. However, implementation challenges remain. Due to diagnostic heterogeneity between settings and sub-populations, users need to select threshold scores rather than use pre-specified ones, but some sites may lack the resources and data to do so. Efficient standardisation is further complicated by frequent updates and new CAD versions, which also challenges implementation and comparison. CAD has not been validated for TB diagnosis in children and its accuracy for identifying non-TB abnormalities remains to be evaluated. A number of economic and political issues also remain to be addressed through regulation for CAD to avoid furthering health inequities. Although CAD-based CXR analysis has proven remarkably accurate for TB detection in adults, the above issues need to be addressed to ensure that the technology meets the needs of high-burden settings and vulnerable sub-populations.

Enhanced Defensive Model Using CNN against Adversarial Attacks for Medical Education through Human Computer Interaction

The design of human-machine interfaces is more precise and demanding in the medical and healthcare industries. Medical monitoring equipment demands more consistent and effective interpretation, as well as fast and straightforward operation due to its monitoring and reference functions. Consequently, it is crucial to consider how people interact with computers when designing the interface for medical monitoring devices. Nowadays people are giving more importance to health than anything in the world. Therefore, as it is related to peoples’ safety, the architecture of human-computer communication must be carefully considered in the studies and development of high-end medical equipment. The price of training physicians and other medical professionals is rising dramatically. Most of the countries have stepped forward from the traditional medical teaching system to a more human computer interactive teaching and learning environment with innovative technologies. This article focuses on the related researches, existing HCI applications for healthcare and the application of deep neural network for disease classification. The proposed work is to develop a healthcare learning platform to offer healthcare education to both medical practitioners and also for common people. This can be implemented as Mobile apps using human-computer interface technology and also as a website with Artificial Intelligence and Machine Learning Techniques. This proposal’s primary goal is to provide anytime, everywhere access to healthcare education for physiological and medical teaching courses, consequently advancing national health care.

A deep learning-based approach for statistical robustness evaluation in proton therapy treatment planning: a feasibility study

Objective. Robustness evaluation is critical in particle radiotherapy due to its susceptibility to uncertainties. However, the customary method for robustness evaluation only considers a few uncertainty scenarios, which are insufficient to provide a consistent statistical interpretation. We propose an artificial intelligence–based approach that overcomes this limitation by predicting a set of percentile dose values at every voxel and allows for the evaluation of planning objectives at specific confidence levels. Approach. We built and trained a deep learning (DL) model to predict the 5th and 95th percentile dose distributions, which corresponds to the lower and upper bounds of a two-tailed 90% confidence interval (CI), respectively. Predictions were made directly from the nominal dose distribution and planning computed tomography scan. The data used to train and test the model consisted of proton plans from 543 prostate cancer patients. The ground truth percentile values were estimated for each patient using 600 dose recalculations representing randomly sampled uncertainty scenarios. For comparison, we also tested whether a common worst-case scenario (WCS) robustness evaluation (voxel-wise minimum and maximum) corresponding to a 90% CI could reproduce the ground truth 5th and 95th percentile doses. Main results. The percentile dose distributions predicted by DL yielded excellent agreements with the ground truth dose distributions, with mean dose errors below 0.15 Gy and average gamma passing rates (GPR) at 1 mm/1% above 93.9, which were substantially better than the WCS dose distributions (mean dose error above 2.2 Gy and GPR at 1 mm1% below 54). We observed similar outcomes in a dose-volume histogram error analysis, where the DL predictions generally yielded smaller mean errors and standard deviations than the WCS evaluation doses. Significance. The proposed method produces accurate and fast predictions (∼2.5 s for one percentile dose distribution) for a given confidence level. Thus, the method has the potential to improve robustness evaluation.

FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution.

Factor analysis is a widely used tool for unsupervised dimensionality reduction of high-throughput datasets in molecular biology, with recently proposed extensions designed specifically for spatial transcriptomics data. However, these methods expect (count) matrices as data input and are therefore not directly applicable to single molecule resolution data, which are in the form of coordinate lists annotated with genes and provide insight into subcellular spatial expression patterns. To address this, we here propose FISHFactor, a probabilistic factor model that combines the benefits of spatial, non-negative factor analysis with a Poisson point process likelihood to explicitly model and account for the nature of single molecule resolution data. In addition, FISHFactor shares information across a potentially large number of cells in a common weight matrix, allowing consistent interpretation of factors across cells and yielding improved latent variable estimates. We compare FISHFactor to existing methods that rely on aggregating information through spatial binning and cannot combine information from multiple cells and show that our method leads to more accurate results on simulated data. We show that our method is scalable and can be readily applied to large datasets. Finally, we demonstrate on a real dataset that FISHFactor is able to identify major subcellular expression patterns and spatial gene clusters in a data-driven manner. The model implementation, data simulation and experiment scripts are available under https://www.github.com/bioFAM/FISHFactor.

