Description Of Class Research Articles

Multi-faceted semantic clustering with text-derived phenotypes

Identification of ontology concepts in clinical narrative text enables the creation of phenotype profiles that can be associated with clinical entities, such as patients or drugs. Constructing patient phenotype profiles using formal ontologies enables their analysis via semantic similarity, in turn enabling the use of background knowledge in clustering or classification analyses. However, traditional semantic similarity approaches collapse complex relationships between patient phenotypes into a unitary similarity scores for each pair of patients. Moreover, single scores may be based only on matching terms with the greatest information content (IC), ignoring other dimensions of patient similarity. This process necessarily leads to a loss of information in the resulting representation of patient similarity, and is especially apparent when using very large text-derived and highly multi-morbid phenotype profiles. Moreover, it renders finding a biological explanation for similarity very difficult; the black box problem. In this article, we explore the generation of multiple semantic similarity scores for patients based on different facets of their phenotypic manifestation, which we define through different sub-graphs in the Human Phenotype Ontology. We further present a new methodology for deriving sets of qualitative class descriptions for groups of entities described by ontology terms. Leveraging this strategy to obtain meaningful explanations for our semantic clusters alongside other evaluation techniques, we show that semantic clustering with ontology-derived facets enables the representation, and thus identification of, clinically relevant phenotype relationships not easily recoverable using overall clustering alone. In this way, we demonstrate the potential of faceted semantic clustering for gaining a deeper and more nuanced understanding of text-derived patient phenotypes.

Tocqueville’s Politics of Grandeur

In his defenses of empire, Alexis de Tocqueville emphasized the need to achieve grandeur for France, and his writings on Algeria have shaped our understanding of his political career. In pursuing empire abroad as a remedy for weak politics at home, scholars maintain that Tocqueville abandoned the participatory politics of Democracy in America. This essay argues, however, that the focus on Tocqueville’s international turn has obscured his interest in the greatness of domestic party politics. It demonstrates that Tocqueville championed a version of grandeur tied to the latent energies of the lower classes and distinct from the Bonapartism and aristocratic nostalgia that characterized his thoughts on empire. This version of grandeur was a political reclamation of disagreement and debate that supported great party opposition to counter the malaise of bourgeois rule. The essay concludes by comparing Tocqueville’s attitude toward foreign others, whose freedoms had to be sacrificed to the cause of French nationalism, with his description of the lower classes within his own nation, whose inclusion in the franchise could foster great politics. This comparison enables us to draw modest lessons for interpreting political grandeur in the present day.

On the nature of adjectives: evidence from Dinka

This paper presents a description of the adjective class in Dinka, and an exploration of its typological relevance to the existence of adjectives cross-linguistically. In Dinka, a subset of intransitive verbs can be defined by two morphophonological characteristics. The overwhelming majority of these are property concepts, despite the fact that the defining characteristics are unrelated to semantic properties. This calls into question whether or not properties provide a useful semantic context in the investigation of adjectives, even in languages where the adjective class is clearly a subclass of another lexical category. While the analysis is based primarily on the Bor South dialect of Dinka, it has been corroborated using evidence from other dialects. Therefore, it is likely that this characterization holds across the language.

Classification of Electronic Health Record-Related Patient Safety Incidents: Development and Validation Study.

