Miracle-dz/UniFAR-FTUs huggingface dataset:
Perivascular Arrest of CD8+ T Cells Is a Signature of Experimental Cerebral Malaria

There is significant evidence that brain-infiltrating CD8+ T cells play a central role in the development of experimental cerebral malaria (ECM) during Plasmodium berghei ANKA infection of C57BL/6 mice. However, the mechanisms through which they mediate their pathogenic activity during malaria infection remain poorly understood. Utilizing intravital two-photon microscopy combined with detailed ex vivo flow cytometric analysis, we show that brain-infiltrating T cells accumulate within the perivascular spaces of brains of mice infected with both ECM-inducing (P. berghei ANKA) and non-inducing (P. berghei NK65) infections. However, perivascular T cells displayed an arrested behavior specifically during P. berghei ANKA infection, despite the brain-accumulating CD8+ T cells exhibiting comparable activation phenotypes during both infections. We observed T cells forming long-term cognate interactions with CX3CR1-bearing antigen presenting cells within the brains during P. berghei ANKA infection, but abrogation of this interaction by targeted depletion of the APC cells failed to prevent ECM development. Pathogenic CD8+ T cells were found to colocalize with rare apoptotic cells expressing CD31, a marker of endothelial cells, within the brain during ECM. However, cellular apoptosis was a rare event and did not result in loss of cerebral vasculature or correspond with the extensive disruption to its integrity observed during ECM. In summary, our data show that the arrest of T cells in the perivascular compartments of the brain is a unique signature of ECM-inducing malaria infection and implies an important role for this event in the development of the ECM-syndrome.
Index Design for Dynamic Personalized PageRank

Personalized page rank, related to random walks with restarts and conductance in resistive networks, is a frequent search paradigm for graph-structured databases. While efficient batch algorithms exist for static whole-graph page rank, interactive query-time personalized page rank has proved more challenging. Here we describe how to select and build indices for a popular class of page rank algorithms, so as to provide real-time personalized page rank and smoothly trade off between index size, preprocessing time, and query speed. We achieve this by developing a precise, yet efficiently estimated performance model for personalized page rank query execution. We use this model in conjunction with a query workload in a cost-benefit type index optimizer. On millions of queries from CiteSeer and its data graphs with 74-320 thousand nodes, our algorithm runs 50-400 x faster than whole-graph page rank, the gap growing with graph size. Index size is 10-20% of a text index. Ranking accuracy is above 94%.
The Interacting Effects of Accountability and Individual Differences on Rater Response to a Performance-Rating Task

We examine the effects of conscientiousness and public self-consciousness in moderating responses to accountability for 137 participants took part in a managerial simulation over a 2-week period. In addition to responding to complex information and decision tasks, participants observed 48 vignettes depicting individual performance for four subordinates on three performance dimensions and subsequently rated that performance. Results show that participants higher in conscientiousness and public self-consciousness perceived a greater need to justify their decisions than those lower in the trait. Public self-consciousness also moderated the relationship between perceived need to justify the rating and participant anxiety about that justification requirement. Subsequent tests of mediation using structural equation modeling found support for partial mediating models and overall model fit improved when personality was considered.
Functional and Structural Characterization of a Receptor-Like Kinase Involved in Germination and Cell Expansion in Arabidopsis

Leucine-rich repeat receptor-like kinases (LRR-RLKs) are widespread in different plant species and play important roles in growth and development. Germination inhibition is vital for the completion of seed maturation and cell expansion is a fundamental cellular process driving plant growth. Here, we report genetic and structural characterizations of a functionally uncharacterized LRR-RLK, named GRACE (Germination Repression and Cell Expansion receptor-like kinase). Overexpression of GRACE in Arabidopsis exhibited delayed germination, enlarged cotyledons, rosette leaves and stubbier petioles. Conversely, these phenotypes were reversed in the T-DNA insertion knock-down mutant grace-1 plants. A crystal structure of the extracellular domain of GRACE (GRACE-LRR) determined at the resolution of 3.0 Å revealed that GRACE-LRR assumed a right-handed super-helical structure with an island domain (ID). Structural comparison showed that structure of the ID in GRACE-LRR is strikingly different from those observed in other LRR-RLKs. This structural observation implies that GRACE might perceive a new ligand for signaling. Collectively, our data support roles of GRACE in repressing seed germination and promoting cell expansion of Arabidopsis, presumably by perception of unknown ligand(s).
Code-aided frequency ambiguity resolution and channel estimation for MIMO OFDM systems

