Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning first-order rules from data with multiple parts: applications on mining chemical compound data

Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorly when compared to the propositional approach. Moreover, in order to choose the appropiate candidates, all Inductive Logic Programming (ILP) systems only use quantitive information, e.g. number of examples covered and length of rules, which is insufficient for search space having many similar candidates. This paper introduces a novel approach to improve ILP by incorporating the qualitative information into the search heuristics by focusing only on a kind of data where one instance consists of several parts, as well as relations among parts. This approach aims to find the hypothesis describing each class by using both individual and relational characteristics of parts of examples. This kind of data can be found in various domains, especially in representing chemical compound structure. Each compound is composed of atoms as parts, and bonds as relations between two atoms. We apply the proposed approach for discovering rules describing the activity of compounds from their structures from two real-world datasets: mutagenicity in nitroaromatic compounds and dopamine antagonist compounds. The results were compared to the existing method using ten-fold cross validation, and we found that the proposed method significantly produced more accurate results in prediction.
A new approach for second‐order perturbation theory

A new second‐order perturbation theory (MP2) approach is presented for closed shell energy evaluations. The new algorithm has a significantly lower memory footprint, a lower FLOP (floating point operations) count, and a lower time to solution compared to previously implemented parallel MP2 methods in the GAMESS software package. Additionally, this algorithm features an adaptive approach for the disk/distributed memory storage of the MP2 amplitudes. The algorithm works well on a single workstation, small cluster, and large Cray cluster, and it allows one to perform large calculations with thousands of basis functions in a matter of hours on a single workstation. The same algorithm has been adapted for graphical processing unit (GPU) architecture. The performance of the new GPU algorithm is also discussed. © 2016 Wiley Periodicals, Inc.
Increased cyclin D1 expression can mediate BRAF inhibitor resistance in BRAF V600E–mutated melanomas

Recent studies have shown that there is a considerable heterogeneity in the response of melanoma cell lines to MEK and BRAF inhibitors. In the current study, we address whether dysregulation of cyclin-dependent kinase 4 (CDK4) and/or cyclin D1 contribute to the BRAF inhibitor resistance of melanoma cells. Mutational screening identified a panel of melanoma cell lines that harbored both a BRAF V600E mutation and a CDK4 mutation: K22Q (1205Lu), R24C (WM39, WM46, and SK-Mel-28), and R24L (WM902B). Pharmacologic studies showed that the presence of a CDK4 mutation did not alter the sensitivity of these cell lines to the BRAF inhibitor. The only cell line with significant BRAF inhibitor resistance was found to harbor both a CDK4 mutation and a CCND1 amplification. Array comparative genomic hybridization analysis showed that CCND1 was amplified in 17% of BRAF V600E–mutated human metastatic melanoma samples, indicating the clinical relevance of this finding. As the levels of CCND1 amplification in cell lines are lower than those seen in clinical specimens, we overexpressed cyclin D1 alone and in the presence of CDK4 in a drug-sensitive melanoma line. Cyclin D1 overexpression alone increased resistance and this was enhanced when cyclin D1 and CDK4 were concurrently overexpressed. In conclusion, increased levels of cyclin D1, resulting from genomic amplification, may contribute to the BRAF inhibitor resistance of BRAF V600E–mutated melanomas, particularly when found in the context of a CDK4 mutation/overexpression. [Mol Cancer Ther 2008;7(9):2876–83]
Optimizing bottle-neck features for lvcsr

This work continues in development of the recently proposed bottle-neck features for ASR. A five-layers MLP used in bottleneck feature extraction allows to obtain arbitrary feature size without dimensionality reduction by transforms, independently on the MLP training targets. The MLP topology - number and sizes of layers, suitable training targets, the impact of output feature transforms, the need of delta features, and the dimensionality of the final feature vector are studied with respect to the best ASR result. Optimized features are employed in three LVCSR tasks: Arabic broadcast news, English conversational telephone speech and English meetings. Improvements over standard cepstral features and probabilistic MLP features are shown for different tasks and different neural net input representations. A significant improvement is observed when phoneme MLP training targets are replaced by phoneme states and when delta features are added.
Corpus-Driven Contextualized Categorization

Ontologies strive to offer a interconnected, hierarchical systems of categories to guide our actions in a complex world. But the boundaries of these categories are highly context-dependent, and what constitutes a prototypical category member in one context may be atypical or unrepresentative in another. In this paper we outline a dynamic, trainable, bottom-up view of category structure based on context-sensitive corpus analysis. By learning from corpora about how people creatively actually use categories in different contexts, we can train our ontologies to creatively adapt themselves to these
Loss of Hippocampal Neurons after Kainate Treatment Correlates with Behavioral Deficits

