Miracle-dz/UniFAR-FTUs huggingface dataset:
The Human Transcriptome During Nontyphoid Salmonella and HIV Coinfection Reveals Attenuated NFκB-Mediated Inflammation and Persistent Cell Cycle Disruption

Background. Invasive nontyphoid Salmonella (iNTS) disease is common and severe in adults with human immunodeficiency virus (HIV) infection in Africa. We previously observed that ex vivo macrophages from HIV-infected subjects challenged with Salmonella Typhimurium exhibit dysregulated proinflammatory cytokine responses. Methods. We studied the transcriptional response in whole blood from HIV-positive patients during acute and convalescent iNTS disease compared to other invasive bacterial diseases, and to HIV-positive and -negative controls. Results. During iNTS disease, there was a remarkable lack of a coordinated inflammatory or innate immune signaling response. Few interferon γ (IFNγ)--induced genes or Toll-like receptor/transcription factor nuclear factor κB (TLR/NFκB) gene pathways were upregulated in expression. Ex vivo lipopolysacharide (LPS) or flagellin stimulation of whole blood, however, showed that convalescent iNTS subjects and controls were competent to mount prominent TLR/NFκB-associated patterns of mRNA expression. In contrast, HIV-positive patients with other invasive bacterial infections (Escherichia coli and Streptococcus pneumoniae) displayed a pronounced proinflammatory innate immune transcriptional response. There was also upregulated mRNA expression in cell cycle, DNA replication, translation and repair, and viral replication pathways during iNTS. These patterns persisted for up to 2 months into convalescence. Conclusions. Attenuation of NFκB-mediated inflammation and dysregulation of cell cycle and DNA-function gene pathway expression are key features of the interplay between iNTS and HIV.
Statistical Interpretation of Compound Nominalisations

This paper presents a method for detecting compound nominalisations from open data, and providing a semantic intepretation. It uses a statistical model based on confidence intervals over frequencies extracted from a large, balanced corpus. Using three paraphrases of the given compound nominalisation, and interpretation preferences of its components, the algorithm achieves about 70% accuracy in classifying the semantic relationship as one of subject, and object, and 57% between subject, direct object, and prepositional object.
Avoiding the Comparative Fallacy inthe Annotation of Learner Corpora

It is becoming more common to use corpora of second language learner data in order to support research on various second language acquisition (SLA) topics (e.g., Römer, 2009; Wulff et al., 2009), but there has been little use of corpus annotation. For many questions in SLA research, using a corpus is simple and in no need of annotation: one can search a corpus for specific words to find relevant examples. For example, if one wants to examine how modal verbs are used by L2 learners (cf., e.g., Aijmer, 2002), one can search for those specific lexical items (can, should, etc.) and analyze the output by hand. Consider a search for syntactic patterns, however, such as examining wh movement (e.g., Juffs, 2005; Wolfe-Quintero, 1992; Schachter, 1989). These types of questions require more linguistic abstraction (cf., e.g., Lüdeling, 2010). If we take the learner sentence (1), for example, what kind of search involving specific words addresses questions about the function of whom? 1 If we search for all instances of whom in a corpus, we still have to determine whether this is a relative clause marker, whether this is subject or object extraction, or what the depth of embedding is; and then we need to do the same for that, which, or even other prepositional objects. We need the data marked with syntactic annotation.
The Influence of Socioeconomic and Environmental Determinants on Health and Obesity: A West Virginia Case Study

A recursive system of ordered self assessed health together with BRFSS data were used to investigate health and obesity in the Appalachian state of West Virginia. Implications of unobserved heterogeneity and endogeneity of lifestyle outcomes on health were investigated. Obesity was found to be an endogenous lifestyle outcome associated with impaired health status. Risk of obesity is found to increase at a decreasing rate with per capita income and age. Intervention measures which stimulate human capital development, diet-disease knowledge and careful land use planning may improve health and obesity outcomes in Appalachia in particular and rural America in general.
DTCO for DSA-MP Hybrid Lithography with Double-BCP Materials in Sub-7nm Node

