Miracle-dz/UniFAR-FTUs huggingface dataset:
Endoscopic ultrasound-guided fine-needle aspiration in the diagnosis of adrenal lesions

The use of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) appears to be a safe and feasible means of confirming or excluding malignancy in the adrenal glands. EUS-FNA with biopsy of suspicious masses in either adrenal gland allows for assessment of these lesions while keeping complications relatively rare. The main advantages of EUS-FNA are that it can be done as an outpatient procedure, with good results, minimal morbidity, and a short hospital stay. Nevertheless, EUS-FNA of adrenal masses should be indicated only in selected cases, in which there is potential to either decrease unnecessary treatment or guide therapy in cancer patients by aiding in either staging of malignancy or treatment of recurrence.v
Coordination of independent learners in cooperative Markov games.

In the framework of fully cooperative multi-agent systems, independent agents learning by reinforcement must overcome several difficulties as the coordination or the impact of exploration. The study of these issues allows first to synthesize the characteristics of existing reinforcement learning decentralized methods for independent learners in cooperative Markov games. Then, given the difficulties encountered by these approaches, we focus on two main skills: optimistic agents, which manage the coordination in deterministic environments, and the detection of the stochasticity of a game. Indeed, the key difficulty in stochastic environment is to distinguish between various causes of noise. The SOoN algorithm is so introduced, standing for “Swing between Optimistic or Neutral”, in which independent learners can adapt automatically to the environment stochasticity. Empirical results on various cooperative Markov games notably show that SOoN overcomes the main factors of non-coordination and is robust face to the exploration of other agents.
Computational Statistics and Data Analysis Bayesian Value-at-risk and Expected Shortfall Forecasting via the Asymmetric Laplace Distribution

A parametric approach to estimating and forecasting Value-at-Risk (VaR) and expected shortfall (ES) for a heteroscedastic financial return series is proposed. The well-known GJR–GARCH form models the volatility process, capturing the leverage effect. To capture potential skewness and heavy tails, the model assumes an asymmetric Laplace form as the conditional distribution of the series. Furthermore, dynamics in higher moments are modeled by allowing the shape parameter in this distribution to be time-varying. Estimation is via an adaptive Markov chain Monte Carlo (MCMC) sampling scheme, employing the Metropolis–Hastings (MH) algorithm with a mixture of Gaussian proposal distributions. A simulation study highlights accurate estimation and improved inference compared to a single-Gaussian-proposal MH method. The model is illustrated by applying it to four international stock market indices and two exchange rates, generating one-step-ahead forecasts of VaR and ES. Standard and non-standard tests are applied to these forecasts, and the finding is that the proposed model performs favourably compared to some popular competitors: in particular it is the only conservative model of risk over the period studied, which includes the recent global financial crisis.
A blind adaptive antenna array for CDMA systems

The performance of receivers for direct sequence spread spectrum systems in multi-path fading environments can be enhanced by using an antenna array which provide spatial diversity and selectivity. In this paper a blind adaptive antenna array, designed to work under multi-path environments, for spread spectrum systems is proposed. The antenna array receiver structure performs spatial filtering to null out interferers, while combining desired signal energy from different propagation paths. Neither synchronization with the interferers nor knowledge of the desired signal's array response vector is assumed. Simulations are performed to show the performance of the algorithm.
Towards an Integrative Cognitive-Socio-Technical Approach in Health Informatics: Analyzing Technology-Induced Error Involving Health Information Systems to Improve Patient Safety

The purpose of this paper is to argue for an integration of cognitive and socio-technical approaches to assessing the impact of health information systems. Historically, health informatics research has examined the cognitive and socio-technical aspects of health information systems separately. In this paper we argue that evaluations of health information systems should consider aspects related to cognition as well as socio-technical aspects including impact on workflow (i.e. an integrated view). Using examples from the study of technology-induced error in healthcare, we argue for the use of simulations to evaluate the cognitive-socio-technical impacts of health information technology [36]. Implications of clinical simulations and analysis of cognitive-social-technical impacts are discussed within the context of the system development life cycle to improve health information system design, implementation and evaluation.
Phloem Unloading in Developing Leaves of Sugar Beet : II. Termination of Phloem Unloading.

