Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Language Models and Information Retrieval: Natural Language Processing Really Meets Retrieval

Traditionally, natural language processing techniques for information retrieval have always been studied outside the framework of formal models of information retrieval. In this article, we introduce a new formal model of information retrieval based on the application of statistical language models. Simple natural language processing techniques that are often used for information retrieval ± we give an introductory overview of these techniques in Section 2 ± can be modeled by the new language modeling approach.
Mating Type Gene Homologues and Putative Sex Pheromone-Sensing Pathway in Arbuscular Mycorrhizal Fungi, a Presumably Asexual Plant Root Symbiont

The fungal kingdom displays a fascinating diversity of sex-determination systems. Recent advances in genomics provide insights into the molecular mechanisms of sex, mating type determination, and evolution of sexual reproduction in many fungal species in both ancient and modern phylogenetic lineages. All major fungal groups have evolved sexual differentiation and recombination pathways. However, sexuality is unknown in arbuscular mycorrhizal fungi (AMF) of the phylum Glomeromycota, an ecologically vital group of obligate plant root symbionts. AMF are commonly considered an ancient asexual lineage dating back to the Ordovician, approximately 460 M years ago. In this study, we used genomic and transcriptomic surveys of several AMF species to demonstrate the presence of conserved putative sex pheromone-sensing mitogen-activated protein (MAP) kinases, comparable to those described in Ascomycota and Basidiomycota. We also find genes for high mobility group (HMG) transcription factors, homologous to SexM and SexP genes in the Mucorales. The SexM genes show a remarkable sequence diversity among multiple copies in the genome, while only a single SexP sequence was detected in some isolates of Rhizophagus irregularis. In the Mucorales and Microsporidia, the sexM gene is flanked by genes for a triosephosphate transporter (TPT) and a RNA helicase, but we find no evidence for synteny in the vicinity of the Sex locus in AMF. Nonetheless, our results, together with previous observations on meiotic machinery, suggest that AMF could undergo a complete sexual reproduction cycle.
Why Global Performance is a Poor Metric for Verifying Convergence of Multi-agent Learning

Experimental verification has been the method of choice for verifying the stability of a multi-agent reinforcement learning (MARL) algorithm as the number of agents grows and theoretical analysis becomes prohibitively complex. For cooperative agents, where the ultimate goal is to optimize some global metric, the stability is usually verified by observing the evolution of the global performance metric over time. If the global metric improves and eventually stabilizes, it is considered a reasonable verification of the system’s stability. The main contribution of this note is establishing the need for better experimental frameworks and measures to assess the stability of large-scale adaptive cooperative systems. We show an experimental case study where the stability of the global performance metric can be rather deceiving, hiding an underlying instability in the system that later leads to a significant drop in performance. We then propose an alternative metric that relies on agents’ local policies and show, experimentally, that our proposed metric is more effective (than the traditional global performance metric) in exposing the instability of MARL algorithms.
Sample Size Planning for the Squared Multiple Correlation Coefficient: Accuracy in Parameter Estimation via Narrow Confidence Intervals

Methods of sample size planning are developed from the accuracy in parameter approach in the multiple regression context in order to obtain a sufficiently narrow confidence interval for the population squared multiple correlation coefficient when regressors are random. Approximate and exact methods are developed that provide necessary sample size so that the expected width of the confidence interval will be sufficiently narrow. Modifications of these methods are then developed so that necessary sample size will lead to sufficiently narrow confidence intervals with no less than some desired degree of assurance. Computer routines have been developed and are included within the MBESS R package so that the methods discussed in the article can be implemented. The methods and computer routines are demonstrated using an empirical example linking innovation in the health services industry with previous innovation, personality factors, and group climate characteristics.
Status Characteristics and Ability Attributions in Hungarian School Classes

We study how the status characteristics gender and ethnicity affect the abilities that adolescents attribute to each other in the Hungarian school context. For this, we derive predictions from status characteristics theory that we test by applying exponential random graph models to data collected among students in 27 school classes. By that, we contribute to the few existing studies of status characteristics in a school context, and we propose a novel approach to handle structural dependencies between individual ability attributions. Our results suggest that across classes, gender does not consistently affect ability attributions, while ethnicity does affect ability attributions. Roma students are on average perceived as less able than their Hungarian peers, even after controlling for the structural embeddedness of these perceptions.
Population of a Knowledge Base for News Metadata from Unstructured Text and Web Data

We present a practical use case of knowledge base (KB) population at the French news agency AFP. The target KB instances are entities relevant for news production and content enrichment. In order to acquire uniquely identified entities over news wires, i.e. textual data, and integrate the resulting KB in the Linked Data framework, a series of data models need to be aligned: Web data resources are harvested for creating a wide coverage entity database, which is in turn used to link entities to their mentions in French news wires. Finally, the extracted entities are selected for instantiation in the target KB. We describe our methodology along with the resources created and used for the target KB population.
The effect of protein degradation on cellular growth characteristics