In the sub-7nm technology nodes, as the mask cost for printing the dense via layers increases dramatically with conventional lithography technique, industries are actively looking for some alternative techniques, such as E-beam, EUV or nanoimprint. In recent years, directed self-assembly (DSA) has been demonstrated to be a promising candidate to reduce the number of masks due to its pitch multiply ability by grouping several vias in the same DSA guiding patterns. A novel idea has been proposed recently to further reduce the mask cost by applying double block copolymer (double-BCP) materials for DSA lithography. However, it is also discovered that new challenges are introduced for the DSA pattern assignment and decomposition problem with double-BCP DSA. This paper discusses the design technology co-optimization (DTCO) for BCP materials and DSA-MP hybrid lithography. We show that it is necessary to consider the pitch-range of BCP materials for the DSA pattern assignment and decomposition. We first propose a pitch-range optimization method for the BCP material to minimize the potential DSA decomposition conflicts. We then solve the double-BCP pattern assignment and decomposition by formulating it to a maximum weighted independent set problem, and obtain the optimal solution with integer linear programming (ILP). We also propose a bounded approximation algorithm to solve the ILP problem more efficiently. The experimental results demonstrate that our pitch-range optimization method can quickly find the pitch-range that can minimize the decomposition conflicts. With the optimized pitch-ranges, double-BCP outperforms single-BCP by reducing more than 500 conflicts for very dense design. In addition, our proposed approximation algorithm solves the problem 38&#xd7; faster than the ILP formulation.
Implementing NAT Traversal on BitTorrent

Network Address Translation (NAT) causes difficulties for peer-to-peer (P2P) communication. For BitTorrent, if only one client is behind NAT, it is possible for two clients to build connection. But for both clients are behind different NATs, currently it is not possible without specific settings on their own NAT. In this work, we integrate TCP NAT traversal scheme into BitTorrent by modifying open source client. Our approach do not need super user privilege and only requires a few modifications.
Expression of Cathepsins B, D, and G in Isocitrate Dehydrogenase-Wildtype Glioblastoma

Aim To investigate the expression of cathepsins B, D, and G, in relation to the cancer stem cell (CSC) subpopulations, we have previously characterized within isocitrate dehydogenase (IDH)-wildtype glioblastoma (IDHWGB). Methods 3,3-Diaminobezidine (DAB) immunohistochemical (IHC) staining for cathepsins B, D, and G, was performed on 4μm-thick formalin-fixed paraffin-embedded IDHWGB samples obtained from six patients. Two representative DHWGB samples from the original cohort of patients were selected for immunofluorescent (IF) IHC staining, to identify the localization of the cathepsins in relation to the CSC subpopulations. NanoString gene expression analysis and colorimetric in situ hybridization (CISH) were conducted to investigate the transcriptional activation of genes encoding for cathepsins B, D, and G. Data obtained from cell counting of DAB IHC-stained slides and from NanoString analysis were subjected to statistical analyses to determine significance. Results Cathepsin B and cathepsin D were detected in IDHWGB by DAB IHC staining. IF IHC staining demonstrated the expression of both cathepsin B and cathepsin D by the OCT4+ and SALL4+ CSC subpopulations. NanoString gene analysis and CISH confirmed the abundant transcript expression of these cathepsins. The transcriptional and translational expressions of cathepsin G were minimal and were confined to cells within the microvasculature. Conclusion This study demonstrated the expression of cathepsin B and cathepsin D but not cathepsin G within the CSC subpopulations of IDHWGB at both the transcriptional and translational level. Cathepsin G was expressed at low levels and was not localized to the CSC population of IDHWGB. The novel finding of cathepsin B and cathepsin D in IDHWGB suggests the presence of bypass loops for the renin-angiotensin system, which may facilitate the production of angiotensin peptides. Elucidating the precise role of these cathepsins may lead to better understanding and more effective treatment of this aggressive tumor.
Entropy-Based TOA Estimation and SVM-Based Ranging Error Mitigation in UWB Ranging Systems

The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach of entropy-based TOA estimation and support vector machine (SVM) regression-based ranging error mitigation is proposed in this paper. The proposed method can estimate the TOA precisely by measuring the randomness of the received signals and mitigate the ranging error without the recognition of the channel conditions. The entropy is used to measure the randomness of the received signals and the FP can be determined by the decision of the sample which is followed by a great entropy decrease. The SVM regression is employed to perform the ranging-error mitigation by the modeling of the regressor between the characteristics of received signals and the ranging error. The presented numerical simulation results show that the proposed approach achieves significant performance improvements in the CM1 to CM4 channels of the IEEE 802.15. 4a standard, as compared to conventional approaches.
mRNA on the Move: The Road to Its Biological Destiny*

Cells have evolved to regulate the asymmetric distribution of specific mRNA targets to institute spatial and temporal control over gene expression. Over the last few decades, evidence has mounted as to the importance of localization elements in the mRNA sequence and their respective RNA-binding proteins. Live imaging methodologies have shown mechanistic details of this phenomenon. In this minireview, we focus on the advanced biochemical and cell imaging techniques used to tweeze out the finer aspects of mechanisms of mRNA movement.
One-Loop Amplitudes in Supersymmetric QCD from MHV Vertices

The Cachazo-Svrcek-Witten (CSW) rule for efficiently calculating gauge theory amplitudes is extended to N = 1 supersymmetric QCD (SQCD), incorporating massless quarks, in a way preserving the manifest supersymmetry. Using this extended CSW rule, we obtain compact expressions of all the one-loop MHV amplitudes in SQCD including one or two external quark-antiquark (chiral-antichiral multiplets) pairs. The collinear sigularities of the five point amplitudes are investigated to confirm the consistency of the results. 1 typeset using PTPTEX.cls 〈Ver.0. 9〉 §
Psychiatrists' experiences of stalking in Ireland: Prevalence and characteristics.

