Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutagenic Analysis of the 3′ cis-Acting Elements of the Rubella Virus Genome

ABSTRACT Thermodynamically predicted secondary structure analysis of the 3′-terminal 305 nucleotides (nt) of the rubella virus (RUB) genome, a region conserved in all RUB defective interfering RNAs, revealed four stem-loop (SL) structures; SL1 and SL2 are both located in the E1 coding region, while SL3 and SL4 are within the 59-nt 3′ untranslated region (UTR) preceding the poly(A) tract. SL2 is a structure shown to interact with human calreticulin (CAL), an autoantigen potentially involved in RUB RNA replication and pathogenesis. RNase mapping indicated that SL2 and SL3 are in equilibrium between two conformations, in the second of which the previously proposed CAL binding site in SL2, a U-U bulge, is not formed. Site-directed mutagenesis of the 3′ UTR with a RUB infectious clone, Robo302, revealed that most of the 3′ UTR is required for viral viability except for the 3′-terminal 5 nt and the poly(A) tract, although poly(A) was rapidly regenerated during subsequent replication. Maintenance of the overall SL3 structure, the 11-nt single-stranded sequence between SL3 and SL4, and the sequences forming SL4 were all important for viral viability. Studies on the interaction between host factors and the 3′ UTR showed the formation of three RNA-protein complexes by gel mobility shift assay, and UV-induced cross-linking detected six host protein species, with molecular masses of 120, 80, 66, 55, 48, and 36 kDa, interacting with the 3′ UTR. Site-directed mutagenesis of SL2 by nucleotide substitutions showed that maintenance of SL2 stem rather than the U-U bulge was critical in CAL binding since mutants having the U-U bulge base paired had a similar binding activity for CAL as the native structure whereas mutants having the SL2 stem destabilized had much lower binding activity. However, all of these mutations gave rise to viable viruses when introduced into Robo302, indicating that binding of CAL to SL2 is independent of viral viability.
Robust Dynamic Optimal Taxation and Environmental Externalities ∗

We study a dynamic stochastic general equilibrium model where agents are concerned about model uncertainty regarding climate change. An externality from greenhouse gas emissions adversely affects the economy’s capital stock. We assume that the mapping from climate change to damages is subject to uncertainty, and we adapt and use techniques from robust control theory in order to study effi ciency and optimal policy. We obtain a sharp analytical solution for the implied environmental externality, and we characterize dynamic optimal taxation. A small increase in the concern about model uncertainty can cause a significant drop in optimal energy extraction. The optimal tax which restores the social optimal allocation is Pigouvian. Under more general assumptions, we develop a recursive method and solve the model computationally. We find that the introduction of uncertainty matters qualitatively and quantitatively. We study optimal output growth in the presence and in the absence of concerns about uncertainty and find that these can lead to substantially different conclusions. ∗We thank participants at the 2013 Midwest Macro Conference and at the Econometric Society Summer 2013 meetings for comments and suggestions. The opinions expressed do not necessarily reflect those of the Federal Reserve System.
Towards optimization of RDF analytical queries on MapReduce

The broadened use of Semantic Web technologies across domains has led to a shift in focus from simple pattern matching queries on RDF data to analytical queries with complex grouping and aggregations. An RDF analytical query involves graph pattern matching, which translates to several join operations due to the fine-grained nature of RDF data model. Complex analytical queries involve multiple grouping-aggregations on different graph patterns, making such tasks join-intensive. Scale-out processing of RDF analytical queries on existing relational-style MapReduce platforms such as Apache Hive and Pig, results in lengthy execution workflows with multiple cycles of I/O and network transfer. Additionally, certain graph patterns result in avoidable redundancy in intermediate results, which negatively impacts processing costs. The PhD thesis summarized in this paper proposes a two-pronged approach to minimize the costs while processing RDF queries on MapReduce: an algebraic approach based on a Nested TripleGroup Data Model and Algebra that reinterprets graph pattern queries in a way that reduces the required number of map-reduce cycles, and special strategies to minimize the redundancy in intermediate data while processing certain graph patterns. The proposed techniques are integrated into Apache Pig. Empirical evaluation of this work for processing graph pattern queries show 45-60% performance gains over systems such as Pig and Hive.
Infant word segmentation : a basic review