BackgroundIt is assumed that the implementation of health information technology introduces new vulnerabilities within a complex sociotechnical health care system, but no international consensus exists on a standardized format for enhancing the collection, analysis, and interpretation of technology-induced errors.ObjectiveThis study aims to develop a classification for patient safety incident reporting associated with the use of mature electronic health records (EHRs). It also aims to validate the classification by using a data set of incidents during a 6-month period immediately after the implementation of a new EHR system.MethodsThe starting point of the classification development was the Finnish Technology-Induced Error Risk Assessment Scale tool, based on research on commonly recognized error types. A multiprofessional research team used iterative tests on consensus building to develop a classification system. The final classification, with preliminary descriptions of classes, was validated by applying it to analyze EHR-related error incidents (n=428) during the implementation phase of a new EHR system and also to evaluate this classification’s characteristics and applicability for reporting incidents. Interrater agreement was applied.ResultsThe number of EHR-related patient safety incidents during the implementation period (n=501) was five-fold when compared with the preimplementation period (n=82). The literature identified new error types that were added to the emerging classification. Error types were adapted iteratively after several test rounds to develop a classification for reporting patient safety incidents in the clinical use of a high-maturity EHR system. Of the 427 classified patient safety incidents, interface problems accounted for 96 (22.5%) incident reports, usability problems for 73 (17.1%), documentation problems for 60 (14.1%), and clinical workflow problems for 33 (7.7%). Altogether, 20.8% (89/427) of reports were related to medication section problems, and downtime problems were rare (n=8). During the classification work, 14.8% (74/501) of reports of the original sample were rejected because of insufficient information, even though the reports were deemed to be related to EHRs. The interrater agreement during the blinded review was 97.7%.ConclusionsThis study presents a new classification for EHR-related patient safety incidents applicable to mature EHRs. The number of EHR-related patient safety incidents during the implementation period may reflect patient safety challenges during the implementation of a new type of high-maturity EHR system. The results indicate that the types of errors previously identified in the literature change with the EHR development cycle.

Development of the\xa0Pulmonary Hypertension Functional Classification Self-Report: a patient version adapted from the World Health Organization Functional Classification measure

BackgroundPulmonary arterial hypertension (PAH) is characterized by progressive limitations on physical activity, right heart failure, and premature death. The World Health Organization functional classification (WHO-FC) is a clinician-rated assessment used widely to assess PAH severity and functioning, but no equivalent patient-reported version of PAH symptoms and activity limitations exists. We developed a version of the WHO-FC for self-completion by patients: the Pulmonary Hypertension Functional Classification Self-Report (PH-FC-SR).MethodsSemistructured interviews were conducted with three health care providers (HCPs) via telephone to inform development of the draft PH-FC-SR. Two rounds of semi-structured interviews were conducted with 14 US patients with a self-reported PAH diagnosis via telephone/online to elicit concepts and iteratively refine the PH-FC-SR.ResultsHCPs reported that the WHO-FC was a useful tool for evaluating patients’ PAH severity over time and for making treatment decisions but acknowledged that use of the measure is subjective. Patients in round 1 interviews (n = 6) reported PAH symptoms, including shortness of breath (n = 6), fatigue (n = 5), syncope (n = 5), chest pains (n = 3), and dizziness (n = 3). Round 1 patients identified challenges with the original WHO-FC, including comprehensibility of clinical terms and overlapping descriptions of class II and III, and preferred the Draft 1 PH-FC-SR over the original WHO-FC. After minor changes were made to Draft 2, round 2 interviews (n = 8) confirmed patients understood the PH-FC-SR class descriptions, interpreting them consistently.ConclusionsThe HCP and patient interviews identified and confirmed certain limitations inherent within the clinician-rated WHO-FC, including subjective assessment and overlapping definitions for class II and III. The PH-FC-SR includes patient-appropriate language, symptoms, and physical activity impacts relevant to patients with PAH. Future research is recommended to validate the PH-FC-SR and explore its correlation with the physician-assessed WHO-FC and other outcomes.

