Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model

Spectral clustering is a celebrated algorithm that partitions the objects based on pairwise similarity information. While this approach has been successfully applied to a variety of domains, it comes with limitations. The reason is that there are many other applications in which only <italic>multi</italic>way similarity measures are available. This motivates us to explore the multiway measurement setting. In this paper, we develop two algorithms intended for such setting: hypergraph spectral clustering (HSC) and hypergraph spectral clustering with local refinement (HSCLR). Our main contribution lies in performance analysis of the polytime algorithms under a random hypergraph model, which we name the weighted stochastic block model, in which objects and multiway measures are modeled as nodes and weights of hyperedges, respectively. Denoting by <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> the number of nodes, our analysis reveals the following: 1) HSC outputs a partition which is better than a random guess if the sum of edge weights (to be explained later) is <inline-formula><tex-math notation="LaTeX">$\Omega (n)$</tex-math> </inline-formula>; 2) HSC outputs a partition which coincides with the hidden partition except for a vanishing fraction of nodes if the sum of edge weights is <inline-formula><tex-math notation="LaTeX">$\omega (n)$</tex-math> </inline-formula>; and 3) HSCLR exactly recovers the hidden partition if the sum of edge weights is on the order of <inline-formula><tex-math notation="LaTeX">$n \log n$</tex-math></inline-formula>. Our results improve upon the state of the arts recently established under the model and they first settle the orderwise optimal results for the binary edge weight case. Moreover, we show that our results lead to efficient sketching algorithms for subspace clustering, a computer vision application. Finally, we show that HSCLR achieves the information-theoretic limits for a special yet practically relevant model, thereby showing no computational barrier for the case.
Effects of the pharmaceutical contaminants ibuprofen, diclofenac, and carbamazepine alone, and in combination, on oxidative stress parameters in early life stages of tench (Tinca tinca)

In the present study, the effects of sub-lethal sub-chronic doses of ibuprofen, diclofenac, and carbamazepine alone, and in combination (concentration range 0.02–60 μg/l), on the early life stages of tench (Tinca tinca) were investigated. The lower concentrations of pharmaceuticals tested (0.02, 0.2, 2 μg/l) represent the concentration values of these substances commonly present in surface waters or effluents from wastewater treatment plants. Multiple biomarkers of biotransformation, antioxidant defence systems, and lipid peroxidation were determined in fish after 35 days of exposure. The evaluated pharmaceuticals induced oxidative stress in fish both alone and in combination with each other. Generally, 60 μg/l of each single pharmaceutical influenced the activity of antioxidant enzymes significantly (P < 0.05), whereas the same concentration of these pharmaceuticals in combination (1 : 1 : 1) did not have any impact on the activity of these enzymes. However, changes in biotransformation and antioxidant enzymes were apparent if lower concentrations of these pharmaceuticals were administered in the mixture. Significant changes (P < 0.05) in the activities of glutathione reductase, glutathione peroxidase, and glutathione-S-transferase were observed even at environmental concentration ranges. A significant effect (P < 0.05) on lipid peroxidation levels was found only in the experimental group exposed to carbamazepine.
Online study of frequency list vocabulary with the WordChamp website

The intentional study of vocabulary is an effective way for learners to increase their vocabulary in the target language. Word frequency lists help learners determine the most useful words to study. In order to systematically study vocabulary, learners may first take a test to determine their vocabulary knowledge, then drill the appropriate words. However, to date, classroom teachers and researchers have focused on traditional methods of intentional study, i.e., non-computer. The worldwide web offers numerous ways to help students study systematically by providing various vocabulary level tests, word frequency lists, and opportunities for language learners to study frequency word vocabulary intentionally. A preliminary study checked the effectiveness and viability of WordChamp study in Japanese university English Communication courses, then a follow-up study compared the usefulness of WordChamp drilling with paper study of frequency word vocabulary. Finally, the way each method was viewed by learners, evidenced by an attitudinal survey, was noted.
Qualitative Methods for Effective Agrarian Surveys: A Research Note on Focus Groups