‘But not that which has lost its soul is what is potentially alive’ – The Relation between Body and Soul in Aristotle

The thus far little noticed element in Aristotle's definition of the soul – namely, its nexus to the particularities of a complex physical body (σῶμα φυσικόν / sôma physikon) – is the key to resolve three apparent inconsistencies of Aristotelian hylomorphism: First, the incompatible modalities of the assumed binding relation between physical body as a simultaneously functional matter and the soul as its form; second, the homonymy problem, i.e., that, according to Aristotle's own statement, a body’s remnant that was abandoned by its soul can only homonymously be called that which it was when it was alive; third, the problem that form in hylomorphism seems to be nothing but a configuration of material parts, which, though conceptualised in abstraction and independent from matter, would nevertheless add nothing new to the material composition in which it is instantiated. If that were so, how, then, can a hylomorphic theory conceive of form as ontologically separate from matter? Without a comprehensive and comprehensible resolution of those three major aporias – that is in line with today’s scientific conception of the world – Aristotle’s definition of the soul as form-without-matter would, in Ackrill's words, ‘resist interpretation’. This paper shows that such a resolution can in fact be achieved and that Aristotle’s hylomorphism allows for a plausible and consistent interpretation.

부가가치세법상 사업상 증여에 대한 연구

The Value-Added Tax Act is the name of the so-called “deemed supply” in Article 10, which does not correspond to the supply of goods in principle, but lists types that should be viewed as the supply of goods and is subject to taxation.
 The deemed supply does not correspond to the supply of goods in its original sense under the VAT Act, but it is understood that the scope of taxation has been expanded through legislation for types that need to be discussed as supply of goods.
 Therefore, this paper reviews the meaning and requirements of the business gift regulations, introduces the practical issues related to the business gift regulations, and examines that the current VAT practice drift apart from the purpose of the law due to formalism.
 As a legislative alternative, it is suggested to remove the business gift regulation from the law. Even if the business gift regulation is deleted from the Value Added Tax Act, the purpose to achieve through the business gift regulation can be regulated through a consistent interpretation of other regulations.
 In conclusion, if it is directly related to the consideration of the main goods and if goods are provided free of charge to an unspecified number of people, the value added tax should be deducted, and if it is not directly related, the related value added tax should not be deducted. In addition, if it is determined that it is not related to the project, it may be regulated through personal supply regulations and in the case of related persons, it may be regulated by rejection of unfair act and calculation.

Optical Transitions and Nonreciprocity in Spatio‐Temporally Periodic Layers of Spherical Particles

AbstractAn extension of the photonic layer multiple scattering methodology to dynamic spherical scatterers, which exhibit a periodic time‐varying response, is presented. The applicability of the method is demonstrated on specific examples of single‐ and bi‐layers of periodically modulated high‐refractive‐index spherical particles arranged on a square lattice. The results provide compelling evidence for strong and tunable inelastic scattering effects under the triple resonance condition, fulfilled for optical transitions between neighboring high‐Q lattice modes of the appropriate symmetry, which originate from multipolar Mie resonances. A consistent interpretation of the underlying mechanisms is provided and potential applications in the design of nonreciprocal devices are discussed.

Developing Shared Ways of Seeing Data: The Perils and Possibilities of Achieving Intercoder Agreement

All research, e.g., qualitative or quantitative, is concerned with the extent to which analyses can adequately describe the phenomena it seeks to describe. In qualitative research, we use internal validity checks like intercoder agreement to measure the extent to which independent researchers observe the same phenomena in data. Researchers report indices of agreement to serve as evidence of consistency and dependability of interpretations, and we do so to make claims about the trustworthiness of our research accounts. However, few studies report the methods of how multiple analysts developed alignment in their interpretation of data, a process that undergirds accounts of consistency, dependability, and trustworthiness. In this article, we review the issues and options around achieving intercoder agreement. Drawing on our experience from a longitudinal, team-based research project that required rapid cycles of qualitative data analysis, we reflect on the challenges we had achieving high intercoder agreement (which refer to as the perils). It was through these challenges that we developed a method that helps to foster shared ways of seeing data, and thus alignment in our interpretations of phenomena in data. In this article, we present this method as a tool for dyadic and team-based qualitative data analysis to facilitate reliable and consistent high-inference interpretations of data with multiple analysts.