Aims and method Accumulating evidence suggest that psychiatrists may be at greater risk of being stalked compared with the general population. We used a self-administered questionnaire to survey psychiatrists in Ireland about their experiences, practices and attitudes regarding work-related stalking. Results We found that 25.1% of psychiatrists in Ireland had been the subject of stalking behaviour at some point in their career. At the time of the survey, 5.5% of respondents were actively being stalked. The majority of the stalking occurred in the workplace and most of the perpetrators were patients. Most of the victims were unaware of guidelines or other supportive mechanisms in their workplace. Of those who reported their experiences to authorities, almost half were not satisfied with the support they received. Clinical implications Stalking of psychiatrists is not uncommon. Employers should put in place supportive structures backed up by education and training to reduce the incidence, associated morbidity and other wider consequences of stalking.
Automatic error detection for unit selection speech synthesis using log likelihood ratio based SVM classifier

This paper proposes a method to detect the errors in synthetic speech of a unit selection speech synthesis system automatically using log likelihood ratio and support vector machine (SVM). For SVM training, a set of synthetic speech are firstly generated by a given speech synthesis system and their synthetic errors are labeled by manually annotating the segments that sound unnatural. Then, two context-dependent acoustic models are trained using the natural and unnatural segments of labeled synthetic speech respectively. The log likelihood ratio of acoustic features between these two models is adopted to train the SVM classifier for error detection. Experimental results show the proposed method is effective in detecting the errors of pitch contour within a word for a Mandarin speech synthesis system. The proposed SVM method using log likelihood ratio between context-dependent acoustic models outperforms the SVM classifier trained on acoustic features directly.
Joint Eurographics -ieee Tcvg Symposium on Visualization (2003) Visualizing Spatial Distribution Data Sets

In this paper, we define distributions as a new data type and address the challenges of visualizing spatial distribution data sets. Numerous visualization techniques exist today for dealing with scalar data. That is, there is a scalar value at each spatial location, which may also be changing over time. Likewise, techniques exist for dealing with vector, tensor and multivariate data sets. However, there is currently no systematic way of dealing with distribution data where there is a collection of values for the same variable at every location and time. Distribution data is increasingly becoming more common as computers and sensor technologies continue to improve. They have also been used in a number of fields ranging from agriculture, engineering design and manufacturing to weather forecasting. Rather than developing specialized visualization techniques for dealing with distribution data, the approach presented in this paper is to find a systematic way of extending existing visualization methods to handle this new data type. For example, we would like to be able to generate isosurfaces of 3D scalar distribution data sets, or generate streamlines of vector distribution data sets. In order to accomplish this goal, we propose the use of a set of mathematically and procedurally defined operators that allow us to work directly on distributions. Color images can also be found in www.cse. ucsc.edu/research/avis/operator.html.
Acknowledgment Use with Synthesized and Recorded Prompts

Acknowledgments, e.g., “yeah” and “uh-huh,” are ubiquitous in human conversation but are rarer in human-computer interaction. What interface factors might contribute to this difference? Using a simple spoken-language interface that responded to acknowledgments, we compared subjects’ use of acknowledgments when the interface used recorded speech with that seen when the interface used synthesized speech. Contrary to our hypothesis, we saw a drop in the numbers of subjects using acknowledgments: subjects appeared to interpret the recorded-voice interface as signalling a more limited interface. These results were consistent for both Mexican Spanish and American English versions of the interface.
Resource-Light Bantu Part-of-Speech Tagging

Recent scientific publications on data-driven part-of-speech tagging of Sub-Saharan African languages have reported encouraging accuracy scores, using off-the-shelf tools and often fairly limited amounts of training data. Unfortunately, no research efforts exist that explore which type of linguistic features contribute to accurate part-of-speech tagging for the languages under investigation. This paper describes feature selection experiments with a memory-based tagger, as well as a resource-light alternative approach. Experimental results show that contextual information is often not strictly necessary to achieve a good accuracy for tagging Bantu languages and that decent results can be achieved using a very straightforward unigram approach, based on orthographic features.
Bioactivation and Regioselectivity of Pig Cytochrome P450 3A29 towards Aflatoxin B1

