Miracle-dz/UniFAR-FTUs huggingface dataset:
Polymorphic Sites at the Immunoregulatory CTLA-4 Gene Are Associated with Chronic Chagas Disease and Its Clinical Manifestations

Background Chagas disease affects approximately 10 million people mainly in Latin America. The immune regulation by the host seems to be an essential factor for disease evolution, and immune system inhibitory molecules such as CTLA-4 and PD-1 favor the maintenance of peripheral tolerance. Considering that polymorphisms at the immunoregulatory CTLA-4 and PDCD1 genes may alter their inhibitory function, we investigated the association of alleles, genotypes and haplotypes of polymorphic sites observed at the CTLA-4 and PDCD1 genes with different clinical manifestations of chronic Chagas disease (indeterminate, cardiac, digestive and mixed). Methods The polymorphisms at the CTLA-4 (-1722T/C, -318C/T and +49A/G) and PDCD1 (PD-1.3G/A) genes were typed using TaqMan methodology in 277 chronic Chagas disease patients classified into four groups, according to clinical characteristics, and 326 non-infected controls. Results Our results showed that CTLA-4 -1722CC genotype (22%), -1722C allele (27%) and CTLA-4 TCG (8.6%), TCA (26%) and CCA (15%) haplotypes were strongly associated with the indeterminate form, while the CTLA-4 -318CT genotype (82%) and CTLA-4 -318T allele (47%) were found mainly in patients with the mixed form of the disease. The CTLA-4 TCG haplotype (10.2%) was associated with the digestive form. On the other hand, the PD-1.3G/A polymorphism was not associated with chronic Chagas disease and its clinical manifestations. Conclusions Here, we showed that alleles, genotypes and haplotypes reported to increase the expression of the regulatory molecule CTLA-4 were associated with the indeterminate form of the disease. Taken together, our data support the idea that polymorphic sites at immunoregulatory genes may influence the development of Chagas disease variants.
Statistical agglomeration: peak summarization for direct infusion lipidomics

MOTIVATION Quantification of lipids is a primary goal in lipidomics. In direct infusion/injection (or shotgun) lipidomics, accurate downstream identification and quantitation requires accurate summarization of repetitive peak measurements. Imprecise peak summarization multiplies downstream error by propagating into species identification and intensity estimation. To our knowledge, this is the first analysis of direct infusion peak summarization in the literature. RESULTS We present two novel peak summarization algorithms for direct infusion samples and compare them with an off-machine ad hoc summarization algorithm as well as with the propriety Xcalibur algorithm. Our statistical agglomeration algorithm reduces peakwise error by 38% mass/charge (m/z) and 44% (intensity) compared with the ad hoc method over three datasets. Pointwise error is reduced by 23% (m/z). Compared with Xcalibur, our statistical agglomeration algorithm produces 68% less m/z error and 51% less intensity error on average on two comparable datasets. AVAILABILITY The source code for Statistical Agglomeration and the datasets used are freely available for non-commercial purposes at https://github.com/optimusmoose/statistical_agglomeration. Modified Bin Aggolmeration is freely available in MSpire, an open source mass spectrometry package at https://github.com/princelab/mspire/.
Transparency in Interactive Technical Illustrations

This paper describes how technical illustrations containing opaque and non‐opaque objects can be automatically generated. Traditional methods to show transparency in manual drawings are evaluated to extract a small and effective set of rules for computer‐based rendering of technical illustrations, leading to a novel view‐dependent transparency model. We propose a hardware‐accelerated depth sorting algorithm in image‐space which specifically meets the requirements of our transparency model. In this way, real‐time rendering of semi‐transparent technical illustrations is achieved. Finally, it is described how our approach can be combined with other methods in the field of non‐photorealistic rendering in order to enhance the visual perception of technical illustrations.
Calcium Channels and Pumps in Cancer: Changes and Consequences*