Fast and accurate interpretation of workload classification model.

How can we interpret predictions of a workload classification model? A workload is a sequence of operations executed in DRAM, where each operation contains a command and an address. Classifying a given sequence into a correct workload type is important for verifying the quality of DRAM. Although a previous model achieves a reasonable accuracy on workload classification, it is challenging to interpret the prediction results since it is a black box model. A promising direction is to exploit interpretation models which compute the amount of attribution each feature gives to the prediction. However, none of the existing interpretable models are tailored for workload classification. The main challenges to be addressed are to 1) provide interpretable features for further improving interpretability, 2) measure the similarity of features for constructing the interpretable super features, and 3) provide consistent interpretations over all instances. In this paper, we propose INFO (INterpretable model For wOrkload classification), a model-agnostic interpretable model which analyzes workload classification results. INFO provides interpretable results while producing accurate predictions. We design super features to enhance interpretability by hierarchically clustering original features used for the classifier. To generate the super features, we define and measure the interpretability-friendly similarity, a variant of Jaccard similarity between original features. Then, INFO globally explains the workload classification model by generalizing super features over all instances. Experiments show that INFO provides intuitive interpretations which are faithful to the original non-interpretable model. INFO also shows up to 2.0× faster running time than the competitor while having comparable accuracies for real-world workload datasets.

Doping as a tuning mechanism for magnetothermoelectric effects to improve zT in polycrystalline NbP

Weyl semimetals combine topological and semimetallic effects, making them candidates for interesting and effective thermoelectric transport properties. Here, we present experimental results on polycrystalline NbP, demonstrating the simultaneous existence of a large Nernst effect and a large magneto-Seebeck effect, which is typically not observed in a single material at the same temperature. We compare transport results from two polycrystalline samples of NbP with previously published work, observing a shift in the temperature at which the maximum Nernst and magneto-Seebeck thermopowers occur, while still maintaining thermopowers of similar magnitude. Theoretical modeling shows how doping strongly alters both the Seebeck and Nernst magnetothermopowers by shifting the temperature-dependent chemical potential, and the corresponding calculations provide a consistent interpretation of our results. Thus, we offer doping as a tuning mechanism for shifting magnetothermoelectric effects to temperatures appropriate for device applications, improving $zT$ at desirable operating temperatures. Furthermore, the simultaneous presence of both a large Nernst and magneto-Seebeck thermopower is uncommon and offers unique device advantages if the thermopowers are used additively. Here, we also propose a unique thermoelectric device that would collectively harness the large Nernst and magneto-Seebeck thermopowers to greatly enhance the output and $zT$ of conventional thermoelectric devices.

Implementation of Exome Sequencing in Prenatal Diagnostics: Chances and Challenges

Whole exome sequencing (WES) has become part of the postnatal diagnostic work-up of both pediatric and adult patients with a range of disorders. In the last years, WES is slowly being implemented in the prenatal setting as well, although some hurdles remain, such as quantity and quality of input material, minimizing turn-around times, and ensuring consistent interpretation and reporting of variants. We present the results of 1 year of prenatal WES in a single genetic center. Twenty-eight fetus-parent trios were analyzed, of which seven (25%) showed a pathogenic or likely pathogenic variant that explained the fetal phenotype. Autosomal recessive (4), de novo (2) and dominantly inherited (1) mutations were detected. Prenatal rapid WES allows for a timely decision-making in the current pregnancy, adequate counseling with the possibility of preimplantation or prenatal genetic testing in future pregnancies and screening of the extended family. With a diagnostic yield in selected cases of 25% and a turn-around time under 4 weeks, rapid WES shows promise for becoming part of pregnancy care in fetuses with ultrasound anomalies in whom chromosomal microarray did not uncover the cause.

The Role of Artificial Intelligence in Echocardiography.