This contribution deals with channel estimation and frequency ambiguity resolution in a MIMO OFDM context. Existing blind frequency-recovery algorithms for OFDM are able to provide a reliable estimate of the frequency offset up to an integer multiple of the subcarrier spacing. To resolve the remaining ambiguity, one can employ either pilot symbols or the unknown coded data symbols. Clearly, the latter method results in a higher bandwidth efficiency. Similar considerations hold for the estimation of a frequency-selective MIMO channel. In this contribution, we propose a code-aided technique to jointly estimate the channel and resolve the frequency ambiguity. The estimator is based on the expectation-maximization (EM) algorithm and exploits information from the unknown coded data symbols and only a small number of pilot symbols. A significant performance gain is observed compared to existing, solely pilot-based estimation techniques.
Reflections on the Cognitive Interviewing Reporting Framework: Efficacy, expectations, and promise for the future.

Based on the experiences of three research groups using and evaluating the Cognitive Interviewing Reporting Framework (CIRF), we draw conclusions about the utility of the CIRF as a guide to creating cognitive testing reports. Authors generally found the CIRF checklist to be usable, and that it led to a more complete description of key steps involved. However, despite the explicit direction by the CIRF to include a full explanation of major steps and features (e.g., research objectives and research design), the three cognitive testing reports tended to simply state what was done, without further justification. Authors varied in their judgments concerning whether the CIRF requires the appropriate level of detail. Overall, we believe that current cognitive interviewing practice will benefit from including, within cognitive testing reports, the 10 categories of information specified by the CIRF. Future use of the CIRF may serve to direct the overall research project from the start, and to further the goal of .
Amniotic Fluid Stem Cells with Low γ-Interferon Response Showed Behavioral Improvement in Parkinsonism Rat Model

Amniotic fluid stem cells (AFSCs) are multipotent stem cells that may be used in transplantation medicine. In this study, AFSCs established from amniocentesis were characterized on the basis of surface marker expression and differentiation potential. To further investigate the properties of AFSCs for translational applications, we examined the cell surface expression of human leukocyte antigens (HLA) of these cells and estimated the therapeutic effect of AFSCs in parkinsonian rats. The expression profiles of HLA-II and transcription factors were compared between AFSCs and bone marrow-derived mesenchymal stem cells (BMMSCs) following treatment with γ-IFN. We found that stimulation of AFSCs with γ-IFN prompted only a slight increase in the expression of HLA-Ia and HLA-E, and the rare HLA-II expression could also be observed in most AFSCs samples. Consequently, the expression of CIITA and RFX5 was weakly induced by γ-IFN stimulation of AFSCs compared to that of BMMSCs. In the transplantation test, Sprague Dawley rats with 6-hydroxydopamine lesioning of the substantia nigra were used as a parkinsonian-animal model. Following the negative γ-IFN response AFSCs injection, apomorphine-induced rotation was reduced by 75% in AFSCs engrafted parkinsonian rats but was increased by 53% in the control group after 12-weeks post-transplantation. The implanted AFSCs were viable, and were able to migrate into the brain’s circuitry and express specific proteins of dopamine neurons, such as tyrosine hydroxylase and dopamine transporter. In conclusion, the relative insensitivity AFSCs to γ-IFN implies that AFSCs might have immune-tolerance in γ-IFN inflammatory conditions. Furthermore, the effective improvement of AFSCs transplantation for apomorphine-induced rotation paves the way for the clinical application in parkinsonian therapy.
Applying Positive Behavior Support and Functional Behavioral Assessment in Schools

Positive behavior support (PBS) and functional behavioral assessment (FBA) are two significant concepts of the 1997 amendments to the Individuals with Disabilities Education Act. These two concepts are not new, but they are important for improving the quality of efforts to educate children and youth with disabilities. The purposes of this article are to describe (a) the context in which PBS and FBA are needed and (b) definitions and features of PBS and FBA. An important message is that positive behavioral interventions and supports involve the whole school, and successful implementation emphasizes the identification, adoption, and sustained use of effective policies, systems, data-based decision making, and practices. Systems-level challenges are also discussed.
Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.

