Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromosomal aberrations and their prognostic value in a series of 174 untreated patients with Waldenström's macroglobulinemia

Waldenström's macroglobulinemia is a disease of mature B cells, the genetic basis of which is poorly understood. Few recurrent chromosomal abnormalities have been reported, and their prognostic value is not known. We conducted a prospective cytogenetic study of Waldenström's macroglobulinemia and examined the prognostic value of chromosomal aberrations in an international randomized trial. The main aberrations were 6q deletions (30%), trisomy 18 (15%), 13q deletions (13%), 17p (TP53) deletions (8%), trisomy 4 (8%), and 11q (ATM) deletions (7%). There was a significant association between trisomy of chromosome 4 and trisomy of chromosome 18. Translocations involving the IGH genes were rare (<5%). Deletion of 6q and 11q, and trisomy 4, were significantly associated with adverse clinical and biological parameters. Patients with TP53 deletion had short progression-free survival and short disease-free survival. Although rare (<5%), trisomy 12 was associated with short progression-free survival. In conclusion, the cytogenetic profile of Waldenström's macroglobulinemia appears to differ from that of other B-cell lymphomas. Chromosomal abnormalities may help with diagnosis and prognostication, in conjunction with other clinical and biological characteristics. This trial is registered with Clinicaltrials.gov, numbers NCT00566332 and NCT00608374.
Using Differential Evolution to Improve Pheromone-based Coordination of Swarms of Drones for Collaborative Target Detection

In this paper we propose a novel algorithm for adaptive coordination of drones, which performs collaborative target detection in unstructured environments. Coordination is based on digital pheromones released by drones when detecting targets, and maintained in a virtual environment. Adaptation is based on the Differential Evolution (DE) and involves the parametric behaviour of both drones and environment. More precisely, attractive/repulsive pheromones allow indirect communication between drones in a flock, concerning the availability/unavailability of recently found targets. The algorithm is effective if structural parameters are properly tuned. For this purpose DE combines different parametric solutions to increase the swarm performance. We focus first on the study of the principal parameters of the DE, i.e., the crossover rate and the differential weight. Then, we compare the performance of our algorithm with three different strategies on six simulated scenarios. Experimental results show the effectiveness of the approach.
A 30-Year Assessment of the Media Planning Literature

Abstract An investigation of media planning articles published from 1962 to 1991 indicated a steady increase, over the years, in the relative number of communication scholars contributing to this literature, although media planning practitioners have continued to make contributions in notable numbers. The eight-year run of the Journal of Media Planning appears to have had a positive effect on the literature. Media modeling and methodological concerns were found to be the major foci of media planning researchers in the early years; more recently the variety of topics investigated by these researchers has increased. A citation analysis undertaken on a subsample of the articles revealed that most-cited authors of recent years represent a generational shift. Specifically, there has been a shift from developing models and explaining media content to examining media planners' usage patters of various models.
ODAC: Hierarchical Clustering of Time Series Data Streams

This paper presents a time series whole clustering system that incrementally constructs a tree-like hierarchy of clusters, using a top-down strategy. The Online Divisive-Agglomerative Clustering (ODAC) system uses a correlation-based dissimilarity measure between time series over a data stream and possesses an agglomerative phase to enhance a dynamic behavior capable of concept drift detection. Main features include splitting and agglomerative criteria based on the diameters of existing clusters and supported by a significance level. At each new example, only the leaves are updated, reducing computation of unneeded dissimilarities and speeding up the process every time the structure grows. Experimental results on artificial and real data suggest competitive performance on clustering time series and show that the system is equivalent to a batch divisive clustering on stationary time series, being also capable of dealing with concept drift. With this work, we assure the possibility and importance of hierarchical incremental time series whole clustering in the data stream paradigm, presenting a valuable and usable option.
Guidelines for the conduction of follow-up studies measuring injury-related disability.

BACKGROUND Scientific knowledge on functional outcome after injury is limited. During the past decade, a variety of measures have been used at various moments in different study populations. Guidelines are needed to increase comparability between studies. METHODS A working group of the European Consumer Safety Association conducted a literature review of empirical studies into injury-related disability (1995-2005). We included injury from all levels of severity and selected studies using generic health status measures with both short-term and long-term follow up. The results were used as input for a consensus procedure toward the development of guidelines for defining the study populations, selecting the health status measures, selecting the timings of the assessments, and data collection procedures. RESULTS The group reached consensus on a common core of health status measures and assessment moments. The group advises to use a combination of EuroQol-5D and Health Utilities Mark III in all studies on injury-related disability. This combination covers all relevant health domains, is applicable in all kinds of injury populations and in widely different age ranges, provides a link with utility scores, and has several practical advantages (e.g., brevity, availability in different languages). For specific types of injury, the common core may be supplemented by injury-specific measures. The group advises a common core of assessments at 1, 2, 4, and 12 months after injury. CONCLUSIONS Our guidelines should be tested and may lead to improved and more consistent epidemiologic data on the incidence, severity, and duration of injury-related disability.
Targeted Next-Generation Sequencing Improves the Diagnosis of Autosomal Dominant Retinitis Pigmentosa in Spanish Patients.