Echocardiography is an integral part of the diagnosis and management of cardiovascular disease. The use and application of artificial intelligence (AI) is a rapidly expanding field in medicine to improve consistency and reduce interobserver variability. AI can be successfully applied to echocardiography in addressing variance during image acquisition and interpretation. Furthermore, AI and machine learning can aid in the diagnosis and management of cardiovascular disease. In the realm of echocardiography, accurate interpretation is largely dependent on the subjective knowledge of the operator. Echocardiography is burdened by the high dependence on the level of experience of the operator, to a greater extent than other imaging modalities like computed tomography, nuclear imaging, and magnetic resonance imaging. AI technologies offer new opportunities for echocardiography to produce accurate, automated, and more consistent interpretations. This review discusses machine learning as a subfield within AI in relation to image interpretation and how machine learning can improve the diagnostic performance of echocardiography. This review also explores the published literature outlining the value of AI and its potential to improve patient care.

Freedom and Agency in The Second Sex

Freedom and Agency in <i>The Second Sex</i>

Gravitational waves from inspiraling black holes in quadratic gravity

We perform a study of gravitational waves emitted by inspiraling black holes in the context of quadratic gravity. By linearizing the field equations around a flat background, we demonstrate that all degrees of freedom satisfy wavelike equations. These degrees of freedom split into three modes: a massive spin-2 mode, a massive spin-0 mode, and the expected massless spin-2 mode. We construct the energy-momentum tensor of gravitational waves and show that, due to the massive spin-2 mode, it presents the Ostrogradsky instability. We also show how to deal with this possible pathology and obtain consistent physical interpretations for the system. Using the energy-momentum tensor, we study the influence of each massive mode in the orbital dynamics and compare it with the standard result of general relativity. Moreover, we present two methods to constrain the parameter $\ensuremath{\alpha}$ associated with the massive spin-2 contribution. From the first method, using the combined waveform for the spin-2 modes, we obtain the constraint $\ensuremath{\alpha}\ensuremath{\lesssim}1.1\ifmmode\times\else\texttimes\fi{}{10}^{21}\text{ }\text{ }{\mathrm{m}}^{2}$. In the second method, using the coalescence time, we get the constraint $\ensuremath{\alpha}\ensuremath{\lesssim}1.1\ifmmode\times\else\texttimes\fi{}{10}^{13}\text{ }\text{ }{\mathrm{m}}^{2}$.

Reconciling experimental and theoretical stacking fault energies in face-centered cubic materials with the experimental twinning stress

Stacking fault energy and twinning stress are thought to be closely correlated. All currently available models predict a monotonous decrease in twinning stress with decreasing stacking fault energy and depart from the assumption that the intrinsic stacking fault energy has a positive value. Opposite to this prediction, for medium- and high-entropy alloys the twinning stress was shown to increase with decreasing SFE. Additionally, for metastable materials, first principles methods predict negative intrinsic stacking fault energy values, whilst experimentally determined values are always positive. In the present communication, it is postulated that the twinning stress scaled by the Burgers vector bridges the difference between intrinsic and experimentally measured stacking fault energy. The assumption is tested for Cu-Al alloys, for pure metals and for medium- and high-entropy alloys and, for the first time, provides a consistent quantitative interpretation of data for both alloys with positive and negative stacking fault energy.

Assessing significant factors that can influence physical fit examinations – Part I. Physical fits of torn and cut duct tapes

This study expands upon a previously developed method that quantifies the similarity of the compared tape edges by systematically studying the effect of several separation methods and tape grades on the quality of a fit. Analysts examined more than 3300 pairs of hand-torn or scissor-cut duct tapes from three different tape grades while they were kept blind from the ground truth to minimize bias. The samples were examined following a three-step methodology: 1) qualitative assessment of the overall edge alignment and description of edge pattern, 2) macroscopic evaluation of the edges’ features, 3) bin by bin subunit assessment of tape edges and estimation of the edge similarity score. A report template was designed to maintain records of the decision-making process. In the second and third steps, eight comparison features were defined and documented using auto-populated cell options. Generally, misidentification rates were low, with no false positives reported. Coinciding with previous research, low scores (under 20%) provided the most support for a non-fit conclusion, while high scores (80% or higher) supported a fit conclusion. A statistical analysis of the separation method and quality of tape revealed a potential interaction between these factors and showed that they significantly impact the edge scores for true fitting pairs, but not the true non-fits’ scores. The developed comparison and documentation criteria can assist practitioners with a more straightforward, consistent, and transparent interpretation and reporting approach.