The role of protein degradation in cellular proliferation was investigated by measurements of the rates of degradation of labile and stable proteins for a number of cell types under various growth conditions. The rate of protein degradation was found to be a relatively invariant parameter in that it did not change after strong inhibition of protein synthesis with cycloheximide or histidinol, it was the same in both exponential and stationary phase, and it did not correlate with the presence or absence of malignant tranformation.
Improving Part-of-speech Tagging for Context-free Parsing

In this paper, we propose a factored parsing model consisting of a lexical and a constituent model. The discriminative lexical model allows the parser to utilize rich contextual features beyond those encoded in the context-free grammar (CFG) in use. Experiment results reveal that our parser achieves statistically significant improvement in both parsing and tagging accuracy on both English and Chinese.
Giving interaction a hand: deep models of co-speech gesture in multimodal systems

Humans frequently join words and gestures for multimodal communication. Such natural co-speech gesturing goes far beyond what can be currently processed by gesture-based interfaces and especially its coordination with speech still poses open challenges for basic research and multimodal interfaces alike. How can we develop computational models for processing and generating natural speech-gesture behavior, in a flexible, fast and adaptive manner similar to humans? In this talk I will review approaches and methods applied to this problem and I will argue that such models need to (and can) based on a deeper understanding of what shapes co-speech gesturing in a particular situation. I will present work that connects empirical analyses with computational modeling and evaluation to unravel the cognitive, embodied and socio-interactional mechanisms underlying the use of speech- accompanying gestural behavior, and to develop deeper models of these mechanisms for interactive systems such as virtual characters, humanoid robots, or multimodal interfaces.
Splitting methods and primal-dual formulations for higher order imaging models

We present an alternating direction implicit method solving numerically the TV-H 1 ow which shows good performance when applied to various imaging problems. Some stability issues depending on the regularization of the total variation may appear, thus explicit terms need to be controlled. A primal-dual approach and its possible applications to such problems is presented as well.
Testing the comparative effectiveness of three procedures aimed at facilitating newcomer orientation

ii List of Tables . iv List of Illustrations . v Introduction . 1 Hypothesis Development . 4 Method . 18 Participants . 18 Procedure . 21 Measures . 27 Results . 33 Discussion . 37 Limitations . 42 Implications for future practice . 43 References . 46 Appendix 1 . 59
Thalamotemporal impairment in temporal lobe epilepsy: A combined MRI analysis of structure, integrity, and connectivity

Thalamic abnormality in temporal lobe epilepsy (TLE) is well known from imaging studies, but evidence is lacking regarding connectivity profiles of the thalamus and their involvement in the disease process. We used a novel multisequence magnetic resonance imaging (MRI) protocol to elucidate the relationship between mesial temporal and thalamic pathology in TLE.
Technicolor/INRIA/Imperial College London at the MediaEval 2012 Violent Scene Detection Task

The MediaEval 2012 A ect Task is the continuation of the MediaEval 2011 A ect Task and aims at detecting violence in movies. This paper presents the work done in Technicolor, INRIA and Imperial College London as a response to the task. Four different systems combining audio and visual features are presented along with a fusion of three of them. Results are reported on the test data and compared with last year's results.
Solid-state Culled Discrete Element Granular Systems

Dry granular materials are common in computer animations, such as when a character drags a ﬁnger through sand or grabs a handful of wheat. However, simulating hundreds of thousands to millions of interacting partic-ulates can take several minutes per frame or longer. More efﬁcient granular material algorithms compromise visual accuracy due to granules’ complex behavior and detail. To shorten simulation times without sacriﬁcing visual ﬁdelity, we simulate individual granules close to the material’s surface and use implicit surfaces and constructive solid geometry boolean functions to cull away solid-state granules beneath the surface and only replace them where the simulation requires. This surface dynamically updates in response to collisions or exposure from the surface granules. Our technique selectively removes the majority of granules for signiﬁcant speedups, while staying ﬂexible enough to cull out and repopulate granules to respond to multiple external forces. Categories and Subject Descriptors (according to ACM CCS) : I.6. 8 [Simulation and Modeling]: Types of Simulation—Discrete event
GenPerm: A Unified Method for Detecting Non-Overlapping and Overlapping Communities

