Miracle-dz/UniFAR-FTUs huggingface dataset:
Variations of physician group profiling indicators for asthma care.

OBJECTIVE To determine how much of the variation in physician group profiling for asthma care can be attributed to physician groups and how reliable those profiling indicators are. STUDY DESIGN Cross-sectional study. Variations attributable to physician groups are presented using the intraclass correlation coefficient (ICC). The reliability of profiling results was determined using the ICC and sample size of the physician group. PARTICIPANTS AND SETTINGS Between July 1998 and February 1999, patients with asthma from 20 California physician groups were randomly selected to be surveyed; 2515 patients responded. MAIN OUTCOME MEASURES Quality indicators for physician group profiling were (1) National Asthma Education and Prevention Program guideline-based processes of care, including accessibility of asthma care, self-management knowledge about asthma care, use of inhaled bronchodilators, and use of inhaled corticosteroids, and (2) patient outcomes, including satisfaction with asthma care, improvement in health status, and emergency department visits and hospitalizations attributable to asthma. RESULTS The variations attributable to physician group were small (< 10%) for process and outcome indicators. For process indicators, self-management knowledge had the highest ICC (9.83%), and use of inhaled bronchodilators had the lowest ICC (3.08%). For outcome indicators, satisfaction with asthma care had the highest ICC (9.53%), and hospitalization had the lowest ICC (1.35%). Despite low ICCs, a large sample size per physician group (n = 126) yielded acceptable reliability (> or = 0.80) for most profiling results. CONCLUSIONS The selected indicators for profiling asthma care at the physician group level were generally reliable. Sampling a sufficient number of cases is key to achieving useful results from profiling.
Morphological Complexity Influences Verb-Object Order in Swedish Sign Language

Computational linguistic approaches to sign languages could benefit from investigating how complexity influences structure. We investigate whether morphological complexity has an effect on the order of Verb (V) and Object (O) in Swedish Sign Language (SSL), on the basis of elicited data from five Deaf signers. We find a significant difference in the distribution of the orderings OV vs. VO, based on an analysis of morphological weight. While morphologically heavy verbs exhibit a general preference for OV, humanness seems to affect the ordering in the opposite direction, with [+human] Objects pushing towards a preference for VO.
ACC 2001 , To appear Motion Planning for Nonlinear Underactuated Vehicles using H ∞ Techniques

This paper presents a new solution to the motion planning problem for nonlinear underactuated vehicles. The approach solves the problem by generating a polynomial curve connecting the desired initial and final positions for the vehicle and then using the curve to estimate the vehicle’s complete configuration along the trajectory. The algorithm introduces an iterative H∞filter to improve upon the initial estimate for the trajectory. The solution to the basic motion planning problem can be coupled with randomized path planning algorithms to solve the obstacle avoidance and multiple vehicle versions of the problem. Numerical simulations illustrate the algorithm’s performance on an underactuated planar vehicle.
Integrating Logical Representations with Probabilistic Information using Markov Logic

First-order logic provides a powerful and flexible mechanism for representing natural language semantics. However, it is an open question of how best to integrate it with uncertain, probabilistic knowledge, for example regarding word meaning. This paper describes the first steps of an approach to recasting first-order semantics into the probabilistic models that are part of Statistical Relational AI. Specifically, we show how Discourse Representation Structures can be combined with distributional models for word meaning inside a Markov Logic Network and used to successfully perform inferences that take advantage of logical concepts such as factivity as well as probabilistic information on word meaning in context.
Behavioral Metrics via Functor Lifting

We study behavioral metrics in an abstract coalgebraic setting. Given a coalgebra alpha: X -> FX in Set, where the functor F specifies the branching type, we define a framework for deriving pseudometrics on X which measure the behavioral distance of states. A first crucial step is the lifting of the functor F on Set to a functor in the category PMet of pseudometric spaces. We present two different approaches which can be viewed as generalizations of the Kantorovich and Wasserstein pseudometrics for probability measures. We show that the pseudometrics provided by the two approaches coincide on several natural examples, but in general they differ. Then a final coalgebra for F in Set can be endowed with a behavioral distance resulting as the smallest solution of a fixed-point equation, yielding the final coalgebra in PMet. The same technique, applied to an arbitrary coalgebra alpha: X -> FX in Set, provides the behavioral distance on X. Under some constraints we can prove that two states are at distance 0 if and only if they are behaviorally equivalent.
Kinetics of Serologic Responses to MERS Coronavirus Infection in Humans, South Korea

We investigated the kinetics of serologic responses to Middle East respiratory syndrome coronavirus (MERS-CoV) infection by using virus neutralization and MERS-CoV S1 IgG ELISA tests. In most patients, robust antibody responses developed by the third week of illness. Delayed antibody responses with the neutralization test were associated with more severe disease.
IL-17A–Mediated Protection against Acanthamoeba Keratitis