Social studies research plays an important role in contributing to our understanding of agricultural sustainability. Often they are empirical in nature. However, little initiative has been taken in noting the critical role of qualitative methods prior to carrying out primary data collection at the farm-level. To fill this gap, this paper provides a research note on qualitative data collection processes as they contribute to the effective survey of social phenomena within agricultural settings. Specifically, our recent experience of focus groups in Malaysia is selected for discussion, since they were found to be useful in the preliminary stages of our social research. The proposed method is particularly helpful in revising hypotheses, assisting questionnaire design, and planning survey operations. Special aspects of each of the five stages of focus groups - (1) focus group design, (2) participant recruitment, (3) implementation, (4) transcribing and analysis, and (5) findings and reporting - are discussed. These procedures should be modified to meet the requirements of specific research topics and contexts. Other than focus groups, future studies should shed light on other qualitative methods.
An offshore Gabon full-waveform inversion case study

AbstractVelocity model building is one of the most difficult aspects of the seismic processing sequence. But it is also one of the most important: an accurate earth model allows an accurate migrated image to be formed, which allows the geologist a better chance at an accurate interpretation of the area. In addition, the velocity model itself can provide complementary information about the geology and geophysics of the region. Full-waveform inversion (FWI) is a popular, high-end velocity model-building tool that can generate high-resolution earth models, especially in regions of the model probed by the transmitted (diving wave) arrivals on the recorded seismic data. The history of the South Gabon Basin is complex, leading to a rich geologic picture today and a very challenging velocity model-building process. We have developed a case study from the offshore Gabon area showing that FWI is able to help with the model-building process, and the resulting velocity model reveals features that improve the migrate.
Static output feedback control for lane change maneuver

This paper addresses the lateral control of a vehicle during lane change maneuvers. The proposed design procedure aims to answer the questions of control using cost-effective sensors implementation, adaptation to measured variables and robustness to unmeasured varying parameters. This is achieved through a static output feedback controller with preview information. The only used measurements are the lateral displacement at sensor location and the yaw angle relative to the lane centerline. The vehicle lateral model is augmented with an integral action, the error signal and the preview reference signal. The controller is synthesized using the LMI framework thanks to a relaxation method that removes the nonlinear terms. Simulations are conducted for various scenarios showing the ability of the design method to handle different performance objectives.
Damage detection in composite materials using lamb wave methods

Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper presents part of an experimental and analytical survey of candidate methods for in situ damage detection of composite materials. Experimental results are presented for the application of Lamb wave techniques to quasi-isotropic graphite/epoxy test specimens containing representative damage modes, including delamination, transverse ply cracks and through-holes. Linear wave scans were performed on narrow laminated specimens and sandwich beams with various cores by monitoring the transmitted waves with piezoceramic sensors. Optimal actuator and sensor configurations were devised through experimentation, and various types of driving signal were explored. These experiments provided a procedure capable of easily and accurately determining the time of flight of a Lamb wave pulse between an actuator and sensor. Lamb wave techniques provide more information about damage presence and severity than previously tested methods (frequency response techniques), and provide the possibility of determining damage location due to their local response nature. These methods may prove suitable for structural health monitoring applications since they travel long distances and can be applied with conformable piezoelectric actuators and sensors that require little power.
Effective Dimension of Exp-concave Optimization