Phloem unloading in developing leaves of Beta vulgaris L. (;Klein E' multigerm) occurred from successively higher order branches of veins as leaves matured. Phloem unloading was studied in autoradiographs of leaf samples taken at various times during the arrival of a pulse of (14)C-labeled photoassimilate. Extension of mass flow of sieve element contents into leaf vein branches was determined from the high level of radiolabel in veins soon after first arrival of the pulse. Rapid entry, indicative of mass flow through open sieve pores, occurred down to the fourth division of veins in young, importing leaves and to the fifth or terminal branch in importing regions near the zone of transition from sink to source. The rate of unloading decreased with leaf age, as evidenced by the increased time required for the vein-mesophyll demarcation to become obscured. The rate of import per unit leaf area, measured by steady state labeling with (14)CO(2) also decreased as a leaf matured. The decline in import appeared to result from progressive changes that increased resistance to unloading of sieve elements and eventually terminated phloem unloading.
Retinoic Acid Promotes Ubiquitination and Proteolysis of Cyclin D1 during Induced Tumor Cell Differentiation*

Mechanisms by which differentiation programs engage the cell cycle are poorly understood. This study demonstrates that retinoids promote ubiquitination and degradation of cyclin D1 during retinoid-induced differentiation of human embryonal carcinoma cells. In response to all-trans-retinoic acid (RA) treatment, the human embryonal carcinoma cell line NT2/D1 exhibits a progressive decline in cyclin D1 expression beginning when the cells are committed to differentiate, but before onset of terminal neuronal differentiation. The decrease in cyclin D1 protein is tightly associated with the accumulation of hypophosphorylated forms of the retinoblastoma protein and G1 arrest. In contrast, retinoic acid receptor γ-deficient NT2/D1-R1 cells do not growth-arrest or accumulate in G1 and have persistent cyclin D1 overexpression despite RA treatment. Notably, stable transfection of retinoic acid receptor γ restores RA-mediated growth suppression and differentiation to NT2/D1-R1 cells and restores the decline of cyclin D1. The proteasome inhibitor LLnL blocks this RA-mediated decline in cyclin D1. RA treatment markedly accelerates ubiquitination of wild-type cyclin D1, but not a cyclin D1 (T286A) mutant. Transient expression of cyclin D1 (T286A) in NT2/D1 cells blocks RA-mediated transcriptional decline of a differentiation-sensitive reporter plasmid and represses induction of immunophenotypic neuronal markers. Taken together, these findings strongly implicate RA-mediated degradation of cyclin D1 as a means of coupling induced differentiation and cell cycle control of human embryonal carcinoma cells.
A Structural Sampling Technique for Better Decision Trees

Since data mining problems contain a large amount of data, sampling is a necessity for the success of the task. Decision trees have been developed for prediction, and finding decision trees with smaller error rates has been a major task for their success. This paper suggests a structural sampling technique that is based on a generated decision tree, where the tree is generated based on fast and dirty tree generation algorithm. Experiments with several sample sizes and representative decision tree algorithms showed that the method is more effective with respect to decision tree size and error rate than conventional random sampling method especially for small sample size.
The Prevalence of Campylobacter amongst a Free-Range Broiler Breeder Flock Was Primarily Affected by Flock Age

Campylobacter successfully colonizes broiler chickens, but little is known about the longer term natural history of colonization, since most flocks are slaughtered at an immature age. In this study, the prevalence and genetic diversity of Campylobacter colonizing a single free-range broiler breeder flock was investigated over the course of a year. The age of the flock was the most important factor in determining both the prevalence and diversity of Campylobacter over time. There was no correlation with season, temperature, the amount of rain and sunshine, or the dynamics of colonization amongst geographically and temporally matched broiler flocks. The higher prevalence rates coincided with the age at which broiler chickens are typically slaughtered, but then in the absence of bio-security or other intervention methods, and despite changes in flock management, the prevalence fell to significantly lower levels for the remainder of the study. The genetic diversity of Campylobacter increased as the flock aged, implying that genotypes were accumulated within the flock and may persist for a long time. A better understanding of the ecology of Campylobacter within commercial chicken flocks will allow the design of more effective farm-based interventions.
Hydrogen Sulfide Attenuates Inflammatory Hepcidin by Reducing IL-6 Secretion and Promoting SIRT1-Mediated STAT3 Deacetylation.