Acanthamoeba keratitis (AK) is a very painful and vision-impairing infection of the cornea that is difficult to treat. Although past studies have indicated a critical role of neutrophils and macrophages in AK, the relative contribution of the proinflammatory cytokine, IL-17A, that is essential for migration, activation, and function of these cells into the cornea is poorly defined. Moreover, the role of the adaptive immune response, particularly the contribution of CD4+ T cell subsets, Th17 and regulatory T cells , in AK is yet to be understood. In this report, using a mouse corneal intrastromal injection-induced AK model, we show that Acanthamoeba infection induces a strong CD4+ T effector and regulatory T cell response in the cornea and local draining lymph nodes. We also demonstrate that corneal Acanthamoeba infection induces IL-17A expression and that IL-17A is critical for host protection against severe AK pathology. Accordingly, IL-17A neutralization in Acanthamoeba-infected wild-type mice or Acanthamoeba infection of mice lacking IL-17A resulted in a significantly increased corneal AK pathology, increased migration of inflammatory cells at the site of inflammation, and a significant increase in the effector CD4+ T cell response in draining lymph nodes. Thus, in sharp contrast with other corneal infections such as herpes and Pseudomonas aeruginosa keratitis where IL-17A exacerbates corneal pathology and inflammation, the findings presented in this article suggest that IL-17A production after Acanthamoeba infection plays an important role in host protection against invading parasites.
Fiber-matrix interface effects in the presence of thermally induced residual stresses

The mechanics of transversely loaded high-temperature composites with a thermally induced residual stress field and a vanishingly weak fiber-matrix interface strength was investigated using two analytical models. In particular, the effects of several physical properties defining the performance of the constituent fiber, matrix, and interface are examined relative to their effect on composite's behavior. Both models demonstrate that, if there is a thermally induced residual stress field in the composite, the initial transverse modulus for the composite will be the same regardless of whether there is a well-bonded or an unbonded interface. 10 refs.
Combining Contexts in Lexicon Learning for Semantic Parsing

We introduce a method for the automatic construction of noun entries in a semantic lexicon. Using the entries already present in the lexicon, semantic features are inherited from known to yet unknown words along similar contexts. As contexts, we use three specific syntactic-semantic relations: modifying adjective, verb-deep-subject and verbdeep-object. The combination of evidences from different contexts yields very high precision for most semantic features, giving rise to the fully automatic incorporation into the lexicon.
Distinct expression and function of the novel mouse chemokine monocyte chemotactic protein-5 in lung allergic inflammation

We have cloned a novel mouse CC chemokine cDNA from the lung during an allergic inflammatory reaction. The protein encoded by this cDNA is chemotactic for eosinophils, monocytes, and lymphocytes in vitro and in vivo. Based on its similarities in sequence and function with other CC chemokines, we have named it mouse monocyte chemotactic protein-5 (mMCP- 5). Under noninflammatory conditions, expression of mMCP-5 in the lymph nodes and thymus is constitutive and is generally restricted to stromal cells. Neutralization of mMCP-5 protein with specific antibodies during an allergic inflammatory reaction in vivo resulted in a reduction in the number of eosinophils that accumulated in the lung. Moreover, mMCP- 5 mRNA expression in vivo is regulated differently from that of other major CC chemokines in the lung during the allergic reaction, including Eotaxin. The presence of lymphocytes is essential for expression of mMCP-5 by alveolar macrophages and smooth muscle cells in the lung, and the induction of mMCP-5 RNA occurs earlier than that of the eosinophil chemokine Eotaxin during allergic inflammation. In contrast to Eotaxin, mRNA for mMCP-5 can be produced by mast cells. From these results, we postulate that mMCP-5 plays a pivotal role during the early stages of allergic lung inflammation.
Incremental transformation of procedural systems to object oriented platforms

Over the past years, the reengineering of legacy software systems to object oriented platforms has received significant attention. In this paper, we present a generic re-engineering source code transformation framework to support the incremental migration of such procedural legacy systems to object oriented platforms. First, a source code representation framework that uses a generic domain model for procedural languages allows for the representation of abstract syntax trees as XML documents. Second, a set of transformations allow for the identification of object models in specific parts of the legacy source code. In this way, the migration process is applied incrementally on different parts of the system. A clustering technique is used to decompose a program into a set of smaller components that are suitable for the incremental migration process. Finally, the migration process gradually composes the object models obtained at every stage to generate an amalgamated object model for the whole system. A case study for the migration of a medium size C system to C++ is discussed as a proof of concept.
Hidden Markov tree models for semantic class induction