Treating rats with kainic acid induces status epilepticus (SE) and leads to the development of behavioral deficits and spontaneous recurrent seizures later in life. However, in a subset of rats, kainic acid treatment does not induce overt behaviorally obvious acute SE. The goal of this study was to compare the neuroanatomical and behavioral changes induced by kainate in rats that developed convulsive SE to those who did not. Adult male Wistar rats were treated with kainic acid and tested behaviorally 5 months later. Rats that had experienced convulsive SE showed impaired performance on the spatial water maze and passive avoidance tasks, and on the context and tone retention tests following fear conditioning. In addition, they exhibited less anxiety-like behaviors than controls on the open-field and elevated plus-maze tests. Histologically, convulsive SE was associated with marked neuron loss in the hippocampal CA3 and CA1 fields, and in the dentate hilus. Rats that had not experienced convulsive SE after kainate treatment showed less severe, but significant impairments on the spatial water maze and passive avoidance tasks. These rats had fewer neurons than control rats in the dentate hilus, but not in the hippocampal CA3 and CA1 fields. Correlational analyses revealed significant relationships between spatial memory indices of rats and neuronal numbers in the dentate hilus and CA3 pyramidal field. These results show that a part of the animals that do not display intense behavioral seizures (convulsive SE) immediately after an epileptogenic treatment, later in life, they may still have noticeable structural and functional changes in the brain.
Lipopolysaccharide (LPS) induced activation of the immune system in control rats and rats chronically exposed to a low level of the organothiophosphate insecticide, acephate

Lipopolysaccharide (LPS), a key inflammatory component of gram-negative bacteria, induces a distinctive pattern of cytokine release that regulates inflammation. An alteration in the LPS response may play a fundamental role in the pathogenesis of a number of inflammatory diseases. Therefore, this study was conducted to determine whether chronic exposure to a low level of acephate (Ace), a commonly used organophosphate insecticide, impaired the LPS response in rats. This study showed that LPS injection in control rats caused (1) a time-dependent increase in blood lymphocyte enumeration and differentiation, and (2) a sequential increase the pro-inflammatory (interleukin-1b (IL1b), tumor necrosis factor-a (TNFa), interferon-g (INTg), and inducible nitric oxide synthase (iNOS)) and anti-inflammatory (interleukin-4 (IL-4), corticotropin-releasing factor (CRF), and blood corticosterone (Cort)) cytokines. The pro-inflammatory cytokines increased after 30 min, while the anti-inflammatory cytokines increased 3 h after LPS injection. An increase in proinflammatory cytokines increased lymphocyte enumeration and differentiation, while the increase in anti-inflammatory cytokines re-established homeostasis. In comparison to the control rats, the Ace-exposed rats exhibited (1) lower levels of IL1b, TNFa and iNOS, (2) higher levels of CRF and Cort, and (3) lower levels of IL-4 in blood and/or brain samples. The abnormal cytokine production may be associated with abnormal phenotypic distribution of B and T cells. Blood IgMhiIgDhi, IgMloIgDlo and CD8+ CD45RA −CCR7+ cells were elevated, while IgMloIgDhi, IgMhiIgDlo, IgMinIgDlo, CD8+ CD45RA +CCR7+ and CD8+ CD45RA− CCR7+ cells were depressed in Ace-exposed rats. Thus, chronic low-level Ace exposure may impair the lineage commitment in lymphocytes, possibly by altering cytokine signaling in the brain.
Clustering moodle data as a tool for profiling students

This paper describes the first step of a research project with the aim of predicting students' performance during an online curriculum on a LMS and keeping them from falling behind. Our research project aims to use data mining, machine learning and artificial intelligence methods for monitoring students in e-learning trainings. This project takes the shape of a partnership between computer science / artificial intelligence researchers and an IT firm specialized in e-learning software. We wish to create a system that will gather and process all data related to a particular e-learning course. To make monitoring easier, we will provide reliable statistics, behaviour groups and predicted results as a basis for an intelligent virtual tutor using the mentioned methods. This system will be described in this article. In this step of the project, we are clustering students by mining Moodle log data. A first objective is to define relevant clustering features. We will describe and evaluate our proposal. A second objective is to determine if our students show different learning behaviours. We will experiment whether there is an overall ideal number of clusters and whether the clusters show mostly qualitative or quantitative differences. Experiments in clustering were carried out using real data obtained from various courses dispensed by a partner institute using a Moodle platform. We have compared several classic clustering algorithms on several group of students using our defined features and analysed the meaning of the clusters they produced.
Out-of-order processing: a new architecture for high-performance stream systems

