Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of exposure to silica on human alveolar macrophages in supporting growth activity in type II epithelial cells.

BACKGROUND: The proliferative response of type II cells is an important event following silica-induced lung injury. Alveolar macrophages, when activated by fibrogenic agents, secrete various biological mediators which affect cell growth. METHODS: Human alveolar macrophages from normal volunteers were incubated in serum-free medium or in the presence of increasing concentrations of silica. Alveolar macrophage conditioned media were diluted and added to type II cell cultures for proliferation studies. Purified type II pneumocytes were isolated from fetal rat lungs for bioassays. Growth factor activities were partially characterised by size exclusion chromatography. Each fractionated mitogenic peak was preincubated with monoclonal antibody against platelet derived growth factor (PDGF) or antisera against insulin-like growth factor 1 (IGF-1) or fibroblast derived growth factor (FGF) in order to study the nature of each activity. RESULTS: Conditioned media from alveolar macrophages exposed to silica induced an increase in type II cell DNA synthesis and cell number over that seen when type II cells were incubated with unstimulated alveolar macrophage supernatants. Size exclusion of alveolar macrophage supernatants exposed to silica showed four peaks of type II cell stimulating activity with apparent molecular weights of 38, 22, 16, and 8 kDa. Anti-PDGF antibody significantly reduced the activity of the first and second peaks, antiserum against IGF-1 partially reduced the activity of the first and fourth peaks, and antiserum against FGF reduced only the third peak of activity. CONCLUSIONS: Human alveolar macrophages exposed to silica in vitro release mitogens for type II pneumocytes including PDGF-like, IGF-1-like, and FGF-like molecules. These agents are likely to be involved in the epithelial repair and type II cell hyperplasia observed in silicosis.
Human herpesvirus 6 DNA in plasma after allogeneic stem cell transplantation: incidence and clinical significance.

BACKGROUND Human herpesvirus 6 (HHV-6) is increasingly recognized as an opportunistic and potentially life-threatening pathogen in recipients of allogeneic stem cell transplants (SCTs). METHODS To clarify the incidence and clinical relevance of active HHV-6 infection, serial titers of plasma HHV-6 DNA were determined for 50 allogeneic SCT recipients, using real-time polymerase chain reaction. RESULTS HHV-6 DNA was detected in plasma from 24 patients (48%). HHV-6 DNA was most frequently apparent approximately 14-27 days after transplantation. An increased risk of a positive result for HHV-6 DNA was associated with transplantation from an allelic-mismatch donor (P = .02) and administration of steroids (P = .04). Steroid use was associated with high HHV-6 DNA loads (P = .02). High HHV-6 DNA loads were correlated with delayed platelet engraftment (P = .04). Among patients who had positive results for HHV-6 DNA, the HHV-6 DNA load was higher in plasma from those who developed limbic encephalitis (n = 4) (P < .0001). CONCLUSIONS Active HHV-6 infection is not rare in SCT recipients. SCT from allelic-mismatch donors is associated with increased risk of active HHV-6 infection. Steroid therapy is associated with not only increased incidence of infection but also accelerated viral replication. Development of limbic encephalitis is associated with high HHV-6 DNA load.
School Choice Policies in Michigan: The Rules Matter.

It is a pleasure for us to be here today. This is precisely the type of audience that we had in mind when we did this work, and I am glad that we have this opportunity. I imagine that many people in this room have had more experience than the three of us with being surprised and bemused by the way your work and comments are portrayed in the media. We released the report yesterday at a news conference. The Detroit News headline: Expand Charters. I went home and found the Ann Arbor News. Its front page: Charter Schools Not Chartering New Course. It was the same report. They had to find Dan Quisenberry of the Michigan Association of Public School Academies, and say "Dan, what's wrong with these charter schools? Why can't they innovate? " Neither of these headlines reflects the message of our report. It could be worse because today's the New York Times headline reads: In Michigan, School Choice Weeds Out Costlier Students. That's not the problem. The story begins: Three professors from the University of Michigan. Not once, not twice, but three times is the University of Michigan referred to in this report. This is a problem.
Evolutionary genetics of maternal effects