In this paper, we propose a new method for semantic class induction. First, we in- troduce a generative model of sentences, based on dependency trees and which takes into account homonymy. Our model can thus be seen as a generalization of Brown clustering. Second, we describe an efficient algorithm to perform inference and learning in this model. Third, we apply our proposed method on two large datasets (10 8 tokens, 10 5 words types), and demonstrate that classes induced by our algorithm improve performance over Brown clustering on the task of semi- supervised supersense tagging and named entity recognition.
Predator-Prey Biogeography-Based Optimization for Bio-inspired Visual Attention

Visual attention mechanism is one of the important techniques in computer vision field, and it can increase the effectiveness of computer image information processing. Biogeography-Based Optimization (BBO) is a bioinspired algorithm for global optimization, searching for the global optimum mainly through two steps: migration and mutation. In this paper, a novel Predator-Prey Biogeography-Based Optimization (PPBBO) is utilized to solve the bio-inspired visual attention problem. In PPBBO method, BBO is combined with the mechanism of predatorprey, which can enhance the global convergence of the algorithm. The convergence property of the PPBBO is analyzed theoretically, and the detailed process is also given. Comparative experimental results with basic BBO, CBBO, CPPBBO, and Particle Swarm Optimization (PSO) demonstrate the feasibility and effectiveness of our presented PPBBO for adjusting combination of feature maps in visual attention.
Relative Risks for Stroke by Age, Sex, and Population Based on Follow-Up of 18 European Populations in the MORGAM Project

Background and Purpose— Within the framework of the MOnica Risk, Genetics, Archiving and Monograph (MORGAM) Project, the variations in impact of classical risk factors of stroke by population, sex, and age were analyzed. Methods— Follow-up data were collected in 43 cohorts in 18 populations in 8 European countries surveyed for cardiovascular risk factors. In 93 695 persons aged 19 to 77 years and free of major cardiovascular disease at baseline, total observation years were 1 234 252 and the number of stroke events analyzed was 3142. Hazard ratios were calculated by Cox regression analyses. Results— Each year of age increased the risk of stroke (fatal and nonfatal together) by 9% (95% CI, 9% to 10%) in men and by 10% (9% to 10%) in women. A 10-mm Hg increase in systolic blood pressure involved a similar increase in risk in men (28%; 24% to 32%) and women (25%; 20% to 29%). Smoking conferred a similar excess risk in women (104%; 78% to 133%) and in men (82%; 66% to 100%). The effect of increasing body mass index was very modest. Higher high-density lipoprotein cholesterol levels decreased the risk of stroke more in women (hazard ratio per mmol/L 0.58; 0.49 to 0.68) than in men (0.80; 0.69 to 0.92). The impact of the individual risk factors differed somewhat between countries/regions with high blood pressure being particularly important in central Europe (Poland and Lithuania). Conclusions— Age, sex, and region-specific estimates of relative risks for stroke conferred by classical risk factors in various regions of Europe are provided. From a public health perspective, an important lesson is that smoking confers a high risk for stroke across Europe.
Material for ” Combinatorial multi-armed bandit : general framework , results and applications ”

We use the following two well known bounds in our proofs. Lemma 1 (Chernoff-Hoeffding bound). Let X1, · · · , Xn be random variables with common support [0, 1] and E[Xi] = μ. Let Sn = X1 + · · ·+Xn. Then for all t ≥ 0, Pr[Sn ≥ nμ+ t] ≤ e−2t /n and Pr[Sn ≤ nμ− t] ≤ e−2t /n Lemma 2 (Bernstein inequality). Let X1, . , Xn be independent zero-mean random variables. If for all 1 ≤ i ≤ n, |Xi| ≤ k, then for all t > 0,
Improving Polymorphism and Concurrency in Common Object Models

Most common object models of distributed object systems have a limited set of object-oriented features, lacking the advanced features of ‘polymorphism’ to assume different forms) and ‘concurrency’ (the ability to have more than one thread of execution in an object simultaneously). The lack of support, for advanced features is a serious limitation because it restricts the development of new components and limits reuse of existing of components that use these advanced features. As a result, wrappers must be used that hide the advanced features or components must be re-implemented using only the features of the common object model. In this dissertation, a new direction of research centered on a subset of object-oriented languages, specifically statically typed languages, is considered. One of the major drawbacks of existing distributed object systems is that they cater to a broad domain of programming languages including both object-oriented as well as non object-oriented languages. Mapping an object model into a non object-oriented language is a complex task and it does not appear natural to a native language user. The interoperable common object model (ICOM) proposed in this dissertation is an attempt to elevate common object models (with the advanced features of polymorphism and concurrency) closer to the object models of statically typed object-oriented languages. Specific features of the ICOM object model include: remote inheritance, method overloading, parameterized types, and guard methods. The actor model and reflection techniques are used to develop a uniform implementation framework for the ICOM object model in C++ and Modula-3. Prototype applications were implemented to demonstrate the utility of the advanced features of the ICOM object model. The main contributions of this dissertation are: design and implementation of a powerful common object model, an architecture for distributed compilation, and an implementation of a distributed object model using the actor model.
State‐of‐the‐art housekeeping proteins for quantitative western blotting: Revisiting the first draft of the human proteome