Increases in intracellular free Ca2+ play a major role in many cellular processes. The deregulation of Ca2+ signaling is a feature of a variety of diseases, and modulators of Ca2+ signaling are used to treat conditions as diverse as hypertension to pain. The Ca2+ signal also plays a role in processes important in cancer, such as proliferation and migration. Many studies in cancer have identified alterations in the expression of proteins involved in the movement of Ca2+ across the plasma membrane and subcellular organelles. In some cases, these Ca2+ channels or pumps are potential therapeutic targets for specific cancer subtypes or correlate with prognosis.
The SystemT IDE: an integrated development environment for information extraction rules

Information Extraction (IE)-the problem of extracting structured information from unstructured text - has become the key enabler for many enterprise applications such as semantic search, business analytics and regulatory compliance. While rule-based IE systems are widely used in practice due to their well-known "explainability," developing high-quality information extraction rules is known to be a labor-intensive and time-consuming iterative process. Our demonstration showcases SystemT IDE, the integrated development environment for SystemT, a state-of-the-art rule-based IE system from IBMResearch that has been successfully embedded in multiple IBM enterprise products. SystemT IDE facilitates the development, test and analysis of high-quality IE rules by means of sophisticated techniques, ranging from data management to machine learning. We show how to build high-quality IE annotators using a suite of tools provided by SystemT IDE, including computing data provenance, learning basic features such as regular expressions and dictionaries, and automatically refining rules based on labeled examples.
Calcium-dependent ADP-ribosylation of high-mobility-group I (HMGI) proteins.

Micrococcal nuclease digestion of nuclei from mouse Lewis lung carcinoma cells releases a protein mixture into the supernatant that lacks histone H1 and contains a full complement of high-mobility-group I (HMGI) proteins (i.e. I, Y and I-C). This implies that all three HMGI proteins are localized at the nuclease-sensitive regions of active chromatin. It is also shown that if Ca2+ ions are present in the nuclear incubation buffer (with or without exogenous nuclease), all three HMGI proteins become ADP-ribosylated. We propose that this modification of HMGI family proteins is part of the general poly(ADP-ribosyl)ation that accompanies DNA damage in apoptosis and other processes.
El conocimiento como necesidad de Estado: las encuestas oficiales sobre Nueva España durante el reinado de Carlos V

While Philip II’s initiatives in the field of statistics (such as the Relaciones Geograficas) have been attended to, very little has been done with regard to the Crownpromoted American encuestas in the time of Charles V, which originated a rich amount of documentation. This is a very serious gap, since it has meant overlooking the political significance of the statistical or pre-statistical initiatives in the first half of the 16th Century, which were both symptomatic and expressive of a new pattern as regards public administration and the State. This new pattern based on the necessity of knowledge appeared very early in Spain and in it America played a key role. It is precisely this process which is studied in this article.
Employee Responses to Job Dissatisfaction

Over the past several years, high unemployment and limited job mobility prospects have kept voluntary employee turnover statistics relatively low. In more favorable job markets, dissatisfied employees are likely to leave undesirable work situations and move on to what they perceive will be more satisfying work relationships. In tight labor markets, dissatisfied employees often find that they are unable to leave dissatisfying jobs. This paper explores two questions pertaining to retention of dissatisfied employees. What can we expect, in terms of turnover, when the job market becomes more favorable to job seekers and how do dissatisfied employees who remain with employers respond behaviorally while continuing to work in a dissatisfying work environment?
Image clustering through community detection on hybrid image similarity graphs

The wide adoption of photo sharing applications such as Flickr © and the massive amounts of user-generated content uploaded to them raises an information overload issue for users. An established technique to overcome such an overload is to cluster images into groups based on their similarity and then use the derived clusters to assist navigation and browsing of the collection. In this paper, we present a community detection (i.e. graph-based clustering) approach that makes use of both visual and tagging features of images in order to efficiently extract groups of related images within large image collections. Based on experiments we conducted on a dataset comprising publicly available images from Flickr ©, we demonstrate the efficiency of our method, the added value of combining visual and tag features and the utility of the derived clusters for exploring an image collection.
An Emotion-based Image Retrieval System by Using Fuzzy Integral with Relevance Feedback