We investigate the role of the effective (a.k.a. statistical) dimension in determining both the statistical and the computational costs associated with exp-concave stochastic minimization. We derive sample complexity bounds that scale with $\frac{d_{\lambda}}{\epsilon}$, where $d_{\lambda}$ is the effective dimension associated with the regularization parameter $\lambda$. These are the first fast rates in this setting that do not exhibit any explicit dependence either on the intrinsic dimension or the $\ell_{2}$-norm of the optimal classifier. We also propose fast preconditioned methods that solve the ERM problem in time $\tilde{O} \left(nnz(X)+\min_{\lambda'\ge\lambda}\frac{\lambda'}{\lambda}~d_{\lambda'}^{2}d \right)$, where $nnz(X)$ is the number of nonzero entries in the data. Our analysis emphasizes interesting connections between leverage scores, algorithmic stability and regularization. In particular, our algorithm involves a novel technique for choosing a regularization parameter $\lambda'$ that minimizes the complexity bound $\frac{\lambda'}{\lambda}\,d_{\lambda'}^{2}d$, while avoiding the entire (approximate) computation of the effective dimension for each candidate $\lambda'$. All of our result extend to the kernel setting.
Inter-ethnic relations of teenagers in England’s schools: the role of school and neighbourhood ethnic composition

ABSTRACT In the context of ongoing debate about the positive and negative consequences of ethnic diversity for intergroup relations, we study inter-ethnic relations among adolescents in England’s schools. In the first national study of schools throughout England to relate inter-ethnic attitudes to both school and area ethnic composition, we combine survey data collected from 14-year-olds in nearly 100 schools with administrative data. We focus on relations between three ethno-racial categories: White-British, Asian-British and Black-British, for three conceptually distinct indicators of inter-ethnic orientations: warmth, friends, and attitudes. We posit that ‘contact’, proxied by school outgroup composition, should lead to more positive intergroup orientations, while ‘exposure’, proxied by neighbourhood outgroup composition, should lead to more negative intergroup relations. We show that higher school outgroup shares are associated with more positive orientations towards that group for almost all relationships and measures. We further show that for the two instances where higher school outgroup shares do not enhance positive intergroup orientations, they nevertheless moderate negative effects of neighbourhood composition. We conclude that schools offer the opportunity to enhance intergroup relations and to mitigate the threats associated with increased neighbourhood diversity with potentially enduring consequences.
Evaluation of the Performance of Congestion Control Methods in Wireless Sensor Networks

─ Wireless sensor networks consist of elements, including sensor, processor and communication elements, which measure the targets in a geographic area. The network can be used at public, commercial, industrial and medical levels. When multiple sensor nodes send packages to a destination node, there will be the possibility of congestion. This leads to the loss of data and excessive consumption of the sensors energy. Therefore, several routing protocols are provided for data transfer and congestion control; each is trying to reduce lost packages and optimal use of energy. In this study, several congestion control methods, including Drop Tail, RED, AVQ were examined and performance of each of the methods was evaluated in the same condition in terms of network topology, number of packages, bandwidth, links, number of buffers and other parameters and compared by calculating the number of packages delivered to the destination node, the number of missing package and so forth. To achieve the above-mentioned goals, NS2 2.35 software simulation environment was used that is an efficient software for wireless sensor networks. Simulated environment was implemented with the same conditions for three congestion control methods of RED, AVQ and Drop Tail. Evaluation and analysis of the results showed that RED algorithm has the best performance and RED Drop Tail has a low performance.
Cleaning up the neighborhood: A full classification for adversarial partial monitoring

Partial monitoring is a generalization of the well-known multi-armed bandit framework where the loss is not directly observed by the learner. We complete the classification of finite adversarial partial monitoring to include all games, solving an open problem posed by Bartok et al. [2014]. Along the way we simplify and improve existing algorithms and correct errors in previous analyses. Our second contribution is a new algorithm for the class of games studied by Bartok [2013] where we prove upper and lower regret bounds that shed more light on the dependence of the regret on the game structure.
Maternal hypothyroxinemia in the first trimester of gestation and association with obstetric and neonatal outcomes and iron deficiency: a prospective Brazilian study