Many stream-processing systems enforce an order on data streams during query evaluation to help unblock blocking operators and purge state from stateful operators. Such in-order processing (IOP) systems not only must enforce order on input streams, but also require that query operators preserve order. This order-preserving requirement constrains the implementation of stream systems and incurs significant performance penalties, particularly for memory consumption. Especially for high-performance, potentially distributed stream systems, the cost of enforcing order can be prohibitive. We introduce a new architecture for stream systems, out-of-order processing (OOP), that avoids ordering constraints. The OOP architecture frees stream systems from the burden of order maintenance by using explicit stream progress indicators, such as punctuation or heartbeats, to unblock and purge operators. We describe the implementation of OOP stream systems and discuss the benefits of this architecture in depth. For example, the OOP approach has proven useful for smoothing workload bursts caused by expensive end-of-window operations, which can overwhelm internal communication paths in IOP approaches. We have implemented OOP in two stream systems, Gigascope and NiagaraST. Our experimental study shows that the OOP approach can significantly outperform IOP in a number of aspects, including memory, throughput and latency.
Baroreflex Buffering of Sympathetic Activation During Sleep: Evidence From Autonomic Assessment of Sleep Macroarchitecture and Microarchitecture

Abstract—We examined the effects of sleep microstructure, ie, the cyclic alternating pattern (CAP), on heart rate (HR)- and blood pressure (BP)-regulating mechanisms and on baroreflex control of HR in healthy humans and tested the hypothesis that sympathetic activation occurring in CAP epochs during non-rapid eye movement (non-REM) sleep periods is buffered by the arterial baroreflex. Ten healthy males underwent polysomnography and simultaneous recording of BP, ECG, and respiration. Baroreflex sensitivity (BRS) was calculated by the sequences method. Autoregressive power spectral analysis was used to investigate R-R interval (RRI) and BP variabilities. During overall non-REM sleep, BP decreased and RRI increased in comparison to wakefulness, with concomitant decreases in low-frequency RRI and BP oscillations and increases in high-frequency RRI oscillations. These changes were reversed during REM to wakefulness levels, with the exception of RRI. During CAP, BP increased significantly in comparison to non-CAP and did not differ from REM and wakefulness. The low-frequency component of BP variability was significantly higher during CAP than non-CAP. RRI and its low-frequency spectral component did not differ between CAP and non-CAP. BRS significantly increased during CAP in comparison to non-CAP. BRS was not different during CAP and REM and was greater during both in comparison with the awake state. Even during sleep stages, like non-REM sleep, characterized by an overall vagal predominance, phases of sustained sympathetic activation do occur that resemble that occurring during REM. Throughout the overnight sleep period, the arterial baroreflex acts to buffer surges of sympathetic activation by means of rapid changes in cardiac vagal circuits.
Effect of an Epidermal Growth Factor Receptor Inhibitor in Mouse Models of Lung Cancer

Gefitinib (Iressa, ZD1839) is a potent high-affinity competitive tyrosine kinase inhibitor aimed primarily at epidermal growth factor receptor (EGFR). Inhibitors in this class have recently been approved for clinical use in the treatment of advanced non–small cell lung cancer as monotherapy following failure of chemotherapy. We examined the efficacy of gefitinib on lung tumorigenesis in mouse models using both postinitiation and progression protocols. Gefitinib was given at a dose of 200 mg/kg body weight (i.g.) beginning either 2 or 12 weeks following carcinogen initiation. In the postinitiation protocol, gefitinib significantly inhibited both tumor multiplicity (∼70%) and tumor load (∼90%) in A/J or p53-mutant mice (P < 0.0001). Interestingly, gefitinib was also highly effective against lung carcinogenesis in the progression protocol when individual animals already have multiple preinvasive lesions in the lung. Gefitinib exhibited ∼60% inhibition of tumor multiplicity and ∼80% inhibition of tumor load when compared with control mice (both P < 0.0001). These data show that gefitinib is a potent chemopreventive agent in both wild-type and p53-mutant mice and that a delayed administration was still highly effective. Analyses of mutations in the EGFR and K-ras genes in lung tumors from either control or treatment groups showed no mutations in EGFR and consistent mutation in K-ras. Using an oligonucleotide array on control and gefitinib-treated lesions showed that gefitinib treatment failed to alter the activity or the expression level of EGFR. In contrast, gefitinib treatment significantly altered the expression of a series of genes involved in cell cycle, cell proliferation, cell transformation, angiogenesis, DNA synthesis, cell migration, immune responses, and apoptosis. Thus, gefitinib showed highly promising chemopreventive and chemotherapeutic activity in this mouse model of lung carcinogenesis. (Mol Cancer Res 2006;4(12):971–81)
Adaptive Cooperative Output Regulation for a Class of Nonlinear Multi-Agent Systems