Universal excursion and bridge shapes in ABBM/CIR/Bessel processes

Several years ago, in the context of the physics of hysteresis in magnetic materials, a simple stochastic model has been introduced: the ABBM model. Later, the ABBM model has been advocated as a paradigm for the description of a broad class of diverse phenomena, baptized ‘crackling noise phenomena’. The model reproduces many statistical features of such intermittent signals, as for instance the statistics of burst (or avalanche) durations and sizes, in particular the power law exponents that would characterize the dynamics as critical. In order to go beyond such ‘critical exponents’, the measure of the average shape of the avalanche has also been proposed. Here, the exact calculation of the average (as well as the fluctuations) of the avalanche shape for the ABBM model is presented, showing that its normalised shape does not depend on the external drive. Moreover, the average (and the fluctuations) of the multi-avalanche shape, that is the average shape of a sequence of avalanches of fixed total duration, is also computed. Surprisingly, the two quantities (avalanche and multi-avalanche normalised shapes) are exactly the same. This result is obtained using the exact solution of the ABBM model, which is obtained leveraging the equivalence with the Cox–Ingersoll–Ross process (CIR), rigorously obtained with a so called ‘time change’. A simple presentation of this and other known relevant exact results is provided: notably the correspondence of the ABBM/CIR model with the Rayleigh model and, more importantly, with the generalised Bessel process, which describes the dynamics of the modulus of the multi dimensional Ornstein–Uhlenbeck process (exactly as the Bessel process does for the Brownian process). As a consequence, our main finding, that is the correspondence between the excursion (avalanche) and bridge (multi-avalanche) shape distributions, turns to apply to all the aforementioned stochastic processes. In simple words: if we consider the distance from the origin of such diffusive particles, the (normalised) average shape of its trajectory (and the fluctuations around that) until a return in a time T is the same, whether it has returned before T or not.

Cardiovascular damage phenotypes and all-cause and CVD mortality in older adults

PurposeThe association between CVD risk factors and mortality is well established, however, current tools for addressing subgroups have focused on the overall burden of disease. The identification of risky combinations of characteristics may lead to a better understanding of physiologic pathways that underlie morbidity and mortality in older adults. MethodsParticipants included 5067 older adults from the Cardiovascular Health Study, followed for up to 6 years. Using latent class analysis (LCA), we created CV damage phenotypes based on probabilities of abnormal brain infarctions, major echocardiogram abnormalities, N-terminal probrain natriuretic peptide, troponin T, interleukin-6, c reactive-protein, galectin-3, cystatin C. We assigned class descriptions based on the probability of having an abnormality among risk factors, such that a healthy phenotype would have low probabilities in all risk factors. Participants were assigned to phenotypes based on the maximum probability of membership. We used Cox-proportional hazards regression to evaluate the association between the categorical CV damage phenotype and all-cause and CVD-mortality. ResultsThe analysis yielded 5 CV damage phenotypes consistent with the following descriptions: healthy (59%), cardio-renal (11%), cardiac (15%), multisystem morbidity (6%), and inflammatory (9%). All four phenotypes were statistically associated with a greater risk of all-cause mortality when compared with the healthy phenotype. The multisystem morbidity phenotype had the greatest risk of all-cause death (HR: 4.02; 95% CI: 3.44, 4.70), and CVD-mortality (HR: 4.90, 95% CI: 3.95, 6.06). ConclusionsFive CV damage phenotypes emerged from CVD risk factor measures. CV damage across multiple systems confers a greater mortality risk compared to damage in any single domain.

Clients in context: Environment, class, race, and therapists' perceptions of generalized anxiety disorder.

To examine how therapists' perceptions of Generalized Anxiety Disorder is influenced by client environmental contextual and identity factors, like class and race. Therapists (n = 138; 76% women; Mage = 38.3) were randomly assigned three of six client vignettes and asked to provide diagnostic recommendations, confidence in diagnosis, and perception of client's concerns. Vignettes differed in their description of client class, race, and contextual factors. A linear mixed-model was used to test confidence in diagnosis and generalized linear mixed-models were conducted to predict diagnosis and client concerns. Therapists altered diagnosis, confidence, and client concerns based on client contextual factors-but not identity factors. Therapists consider contextual factors in making clinical decisions, with overall tendency towards diagnosis regardless of if symptoms met the diagnostic criteria of being "excessive" given the environmental context.

Artin groups of types F4 and H4 are not commensurable with that of type D4

In a recent article, Cumplido and Paris studied the question of commensurability between Artin groups of spherical type. Their analysis left six cases undecided, for the following pairs of Artin groups: (F4,D4), (H4,D4), (F4,H4), (E6,D6), (E7,D7), and (E8,D8). In this note we resolve the first two of these cases, namely, we show that the Artin groups of types F4 and H4 are not commensurable with that of type D4. As a key step, we realize the abstract commensurator of the Artin group of type D4 as the extended mapping class group of the torus with three punctures. We also find the automorphism group of the Artin group of type D4 and obtain a description of torsion elements, their orders and conjugacy classes in all irreducible Artin groups of spherical type modulo their centers.