Western blotting (WB) analysis is the most popular and widely used methodology for protein detection and characterization over recent decades. In accordance with the advancement of the technologies for the acquisition of WB signals, a quantitative value is used to present the abundance of target proteins in a complex sample, thereby requiring the use of specific proteins as internal references that represent total proteins. Heretofore, proteins encoded by housekeeping genes such as GAPDH, β‐tubulin and β‐actin have been commonly used as loading controls without any hesitation because their mRNA expression levels tend to be high and constant in many different cells and tissues. Experimentally, however, some of the housekeeping reference proteins are often displayed with inconsistent expression levels in both homogeneous and heterogeneous tissues, and, in terms of mRNA levels, they have a weak correlation to the abundance of proteins. To estimate accurate, reliable, and reproducible protein quantifications, it is crucial to define appropriate reference controls. For this paper, we explored the recently released large‐scale, human proteomic database ProteomicsDB including 16 857 liquid chromatography tandem‐mass‐spectrometry data from 27 human tissues, and suggest 20 ubiquitously‐ and constitutively‐expressed, putative internal‐reference controls for the quantification of differential protein expressions. Intriguingly, the most commonly used, known housekeeping genes were entirely excluded in our newly defined candidates. Although the applications of the candidates under many different biological conditions and in other organisms are yet to be empirically verified, we propose reliable, potential loading controls for a WB analysis in this paper.
Identification and Classification of Hubs in Brain Networks

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.
Neuroscience and Biobehavioral Reviews The mediodorsal thalamus as a higher order thalamic relay nucleus important for learning and decision-making

Recent evidence from monkey models of cognition shows that the magnocellular subdivision of the mediodorsal thalamus (MDmc) is more critical for learning new information than for retention of previously acquired information. Further, consistent evidence in animal models shows the mediodorsal thalamus (MD) contributes to adaptive decision-making. It is assumed that prefrontal cortex (PFC) and medial temporal lobes govern these cognitive processes so this evidence suggests that MD contributes a role in these cognitive processes too. Anatomically, the MD has extensive excitatory cortico-thalamo-cortical connections, especially with the PFC. MD also receives modulatory inputs from forebrain, midbrain and brainstem regions. It is suggested that the MD is a higher order thalamic relay of the PFC due to the dual cortico-thalamic inputs from layer V (‘driver’ inputs capable of transmitting a message) and layer VI (‘modulator’ inputs) of the PFC. Thus, the MD thalamic relay may support the transfer of information across the PFC via this indirect thalamic route. This review summarizes the current knowledge about the anatomy of MD as a higher order thalamic relay. It also reviews behavioral and electrophysio-logical studies in animals to consider how MD might support the transfer of information across the cortex during learning and decision-making. Current evidence suggests the MD is particularly important during rapid trial-by-trial associative learning and decision-making paradigms that involve multiple cognitive processes. Further studies need to consider the inﬂuence of the MD higher order relay to advance our knowledge about how the cortex processes higher order cognition.
Development of Multiple-Locus Variable-Number Tandem-Repeat Analysis for Molecular Typing of Mycoplasma pneumoniae

ABSTRACT In this study we report on the development of a multilocus variable-number tandem-repeat (VNTR) analysis (MLVA) method for the molecular typing of Mycoplasma pneumoniae. The genomic content of M. pneumoniae M129 was analyzed for VNTRs, and 5 of the 17 VNTRs identified were selected for use in an MLVA assay. The method was based on a GeneScan analysis of VNTR loci labeled with fluorescent dyes by multiplex PCR and capillary electrophoresis. This approach was applied to a collection of 265 isolates from various European countries, Japan, and Tunisia; and 26 distinct VNTR types were found. The VNTR assay was compared to the P1 adhesin PCR-restriction fragment length polymorphism (RFLP) typing method and showed a far better resolution than the P1 PCR-RFLP method. The discriminatory power of MLVA (Hunter-Gaston diversity index [HGDI], 0.915) for the 265 isolates was significantly higher than that of the P1 PCR-RFLP method (HGDI, 0.511). However, there was a correlation between the typing results obtained by MLVA and the P1 gene PCR-RFLP method. The potential value of MLVA of M. pneumoniae as an epidemiological tool is discussed, and the use of the VNTR markers in further investigations of the potential use of MLVA in outbreaks of M. pneumoniae infections is proposed.