From pilot knowledge via integrated reservoir characterization to utilization perspectives of deep geothermal reservoirs: the 3D model of Groß Schönebeck (North German Basin)

The Groß Schönebeck site in the North German Basin serves as research platform to study the geothermal potential of deeply buried Permian reservoir rocks and the technical feasibility of heat extraction. The structural setting of the site was investigated in more detail by a newly acquired 3D-seismic survey to improve the former conceptual model that was based on several old 2D seismic lines. The new data allow a revision of the geological interpretation, enabling the setup of a new reservoir model and providing base information for a possible further site development of Permo-Carboniferous targets. The 3D seismic allows for the first time a consistent geological interpretation and model parameterization of the well-studied geothermal site. Main reflector horizons and the corresponding stratigraphic units were mapped and the structural pattern of the subsurface presented in the 8 km × 8 km × 4 km large seismic volume. Attribute analysis revealed some fracture and fault patterns in the upper Zechstein and post-Permian units, while formerly hypothesized large offset faults are not present in the Rotliegend reservoir. However, a well-established graben-like structure at the top of the Zechstein succession is most likely related to broken anhydritic brittle intra-salt layers of some meter of thickness. Most reflectors above the salt show a rather undisturbed pattern. The main reservoir sandstone of the Dethlingen Formation (Rotliegend) was mapped and characterized. The base of the underlying Permo-Carboniferous volcanic rock sequence and hence its thickness could not be depicted reliably from the geophysical data. Based on the seismic data and the available reconnaissance drilling, logging, and laboratory data of the Groß Schönebeck research site, the thickness and distribution of the sedimentary Rotliegend (with emphasis of the sandy reservoir section) and of the volcanic rock sequence was modelled and stochastically parameterized with petrophysical properties guided by seismic facies pattern correlation, providing a more realistic reservoir description. Properties include total and effective porosity, permeability, bulk density, thermal conductivity, thermal diffusivity, and specific heat capacity. The data and interpretation constitute the basis for a better understanding of the thermo and hydromechanical processes at the site and for future measures. Further site development could include a deepening of one well to provide evidence on the volcanic rock sequence and consider deviated wells into favourable zones and the design of a fracture-dominated utilization approach.

Implementing HL7 FHIR

Fast Healthcare Interoperability Resources (FHIR), created by HL7 more than a decade ago, has become a global standard for exchanging data. Communities of interest have organized under the HL7 FHIR Accelerator Program to develop implementation guides and applications for patient care, health payment systems, public health, patient engagement, clinical and basic research, and social determinants of health. Despite efforts to coordinate the creation of applications in an ever-increasing diversity of use cases, there have been challenges to ensure semantic interoperability, security, privacy, consistent interpretation of the specifications, and the workforce capacity across the industry. In response to these challenges, HL7 created the Standards Implementation Division with the aims of developing a unique ecosystem for continuous testing and discovery, building a global education and certification program, and facilitating advancement across the diverse FHIR implementation communi

Völkerrechtskonforme Auslegung aus schweizerischer Sicht: Ein Randphänomen?

This article discusses the scope and limits of consistent interpretation in Switzerland and discusses the extent to which construing national law in conformity with public international law is indicative of the ‘friendliness towards international law’ of a constitution. I argue, first, that consistent interpretation in Switzerland has certainly served the cause of friendliness towards international law, but that three conditions must be met before it can come into play. Second, the article concludes that consistent interpretation is, nevertheless, of limited use in ‘measuring’ the international law friendliness of the Swiss legal system because consistent interpretation does not come into play in numerous constellations and narrows the view to a modest number of court cases. In relation to the sum of challenges related to the implementation of international law domestically, consistent interpretation is a marginal phenomenon.

Romanesque Architecture and Urbanism of Banská Štiavnica – Research Results

The architectural appearance of Banská Štiavnica in the Romanesque period, especially its older developmental stages, is still not clear to us from an architectural or urban planning point of view. Since the declaration of the city as a Preserved Area (since 1950), much architectural-historical research has been carried out, which enables the summarization of new knowledge in the context of urban development. The current identifi cation and documentation of the oldest houses of burghers and miners followed up on previous research carried out in the 1980s and 1990s, which, however, lacked consistent documentation and interpretation. Although the results of our research still do not allow a complete identifi cation of the oldest buildings in the entire assumed urban area, this study presents the results of research into the architectural- and urban-historical development of the prosperous mining town of Banská Štiavnica during the Middle Ages. URL: https://www.upjs.sk/filozoficka-fakulta/katedra-historie/10984/