ABSTRACT Objective: To evaluate the association of isolated hypothyroxinemia in the first trimester with obstetric and neonatal outcomes and iron deficiency. Subjects and methods: The study was prospective. Women who had become pregnant spontaneously were initially selected. Next, anti-thyroid peroxidase antibodies (TPOAb), free T4 (FT4), total T4 (TT4), TSH, and ferritin were measured. TPOAb-positive women were excluded. The final sample consisted of 596 women with serum TSH between 0.1 and 2.5 mIU/l. Hypothyroxinemia was defined as FT4 < 0.86 ng/dL and < 0.92 ng/dL, corresponding to the 5th and 10th percentiles, respectively, and TT4 < 7.8 ng/dL. None of the pregnant women was treated with levothyroxine until the end of pregnancy. Results: The women ranged in age from 18 to 36 years, with a median gestation of 9 weeks. T4 levels were not correlated with BMI or maternal TSH. Isolated hypothyroxinemia was observed in 4.3% (FT4 < 0.86 ng/dL), 9% (FT4 < 0.92 ng/dL), and 7% (TT4 < 7.8 ng/dL) of the pregnant women. The frequencies of obstetric and neonatal outcomes were similar in women with versus without hypothyroxinemia. In women without iron deficiency, 8.4%, 3.9%, and 6.5% had FT4 < 0.92 ng/dl, FT4 < 0.86 ng/dL and TT4 < 7.8 ng/dL, respectively. These frequencies of hypothyroxinemia were significantly higher among women with iron deficiency (20.7%, 14.8% and 17.2%, respectively). Conclusions: This prospective Brazilian study found no association between isolated hypothyroxinemia in the first trimester of gestation and obstetric or neonatal outcomes, but an association was demonstrated with iron deficiency.
IGGSA Shared Task on Source and Target Extraction from Political Speeches

We present the second iteration of IGGSA’s Shared Task on Sentiment Analysis for German. It resumes the STEPS task of IG-GSA’s 2014 evaluation campaign: Source, Subjective Expression and Target Extraction from Political Speeches . As before, the task is focused on ﬁne-grained sentiment analysis, extracting sources and targets with their associated subjective expressions from a corpus of speeches given in the Swiss parliament. The second iteration exhibits some differences, however; mainly the use of an adjudicated gold standard and the availability of training data. The shared task had 2 participants submitting 7 runs for the full task and 3 runs for each of the subtasks. We evaluate the results and compare them to the base-lines provided by the previous iteration. The shared task homepage can be found at http://iggsasharedtask2016. github.io/ .
P-wave and QT dispersion in hypertensive disorders of pregnancy

Abstract Aim: To compare P-wave and QT dispersion values in hypertensive disorders of pregnancy and controls and also in preeclampsia, chronic hypertension, and gestational hypertension separately. Material and methods: We included 140 hypertensive pregnants and 110 healthy age-matched pregnants in this study. The hypertensive pregnants were divided into three subgroups: preeclampsia (n = 43), chronic hypertension (n = 51), and gestational hypertension (n = 46). P-wave and QT dispersion values were compared between groups. Results: Hypertensive pregnants had higher P-wave (41.74 ± 5.51 vs. 37.73 ± 5.62, p < .001) and QTc dispersion (45.44 ± 7.62 vs. 39.77 ± 8.34, p < .001) values. In subgroup analysis, P-wave dispersion and QTc dispersion were different between preeclamptic, chronic hypertensive, and gestational hypertensive patients. Also, they were significantly higher in chronic hypertension as compared to gestational hypertension and they were higher in preeclampsia than in gestational hypertension. No difference was found according to these parameters between preeclampsia and chronic hypertension. In correlation analysis, both P-wave dispersion and QTc dispersion were positively correlated with systolic (r = 0.409, p < .001 and r = 0.306, p < .001) and diastolic blood pressure (r = 0.390, p < .001 and r = 0.287, p < .001) which are main clinical determinants of hypertensive disorders. Conclusion: In clinical practice, chronic hypertensive pregnants are generally followed up in their future life for cardiovascular disorders. Also, we recommend that we must inform and follow preeclamptic patients for future cardiovascular diseases.
Differential Signaling via Tumor Necrosis Factor-Associated Factors (TRAFs) by CD27 and CD40 in Mouse B Cells