Maternal genetic effects (MGEs), where genes expressed by mothers affect the phenotype of their offspring, are important sources of phenotypic diversity in a myriad of organisms. We use a single‐locus model to examine how MGEs contribute patterns of heritable and nonheritable variation and influence evolutionary dynamics in randomly mating and inbreeding populations. We elucidate the influence of MGEs by examining the offspring genotype‐phenotype relationship, which determines how MGEs affect evolutionary dynamics in response to selection on offspring phenotypes. This approach reveals important results that are not apparent from classic quantitative genetic treatments of MGEs. We show that additive and dominance MGEs make different contributions to evolutionary dynamics and patterns of variation, which are differentially affected by inbreeding. Dominance MGEs make the offspring genotype‐phenotype relationship frequency dependent, resulting in the appearance of negative frequency‐dependent selection, while additive MGEs contribute a component of parent‐of‐origin dependent variation. Inbreeding amplifies the contribution of MGEs to the additive genetic variance and, therefore enhances their evolutionary response. Considering evolutionary dynamics of allele frequency change on an adaptive landscape, we show that this landscape differs from the mean fitness surface, and therefore, under some condition, fitness peaks can exist but not be “available” to the evolving population.
Global semi-Lagrangian advection

In the recent years, many international centers for numerical weather prediction and climate modeling have adopted in their operational codes a semiLagrangian scheme for transport. This numerical technique became very popular due to its stability and accuracy properties. The time step is only restricted by accuracy and not by a CFL stability condition. In a joint effort with CPTEC/INPE (the Brazilian Center for Weather Prediction and Climate Studies), a semi-Lagrangian model has been developed in FORTRAN90 in an object-oriented style. This code (called WEATHER) simulates the fully 3D passive-advection on a sphere. Some technical details and results will be presented in this article. Currently the semi-Lagrangian model is being coupled to a spectral solver, capable of handling the stiff-linear terms of the prognostic equations. These new numerical tools will be adopted by the operational CPTEC/COLA code.
Modeling Unsupervised Learning with SUSTAIN

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a network model of human category learning. This paper extends SUSTAIN so that it can be used to model unsupervised learning data. A modified recruitment mechanism is introduced that creates new conceptual clusters in response to surprising events during learning. Two seemingly contradictory unsupervised learning data sets are modeled using this new recruitment method. In addition, the feasibility of using a unified recruitment method for both supervised and unsupervised learning is discussed.
Analysis of Turnover and Translation Regulatory RNA-Binding Protein Expression through Binding to Cognate mRNAs

ABSTRACT RNA-binding proteins (RBPs) that associate with specific mRNA sequences and function as mRNA turnover and translation regulatory (TTR) RBPs are emerging as pivotal posttranscriptional regulators of gene expression. However, little is known about the mechanisms that govern the expression of TTR-RBPs. Here, we employed human cervical carcinoma HeLa cells to test the hypothesis that TTR-RBP expression is influenced posttranscriptionally by TTR-RBPs themselves. Systematic testing of the TTR-RBPs AUF1, HuR, KSRP, NF90, TIA-1, and TIAR led to three key discoveries. First, each TTR-RBP was found to associate with its cognate mRNA and with several other TTR-RBP-encoding mRNAs, as determined by testing both endogenous and biotinylated transcripts. Second, silencing of individual TTR-RBPs influenced the expression of other TTR-RBPs at the mRNA and/or protein level. Third, further analysis of two specific ribonucleoprotein (RNP) complexes revealed that TIA-1 expression was controlled via HuR-enhanced mRNA stabilization and TIAR-repressed translation. Together, our findings underscore the notion that TTR-RBP expression is controlled, at least in part, at the posttranscriptional level through a complex circuitry of self- and cross-regulatory RNP interactions.
Reliable on-chip network design using an agent-based management method

As the complexity of evolving integrated circuits and the number of cores in each chip increase, reliability aspects are becoming an important issue in complex chip designs. In this paper, we present an on-chip network architecture that incorporates a novel agent-based management method to enhance the reliability and performance of network-based Chip Multi-Processor (CMP) and System-on-Chip (SoC) designs against faulty links and routers. In addition, to utilize the fault information required for the routing process in a scalable manner, we classify the fault information to be exploited in the proposed distributed and hierarchical management structure. The experimental results show that the proposed architecture incurs only a small hardware overhead.
Generalized weighted Chinese restaurant processes for species sampling mixture models

