Miracle-dz/UniFAR-FTUs huggingface dataset:
Childcare attendance and Helicobacter pylori infection: systematic review and meta-analysis

Helicobacter pylori infection is acquired predominantly during childhood. Childcare promotes interpersonal contact and may be an important determinant of infection. The aim was to quantify the association between childcare attendance and H. pylori infection in childhood or adolescence. PubMed was searched up to July 2012 to identify eligible studies. The DerSimonian and Laird method was used to compute summary odds ratio (OR) estimates and 95% confidence intervals (CIs); heterogeneity was quantified with the I2 statistic and explained through stratified analyses and metaregression. Sixteen studies compared participants attending childcare with those not exposed. The summary OR was 1.12 (95% CI: 0.82–1.52, I2=77.4%). Summary estimates were similar for crude and adjusted estimates, and higher when the infection was evaluated in children of 3 years or younger (OR=2.00, 95% CI: 0.94–4.29, I2=55.0%). Studies based on the detection of stool antigens yielded higher estimates (OR=2.65, 95% CI: 1.24–5.66, I2=36.4%). Those conducted in settings with a high prevalence of H. pylori infection yielded stronger associations (OR=1.44, 95% CI: 0.94–2.20, I2=74.3%). In multivariate metaregression, there was no significant association with any of these variables; taking them into account contributed to a reduction of I2 to 67%. The role of childcare as a risk factor for H. pylori infection is confirmed by our results, especially in settings with a high prevalence of infection. However, the association was moderate, and the effect of the type of childcare setting or the duration or the intensity of exposure was seldom addressed, leaving considerable scope for improving our understanding of how this modifiable exposure contributes towards H. pylori infection.
Dynamic VAR planning for rotor-angle and short-term voltage stability enhancement

In the short-term timescale, separation between load-driven and generator-driven stability problems is rarely well-defined. Allocation of VSC-based VAR compensation, such as STATCOM, has the ability to boost system voltages in the fault-on condition, thus reducing generator power swing, in addition to circumventing delayed voltage recovery upon fault clearing, thereby reducing the risk of induction motor stalling. This paper proposes a multi-objective, hybrid static/dynamic VAR planning strategy incorporating distinct rotor angle and voltage stability indices found through time-domain simulations of full-order system models. The proposed method utilizes parallel high performance computing (HPC) capabilities combined with a genetic algorithm (GA) and is applied on the New England 39-bus system with assumed high penetration of induction machines. The study demonstrates that compared to voltage stability enhancement, improvement of rotor-angle stability through shunt dynamic VAR requires substantial additional capacity, the cost of which can be reduced using hybrid static/dynamic installations.
Chapter 1 Fusion of Manual and Non-Manual Information in American Sign Language Recognition

We present a bottom-up approach to continuous American sign language recognition without wearable aids, but with simple low-level processes operating on images and building realistic representations that are fed into intermediate level processes, to form sign hypotheses. At the intermediate level, we construct representations for both manual and non-manual aspects, such as hand movements, facial expressions and head nods. The manual aspects are represented using Relational Distributions that capture the statistical distribution of the relationships among the low-level primitives from the body parts. These relational distributions, which can be constructed without the need for part level tracking, are efficiently represented as points in the Space of Probability Functions (SoPF). Manual dynamics are thus represented as tracks in this space. The dynamics of facial expressions along with a sign are also represented as tracks, but in the expression subspace, constructed using principal component analysis (PCA). Head motions are represented as 2D image tracks. The integration of manual with non-manual information is sequential, with non-manual information refining the manual information based hypotheses set. We show that with just image-based manual information, the correct detection rate is around 88%. However, with the use of facial information, accuracy increases to 92%. Thus face contributes valuable information towards ASL recognition. ‘Negation’ in sentences is correctly detected in 90% of the cases using just 2D head motion information.
Stochastic resonance effects of human visual perception

The research about human visual perception has increased noticeably and it serves as the basis for the study of image processing. Basically, the behavior in human visual perception is highly pertinent to perceptual image quality, therefore influence on visual perception resulted in by distorted, noisy image is a crucial issue. One method applying the called "Stochastic Resonance" to noised signal processing has attracted increasing attention in recent years. The concept of stochastic resonance is that noised signal will be easier to recognize than the one without noise under appropriate noise and threshold level. There are plenty of researches about effect of stochastic resonance in biological signal processing and image processing fields. Furthermore, the effect of stochastic resonance in human visual perception was verified by related psychophysical experiments and pertinent researches were revealed. In the article, stochastic resonance phenomenon in human visual perception is investigated, especially, the effect of wavelet filtering on the stochastic resonance. Here a comparison between static image quality assessment and subjective human visual image quality evaluation of dynamical video, which is composed of low-pass filtered image, will be considered as an analytic vehicle to discuss the influence of low-pass filtering to the effect of stochastic resonance in human visual perception.
Optimal Induced Universal Graphs and Adjacency Labeling for Trees