AIMS Anemia of inflammation is quite prevalent in hospitalized patients with poor prognosis. Concerns about the effectiveness and safety of iron supplementation have arisen, driving the demand for alternative therapies. Induction of hepatic hepcidin, the master hormone of iron homeostasis, causes anemia under inflammatory conditions. Previous studies indicated that hydrogen sulfide (H2S), the third gasotransmitter and a well-known regulator of inflammation, may inhibit the secretion of inflammatory cytokines. We thus investigated the effect of H2S on inflammatory hepcidin induction. RESULTS H2S suppressed lipopolysaccharide (LPS)-induced hepcidin production and regulated iron homeostasis in mice by decreasing serum interleukin-6 (IL-6) and Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) activation; similar results were obtained in Huh7 cells exposed to conditioned medium from LPS-challenged THP-1 macrophages. Intriguingly, we found H2S also attenuated hepcidin levels in Huh7 cells and mouse primary hepatocytes in a sirtuin 1 (SIRT1)-dependent manner. By promoting SIRT1 expression and stabilizing SIRT1-STAT3 interactions, H2S ameliorated IL-6-induced STAT3 acetylation, resulting in reduced hepcidin production. Inhibition and silencing of SIRT1 diminished H2S-mediated suppression of hepcidin, as opposed to SIRT1 activation and overexpression. Consistent results were observed in vivo. Furthermore, knockout of cystathionine γ-lyase (CSE), an endogenous H2S synthase, exaggerated inflammatory hepcidin expression in mice. INNOVATION For the first time, we elucidated the effects and possible mechanisms of H2S on inflammatory hepcidin and established a novel regulatory link between SIRT1 and hepcidin. CONCLUSION Our work demonstrates that H2S attenuates inflammation-induced hepatic hepcidin via multipathways and suggests new treatment strategies for anemia of inflammation.
Optimal feature selection for subspace image matching

Image matching has been a central research topic in computer vision over the last decades. Typical approaches to correspondence involve matching features between images. In this paper, we present a novel problem for establishing correspondences between a sparse set of image features and a previously learned subspace model. We formulate the matching task as an energy minimization, and jointly optimize over all possible feature assignments and parameters of the subspace model. This problem is in general NP-hard. We propose a convex relaxation approximation, and develop two optimization strategies: naive gradient-descent and quadratic programming. Alternatively, we reformulate the optimization criterion as a sparse eigenvalue problem, and solve it using a recently proposed backward greedy algorithm. Experimental results on facial feature detection show that the quadratic programming solution provides better selection mechanism for relevant features.
Critical Function of a Chlamydomonas reinhardtii Putative Polyphosphate Polymerase Subunit during Nutrient Deprivation[C][W]