PURPOSE Next-generation sequencing (NGS) has been demonstrated to be an effective strategy for the detection of mutations in retinal dystrophies, a group of inherited diseases that are highly heterogeneous. Therefore, the aim of this study is the application of an NGS-based approach in a Spanish cohort of autosomal dominant retinitis pigmentosa (RP) patients to find out causative mutations. METHODS Index cases of 59 Spanish families with initial diagnosis of autosomal dominant RP and unsuccessfully studied for mutations in the most common RP causal genes, were selected for application of a NGS-based approach with a custom panel for 73 genes related to retinal dystrophies. Candidate variants were select based on frequency, pathogenicity, inherited model, and phenotype. Subsequently, confirmation by Sanger sequencing, cosegregation analysis, and population studies, was applied for determining the implication of those variants in the pathology. RESULTS Overall 31 candidate variants were selected. From them, 17 variants were considered as mutations causative of the disease, 64% (11/17) of them were novel and 36% (6/17) were known RP-related mutations. Therefore, applying this technology16 families were characterized rendering a mutation detection rate of 27% (16/59). Of them, 5% (3/59) of cases displayed mutations in recessive or X-linked genes (ABCA4, RPGR, and RP2) allowing a genetic and clinical reclassification of those families. Furthermore, seven novel variants with uncertain significance and seven novel variants probably not causative of disease were also found. CONCLUSIONS This NGS strategy is a fast, effective, and reliable tool to detect known and novel mutations in autosomal dominant RP patients allowing genetic reclassification in some cases and increasing the knowledge of pathogenesis in retinal dystrophies.
Reassessing the bilingual advantage in theory of mind and its cognitive underpinnings*

The present study aimed (a) to determine whether the bilingual advantage in false-belief (FB) understanding is replicated when considering socio-economic status and (b) to assess whether conflict inhibition and/or working memory underpin the advantage, if there is one. Monolingual preschoolers (24 English monolinguals and 24 French monolinguals) and 24 English–French bilingual counterparts received FB, conflict inhibition, working memory, and verbal ability tests. Monolingual and bilingual groups were equivalent on parental income and education, measured through a parental questionnaire. Results indicated that bilinguals significantly outperformed monolinguals on FB, but only after statistically controlling for language proficiency and age. Working memory likely compensated for the potential negative impact of bilinguals’ low language proficiency on FB.
Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification

The most BCI systems that rely on EEG signals employ Fourier based methods for time-frequency decomposition for feature extraction. The band-limited multiple Fourier linear combiner is well-suited for such band-limited signals due to its real-time applicability. Despite the improved performance of these techniques in two channel settings, its application in multiple-channel EEG is not straightforward and challenging. As more channels are available, a spatial filter will be required to eliminate the noise and preserve the required useful information. Moreover, multiple-channel EEG also adds the high dimensionality to the frequency feature space. Feature selection will be required to stabilize the performance of the classifier. In this paper, we develop a new method based on Evolutionary Algorithm (EA) to solve these two problems simultaneously. The real-valued EA encodes both the spatial filter estimates and the feature selection into its solution and optimizes it with respect to the classification error. Three Fourier based designs are tested in this paper. Our results show that the combination of Fourier based method with covariance matrix adaptation evolution strategy (CMA-ES) has the best overall performance.
Spoken language understanding

Semantics deals with the organization of meanings and the relations between sensory signs or symbols and what they denote or mean. Computational semantics performs a conceptualization of the world using computational processes for composing a meaning representation structure from available signs and their features present, for example, in words and sentences. Spoken language understanding (SLU) is the interpretation of signs conveyed by a speech signal. SLU and natural language understanding (NLU) share the goal of obtaining a conceptual representation of natural language sentences. Specific to SLU is the fact that signs to be used for interpretation are coded into signals along with other information such as speaker identity. Furthermore, spoken sentences often do not follow the grammar of a language; they exhibit self-corrections, hesitations, repetitions, and other irregular phenomena. SLU systems contain an automatic speech recognition (ASR) component and must be robust to noise due to the spontaneous nature of spoken language and the errors introduced by ASR. Moreover, ASR components output a stream of words with no structure information like punctuation and sentence boundaries. Therefore, SLU systems cannot rely on such markers and must perform text segmentation and understanding at the same time.
Stimulus‐evoked resetting of the dentate theta rhythm: relation to working memory