The emotional information processing is to simulate and recognize human sensibility, sensuality or emotion, to realize natural and harmonious human-machine interface. This paper proposes an emotion-based image retrieval method. In this method, user can choose a linguistic query among some emotional adjectives. Then the system shows some corresponding representative images that are pre-evaluated by experts. Again the user can select a representative one among the representative images to initiate traditional content-based image retrieval (CBIR). By this proposed method any CBIR can be easily expanded as emotion-based image retrieval. In CBIR of our system, we use several color and texture visual descriptors recommended by MPEG-7. We also propose a fuzzy similarity measure based on Choquet integral in the CBIR system. For the communication between system and user, a relevance feedback mechanism is used to represent human subjectivity in image retrieval. This can improve the performance of image retrieval, and also satisfy the user’s individual preference.
Neutrophils Promote Mononuclear Cell Infiltration During Viral-Induced Encephalitis1

Neutrophils are the first infiltrating cell population to appear within the CNS during infection with the neurotropic JHM strain of mouse hepatitis virus (JHMV). To determine whether neutrophils play a role in limiting acute JHMV infection, mice were depleted of neutrophils. Infection of neutropenic animals resulted in increased levels of virus replication and mortality compared with control mice. Furthermore, neutropenia resulted in significantly reduced mononuclear leukocyte infiltration possibly due to reduced loss of blood brain barrier integrity during acute JHMV infection. These data suggest that infiltrating neutrophils are crucial for limiting virus replication during acute JHMV infection, contribute to the loss of blood brain barrier integrity and play a role in shaping adaptive immunity within the CNS.
On Combining Distributed Joint Source-Channel-Network Coding and Turbo Equalization in Multiple Access Relay Networks

We consider a multiple access relay channel where two sources S1 and S2 send their data to a common destination node aided by a shared relay node. In this paper we extend previous work on this topic by assuming that the output of both information sources are correlated with memory. Furthermore, we consider frequency-selective fading channels, which introduce inter-symbol interference among the transmitted symbols. In this context, we propose an iterative receiver which comprises turbo maximum a posteriori (MAP) equalization and distributed source-channel- network decoding in an iterative fashion. Various relaying strategies such as network coding or time multiplexing are analyzed in detail. In addition, a suboptimal but less complex minimum mean square error (MMSE) linear equalizer is also utilized to account for communication scenarios with constrained complexity. Simulation results show that network coding based strategy outperforms, in all cases, the other considered forwarding schemes.
Iris codes classification using discriminant and witness directions

The main topic discussed in this paper is how to use intelligence for biometric decision defuzzification. A neural training model is proposed and tested here as a possible solution for dealing with natural fuzzification that appears between the intra-and inter-class distributions of scores computed during iris recognition tests. It is shown here that the use of proposed neural network support leads to an improvement in the artificial perception of the separation between the intra-and inter-class score distributions by moving them away from each other.
Tangible avatar and tangible earth: a novel interface for astronomy education

The capability to support spatial perception plays an important role in developing material for astronomy education. Considering this, we developed a novel tangible user interface consisting of a glove and a physical avatar attached on its surface. Virtual reality graphics of the solar system can be controlled manually with the glove and avatar. Preliminary experiments have indicated the advantages of the proposed tangible user interface for astronomy education.
Proactive Response to Eye Movements

Proactive computing reinforces the need for non-command interfaces that fulfill the user’s intentions without explicit commands. Eye gaze is a natural modality to be used in this connection, because it is also used proactively in everyday life. Previously eye-tracking has been used mostly for research purposes or in applications targeted for users with special needs. We present iDict, a gaze-assisted application for reading electronic documents written in a foreign language. iDict observes the reader’s eye movements and behaves proactively by providing help when the user has comprehension problems. The lessons learnt (coping with inaccurate input data, need to control the level of proactivity, and delicacy of proactive adaptation) are of interest to the development of proactive applications in general and to eye-aware applications in particular.
Reducing catastrophic forgetting in neural networks using slow learning