We show that there exists a graph G with O(n) nodes, where any forest of n nodes is a node-induced subgraph of G. Furthermore, for constant arboricity k, the result implies the existence of a graph with O(nk) nodes that contains all n-node graphs as node-induced subgraphs, matching a Ω(nk) lower bound. The lower bound and previously best upper bounds were presented in Alstrup and Rauhe (FOCS'02). Our upper bounds are obtained through a log2 n + O(1) labeling scheme for adjacency queries in forests. We hereby solve an open problem being raised repeatedly over decades, e.g. in Kannan, Naor, Rudich (STOC 1988), Chung (J. of Graph Theory 1990), Fraigniaud and Korman (SODA 2010).
Modeling the two-way coupling between Lanice conchilega and sand waves on the bottom of the North Sea

The tube-building worm Lanice conchilega is an ecosystem engineer, which affects its environment by changing the local hydrodynamics and therewith the sediment dynamics. The worm occurs in subtidal and intertidal areas and it lives in patches of hundreds per m2. They form mounds of 10-80 cm height in soft-bottom sediments. The goal of this study is to determine the effects of a two-way coupling between dynamic patches of Lanice conchilega and dynamically active sand waves on the bottom of the North Sea. The effects of Lanice conchilega onto sand waves are studies as well as the effects of the sand waves on the tubes. The numerical process-based model Delft3D has been used to the study the two-way coupling. The tubes are modeled as thin solid piles that affect drag and turbulence, thereby they affect the local sediment dynamics. The effects of Lanice conchilega on the local hydrodynamics and morphodynamics are investigated by modeling static patches with tubes on a flat bottom. The patches are also modeled in sand waves, to study the two-way coupling. The bathymetries consisted of a sinusoidal and a self-organizational bottom. The patches were located where the bed shear stress was lower than the mean tide-averaged bed shear stress for the model domain. The density of the patch was updated every season by a growth curve and the available suspended sediment. Furthermore, the patches disappeared every year, every five years, and never. The protruding tubes from the sediment cause more bottom roughness, therefore, within the patch, the near-bottom flow is decreased and the turbulence is increasing to its maximum value which occurs at the top of the tubes. Due to the decrease of near bottom flow, sediment was deposited between the tubes and this forms mounds. At the leading edge (zero cm in front of the patch) erosion holes were formed due to an increased flow velocity. Because of tidal symmetry, the leading edge switches and erosion holes are formed at both sides of the patch. Patches of Lanice conchilega were also implemented in sand waves. After one year of morphological development, both for the sinusoidal and self-organizational bottom, the bed level was only locally changed at the locations of the patches. The degradation rates of the mounds were different in troughs, half-way the flanks, and at local crests (only in self-organizational bottom), because of differences in bed shear stresses. After 20 years of morphological development the case where the patches disappeared every year was the most realistic case, because the mound heights were in agreement with field studies. Furthermore, for the self-organizational bottom, a smaller sand wave growth was shown for the bottom with patches compared to the bottom without patches.
Molecular cloning and characterization of a surface antigen preferentially overexpressed on multiple myeloma cells.

HM1.24 antigen has been identified as a surface molecule preferentially expressed on terminally differentiated B cells, and its overexpression is observed in multiple myeloma cells. The HM1.24 antigen is, therefore, expected as a most potent target molecule for antibody-based immunotherapy for multiple myeloma. Here, we have identified the cDNA for human HM1.24 antigen and also analyzed its gene structure including the promoter region. The HM1.24 antigen is a type II membrane glycoprotein, which has been reported as a bone marrow stromal cell surface antigen BST2, and may exist as a homodimer on myeloma cell surface. Although a reason for the overexpression in myeloma cells is not understood, very interestingly, the promoter region of the HM1.24 gene has a tandem repeat of three cis elements for a transcription factor, STAT3, which mediates interleukin-6 (IL-6) response gene expression. Since IL-6 is a differentiation factor for B cells, and known as a paracrine/autocrine growth factor for multiple myeloma cells, the expression of HM1.24 antigen may be regulated by the activation of STAT3. Importantly, a humanized anti-HM1.24 antibody effectively lysed the CHO transformants which expressed HM1.24 antigen as high as human multiple myeloma cells, but not the cells with lower antigen expression. This evaluation shows that ADCC heavily depends on the expression level of target antigens and, therefore, the immunotherapy targeting the HM1.24 antigen should have a promising potential in clinical use.
Stopping Rules for Randomized Greedy Triangulation Schemes

Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth — a parameter of the underlying graph structure. Computing the (minimal) treewidth is NPcomplete, so stochastic algorithms are sometimes used to find low width tree decompositions. A common approach for finding good decompositions is iteratively executing a greedy triangulation algorithm (e.g. minfill) with randomized tie-breaking. However, utilizing a stochastic algorithm as part of the inference task introduces a new problem — namely, deciding how long the stochastic algorithm should be allowed to execute before performing inference on the best tree decomposition found so far. We refer to this dilemma as the Stopping Problem and formalize it in terms of the total time needed to answer a probabilistic query. We propose a rule for discontinuing the search for improved decompositions and demonstrate the benefit (in terms of time saved) of applying this rule to Bayes and Markov network instances.
Investigating a Rock Art Site in Paraná State, South of Brazil

Abstract Jaguariaíva 1 is a sandstone rockshelter located in Jaguariaíva, Paraná State, Brazil, with rock art on the surface of the walls and ceiling. A stratigraphic analysis of the soil within the shelter showed six occupational layers and a superficial disturbed layer with evidence from the end of the 19th century. The establishment of a rock-art chronology became possible using fallen painted rock sections incorporated into three sedimentary levels underlying this rock shelter. These show superimpositions of several pictures of differently sized animals, such as deer, and lattice motifs, which are generally associated with the Planalto rock art tradition. The chronological study was performed based on radiocarbon (14C) analysis of charcoal collected from six excavated subsurface archaeological contexts. The two oldest layers, associated with hunters and gatherers of the Umbu tradition, were dated to 7680–7516 cal BP and 6913–6656 cal BP. There are four occupational layers from ceramists and farmers related to the south Jê linguistic family, and linked to the Itararé-Taquara archaeological tradition: layer 3 linked to the oldest of such occupation, dated to 3058–2796 cal BP, followed by layer 4, dated to 2080–1701 cal BP. Layers 5 and 6, dated to 1995–1526 cal BP and 540–152 cal BP, respectively.
Monitoring Access to Shared Memory-Mapped Files

The post-mortem state of a compromised system may not contain enough evidence regarding what transpired during an attack to explain the attacker’s modus operandi. Current systems that reconstruct sequences of events gather potential evidence at runtime by monitoring events and objects at the system call level. The reconstruction process starts with a detection point, such as a file with suspicious contents, and establishes a dependency chain with all the processes and files that could be related to the compromise, building a path back to the origin of the attack. However, system call support is lost after a file is memory-mapped because all read and write operations on the file in memory thereafter are through memory pointers. We present a runtime monitor to log read and write operations in memory-mapped files. The basic concept of our approach is to insert a page fault monitor in the kernel’s memory management subsystem. This monitor guarantees the correct ordering of the logs that represent memory access events when two or more processes operate on a file in memory. Our monitor increases accuracy to current reconstruction systems by reducing search time, search space, and false dependencies.
A Fern Fractal Leaf Inspired Wideband Antipodal Vivaldi Antenna for Microwave Imaging System

This communication presents a new approach to implement planar antipodal Vivaldi antenna design. A nature fern inspired fractal leaf structure is implemented here. Impedance bandwidth (−10 dB) of the proposed antenna is around 19.7 GHz starting from 1.3 to 20 GHz. The lower operating frequency of this antenna is reduced by 19% with the second iteration as compared to the first iteration of fractal leaf structure. The prototype antenna is fabricated and tested in frequency as well as in time domains to obtain various transfer characteristics along with common antenna parameters. Experimental results show that good wideband feature, stable radiation pattern, and promising group delay of less than 1 ns signatures are obtained, which agree well with the simulated data. The miniaturized proposed antenna structure becomes an attractive choice in microwave imaging applications because of its ultrawide fractional bandwidth at 175%, high directive gain of 10 dBi, and finally appreciably large fidelity factor above (>90%).
FingARtips: gesture based direct manipulation in Augmented Reality

This paper presents a technique for natural, fingertip-based interaction with virtual objects in Augmented Reality (AR) environments. We use image processing software and finger- and hand-based fiducial markers to track gestures from the user, stencil buffering to enable the user to see their fingers at all times, and fingertip-based haptic feedback devices to enable the user to feel virtual objects. Unlike previous AR interfaces, this approach allows users to interact with virtual content using natural hand gestures. The paper describes how these techniques were applied in an urban planning interface, and also presents preliminary informal usability results.
Mouse Disabled 1 Regulates the Nuclear Position of Neurons in a Drosophila Eye Model