OBJECTIVE The authors consider the problem of exact string pattern matching using algorithms that do not require any preprocessing. To choose the most appropriate algorithm, distinctive features of the medical language must be taken into account. The characteristics of medical language are emphasized in this regard, the best algorithm of those reviewed is proposed, and detailed evaluations of time complexity for processing medical texts are provided. DESIGN The authors first illustrate and discuss the techniques of various string pattern-matching algorithms. Next, the source code and the behavior of representative exact string pattern-matching algorithms are presented in a comprehensive manner to promote their implementation. Detailed explanations of the use of various techniques to improve performance are given. MEASUREMENTS Real-time measures of time complexity with English medical texts are presented. They lead to results distinct from those found in the computer science literature, which are typically computed with normally distributed texts. RESULTS The Boyer-Moore-Horspool algorithm achieves the best overall results when used with medical texts. This algorithm usually performs at least twice as fast as the other algorithms tested. CONCLUSION The time performance of exact string pattern matching can be greatly improved if an efficient algorithm is used. Considering the growing amount of text handled in the electronic patient record, it is worth implementing this efficient algorithm.
Data-Driven Grasp Synthesis—A Survey

We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps. We divide the approaches into three groups based on whether they synthesize grasps for known, familiar, or unknown objects. This structure allows us to identify common object representations and perceptual processes that facilitate the employed data-driven grasp synthesis technique. In the case of known objects, we concentrate on the approaches that are based on object recognition and pose estimation. In the case of familiar objects, the techniques use some form of a similarity matching to a set of previously encountered objects. Finally, for the approaches dealing with unknown objects, the core part is the extraction of specific features that are indicative of good grasps. Our survey provides an overview of the different methodologies and discusses open problems in the area of robot grasping. We also draw a parallel to the classical approaches that rely on analytic formulations.
An arbitrary waveform generator for SAR test-bench application

Function and performance simulation is an effective method for the development and verification of modern radar modes. Gathering radar raw data during flight trials is an essential but expensive way. In order to minimize such costs, synthetic radar raw data at an early system design stage is adopted widely. In this paper, an arbitrary waveform generator for synthetic aperture radar (SAR) test-bench application is presented. This waveform generator uses high speed multi-DSPs to accelerate the processing to obtain a near real-time baseband echo signal of SAR, and a DDS based frequency synthesizer is used to shift the signal to the operating band. By this way, a lot of system parameters and different target features is simulated and verified. Some result waveforms gained with data created for certain test scenarios by this generator are presented.
(3, L) quasi-cyclic LDPC codes: Simplified exhaustive search and designs

There exist lots of (3, L)-regular quasi-cyclic (QC) LDPC codes constructed from finite fields, protographs, array codes, and computer search under some design rules. For a given code length and rate, how to select the best one from these codes is considerable. In this paper, we study (3, L)-regular QC LDPC codes from the perspective of graph isomorphism, and non-isomorphic (3, L)-regular QC LDPC codes are determined. By analyzing the cycle structures of the resulting non-isomorphic codes, an efficient algorithm for counting cycles is presented. Also proposed is a simplified exhaustive search of non-isomorphic (3, L)-regular QC LDPC codes free of cycles of length less than g0, where g0 is the estimated optimal girth value for a given code length. Based on these two algorithms, we can easily construct a (3, L)-regular QC LDPC code with optimized cycle distribution for a given L and code length. Numerical results show that the constructed codes have better performance under the iterative decoding algorithms.
How Age and Linguistic Competence Affect Memory for Heard Information

The short-term memory performance of a group of younger adults, for whom English was a second language (young EL2 listeners), was compared to that of younger and older adults for whom English was their first language (EL1 listeners). To-be-remembered words were presented in noise and in quiet. When presented in noise, the listening situation was adjusted to ensure that the likelihood of recognizing the individual words was comparable for all groups. Previous studies which used the same paradigm found memory performance of older EL1 adults on this paired-associate task to be poorer than that of their younger EL1 counterparts both in quiet and in a background of babble. The purpose of the present study was to investigate whether the less well-established semantic and linguistic skills of EL2 listeners would also lead to memory deficits even after equating for word recognition as was done for the younger and older EL1 listeners. No significant differences in memory performance were found between young EL1 and EL2 listeners after equating for word recognition, indicating that the EL2 listeners' poorer semantic and linguistic skills had little effect on their ability to memorize and recall paired associates. This result is consistent with the hypothesis that age-related declines in memory are primarily due to age-related declines in higher-order processes supporting stream segregation and episodic memory. Such declines are likely to increase the load on higher-order (possibly limited) cognitive processes supporting memory. The problems that these results pose for the comprehension of spoken language in these three groups are discussed.
The moral glocalization of sport: Local meanings of football in Chota Valley, Ecuador

Studies of the glocalization of sport usually focus on ‘aesthetic glocalization’ (how local actors adopt a global sport and create a new hybrid aesthetic). This has led some critics to dismiss glocalization as a superficial ‘façade’ of diversity hiding global homogeneity. This paper challenges this view by looking at the ‘moral glocalization’ of sport and at the ways local actors give global sports local moral meanings. Drawing on interviews with Afro-descendants from Chota valley, Ecuador, it shows that in this peripheral community football is seen as: (1) a morally safe emotional outlet; (2) a moral education; (3) a source of national ‘communitas’; (4) racial pride; (5) a space for local moral heroes; and (6) a gateway to communal progress. In conclusion, local actors give global football deep moral meaning when they can associate it to local conceptions of the sacred.
Randomized controlled trial of the A.P. Advance, McGrath, and Macintosh laryngoscopes in normal and difficult intubation scenarios: a manikin study.