The VTC1 protein is necessary for acclimation of the green alga Chlamydomonas to nutrient deprivation. A mutant defective for the VTC1 gene cannot make acidocalcisomes (type of vacuole), is unable to traffic a group of extracellular, nutrient-deprivation induced proteins to their site of function, and dies earlier then wild-type cells following the imposition of nutrient deprivation. Forward genetics was used to isolate Chlamydomonas reinhardtii mutants with altered abilities to acclimate to sulfur (S) deficiency. The ars76 mutant has a deletion that eliminates several genes, including VACUOLAR TRANSPORTER CHAPERONE1 (VTC1), which encodes a component of a polyphosphate polymerase complex. The ars76 mutant cannot accumulate arylsulfatase protein or mRNA and shows marked alterations in levels of many transcripts encoded by genes induced during S deprivation. The mutant also shows little acidocalcisome formation compared with wild-type, S-deprived cells and dies more rapidly than wild-type cells following exposure to S-, phosphorus-, or nitrogen (N)-deficient conditions. Furthermore, the mutant does not accumulate periplasmic l-amino acid oxidase during N deprivation. Introduction of the VTC1 gene specifically complements the ars76 phenotypes, suggesting that normal acidocalcisome formation in cells deprived of S requires VTC1. Our data also indicate that a deficiency in acidocalcisome function impacts trafficking of periplasmic proteins, which can then feed back on the transcription of the genes encoding these proteins. These results and the reported function of vacuoles in degradation processes suggest a major role of the acidocalcisome in reshaping the cell during acclimation to changing environmental conditions.
Unsupervised Shilling Detection for Collaborative Filtering

Collaborative Filtering systems are essentially social systems which base their recommendation on the judgment of a large number of people. However, like other social systems, they are also vulnerable to manipulation. Lies and Propaganda may be spread by malicious users who may have an interest in promoting an item, or downplaying the popularity of another one. By doing this systematically, with either multiple identities, or by involving more people, malicious shilling user profiles can be injected into a collaborative recommender system which can significantly affect the robustness of a recommender system. While current detection algorithms are able to use certain characteristics of shilling profiles to detect them, they suffer from low precision, and require a large amount of training data. The aim of this work is to explore simpler unsupervised alternatives which exploit the nature of shilling profiles, and can be easily plugged into collaborative filtering framework to add robustness. Two statistical methods are developed and experimentally shown to provide high accuracy in shilling attack detection.
Active Learning Methods for Semi-supervised Manifold Learning

The objective of this paper is to propose a principled approach for selecting the data points for labeling used in semi-supervised manifold learning. We postulate that the data points should be chosen so that the alignment matrix for the remaining data points will have the best condition number possible. We also proposed an efficient algorithm for selecting principal submatrices of the alignment matrices with good condition numbers. Experiments on both synthetic and real-world problems show that our proposed method can substantially improve the accuracy of the computed global parameterizations over several alternative methods.
Changes in serum trough levels of infliximab during treatment intensification but not in anti-infliximab antibody detection are associated with clinical outcomes after therapeutic failure in Crohn's disease.

BACKGROUND AND AIMS Intensification of the infliximab (IFX) regimen is recommended if the treatment effect is inadequate. However, the rationale for this is not well defined as the underlying mechanisms vary. The aim of this study was to explore the association between changes in serum IFX and anti-IFX antibodies (Abs) after IFX intensification and clinical outcomes. METHODS We performed a post hoc analysis of a randomized clinical trial including 42 Crohn's disease patients with IFX treatment failure, all treated with an intensified IFX regimen (5mg/kg every 4 week) for 12 weeks. Trough serum IFX and anti-IFX Ab concentrations were measured by a homogeneous mobility shift binding assay (HMSA) and a functional cell-based reporter gene assay (RGA) at treatment failure and the end of the trial. RESULTS Twenty-one patients (50%) regained clinical response on the intensified IFX regimen. The increase in serum trough levels of IFX during treatment intensification was higher among responders than non-responders (RGA, 8.8 versus 3.0 μg/mL, p = 0.035; HMSA, 9.9 versus 4.7 μg/mL, p = 0.040), and differentiated patients by clinical outcome (RGA, area under receiver operating characteristic curve [AUC] 0.75 [0.53-0.97], p = 0.035; HMSA, AUC 0.74 [0.53-0.95], p = 0.042). All responders exhibited an IFX increase ≥2.6 μg/mL (sensitivity 100%, specificity 50%). Anti-IFX Abs detected by HMSA in 13 patients (32%) were often non-functional and became undetectable during IFX intensification. However, even functional anti-IFX Abs detected by RGA in six patients (15%) became undetectable. CONCLUSION Increase in IFX levels following treatment intensification was associated with improved clinical outcomes, indicating insufficient drug levels in a subgroup of patients. Anti-IFX Abs may become undetectable during treatment intensification, suggesting lowered production or the formation of immune complexes.
Application of Newton's Method to action selection in continuous state- and action-space reinforcement learning