THE relationship between memory and rhythmic neural activity in the dentate gyrus was investigated by analyzing spontaneous dentate field potentials in rats performing either a working or reference memory task. The baseline level of rhythmic theta activity was similar in both groups. Following an initial negative potential in the sensory-evoked response, a resetting of the rhythmic activity which was time-locked to the stimulus onset was observed in rats performing the working memory task, but not in rats performing the reference memory task. The results suggest that the resetting of the theta rhythm by behaviorally-relevant stimuli may have an important role in working memory.
Current Concept Review: Osteochondral Lesions of the Talus

Osteochondral lesion of the talus (OLT) is a broad term used to describe an injury or abnormality of the talar articular cartilage and adjacent bone. Historically, a variety of terms have been used to refer to this clinical entity including osteochondritis dissecans, osteochondral fracture, and osteochondral defect. Currently, six characteristics are used to categorize a particular lesion (Table 2). An OLT can be described as chondral (cartilage only), chondral-subchondral (cartilage and bone), subchondral (intact overlying cartilage), or cystic. Lesions can then be subdivided as stable or unstable and non-displaced or displaced. The stability of a lesion can be assessed directly with arthroscopy or indirectly with MRI using DeSmet’s criteria.6 A lesion can also be categorized by its location on the articular surface of the talus as medial, lateral, or central with added subdivisions into anterior, central, or posterior as advocated by some authors.82 An additional description of identifying whether the lesion is contained or uncontained (shoulder) may also be included. Finally, although no accepted definition of lesion size exists, OLTs can generally be considered as either small or large based on their cross-sectional area or greatest diameter (area greater than or less than 1.5 cm2 or diameter greater than or less than 15 mm). Although these characteristics provide a scheme to classify OLTs and to select a therapeutic modality, they do not reliably predict the outcome of treatment. While the exact incidence of symptomatic OLTs is unknown, they are quite prevalent and are a significant
Integrated Oversampling for Imbalanced Time Series Classification

This paper proposes a novel Integrated Oversampling (INOS) method that can handle highly imbalanced time series classification. We introduce an enhanced structure preserving oversampling (ESPO) technique and synergistically combine it with interpolation-based oversampling. ESPO is used to generate a large percentage of the synthetic minority samples based on multivariate Gaussian distribution, by estimating the covariance structure of the minority-class samples and by regularizing the unreliable eigen spectrum. To protect the key original minority samples, we use an interpolation-based technique to oversample a small percentage of synthetic population. By preserving the main covariance structure and intelligently creating protective variances in the trivial eigen dimensions, ESPO effectively expands the synthetic samples into the void area in the data space without being too closely tied with existing minority-class samples. This also addresses a key challenge for applying oversampling for imbalanced time series classification, i.e., maintaining the correlation between consecutive values through preserving the main covariance structure. Extensive experiments based on seven public time series data sets demonstrate that our INOS approach, used with support vector machines (SVM), achieved better performance over existing oversampling methods as well as state-of-the-art methods in time series classification.
A Brugia malayi Homolog of Macrophage Migration Inhibitory Factor Reveals an Important Link Between Macrophages and Eosinophil Recruitment During Nematode Infection1

Infections with the helminth parasite Brugia malayi share many key features with Th2-mediated allergic diseases, including recruitment of eosinophils. We have investigated the dynamics of inflammatory cell recruitment under type 2 cytokine conditions in mice infected with B. malayi. Among the cells recruited to the site of infection is a novel population of “alternatively activated” macrophages that ablate cell proliferation and enhance Th2 differentiation. By profiling gene expression in this macrophage population, we found a dramatic up-regulation of a recently described eosinophil chemotactic factor, eosinophil chemotactic factor-L/Ym1, representing over 9% of clones randomly selected from a cDNA library. Because B. malayi is known to secrete homologs (Bm macrophage migration inhibitory factor (MIF)-1 and -2) of the human cytokine MIF, we chose to investigate the role this cytokine mimic may play in the development of the novel macrophage phenotype observed during infection. Strikingly, administration of soluble recombinant Bm-MIF-1 was able to reproduce the effects of live parasites, leading both to the up-regulation of Ym1 by macrophages and a marked recruitment of eosinophils in vivo. Because activity of Bm-MIF-1 is dependent upon an amino-terminal proline, this residue was mutated to glycine; the resultant recombinant (Bm-MIF-1G) was unable to induce Ym1 transcription in macrophages or to mediate the recruitment of eosinophils. These data suggest that macrophages may provide a crucial link between helminth parasites, their active cytokine mimics, and the recruitment of eosinophils in infection.
Rapid reconstruction of small objects on mobile phones