The abstract problem of speech segmentation can be formulated computationally: given strings (si ∈ Σ∗) over some alphabet (Σ) and the knowledge that each string (si) is a concatenation of words from some set (W ⊆ Σ∗), how does the learner determine what the words (W ) are and segment new strings? Even assuming that the alphabet (Σ) is known (Σ can be {syllables}, {segments}, .), this is a daunting problem. In the context of natural language, this abstract problem intuitively seems overly difficult, since written words are separated by spaces and spoken words seem separated by pauses. However, as can be seen in a spectrogram of spoken English, pauses at word boundaries are in fact no longer than between arbitrary syllables; indeed phoneticians have found no systematic cues to word boundaries in speech [17, 19, 18]. So the segmentation problem faced by humans is at least as hard as that described above, yet infants routinely solve it early in language acquisition. Segmentation is easy enough for humans that many written languages do not include spaces. How do infants learn to segment their native language(s)? The consensus of most experimenters is that infants gradually integrate a range of cues, each of which is insufficient in isolation, to segment in progressively greater detail. This general statement admits a range of hypotheses, since for each potential cue one can ask five questions:
Learning in a pairwise term-term proximity framework for information retrieval

Traditional ad hoc retrieval models do not take into account the closeness or proximity of terms. Document scores in these models are primarily based on the occurrences or non-occurrences of query-terms considered independently of each other. Intuitively, documents in which query-terms occur closer together should be ranked higher than documents in which the query-terms appear far apart. This paper outlines several term-term proximity measures and develops an intuitive framework in which they can be used to fully model the proximity of all query-terms for a particular topic. As useful proximity functions may be constructed from many proximity measures, we use a learning approach to combine proximity measures to develop a useful proximity function in the framework. An evaluation of the best proximity functions show that there is a significant improvement over the baseline ad hoc retrieval model and over other more recent methods that employ the use of single proximity measures.
Resolving Terminology Heterogeneity in Digital Forensics Using the Web

Frequency generators are devices that are widely used in the field of medicine in an attempt to effect chemical changes in the human body for the purpose of curing certain diseases. In addition, it is believed by many medical practitioners and researchers that frequencies can be generated, using sympathetic resonance to stimulate organ function or even to physically vibrate offending bacteria, viruses and parasites, resulting in their elimination from the human body. Digital forensics, which is rather a relatively new branch of forensic science, has attracted a wider array of people, such as computer professionals, law enforcement agencies and practitioners, that always need to cooperate in this profession. However, this has inflicted new problems with terminology heterogeneity within the domain, analogous to the offending bacteria, viruses and parasites in the human body, which needs to be resolved and/or eliminated. This paper therefore, proposes a new method that uses the Web in an attempt to resolve terminology heterogeneity in the digital forensic domain. The proposed method is based on ‘terminology frequency’ which is automatically generated by the Web each time new information is added. We refer to this frequency as the Web Terminology Frequency (WTF) in this paper. Web search engines are however employed as tools that have the ability to capture the terminology frequencies. Finally, we show how the computed WTF is used to deduce a method coined as the ‘Terminology Heterogeneity Resolver’ (TE-HERE) in this paper. Experiments conducted using the proposed TE-HERE method focuses on the digital forensic domain terminologies. However, in the authors’ opinion, the TE-HERE which is technically simple and does not require any human-annotated knowledge can as well be applied in other domains. This is because the findings presented in this paper indicate that the TE-HERE method produce influential results. TE-HERE is a novel approach to resolving terminology heterogeneity in digital forensics and constitutes the main contribution of this paper
Stable Pushing: Mechanics, Controllability, and Planning

We would like to give robots the ability to position and orient parts in the plane by pushing, particularly when the parts are too large or heavy to be grasped and lifted. Unfortunately, the motion of a pushed object is generally unpredictable due to unknown support friction forces. With multiple pushing contact points, however, it is possible to find pushing directions that cause the object to remain fixed to the manipulator. These are called stable pushing directions. In this article we consider the problem of planning pushing paths using stable pushes. Pushing imposes a set of nonholonomic velocity constraints on the motion of the object, and we study the issues of local and global controllability during pushing with point contact or stable line contact. We describe a planner for finding stable pushing paths among obstacles, and the planner is demon strated on several manipulation tasks.
Circulating levels of KL‐6 in acute respiratory distress syndrome sepsis or traumatic brain injury in critically ill children