BACKGROUND Several videolaryngoscopes are available which may facilitate tracheal intubation in difficult airways. We compared the McGrath(®) Series 5 and the Venner™ A.P. Advance™ (APA) videolaryngoscopes with a Macintosh laryngoscope by studying the performance of experienced anaesthetists using manikins in normal and difficult airway scenarios. METHODS We recruited 48 anaesthetists into a randomized trial. Each performed tracheal intubation with each laryngoscope in one easy and one difficult laryngoscopy scenario. The primary endpoint was time to intubation. Other endpoints were time to best glottic visualization, grade of view, and number of glottic advances. RESULTS There were no dropouts. In the easy scenario, the time to intubation was greater using the McGrath [median time 40.7 s, inter-quartile range (IQR) 31.0, 57.4, P<0.001] than the other devices. In the difficult scenario, the time to intubation using the APA with Difficult Airway Blade (DAB) was less (median time 23.2 s, IQR 19.8, 29.0, P<0.001) than the other devices. Time to glottic visualization was reduced using the McGrath and the APA with DAB. Glottic advances were fewer using the APA with DAB. CONCLUSIONS Experienced anaesthetists required a longer time for intubation in a standard manikin using a McGrath compared with other laryngoscopes, but a shorter time for intubation in a difficult manikin using an APA with DAB, and with fewer glottic advances, compared with other laryngoscopes.
A Bayesian Approach to the Analysis of Microarray Datasets using Variational Inference

Background: We present a variational Bayesian approach to inference in a probabilistic model for microarray gene expression data. The algorithmic approach efficiently maximises the probability of the model given the data and provides an unbiased indication of the most probable number of processes or soft clusters in the data. Compared to hierarchical cluster analysis, the method has a number of practical advantages such as an objective assessment of the number of soft clusters in the data, the ability to handle missing values and the ability to provide a confidence measure for process membership. Results: We describe the method and its implementation. We compare the method to a previous variational graphical model, proposed by the authors, and argue that model selection is improved. As examples, we apply the algorithm to microarray datasets for breast cancer, prostate cancer and leukemia. The most detailed application is to breast cancer with a comparative study across 7 microarray datasets. We particularly focus on one subtype indicated by the method (the basaloid subtype) where it delineates a common genetic signature across all these datasets and it suggests a therapeutic target.
Improvements in Factor Analysis Based Speaker Verification

We present the results of speaker verification experiments conducted on the NIST 2005 evaluation data using a factor analysis of speaker and session variability in 6 telephone speech corpora distributed by the Linguistic Data Consortium. We demonstrate the effectiveness of zt-norm score normalization and a new decision criterion for speaker recognition which can handle large numbers of t-norm speakers and large numbers of speaker factors at little computational cost. The best result we obtained was a detection cost of 0.016 on the core condition (all trials) of the evaluation
Analysis of the Volvo IT Incident and Problem Handling Processes using Process Mining and Social Network Analysis

Volvo IT Belgium has provided real-life datasets for the need of the Third International Business Process Intelligence Challenge, in the form of event logs generated by the VINST system used across the Volvo corporation to support incident and problem handling. Volvo has also pointed 4 aspects of their business operations they would like to be scrutinized. 1) Are the incidents contained within the 1st support line? 2) Is bouncing delegation, a.k. a. ping-pong, a frequent phenomenon? 3) Are employees cheating on VINST by faking inexistent waits from endusers? 4) Are real process instances conform with the process model proposed by Volvo IT? In this paper, we provide answers to all these questions using process mining and social network analysis techniques, and we state the existence of hidden support lines degrading the overall performance of incident handling, little localized ping-pong behavior and wait-user misuse, and various levels of conformity across organizations.
Robot-aided rehabilitation task design for inner shoulder muscles

In this paper, we propose a simultaneous design method of motion and external force trajectories for shoulder inner muscles in the robot-aided rehabilitation system, based on a biomechanical analysis of patient's body. The rehabilitation efficiency evaluation function was maximized by Genetic Algorithm (GA), where the structure of spline curves parameters are pre-defined, and the structural parameters are explored to design smooth rehabilitation motion and external force trajectories.