Augmented Reality (AR) on mobile phones is receiving more and more attention recently, becoming a popular research topic and an important commercial field. In this paper we present a lightweight method to create coarse 3D models of small-scale objects. The goal is to give the users the possibility to create and maintain AR content themselves without the need for expensive tools and complex interaction. Our algorithm is based on shape-from-silhouette using voxel carving and runs on modern smartphone hardware. 3D models of certain object groups can be generated interactively and instantly. The actual result is visualized continuously using image based rendering methods to inform the user about the actual model quality. Given a suitably accurate model it can further be used for any means of AR and can easily be shared with other users. The usability of our approach is evaluated using modern smartphone hardware (see Figure 1). The advantages are demonstrated using a set of models for playing a board game.
Estimation des paramètres dans les chaînes de Markov cachées et segmentation d ' image s Parameter Estimation in Hidden Markov Chains and Segmentation of Images vcherche par

Notre étude traite de l'estimation des paramètres dans les chaînes de Marko v cachées et de la segmentation statistique non supervisée d'images . Nous proposons deux algorithmes originaux d'estimation obtenus à partir des méthode s Iterative Conditional Estimation (ICE) et Stochastic Expectation Maximisation (SEM), notés MICE et MSEM respectivement, et montrons leur compétitivité vis-à-vis de l'algorithme Expectation Maximisation (EM) dans différents cas d'homogénéité et de bruitage des chaînes . L'étude du comportement des trois algorithmes de restauration non supervisée des chaînes obtenus par l'adjonction à l a méthode Mode de la Marginale a Posteriori (MPM) des algorithmes EM, MICE, MSEM respectivement est ensuite proposée . La transformation des processus bidimentionnels en processus mono-dimentionnels par le parcours de Peano rend possible l'application de ces algorithmes au problème de la segmentation statistique non supervisée d'images . On obtient ainsi des méthodes plus rapides que celles utilisant des modélisations par champs de Markov cachés et nous montron s que la perte de l'efficacité est, en général, acceptable . La souplesse de notre modélisation permet par ailleurs la conception de nombreux algorithmes de segmentatio n statistique non supervisée spatio-temporelle d'images . Nous en proposons troi s et présentons les résultats de leur application à la segmentation d'une séquenc e d'images réelles .
Cloud for Distributed Data Analysis Based on the Actor Model

This paper describes the construction of a Cloud for Distributed Data Analysis (CDDA) based on the actor model. The design uses an approach to map the data mining algorithms on decomposed functional blocks, which are assigned to actors. Using actors allows users to move the computation closely towards the stored data. The process does not require loading data sets into the cloud and allows users to analyze confidential information locally. The results of experiments show that the efficiency of the proposed approach outperforms established solutions.
Stability of human rapamycin-expanded CD4+CD25+ T regulatory cells

Background The clinical use of ex vivo-expanded T-regulatory cells for the treatment of T-cell-mediated diseases has gained increasing momentum. However, the recent demonstration that FOXP3+ T-regulatory cells may contain interleukin-17–producing cells and that they can convert into effector cells once transferred in vivo raises significant doubts about their safety. We previously showed that rapamycin permits the ex vivo expansion of FOXP3+ T-regulatory cells while impairing the proliferation of non-T-regulatory cells. Here we investigated the Th17-cell content and the in vivo stability of rapamycin-expanded T-regulatory cells as pertinent aspects of cell-based therapy. Design and Methods T-regulatory-enriched cells were isolated from healthy volunteers and were expanded ex vivo with rapamycin with a pre-clinical applicable protocol. T-regulatory cells cultured with and without rapamycin were compared for their regulatory activity, content of pro-inflammatory cells and stability. Results We found that CD4+CCR6+CD161+ T cells (i.e., precursor/committed Th17 cells) contaminate the T-regulatory cells cultured ex vivo in the absence of rapamycin. In addition, Th17 cells do not expand when rapamycin-treated T-regulatory cells are exposed to a “Th17-favorable” environment. Rapamycin-expanded T-regulatory cells maintain their in vitro regulatory phenotype even after in vivo transfer into immunodeficient NOD-SCID mice despite being exposed to the irradiation-induced pro-inflammatory environment. Importantly, no additional rapamycin treatment, either in vitro or in vivo, is required to keep their phenotype fixed. Conclusions These data demonstrate that rapamycin secures ex vivo-expanded human T-regulatory cells and provide additional justification for their clinical use in future cell therapy-based trials.
The Role of Mood in Advertising Effectiveness

This study demonstrates the facilitating effect of positive mood on brand attitudes for readers of print advertising and explores contingencies and cognitive processes underlying that effect. Mood appears to affect the amount of total cognitive elaboration, bias the evaluation of argument quality, and peripherally affect brand attitudes. An experiment using print ads reveals that positive moods create less elaboration, which results in more heuristic processing and reduces the extent to which message evaluation--itself favorably influenced by positive moods--mediates brand attitudes. The effect is greater when the reader has a low need for cognition and when the ad contains weak message arguments. Copyright 1990 by the University of Chicago.