Detection of non-overlapping and overlapping communities are essentially the same problem. However, current algorithms focus either on finding overlapping or non-overlapping communities. We present a generalized framework that can identify both non-overlapping and overlapping communities, without any prior input about the network or its community distribution. To do so, we introduce a vertex-based metric, GenPerm, that quantifies by how much a vertex belongs to each of its constituent communities. Our community detection algorithm is based on maximizing the GenPerm over all the vertices in the network. We demonstrate, through experiments over synthetic and real-world networks, that GenPerm is more effective than other metrics in evaluating community structure. Further, we show that due to its vertex-centric property, GenPerm can be used to unfold several inferences beyond community detection, such as core-periphery analysis and message spreading. Our algorithm for maximizing GenPerm outperforms six state-of-the-art algorithms in accurately predicting the ground-truth labels. Finally, we discuss the problem of resolution limit in overlapping communities and demonstrate that maximizing GenPerm can mitigate this problem.
Variability comparison of simultaneous brain near-infrared spectroscopy (NIRS) and functional MRI (fMRI) during visual stimulation

Brain near-infrared spectroscopy (NIRS) is emerging as a potential alternative to functional MRI (fMRI). To date, no study has explicitly compared the two techniques in terms of measurement variability, a key parameter dictating attainable statistical power. Here, NIRS and fMRI were simultaneously recorded during event-related visual stimulation. Inter-subject coefficients of variation (CVs) for peak response amplitude were considerably larger for NIRS than fMRI, but inter-subject CVs for response latency and intra-subject CVs for response amplitude were overall comparable. Our results may represent an optimistic estimate of the CVs of NIRS measurements, as optode positioning was guided by structural MRI, which is normally unavailable. We conclude that fMRI may be preferable to NIRS for group comparisons, but NIRS is equally powerful when comparing conditions within participants. The discrepancy between inter- and intra-subject CVs is likely related to variability in head anatomy and tissue properties which may be better accounted for by emerging NIRS technology.
Advanced multiple objects tracking by fusing radar and image sensor data - Application on a case study.

The aim of this paper is to present a multiple object tracking data fusion technique, which fuses radar, image, and ego vehicle odometry. The data are fused at a high level, which leads to reliable and stable tracking results providing also additional features as width estimation and the detection of stationary objects. A ldquorealrdquo application of these algorithms is illustrated on a specific use-case: the SASPENCE system, developed inside the Integrated Project PReVENT. The principle results show that such a data-fusion technique is actually able to improve the SASPENCE performances, especially in terms of extension of operative scenarios, a basic issue for the system functionality.
Peer Mentor Characteristics That Predict Supportive Relationships With First-Year Students: Implications for Peer Mentor Programming and First-Year Student Retention

Peer mentoring programs frequently are implemented on college campuses to enhance first-year college student retention; however, few studies have examined characteristics of peer mentors that are associated with more supportive mentor–mentee relationships, leaving college personnel with a limited understanding of how to improve these vital programs. Accordingly, in this prospective study, we examined whether mentors’ attachment style and self-efficacy to mentor predicted peer mentors’ (n = 76) or mentees’ (n = 999) ratings of mentor-provided support. Results showed that mentor self-efficacy mediated the relation between an avoidant attachment style and mentor-reported support; that is, peer mentors with a more avoidant attachment style reported lower self-efficacy to mentor and, in turn, endorsed providing lower levels of support for mentees. Mentor–mentee contact, however, was the only predictor of mentees’ ratings of mentor support. Future research should aim to extend these preliminary findings so as to inform the selection, training, and supervision of peer mentors in college settings, with the ultimate goal of enhancing first-year student retention.
Climate Extremes, Vegetation Change, and Decoupling of Interactive Fire-Grazing Processes Exacerbate Fly Parasitism of Cattle

Abstract We assessed local horn fly (Haematobia irritans L.) and face fly (Musca autumnalis De Geer) communities on cattle in 2012 and 2013 relative to vegetation and climate data to understand how parasitism of cattle is influenced by change in climate and vegetation structure. We compared heterogeneity management using spatially and temporally discrete fires (i.e., patch-burning one-third of a pasture annually) to homogeneity management (i.e., burning entire pasture in 2012 then no burning in 2013), with cattle grazing all years in both treatments. Predicted emergence of horn flies and face flies was 24 and 34 d earlier in 2012 associated with earlier spring warming, a significant deviation from the five-year mean. Intraannual horn fly dynamics were explained by concurrent high ambient air temperature the day of observations, but face flies were explained by low ambient air temperatures and dry conditions 3 wk before observations. Importance values of information for the theoretic models including fire treatments ranged from 0.89 to 1, indicating that both horn flies and face flies are sensitive to habitat alterations and fire-driven animal movements. Ordination indicates herds on unburned pastures were dissimilar to herds on pastures burned with patchy fires or pastures burned completely and species-specific fly responses to different vegetation structure metrics. For example, horn flies were correlated with vegetation visual obstruction, and face flies were correlated with woody plant cover. Vegetation structure may be as important as climate in driving the dynamics of fly parasites of cattle.
ANGPTL4 promotes the progression of cutaneous melanoma to brain metastasis