Passivity of boundary controlled and observed stochastic port-Hamiltonian systems subject to multiplicative and input noise

We study infinite-dimensional stochastic port-Hamiltonian systems (SPHSs) having multiplicative and boundary input noise. Using Itô and Stratonovich integrals on Hilbert spaces, a formal mathematical description of this specific class of stochastic systems is presented, and some properties, including almost sure and weak passivity, are investigated. By considering dissipative effects, we derive a condition for SPHSs to be weakly passive. Finally, the stochastic port-Hamiltonian framework and the passivity concepts are illustrated on the example of an inhomogeneous vibrating string subject to random damping and state noises.

Constructive Description of Hölder Classes on Some Multidimensional Compact Sets

In this paper, a constructive description of Holder classes of functions on certain compact sets in $${{\mathbb{R}}^{m}}$$ (m $$ \geqslant $$ 3) is given in terms of the rate of approximation by harmonic functions in shrinking neighborhoods of these compact sets. The compact sets under consideration are a higher-dimensional generalization of compact subsets of curves in $${{\mathbb{R}}^{3}}$$ whose arc is commensurable with chord. The neighborhood size is directly connected with the rate of approximation: it shrinks when the approximation is getting more accurate. In addition to being harmonic in the neighborhood of the compact, the approximating functions are subject to the condition that looks similar to the Holder condition, but is weaker. Namely, the difference in values at two points is estimated in terms of the size of the neighborhood, if the distance between these points is commensurate with the size of the neighborhood (and thus estimated in terms of the distance between the points).

Developments in Treatment Methodologies Using Dendrimers for Infectious Diseases.

Dendrimers comprise a specific group of macromolecules, which combine structural properties of both single molecules and long expanded polymers. The three-dimensional form of dendrimers and the extensive possibilities for use of additional substrates for their construction creates a multivalent potential and a wide possibility for medical, diagnostic and environmental purposes. Depending on their composition and structure, dendrimers have been of interest in many fields of science, ranging from chemistry, biotechnology to biochemical applications. These compounds have found wide application from the production of catalysts for their use as antibacterial, antifungal and antiviral agents. Of particular interest are peptide dendrimers as a medium for transport of therapeutic substances: synthetic vaccines against parasites, bacteria and viruses, contrast agents used in MRI, antibodies and genetic material. This review focuses on the description of the current classes of dendrimers, the methodology for their synthesis and briefly drawbacks of their properties and their use as potential therapies against infectious diseases.

Special precovering classes in comma categories

Let T be a right exact functor from an abelian category ℬ into another abelian category \({\mathscr A}\). Then there exists a functor p from the product category \({\mathscr A} \times {\mathscr B}\) to the comma category (\(\left( {T \downarrow {\mathscr A}} \right)\)). In this paper, we study the property of the extension closure of some classes of objects in (\(\left( {T \downarrow {\mathscr A}} \right)\)), the exactness of the functor p and the detailed description of orthogonal classes of a given class \({\rm{P}}\left( {{\cal X},{\cal Y}} \right)\) in (\(\left( {T \downarrow {\mathscr A}} \right)\)). Moreover, we characterize when special precovering classes in abelian categories \({\mathscr A}\) and ℬ can induce special precovering classes in (\(\left( {T \downarrow {\mathscr A}} \right)\)). As an application, we prove that under suitable cases, the class of Gorenstein projective left Λ-modules over a triangular matrix ring \({\rm{\Lambda }} = \left( {\matrix{ R & M \cr 0 & S \cr } } \right)\) is special precovering if and only if both the classes of Gorenstein projective left R-modules and left S-modules are special precovering. Consequently, we produce a large variety of examples of rings such that the class of Gorenstein projective modules is special precovering over them.