This thesis describes a connectionist approach to learning and long-term memory consolidation, inspired by empirical studies on the roles of the hippocampus and neocortex in the brain. The existence of complementary learning systems is due to demands posed on our cognitive system because of the nature of our experiences. It has been shown that dual-network architectures utilizing information transfer successfully can avoid the phenomenon of catastrophic forgetting involved in multiple sequence learning. The experiments involves a Reverberated Simple Recurrent Network which is trained on multiple sequences with the memory being reinforced by means of self-generated pseudopatterns. My focus will be on the implications of how differentiated learning speed affects the level of forgetting, without explicit training on the data used to form the existing memory.
Genetic Analysis of T Cell Lymphomas in Carbon Ion-Irradiated Mice Reveals Frequent Interstitial Chromosome Deletions: Implications for Second Cancer Induction in Normal Tissues during Carbon Ion Radiotherapy

Monitoring mice exposed to carbon ion radiotherapy provides an indirect method to evaluate the potential for second cancer induction in normal tissues outside the radiotherapy target volume, since such estimates are not yet possible from historical patient data. Here, male and female B6C3F1 mice were given single or fractionated whole-body exposure(s) to a monoenergetic carbon ion radiotherapy beam at the Heavy Ion Medical Accelerator in Chiba, Japan, matching the radiation quality delivered to the normal tissue ahead of the tumour volume (average linear energy transfer = 13 keV.μm-1) during patient radiotherapy protocols. The mice were monitored for the remainder of their lifespan, and a large number of T cell lymphomas that arose in these mice were analysed alongside those arising following an equivalent dose of 137Cs gamma ray-irradiation. Using genome-wide DNA copy number analysis to identify genomic loci involved in radiation-induced lymphomagenesis and subsequent detailed analysis of Notch1, Ikzf1, Pten, Trp53 and Bcl11b genes, we compared the genetic profile of the carbon ion- and gamma ray-induced tumours. The canonical set of genes previously associated with radiation-induced T cell lymphoma was identified in both radiation groups. While the pattern of disruption of the various pathways was somewhat different between the radiation types, most notably Pten mutation frequency and loss of heterozygosity flanking Bcl11b, the most striking finding was the observation of large interstitial deletions at various sites across the genome in carbon ion-induced tumours, which were only seen infrequently in the gamma ray-induced tumours analysed. If such large interstitial chromosomal deletions are a characteristic lesion of carbon ion irradiation, even when using the low linear energy transfer radiation to which normal tissues are exposed in radiotherapy patients, understanding the dose-response and tissue specificity of such DNA damage could prove key to assessing second cancer risk in carbon ion radiotherapy patients.
Post-College Experiences and Epistemology

Epistemological development research indicates that many seniors hold assumptions about knowledge that hinder them in forming critical perspectives. This article reports that seniors with such assumptions, after graduation, had experiences that nurtured more complex assumptions about knowledge by emphasizing independent functioning, collaboration, direct involvement in learning, and subjective decision-making. The essay recommends incorporating the characteristics of these experiences into college curricula to promote more complex ways of knowing.
From Laser Scanning to Finite Element Analysis of Complex Buildings by Using a Semi-Automatic Procedure