In an ongoing effort to identify molecular determinants regulating melanoma brain metastasis, we previously identified Angiopoietin-like 4 (ANGPTL4) as a component of the molecular signature of such metastases. The aim of this study was to determine the functional significance of ANGPTL4 in the shaping of melanoma malignancy phenotype, especially in the establishment of brain metastasis. We confirmed that ANGPTL4 expression is significantly higher in cells metastasizing to the brain than in cells from the cutaneous (local) tumor from the same melanoma in a nude mouse xenograft model, and also in paired clinical specimens of melanoma metastases than in primary melanomas from the same patients. In vitro experiments indicated that brain-derived soluble factors and transforming growth factor β1 (TGFβ1) up-regulated ANGPTL4 expression by melanoma cells. Forced over-expression of ANGPTL4 in cutaneous melanoma cells promoted their ability to adhere and transmigrate brain endothelial cells. Over-expressing ANGPTL4 in cells derived from brain metastases resulted in the opposite effects. In vivo data indicated that forced overexpression of ANGPTL4 promoted the tumorigenicity of cutaneous melanoma cells but did not increase their ability to form brain metastasis. This finding can be explained by inhibitory activities of brain-derived soluble factors. Taken together these findings indicate that ANGPTL4 promotes the malignancy phenotype of primary melanomas of risk to metastasize to the brain.
The perceptions of non music staff and senior management of the impact of the implementation of the Musical Futures approach on the whole school

This research aimed to provide an account of the impact of the Musical Futures approach on the wider school community in Musical Futures ‘Champion Schools’. Questionnaires were completed by 344 non-music teachers. Interviews were undertaken with members of senior management teams. The majority of staff indicated that Musical Futures had had a positive impact on student motivation, well-being, self-esteem and confidence and had encouraged students to work together. There was less agreement that it had improved student concentration, organisation and students’ attitudes towards learning and academic progression. The interviews provided deeper insights into the issues relating to implementation.
Do gap junctions regulate synchrony in the parkinsonian basal ganglia

Patients with Parkinson’s disease (PD) typically suffer severely from different types of symptoms. Motor symptoms, restricting the patients’ ability to perform controlled movements in daily life, are of special clinical interest and have been related to neural activity in the basal ganglia. Low-frequency oscillations, bursting (short periods of high-frequency spiking) and especially synchrony of basal ganglia activity emerge after dopamine depletion that follows cell death in the substantia nigra pars compacta. These changes are all believed to contribute to motor symptoms. In this thesis, we described a possible mechanism for the emergence of synchrony in the basal ganglia of PD patients based on gap junctions in the external part of the globus pallidus (GPe), using a combination of experimental and computational methods. We first describe why we focus on the GPe (Chapter 2), and then seek experimental evidence for the occurrence of gap junctions in GPe (Chapter 3). A computational model of the basal ganglia is used in Chapter 4 to estimate the effect of sparse gap junction coupling between GPe neurons on basal ganglia activity. Finally, in Chapter 5, we study the impact of basal ganglia activity in general on downstream structures. In conclusion, this work introduces a novel theory: contributions of gap junctions to synchrony and potentially motor symptoms of PD patients. It remains to be shown how many of the detected gap junctions are functional and how large their impact on beta oscillations as well as motor symptoms is.
Cardiovascular Magnetic Resonance Imaging in Experimental Models

Cardiovascular magnetic resonance (CMR) imaging is the modality of choice for clinical studies of the heart and vasculature, offering detailed images of both structure and function with high temporal resolution. Small animals are increasingly used for genetic and translational research, in conjunction with models of common pathologies such as myocardial infarction. In all cases, effective methods for characterising a wide range of functional and anatomical parameters are crucial for robust studies. CMR is the gold-standard for the non-invasive examination of these models, although physiological differences, such as rapid heart rate, make this a greater challenge than conventional clinical imaging. However, with the help of specialised magnetic resonance (MR) systems, novel gating strategies and optimised pulse sequences, high-quality images can be obtained in these animals despite their small size. In this review, we provide an overview of the principal CMR techniques for small animals for example cine, angiography and perfusion imaging, which can provide measures such as ejection fraction, vessel anatomy and local blood flow, respectively. In combination with MR contrast agents, regional dysfunction in the heart can also be identified and assessed. We also discuss optimal methods for analysing CMR data, particularly the use of semi-automated tools for parameter measurement to reduce analysis time. Finally, we describe current and emerging methods for imaging the developing heart, aiding characterisation of congenital cardiovascular defects. Advanced small animal CMR now offers an unparalleled range of cardiovascular assessments. Employing these methods should allow new insights into the structural, functional and molecular basis of the cardiovascular system.