KL‐6 is a high molecular weight glycoprotein that is expressed on the apical borders of normal secretary alveolar epithelial cells. The aim of our study was to elucidate the potential role of circulating levels of KL‐6, related to C‐reacting protein (CRP), disease severity (PRISM, TISS), length of stay (LOS) or mechanical ventilation (LOMV), and outcome, in children with acute respiratory distress syndrome (ARDS), sepsis, or traumatic brain injury (TBI). KL‐6 concentrations were monitored using solid phase sandwich enzyme‐linked immunosorbent assay in plasma of nine patients with ARDS and compared to nine patients with TBI, nine with sepsis, and nine ventilated patients with cancer of matched illness severity on days 1, 3, 5, 7, and 10. Initial respiratory/ventilatory parameters (oxygenation index, plateau pressures) were recorded for ARDS patients. Patients with ARDS had higher early plasma levels of KL‐6 (956 ± 400 U/ml), as compared to patients with TBI (169 ± 9 U/ml), sepsis (282 ± 81 U/ml), and ventilated controls (255 ± 40 U/ml). Significant correlations were demonstrated between plasma KL‐6 concentration and oxygenation index, PaO2: FiO2 ratio, LOS and LOMV, but not with CRP or PRISM. Only in patients with ARDS, plasma KL‐6 levels were higher in non‐survivors than survivors (P < 0.03). Plasma KL‐6 levels have possible prognostic significance and may provide a useful marker for ARDS in critically ill children. Pediatr Pulmonol. 2006; 41: 790–795. © 2006 Wiley‐Liss, Inc.
An expert disambiguation method based on attributed graph clustering

Leveraging expert attributes and their attribute-associated features, we propose an expert disambiguation method based on experts' attributed graph clustering model. In the method, firstly, the attributes and their co-occurrences are identified and extracted. Secondly, based on graph theory, the augmented expert attribute nodes are established and their correlations are connected to form a network of augmented expert attribute graph, which combines experts' attribute consistency and graph' structural consistency. Finally, we establish an entropy model to measure attribute information and structural information, and by minimizing the entropy of super nodes and super edges, we obtain the clustering partition for multiple expert nodes. The experimental results on real-world datasets show that the proposed method significantly outperforms the state-of-art spectral clustering method and the semi-supervised graph clustering method for the accuracy of disambiguation.
The Role of FOXO and PPAR Transcription Factors in Diet-Mediated Inhibition of PDC Activation and Carbohydrate Oxidation During Exercise in Humans and the Role of Pharmacological Activation of PDC in Overriding These Changes

High-fat feeding inhibits pyruvate dehydrogenase complex (PDC)–controlled carbohydrate (CHO) oxidation, which contributes to muscle insulin resistance. We aimed to reveal molecular changes underpinning this process in resting and exercising humans. We also tested whether pharmacological activation of PDC overrides these diet-induced changes. Healthy males consumed a control diet (CD) and on two further occasions an isocaloric high-fat diet (HFD). After each diet, subjects cycled for 60 min after intravenous infusion with saline (CD and HFD) or dichloroacetate (HFD+DCA). Quadriceps muscle biopsies obtained before and after 10 and 60 min of exercise were used to estimate CHO use, PDC activation, and mRNAs associated with insulin, fat, and CHO signaling. Compared with CD, HFD increased resting pyruvate dehydrogenase kinase 2 (PDK2), PDK4, forkhead box class O transcription factor 1 (FOXO1), and peroxisome proliferator–activated receptor transcription factor α (PPARα) mRNA and reduced PDC activation. Exercise increased PDC activation and whole-body CHO use in HFD, but to a lower extent than in CD. Meanwhile PDK4 and FOXO1, but not PPARα or PDK2, mRNA remained elevated. HFD+DCA activated PDC throughout and restored whole-body CHO use during exercise. FOXO1 appears to play a role in HFD-mediated muscle PDK4 upregulation and inhibition of PDC and CHO oxidation in humans. Also, pharmacological activation of PDC restores HFD-mediated inhibition of CHO oxidation during exercise.
Purinergic Signaling and Hippocampal Long-Term Potentiation

The purines ATP and adenosine are widely recognized for their neuromodulatory effects. They have been shown to have effects on neurons via various receptors and interactions with glial cells. In particular, long-term potentiation (LTP) in hippocampal slice preparations has been found to be modulated by ATP and adenosine. This review gives an overview of purinergic signaling in relation to hippocampal LTP and memory formation. The data supports the hypothesis that adenosine mediates a tonic suppression of synaptic transmission. Thus, low adenosine levels appear to increase basal synaptic activity via a decreased activation of the inhibitor A1 receptor, consequently making it more difficult to induce LTP because of lower contrast. During high stimulation, the inhibition of neighboring pathways by adenosine, in combination with an A2a receptor activation, appears to increase contrast of excited pathways against a nonexcited background. This would enable amplification of specific signaling while suppressing non-specific events. Although a clear role for purinergic signaling in LTP is evident, more studies are needed to scrutinize the modulatory role of ATP and adenosine and their receptors in synaptic plasticity and memory.
Fourier analysis of facial profiles of young twins.