A Deep Learning Model in the Detection of Alzheimer Disease

Precise detection of Alzheimer's disease (AD) plays an important role in health treatment, particularly at an early stage, since understanding of the likelihood of incidence and development helps patients to take preventive steps before permanent brain damage is induced. While several experiments have recently used machine learning approaches for the computer-aided diagnosis of AD, a bottleneck in diagnostic performance has been found in most of the previous studies, mainly due to the congenital defects of the selected learning models. In this research paper, to resolve the bottleneck and help diagnose AD and its prodromal level, Mild Cognitive Impairment (MCI), with stacked auto-encoders and a softmax output layer, we have created a deep learning architecture. Compared to previous workflows, our approach is capable of evaluating a variety of groups in a single setting that involve fewer labeled training samples and limited prior domain awareness. A substantial improvement in efficiency was achieved in the description of all diagnostic classes in this research paper.

Strict algebraic models for rational parametrised spectra, I

Building on Quillen's rational homotopy theory, we obtain algebraic models for the rational homotopy theory of parametrised spectra. For any simply-connected space $X$ there is a dg Lie algebra $\Lambda_X$ and a (coassociative cocommutative) dg coalgebra $C_X$ that model the rational homotopy type. In this article, we prove that the rational homotopy type of an $X$-parametrised spectrum is completely encoded by a $\Lambda_X$-representation and also by a $C_X$-comodule. The correspondence between rational parametrised spectra and algebraic data is obtained by means of symmetric monoidal equivalences of homotopy categories that vary pseudofunctorially in the simply-connected parameter space $X$. Our results establish a comprehensive dictionary enabling the translation of topological constructions into homological algebra using Lie representations and comodules, and conversely. For example, the fibrewise smash product of parametrised spectra is encoded by the derived tensor product of dg Lie representations and also by the derived cotensor product of dg comodules. As an application, we obtain algebraic descriptions of rational homotopy classes of fibrewise stable maps, providing new tools for the study of spaces of sections.

Geometric Designs and Rotatable Designs I

Victoir (2004) developes a powerful method for constructing high-dimensional cubature formulas with small number of points, which consists of the corner-vector approach for the hyperoctahedral group $$B_d$$ and the thinning approach based on orthogonal arrays and combinatorial designs. Hirao et al. (2014) applies this to constructions of optimal rotatable designs on the d-dimensional unit ball $${\varvec{B}}^d$$ and thereby finds some infinite series of third-order designs with small number of points. Afterwards, Sawa and Hirao (2017) discusses the corner-vector approach for group $$D_d$$ that can be realized as the symmetry group of a demihypercube in $${\mathbb {R}}^d$$ . In the present paper we discuss a further generalization and improvement of these works, and describe many examples and infinite series of D-optimal rotatable designs with small number of points. The core and novelty in the presentation lies in the focus on the cubature theory in numerical analysis or Euclidean design theory in combinatorics, which not only improves and/or generalizes previous works in those fields of mathematics but also provides a unified mathematical description of various classes of factorial designs, including Box–Hunter solid designs, Box–Behnken designs, central composite designs and Plackett–Burman designs, in the modern framework of the cubature theory. Our new framework enables one, for example, to briefly evaluate the maximum integer t for which such classical factorial designs are of t-th order rotatable.

Investigating the Bilateral Connections in Generative Zero-Shot Learning.

Zero-shot learning (ZSL) is a pretty intriguing topic in the computer vision community since it handles novel instances and unseen categories. In a typical ZSL setting, there is a main visual space and an auxiliary semantic space. Most existing ZSL methods handle the problem by learning either a visual-to-semantic mapping or a semantic-to-visual mapping. In other words, they investigate a unilateral connection from one end to the other. However, the connection between the visual space and the semantic space are bilateral in reality, that is, the visual space depicts the semantic space; the semantic space, on the other hand, describes the visual space. In this article, therefore, we investigate the bilateral connections in ZSL and present a novel model, called Boomerang-GAN, by taking advantage of conditional generative adversarial networks (GANs). Specifically, we generate unseen visual samples from their category semantic embeddings by a conditional GAN. Different from the existing generative ZSL methods that only consider generating visual features from class descriptions, our method also considers that the generated visual features can be translated back to their corresponding semantic embeddings by introducing a multimodal cycle-consistent loss. Extensive experiments of both ZSL and generalized ZSL on five widely used datasets verify that our method is able to outperform previous state-of-the-art approaches in both recognition and segmentation tasks.