The class of species sampling mixture models is introduced as an exten- sion of semiparametric models based on the Dirichlet process to models based on the general class of species sampling priors, or equivalently the class of all exchangeable urn distributions. Using Fubini calculus in conjunction with Pitman (1995, 1996), we derive characterizations of the posterior distribution in terms of a posterior par- tition distribution that extend the results of Lo (1984) for the Dirichlet process. These results provide a better understanding of models and have both theoretical and practical applications. To facilitate the use of our models we generalize the work in Brunner, Chan, James and Lo (2001) by extending their weighted Chinese restaurant (WCR) Monte Carlo procedure, an i.i. d. sequential importance sampling (SIS) procedure for approximating posterior mean functionals based on the Dirich- let process, to the case of approximation of mean functionals and additionally their posterior laws in species sampling mixture models. We also discuss collapsed Gibbs sampling, Polya urn Gibbs sampling and a Polya urn SIS scheme. Our framework allows for numerous applications, including multiplicative counting process models subject to weighted gamma processes, as well as nonparametric and semiparamet- ric hierarchical models based on the Dirichlet process, its two-parameter extension, the Pitman-Yor process and finite dimensional Dirichlet priors.
Content based image retrieval using statistical features of color histogram

Content based image retrieval (CBIR) is the process of searching similar images from an image database based on the visual contents of the input query image. In CBIR, color is considered as one of the prominent features of the image data, so in this paper, the authors have presented a CBIR technique using color based feature. Since a color image, consists of three basic color components, i.e. red, green and blue, so in this work, we have given the same importance on all three color components during image retrieving process. In the presented CBIR technique, initially we have constructed three probability histograms for each color component and subsequently the histograms are divided into several numbers of significant bins and from each bin, we have computed several statistical values like standard deviation, skewness and kurtosis. The computed statistical values are used as extracted features of the image data. The processing cost of the presented CBIR technique is significantly low. The technique has been tested on standard image databases and satisfactory results have been achieved.
Problematic, disturbing and non-conforming children’s behaviors: the concepts and care demands related to agitation in children in Santos and Campinas, Brazil

Abstract This article discusses the social consequences of the impossibility of specifically defining the boundaries of the concept of mental disorder, which seems to be a “vague” term with no satisfactory definition, especially when referred to children’s behaviors. We argue that when discussing children’s problematic, disturbing or non-conforming behaviors it is necessary to understand how these concepts are related to the classificatory categories of children’s behaviors and presented as care demands, whether in common sense or in biomedical discourses. Data were collected in qualitative research developed in three different child mental health services (CMHS), one in Santos (2012) and two in Campinas (2009-2010; 2017-2018), Brazil. Based on what seems to be a relation between biological-psychological dysfunction and social-cultural expectation or response, our starting point is that agitation is also a multidimensional and vague category, presenting a description and theoretical reflection about the various concepts regarding agitation. The analysis focuses on the different uses of the concepts of agitation; the social actors and institutions involved in care demands and how they are interdependently connected; then revealing, from a sociocultural perspective, the implications of classifying and defining children’s behavior from this vague category.
New top-down methods using SVMs for Hierarchical Multilabel Classification problems

Hierarchical Multilabel Classification is a problem where the classes involved are hierarchically structured, and examples can be assigned to more than one class simultaneously at a same hierarchical level. This paper describes and evaluates five different methods for this classification task, based on two approaches, named top-down and one-shot. In the top-down approach, the classification task is carried out by discriminating the classes, level by level, in the hierarchy. In the one-shot approach, the methods consider the whole set of classes at once in the classification. Based on the top-down approach, two new hierarchical methods (with label combination and with label decomposition) and the well-known binary hierarchical method are investigated using SVM classifiers. Other two methods from the literature, named HC4.5 and Clus-HMC, based on the one-shot approach, are also used. The methods are applied to ten biological datasets and evaluated using specific metrics for this kind of classification. The experimental results showed that the proposed methods can improve the classification accuracy.
Optimal Operation of a Wind Farm equipped with a Storage Unit

Due to the fluctuations in their production, wind farm owners are subject to financial penalties. To limit these penalties the use of a storage device is studied. We define in this paper a large class of production/storage models in continuous time which verify the physical limits of the facility. In these models, the optimal operation of the storage device becomes an optimal stochastic control problem. We prove that this problem is equivalent to solving an Hamilton-Jacobi-Bellman PDE. Further, this PDE verifies the comparison principle and has thus a unique solution. Using a Semi-Lagrangian approach, we obtain an algorithm for this PDE. As the PDE verify the maximum principle, by using classical tools, we prove that this algorithm is convergent. Finally we present some numerical results.
Using gradient model to compare between treatment samples and non-treatment samples