An algorithm based on Newton's Method is proposed for action selection in continuous state- and action-space reinforcement learning without a policy network or discretization. The proposed method is validated on two benchmark problems: Cart-Pole and double Cart-Pole on which the proposed method achieves comparable or improved performance with less parameters to tune and in less training episodes than CACLA, which has previously been shown to outperform many other continuous state- and action-space reinforcement learning algorithms.
BRAD: Background regression based hyperspectral anomaly detection, a k-nn score estimation aspect

Robust background representation is a key issue for detecting anomaly targets in hyperspectral imagery. Meanwhile, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection process. This paper for the first time aims to implement robust background representation, as well as to explore the intrinsic data structure of the hyperspectral imagery simultaneously. Robust background dataset and potential anomaly dataset are firstly assigned by a robust background regression (RBR) procedure. In the RBR, a minimum squared loss relationship is constructed between the nonlinear data density feature and the corresponding assigned labels, to formulate the foundation of the regression. Furthermore, a manifold regularization term and a robust background average margin maximization term are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation is undertaken to implement the detection output. Experimental results prove that the proposed method outperforms some other state-of-the-art anomaly detectors.
Cold-Injury of the Cerebral Cortex: Immunolocalization of Cellular Proteins and Blood-Brain Barrier Permeability Studies

The occurrence of blood-brain barrier (BBB) permeability alterations and neovascularization are well documented in the cerebral cortical cold-injury model. This model was used to determine whether the glucose transporter (glutl) protein was present in endothelium of cerebral vessels with breakdown of BBB to protein and when regenerating endothelial cells become immunoreactive for glutl protein. Secondly, the protein products of c-fos and c-jun were localized to determine whether these early immediate genes are activated in this model. Observations were made over a period of 12 hours to 14 days after the cold-injury. Blood-brain barrier permeability was assessed using horseradish peroxidase (HRP) as a tracer. Since HRP may not be able to enter thrombosed vessels within the cold lesion, immunohistochemistry was used to detect extravasation of endogenous serum proteins using antisera to rat serum proteins. The proteins—glutl, GFAP, c-fos and c-jun—were localized by immunohistochemistry. Endothelium of vessels which were permeable to protein, whether in the cold-injury site or in the perilesional area, all contained glutl protein; hence, the presence of glutl did not appear to correlate with an intact BBB to protein. An interesting point is that in the process of neovascularization, regenerating endothelial cells become immunoreactive for glutl at 5 days and this coincides with the presence of tight junctions in these cells. Immunoreactivity for c-fos was observed in regenerating endothelium within the lesion site, in astrocytes, and to a lesser extent in endothelial cells and neurons in the perilesional area. Few astrocytes showed immunoreactivity for c-jun at 4 and 5 days. Possibly, the growth factors generated to promote angiogenesis and repair led to activation of the c-fos gene with deposition of c-fos protein. The results suggest that during nervous system development or endothelial regeneration, the presence of glutl in cerebral endothelium coincides with the presence of an intact BBB to protein and protein tracers. However, in pathological states presence of glutl in cerebral endothelium does not appear to correlate with an intact BBB to protein. This model lends itself to the study of angiogenesis and repair processes in the cerebral cortex in an environment unaffected by ischemia and thus the findings may be relevant to traumatic injuries of the human cerebral cortex.
JILL: Japanese incidental language learning

We present a Web-based environment for incidental learning of Japanese. As the two key enabling technologies we use augmented browsing at the client and logic programming at the server. This way we can create a learning experience which blends foreign language acquisition with the user's everyday browsing activities. Main features presented in this paper are an intuitive visual presentation of sentence structures, comprehensive support at the word level by integrating several lexical resources including DBpedia, and multiple customization options.