ABSTRACT Nucleokinesis has recently been suggested as a critical regulator of neuronal migration. Here we show that Disabled 1 (Dab1), which is required for neuronal positioning in mammals, regulates the nuclear position of postmitotic neurons in a phosphorylation-site dependent manner. Dab1 expression in the Drosophila visual system partially rescues nuclear position defects caused by a mutation in the Dynactin subunit Glued. Furthermore, we observed that a loss-of-function allele of amyloid precursor protein (APP)-like, a kinesin cargo receptor, enhanced the severity of a Dab1 overexpression phenotype characterized by misplaced nuclei in the adult retina. In mammalian neurons, overexpression of APP reduced the ability of Reelin to induce Dab1 tyrosine phosphorylation, suggesting an antagonistic relationship between APP family members and Dab1 function. This is the first evidence that signaling which regulates Dab1 tyrosine phosphorylation determines nuclear positioning through Dab1-mediated influences on microtubule motor proteins in a subset of neurons.
Considerations in maximum mutual information and minimum classification error training for statistical machine translation

Discriminative training methods are used in statistical machine translation to effectively introduce and combine additional knowledge sources within the translation process. Although these methods are described in the accompanying literature and comparative studies are available for speech recognition, additional considerations are introduced when applying discriminative training to statistical machine translation. In this paper we pay special attention to the comparison and formalization of discriminative training criteria and their respective optimization methods with the goal of improving translation performance measured by the corpus level BLEU metric for a Viterbi beam based decoder. We frame this work within the current trends in discriminative training and present reproducible re-sults that highlight the potential as well as shortcomings of N-Best list based discriminative training.
A Class 1 Integron Present in a Human Commensal Has a Hybrid Transposition Module Compared to Tn402: Evidence of Interaction with Mobile DNA from Natural Environments

ABSTRACT In a survey of class 1 integrons from human stools, an unusual class 1 integron from a strain of Enterobacter cloacae was isolated and characterized in detail. Sequence analysis of a fosmid containing the class 1 integron revealed a complex set of transposons which included two Tn402-like transposons. One of these transposons, Tn6007, included a class 1 integron with two non-antibiotic-resistance-type gene cassettes and a complete transposition module. This tni module is a hybrid with a boundary within the res site compared to Tn402, implying that a site-specific recombination event generated either Tn6007 or Tn402. The second Tn402-like transposon, Tn6008, possesses neither a mer operon nor an integron, and most of its tni module has been deleted. Tn6007, Tn6008, and the 2,478 bases between them, collectively designated Tn6006, have transposed into a Tn5036/Tn3926-like transposon as a single unit. Tn6006, Tn6007, and Tn6008 could all transpose as discrete entities. Database analysis also revealed that a version of Tn6008 was present in the genome of Xanthomonas campestris pv. vesicatoria. Overall, the E. cloacae isolate further demonstrated that functional class 1 integrons/transposons are probably common in bacterial communities and have the potential to add substantially to the problem of multidrug-resistant nosocomial infections.
SINotas: the Evaluation of a NLG Application

SINotas is a data-to-text NLG application intended to produce short textual reports on students academic performance from a database conveying their grades, weekly attendance rates and related academic information. Although developed primarily as a testbed for Portuguese Natural Language Generation, SINotas generates reports of interest to both students keen to learn how their professors would describe their efforts, and to the professors themselves, who may benefit from an at-a-glance view of the students performance. In a traditional machine learning approach, SINotas uses a data-text aligned corpus as training data for decision-tree induction. The current system comprises a series of classifiers that implement major Document Planning subtasks (namely, data interpretation, content selection, within- and between-sentence structuring), and a small surface realisation grammar of Brazilian Portuguese. In this paper we focus on the evaluation work of the system, applying a number of intrinsic and user-based evaluation metrics to a collection of text reports generated from real application data.
Extending CCG-based Syntactic Constraints in Hierarchical Phrase-Based SMT

In this paper, we describe two approaches to extending syntactic constraints in the Hierarchical Phrase-Based (HPB) Statistical Machine Translation (SMT) model using Combinatory Categorial Grammar (CCG). These extensions target the limitations of previous syntax-augmented HPB SMT systems which limit the coverage of the syntactic constraints applied. We present experiments on Arabic‐English and Chinese‐English translation. Our experiments show that using extended CCG labels helps to increase nonterminal label coverage and achieve significant improvements over the baseline for Arabic‐ English translation. In addition, combining extended CCG labels with CCGaugmented glue grammar helps to improve the performance of the Chinese‐English translation over the baseline systems.
Towards a Principled Integration of Multi-camera Re-identification and Tracking Through Optimal Bayes Filters

With the rise of end-to-end learning through deep learning, person detectors and re-identification (ReID) models have recently become very strong. Multi-target multicamera (MTMC) tracking has not fully gone through this transformation yet. We intend to take another step in this direction by presenting a theoretically principled way of integrating ReID with tracking formulated as an optimal Bayes filter. This conveniently side-steps the need for dataassociation and opens up a direct path from full images to the core of the tracker. While the results are still sub-par, we believe that this new, tight integration opens many interesting research opportunities and leads the way towards full end-to-end tracking from raw pixels. Code and models for all experiments are publicly available.