In this technical note, an adaptive cooperative output regulation problem for a class of nonlinear multi-agent systems is considered. The cooperative output regulation problem is first converted into an adaptive stabilization problem for an augmented multi-agent system. A distributed adaptive control law with adoption of Nussbaum gain technique is then proposed to globally stabilize this augmented system. This control scheme is designed such that, in the presence of unknown control direction and large parameter variations in each agent, the closed-loop system maintains global stability and the output of each agent tracks a class of prescribed signals asymptotically.
Failure of a Carbon Fiber Implant: A Case Report

Study Design. Case report. Objectives. Failure of a carbon fiber implant. Summary of Background Data. To simplify the procedure of posterior lumbar interbody fusion, a carbonfiber‐reinforced polymer implant has been developed. The implant has ridges to resist retropulsion, struts to support weight, and a hollow area to allow packing of autologous bone graft. So far, no complications have been reported from the use of carbon implant as a fusion aid in spine surgery. Methods. A patient with postoperative infection has been followed with computed tomography images and histologic examination from a reoperation. Results. An entire nonunion across the width of the disc space and a clearly broken cage was visualized with computed tomography. The spinal canal was explored during a reoperation and the tissue surrounding the dura and nerves were all black. Microscopic examination showed a large quantity of carbon particulate debris. The authors have operated on approximately 100 patients so far and no other carbon cage has broken, to their knowledge. Conclusions. Carbon cages can break if a nonunion occurs and as a result free carbon particles move out to the spinal canal.
The influence of environmental and body-based action constraints on distance judgments

To determine action capabilities, an actor must take into account environmental features and the actor’s individual body and capabilities. Previous research has shown that changing an actor’s ability to reach by changing the body influences judgments of distance to reachable objects. The current studies tested whether both environmental and body constraints that limit reaching would influence judged distances to reachable objects. In Experiment 1, participants estimated distances to a small object when it was both in front of and behind a clear, reach-limiting Plexiglas barrier. Participants estimated their ability to reach the object (yes or no response), and then visually matched the distance from the edge of the table to the object with a tape measure. Participants judged the distance to the object as farther when the object was behind the barrier than when it was in front of the barrier; the barrier also reduced estimates of reach ability. In Experiment 2 participants estimated distances in front of and behind a barrier while their dominant or non-dominant hand was weighted, a body constraint on action. Distances within reachable space were judged to be significantly farther than the other conditions when the target was behind the barrier and the dominant (reaching) hand was weighted. This study suggests that action-relevant environmental constraints do influence judgment of distances and interact with body-based
The Ins and Outs of Dutch noun countability classification

This paper presents a range of methods for classifying Dutch noun countability based on either Dutch or English data. The classification is founded on translational equivalences and the corpus analysis of linguistic features which correlate with particular countability classes. We show that crosslingual classification on the basis of word-to-word or featureto-feature mappings between English and Dutch performs at least as well as in-language classification based on gold-standard Dutch countability data.
A discourse coding scheme for conversational Spanish

This paper describes a 3-level manual discourse coding scheme that we have devised for manual tagging of the CallHome Spanish (CHS) and CallFriend Spanish (CFS) databases used in the CLARITY project. The goal of CLARITY is to explore the use of discourse structure in understanding conversational sp eech. The project combines empirical methods for dialogue processing with state-of-the art LVCSR (using the JANUS recognizer). The three levels of the coding scheme are (1) a speech act level consisting of a tag set extended from DAMSL and Switchboard; (2) dialogue game level defined by initiative and intention; and (3) an act ivity level defined within topic units. The manually tagged dialog ues are used to train automatic classifiers. We present preliminary results for statement categorization, and give an in-progress repo rt of automatic speech act classification and topic boundary identific ation.
Mental Representation of Logical Connectives

Logical connectives, such as “AND”, “OR”, “IF… THEN”, and “IF AND ONLY IF” are ubiquitous in both language and cognition; however, reasoning with logical connectives is error–prone. We argue that some of these errors may stem from people's tendency to minimize the number of possibilities compatible with logical connectives and to construct a “minimalist” one–possibility representation. As a result, connectives denoting a single possibility (e.g., conjunctions) are likely to be represented correctly, whereas connectives denoting multiple possibilities (e.g., disjunctions or conditionals) are likely to be erroneously represented as conjunctions. These predictions were tested and confirmed in three experiments using different paradigms. In Experiment 1, participants were presented with a multiple–choice task and asked to select all and only those possibilities that would indicate that compound verbal propositions were true versus false. In Experiment 2, a somewhat similar task was used, except that participants were asked later to perform a cued recall of verbal propositions. Finally, Experiment 3 used an old/new recognition paradigm to examine participants’ ability to accurately recognize different logical connectives. The results of the three experiments are discussed in relation to theories of representation of possibilities and theories of reasoning.