Background: CD27 is recently known as a memory B cell marker and is mainly expressed in activated T cells, some B cell population and NK cells. CD27 is a member of tumor necrosis factor receptor family. Like CD40 molecule, CD27 has (P/S/T/A) X(Q/E)E motif for interacting with TNF receptor-associated factors (TRAFs), and TRAF2 and TRAF5 bindings to CD27 in 293T cells were reported. Methods: To investigate the CD27 signaling effect in B cells, human CD40 extracellular domain containing mouse CD27 cytoplamic domain construct (hCD40-mCD27) was transfected into mouse B cell line CH12.LX and M12.4. 1. Results: Through the stimulation of hCD40-mCD27 molecule via anti-human CD40 antibody or CD154 ligation, expression of CD11a, CD23, CD54, CD70 and CD80 were increased and secretion of IgM was induced, which were comparable to the effect of CD40 stimulation. TRAF2 and TRAF3 were recruited into lipid-enriched membrane raft and were bound to CD27 in M12.4. 1 cells. CD27 stimulation, however, did not increase TRAF2 or TRAF3 degradation. Conclusion: In contrast to CD40 signaling pathway, TRAF2 and TRAF3 degradation was not observed after CD27 stimulation and it might contribute to prolonged B cell activation through CD27 signaling.
The impact of the Val 158 Met catechol-O-methyltransferase genotype on neural correlates of sad facial affect processing in patients with bipolar disorder and their relatives

1 Section of Neurobiology of Psychosis, Institute of Psychiatry, King’s College London, UK 2 Department of Psychiatry, Sant’Andrea Hospital, Second Medical School, La Sapienza University, Rome, Italy 3 MRC Centre for Neurodegeneration Research, Department of Neuroscience, Institute of Psychiatry, London, UK 4 Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, London, UK
Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference

This paper introduces a novel Hilbert space representation of a counterfactual distribution---called counterfactual mean embedding (CME)---with applications in nonparametric causal inference. Counterfactual prediction has become an ubiquitous tool in machine learning applications, such as online advertisement, recommendation systems, and medical diagnosis, whose performance relies on certain interventions. To infer the outcomes of such interventions, we propose to embed the associated counterfactual distribution into a reproducing kernel Hilbert space (RKHS) endowed with a positive definite kernel. Under appropriate assumptions, the CME allows us to perform causal inference over the entire landscape of the counterfactual distribution. The CME can be estimated consistently from observational data without requiring any parametric assumption about the underlying distributions. We also derive a rate of convergence which depends on the smoothness of the conditional mean and the Radon-Nikodym derivative of the underlying marginal distributions. Our framework can deal with not only real-valued outcome, but potentially also more complex and structured outcomes such as images, sequences, and graphs. Lastly, our experimental results on off-policy evaluation tasks demonstrate the advantages of the proposed estimator.
Microglial Dynamics During Human Brain Development

Microglial cells are thought to colonize the human cerebrum between the 4th and 24th gestational weeks. Rodent studies have demonstrated that these cells originate from yolk sac progenitors though it is not clear whether this directly pertains to human development. Our understanding of microglial cell dynamics in the developing human brain comes mostly from postmortem studies demonstrating that the beginning of microglial colonization precedes the appearance of the vasculature, the blood–brain barrier, astrogliogenesis, oligodendrogenesis, neurogenesis, migration, and myelination of the various brain areas. Furthermore, migrating microglial populations cluster by morphology and express differential markers within the developing brain and according to developmental age. With the advent of novel technologies such as RNA-sequencing in fresh human tissue, we are beginning to identify the molecular features of the adult microglial signature. However, this is may not extend to the much more dynamic and rapidly changing antenatal microglial population and this is further complicated by the scarcity of tissue resources. In this brief review, we first describe the various historic schools of thought that had debated the origin of microglial cells while examining the evidence supporting the various theories. We then proceed to examine the evidence we have accumulated on microglial dynamics in the developing human brain, present evidence from rodent studies on the functional role of microglia during development and finally identify limitations for the used approaches in human studies and highlight under investigated questions.