Land cover dynamics and their driving factors in a protected floodplain ecosystem

AbstractFloodplains are simultaneously the most productive and threatened ecosystems in the world, with land cover integrity compromised even in “protected” floodplains. Due to their rich biodiversity, monitoring of land cover and understanding the causative drivers becomes imperative in the protected floodplains. This work performs spatio‐temporal assessment of land cover changes and discovers the underlying processes in the largest protected floodplain of the Brahmaputra River (BR)—Kaziranga National Park (KNP). Remotely sensed images of 1988, 1998, 2008, and 2018 were analyzed using visual interpretation techniques coupled with class description keys in GIS platform along with ground‐based surveys. Results show a substantial area decline under Dense Forest (7.7%), Open Forest (10%), Waterlogged wetland (31.3%), and Marsh/Swamp (70.4%) land cover classes between 1988 and 2018. The considerable reduction in forests and wetlands is likely to impact the life support system of the park as they form the key habitats and food resources. Concurrently, dramatic area increase under riverine classes has led to huge landmass loss along the northern and eastern stretch. Though the BR and the local flood pulse are essential source of nutrient replenishment in the park, they also act as primary drivers of land cover alteration. Hydro‐geomorphic processes like bank erosion, high‐flood events, and siltation in association with vegetation succession and invasive species control the inter‐conversion of land cover classes in the KNP. The findings of this work provide an insight into the natural factors that instigate the land cover modification on large floodplains in general, and particularly in KNP.

Rigorous Mathematical Investigation of a Nonlocal and Nonlinear Second-Order Anisotropic Reaction-Diffusion Model: Applications on Image Segmentation

In this paper we are addressing two main topics, as follows. First, a rigorous qualitative study is elaborated for a second-order parabolic problem, equipped with nonlinear anisotropic diffusion and cubic nonlinear reaction, as well as non-homogeneous Cauchy-Neumann boundary conditions. Under certain assumptions on the input data: f(t,x), w(t,x) and v0(x), we prove the well-posedness (the existence, a priori estimates, regularity, uniqueness) of a solution in the Sobolev space Wp1,2(Q), facilitating for the present model to be a more complete description of certain classes of physical phenomena. The second topic refers to the construction of two numerical schemes in order to approximate the solution of a particular mathematical model (local and nonlocal case). To illustrate the effectiveness of the new mathematical model, we present some numerical experiments by applying the model to image segmentation tasks.

Zero-Shot Audio Classification Via Semantic Embeddings

In this paper, we study zero-shot learning in audio classification via semantic embeddings extracted from textual labels and sentence descriptions of sound classes. Our goal is to obtain a classifier that is capable of recognizing audio instances of sound classes that have no available training samples, but only semantic side information. We employ a bilinear compatibility framework to learn an acoustic-semantic projection between intermediate-level representations of audio instances and sound classes, i.e., acoustic embeddings and semantic embeddings. We use VGGish to extract deep acoustic embeddings from audio clips, and pre-trained language models (Word2Vec, GloVe, BERT) to generate either label embeddings from textual labels or sentence embeddings from sentence descriptions of sound classes. Audio classification is performed by a linear compatibility function that measures how compatible an acoustic embedding and a semantic embedding are. We evaluate the proposed method on a small balanced dataset ESC-50 and a large-scale unbalanced audio subset of AudioSet. The experimental results show that classification performance is significantly improved by involving sound classes that are semantically close to the test classes in training. Meanwhile, we demonstrate that both label embeddings and sentence embeddings are useful for zero-shot learning. Classification performance is improved by concatenating label/sentence embeddings generated with different language models. With their hybrid concatenations, the results are improved further.