Due to unavoidable contaminations in feedstuff, pigs are easily exposed to aflatoxin B1 (AFB1) and suffer from poisoning, thus the poisoned products potentially affect human health. Heretofore, the metabolic process of AFB1 in pigs remains to be clarified, especially the principal cytochrome P450 oxidases responsible for its activation. In this study, we cloned CYP3A29 from pig liver and expressed it in Escherichia coli, and its activity has been confirmed with the typical P450 CO-reduced spectral characteristic and nifedipine-oxidizing activity. The reconstituted membrane incubation proved that the recombinant CYP3A29 was able to oxidize AFB1 to form AFB1-exo-8,9-epoxide in vitro. The structural basis for the regioselective epoxidation of AFB1 by CYP3A29 was further addressed. The T309A mutation significantly decreased the production of AFBO, whereas F304A exhibited an enhanced activation towards AFB1. In agreement with the mutagenesis study, the molecular docking simulation suggested that Thr309 played a significant role in stabilization of AFB1 binding in the active center through a hydrogen bond. In addition, the bulk phenyl group of Phe304 potentially imposed steric hindrance on the binding of AFB1. Our study demonstrates the bioactivation of pig CYP3A29 towards AFB1 in vitro, and provides the insight for understanding regioselectivity of CYP3A29 to AFB1.
Evaluator-executor transformation for efficient pipelining of loops with conditionals

Control divergence poses many problems in parallelizing loops. While predicated execution is commonly used to convert control dependence into data dependence, it often incurs high overhead because it allocates resources equally for both branches of a conditional statement regardless of their execution frequencies. For those loops with unbalanced conditionals, we propose a software transformation that divides a loop into two or three smaller loops so that the condition is evaluated only in the first loop, while the less frequent branch is executed in the second loop in a way that is much more efficient than in the original loop. To reduce the overhead of extra data transfer caused by the loop fission, we also present a hardware extension for a class of Coarse-Grained Reconfigurable Architectures (CGRAs). Our experiments using MiBench and computer vision benchmarks on a CGRA demonstrate that our techniques can improve the performance of loops over predicated execution by up to 65% (37.5%, on average), when the hardware extension is enabled. Without any hardware modification, our software-only version can improve performance by up to 64% (33%, on average), while simultaneously reducing the energy consumption of the entire CGRA including configuration and data memory by 22%, on average.
The Good Working Mother: Managerial Women’s Sensemaking and Feelings About Work–Family Issues

We use a sensemaking lens to explore how women managers experience and articulate work–life concerns upon their return to paid work following maternity leaves. We focus on 11 women who held different types of managerial positions, including vice presidents, circulation managers, and human resources experts. We found that our participants re‐framed the good mother image into a good working mother role that fit their lifestyles and interests. To accomplish this reframing, participants engaged in three thematic processes supportive of the good working mother image: (a) good working mothers arrange quality child care; (b) good working mothers are (un)equal partners; and (c) good working mothers feel pleasure in their working mother role. These themes and image were both ironic and fragile constructions of working motherhood. Because these themes and images enable participants to make sense of and establish the worth of working motherhood to family members, friends, acquaintances, organizational members, and community members, they provide a reason why middle‐ or upper‐class working and stay‐at‐home mothers may be in conflict about work and family choices.
Minimum Average Cost Clustering

A number of objective functions in clustering problems can be described with submodular functions. In this paper, we introduce the minimum average cost criterion, and show that the theory of intersecting submodular functions can be used for clustering with submodular objective functions. The proposed algorithm does not require the number of clusters in advance, and it will be determined by the property of a given set of data points. The minimum average cost clustering problem is parameterized with a real variable, and surprisingly, we show that all information about optimal clusterings for all parameters can be computed in polynomial time in total. Additionally, we evaluate the performance of the proposed algorithm through computational experiments.
Using Attribute Construction to Improve the Predictability of a GP Financial Forecasting Algorithm

Financial forecasting is an important area in computational finance. EDDIE 8 is an established Genetic Programming financial forecasting algorithm, which has successfully been applied to a number of international datasets. The purpose of this paper is to further increase the algorithm's predictive performance, by improving its data space representation. In order to achieve this, we use attribute construction to create new (high-level) attributes from the original (low-level) attributes. To examine the effectiveness of the above method, we test the extended EDDIE's predictive performance across 25 datasets and compare it to the performance of two previous EDDIE algorithms. Results show that the introduction of attribute construction benefits the algorithm, allowing EDDIE to explore the use of new attributes to improve its predictive accuracy.