Applications of digital image processing are mostly in the area of medical, plants laboratory, in the surgery images, Cameras, Video, Electro-photographic and Television images for improving the quality of images and code system. The scanning electron microscope (SEM) is the most acceptable tool being used for bio-measurements and in this paper we have designed the Gradient model to help us detecting and comparing between treatment samples and non-treatment samples in bacteria samples. The error probability of discussion becomes high due to poor information occurrence of some natural properties. We have addressed this issue in our paper by using different image processing technique in order to get more clarity and sufficiency of information. This analysis technique is called Gradient model (GD) and the model starts converting two dimensional images of the prepared samples to data file (*.dat). This 2D data is subsequently converted to 3D data file by using OpenGL under Visual C++ Language programming which after conversion, finally, can draw up time series charts like histogram; and traces management contours; and 3D surface to carry out image analysis. This analysis is of vital importance and can help in comparing between the treatment of bacterial samples and non-treatment samples. Instead of carryout full analysis again and again, this method facilitates partial analysis of any part of any randomly selected image and can accommodate different sizes of the images as well. This property and functionality of the model ensures more accuracy of the analysis and reduces the cost of hardware used.
Focal colors across languages are representative members of color categories

Significance The best examples of color terms across languages are often held to reflect universal focal colors in the opponent pairs red vs. green and yellow vs. blue. An opposing view holds that best examples reflect categories that are determined by local linguistic convention. We argue for a synthesis of these two proposals. We show that best examples of color terms across languages can be predicted from color term extensions using a statistical model that indicates which samples are most representative of a distribution. This model accounts for universal tendencies in best example choices across languages, and also accounts for cross-language variation. Our findings suggest that general statistical principles may illuminate fundamental aspects of color naming across languages. Focal colors, or best examples of color terms, have traditionally been viewed as either the underlying source of cross-language color-naming universals or derived from category boundaries that vary widely across languages. Existing data partially support and partially challenge each of these views. Here, we advance a position that synthesizes aspects of these two traditionally opposed positions and accounts for existing data. We do so by linking this debate to more general principles. We show that best examples of named color categories across 112 languages are well-predicted from category extensions by a statistical model of how representative a sample is of a distribution, independently shown to account for patterns of human inference. This model accounts for both universal tendencies and variation in focal colors across languages. We conclude that categorization in the contested semantic domain of color may be governed by principles that apply more broadly in cognition and that these principles clarify the interplay of universal and language-specific forces in color naming.
Evidence-based Medical Recommender Systems : A Review

Recommender Systems are effective methods that have been developed successfully in e-commerce to provide personal recommendations based on user’s previous preferences. A recommender system assists users in a decision-making process to suggest interesting items from overwhelming flood of data available in the system. Suitably adapting the technology, recommender systems for medical purposes have been presented in some researches, which are applied in medical care or diagnosis called Medical Recommender Systems. They are intelligent methods that originally contain the medical knowledge from both historical data and example cases, as well as utilized for Telemedicine. Moreover, to maximize the effectiveness and quality of medical services, not only medical knowledge but also available external evidences named “Evidence-based Medicine” should be considered together. Therefore, this paper proposes Medical Recommender Systems combined with Evidence-based Medicine, which is called “Evidence-based Medical Recommender Systems”.
Chromosomally abnormal cells are not selected for the extra-embryonic compartment of the human preimplantation embryo at the blastocyst stage.

BACKGROUND Although well defined for embryos at cleavage stages, the occurrence and frequency of chromosomal aberrations in human blastocysts is relatively unknown. It has been reported that only one in four blastocysts is comprised totally of chromosomally normal cells. One of the selection mechanisms for the embryo proper to become free of these chromosomally abnormal cells would be to sequester them to the extra-embryonic compartment during development. The study aim was to investigate whether such a mechanism of selection exists in human preimplantation embryos. METHODS Inner cell mass (ICM)/trophectoderm (TE) differentiation was performed, followed by fluorescence in-situ hybridization (FISH), to study the chromosomal distribution in both populations of cells. RESULTS Of the 94 successfully analysed blastocysts, 68.8 +/- 1.5% of all analysable nuclei per blastocyst showed a disomic chromosomal content. Only 22.6% of blastocysts analysed were classified as normal. Of the embryos classified as abnormal at the blastocyst stage, 11.9% showed a simple mosaic pattern and 32.1% a complex mosaic pattern. An equally large group of blastocysts showed either a chaotic pattern (16.7%), or the chromosomal pattern could not be classified. The average degree of normal cells in the ICM (67.9%) was similar to the degree observed in the TE (69.5%). CONCLUSIONS These findings indicate that chromosomally abnormal cells are not preferentially segregating to the extra-embryonic compartment of the human preimplantation embryo at the blastocyst stage. Hence, other mechanisms should be responsible for an absence of chromosomally abnormal cells in the embryo proper at later stages of development. One possible mechanism might be the elimination of the chromosomally abnormal cells by selective cell death activation.