In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sections. The complexity of the clouds is arbitrary, since the procedure is designed for terrestrial laser scanner surveys applied to buildings with irregular geometry, such as historical buildings. The procedure aims at solving the problems connected to the generation of finite element models of these complex structures by constructing a fine discretized geometry with a reduced amount of time and ready to be used with structural analysis. If the starting clouds represent the inner and outer surfaces of the structure, the resulting finite element model will accurately capture the whole three-dimensional structure, producing a complex solid made by voxel elements. A comparison analysis with a CAD-based model is carried out on a historical building damaged by a seismic event. The results indicate that the proposed procedure is effective and obtains comparable models in a shorter time, with an increased level of automation.
Thyroid peroxidase autoantigen : localization of autoantigenic epitopes on recombinant protein and prediction of secondary structure

The cloning and expression of TPO as a recombinant protein has allowed progress on the characterisation of the autoantigenic epitopes recognised by autoantibodieJ. fhe main immunogenic region of the molecule recognised by autoaniibodies has been localized to the carboxyl terminal. Multiple sequence alignment and secondary structure prediction methods used in conjunction with circular dichroic spectroscopy indicate that TpO structure is pr incipal ly alpha-hel ical . Together with a knowledge of the exon-intron boundaries uggests a model for the domain organization of the TPO molecule. The ability in the future to-irap the autoantigenic epitopes on a three dimensional structural model of ine TpO molecule will allow a Sreater understanding of the aetiological basis of autoimmune disease and allow the design of therapeutic strategies at an antigen specific level to be addressed.
Privacy Games: Optimal User-Centric Data Obfuscation

Abstract Consider users who share their data (e.g., location) with an untrusted service provider to obtain a personalized (e.g., location-based) service. Data obfuscation is a prevalent user-centric approach to protecting users’ privacy in such systems: the untrusted entity only receives a noisy version of user’s data. Perturbing data before sharing it, however, comes at the price of the users’ utility (service quality) experience which is an inseparable design factor of obfuscation mechanisms. The entanglement of the utility loss and the privacy guarantee, in addition to the lack of a comprehensive notion of privacy, have led to the design of obfuscation mechanisms that are either suboptimal in terms of their utility loss, or ignore the user’s information leakage in the past, or are limited to very specific notions of privacy which e.g., do not protect against adaptive inference attacks or the adversary with arbitrary background knowledge. In this paper, we design user-centric obfuscation mechanisms that impose the minimum utility loss for guaranteeing user’s privacy. We optimize utility subject to a joint guarantee of differential privacy (indistinguishability) and distortion privacy (inference error). This double shield of protection limits the information leakage through obfuscation mechanism as well as the posterior inference. We show that the privacy achieved through joint differential-distortion mechanisms against optimal attacks is as large as the maximum privacy that can be achieved by either of these mechanisms separately. Their utility cost is also not larger than what either of the differential or distortion mechanisms imposes. We model the optimization problem as a leader-follower game between the designer of obfuscation mechanism and the potential adversary, and design adaptive mechanisms that anticipate and protect against optimal inference algorithms. Thus, the obfuscation mechanism is optimal against any inference algorithm.
Movement and interaction in semantic GRIDs: dynamic service generation for Agents in the MIC* deployment environment

We present in this position paper the foundations of the MIC* model and deployment environment as they have emerged in the last years, relate them to current evolutions on semantic GRID dynamic service generation, as reflected by OGSA/I and, more recently, by WSRF, and propose an integrated view with the previously proposed STROBE model for communicating agents leading to a quite simple yet very promising architecture that may include Human agents in the loop, uninspectable as most artificial agents, yet behaving autonomously by interacting. Modeling Human agents seems to us of high importance in the high level service generation required by complex, semantically rich applications, such as those of e-Learning, e-Science or e-Commerce envisaged in the years to come.
Lexical similarity metrics for vocabulary learning modeling in Computer-Assisted Language Learning ( CALL )

This paper discusses a technique for measuring lexical similarity in terms of its effect on the perceptual ability of learners in recognizing L2 words with the help of L1. This technique can be used in many modules of an ITS CALL implementation, in particular in the initialization of the learner model based on his/her native language and in the diagnose of errors due to interference from L1. The rationale for such an implementation is discussed and a brief description of the technique is given.