Twins studies provide a powerful approach to determining the relative contribution of genetics and environment to observed variation. Such studies assume trait differences in monozygous (MZ) twins are due to environmental factors and those in dizygous (DZ) twins are due to both genetic and environmental factors. This study quantitated facial profiles of twins using Fourier equations, determining their value in profile analysis and the assessment of the genetic contribution to facial shape. Standardized profile slide photographs of 79 pairs of 4-6 year-old twins (37 MZ pairs, 42 DZ pairs) were scanned and x and y coordinates were extracted from each profile using sellion and Camper's plane as references. The coordinates were subjected to Fourier analysis and the normalised vertex projection coefficients were studied. The means of the differences between coefficients for MZ co-twins did not differ significantly from that of DZ co-twins, although the DZ group showed higher mean differences in the higher harmonics. Subjective examination of superimposed reconstructions showed wider variation between DZ co-twins than MZ co-twins. Correct classification of twins by discriminant function analysis using Fourier coefficients was similar for both groups (MZ: 70.3%; DZ: 73.8%). Fourier analysis could quantitate facial profiles of young children and differentiate some details, but was unable to discriminate between genetic and environmental influences, and any possible interactions between these influences, on their overall facial profiles at this developmental stage.
Simulation modeling and analysis on asset planning for Emergency Medical System (EMS)

In recent decades, health care cost has increased dramatically, while health care organizations have been under severe pressure to provide improved quality health care for their patients. Several health care administrators have used discrete event simulation as an effective way for allocating resources to improve patient flow, while meeting health care delivery budget and increase patient satisfaction. The rapid growth in simulation software technology has created numerous new application opportunity, including more sophisticated implementations, as well as combining optimization and simulation for complex integrated facilities. This paper surveys the application of discrete-event simulation modeling to healthcare systems of clinics. We also present the overview of how simulation was used to investigate the reduction of waiting times in an mid-size city's Emergency Medical System, as well as in meeting future demand growth while minimizing long term capital expenditures.
A Connectionist Approach to Word Sense Disambiguation

Effective word sense disambiguation can play a crucial role in several important computational linguistic tasks. Problems such as information retrieval and machine translation rely upon accurate tagging of word senses. This paper will present an English word sense classifier based upon connectionist models of learning and behavior. Results perform comparably with state of the art statistical approaches in finely grained word sense disambiguation.
Advanced tree species identification using multiple leaf parts image queries

There has recently been increasing interest in using advanced computer vision techniques for automatic plant identification. Most of the approaches proposed are based on an analysis of leaf characteristics. Nevertheless, two aspects have still not been well exploited: (1) domain-specific or botanical knowledge (2) the extraction of meaningful and relevant leaf parts. In this paper, we describe a new automated technique for leaf image retrieval that attempts to take these particularities into account. The proposed method is based on local representation of leaf parts. The part-based decomposition is defined and usually used by botanists. The global image query is a combination of part sub-images queries. Experiments carried out on real world leaf images, the Pl@ntLeaves scan images (3070 images totalling 70 species), show an increase in performance compared to global leaf representation.
Black hole relics and inflation: Limits on blue perturbation spectra.

Blue primordial power spectra have spectral index [ital n][gt]1 and arise naturally in the recently proposed hybrid inflationary scenario. An observational upper limit on [ital n] is derived by normalizing the spectrum at the quadrupole scale and considering the possible overproduction of Planck mass relics formed in the final stage of primordial black hole evaporation. In the inflationary Universe with the maximum reheating temperature compatible with the observed quadrupole anisotropy, the upper limit is [ital n]=1.4, but it is slightly weaker for lower reheat temperatures. This limit applies over 57 decades of mass and is therefore insensitive to cosmic variance and any gravitational wave contribution to the quadrupole anisotropy. It is also independent of the dark matter content of the Universe and therefore the bias parameter. In some circumstances, there may be an extended dustlike phase between the end of inflation and reheating. In this case, primordial black holes form more abundantly and the upper limit is [ital n]=1.3.
Up From the Ashes: Age and Gender Effects on Post-Traumatic Growth in Bereavement

Researchers and clinicians are increasingly exploring the predictors and moderators of posttraumatic growth. To date, however, no studies have fully examined the interactive effects of age and gender in grief and post-traumatic growth. To that end, we examined the moderating effects of age and gender on the relations between grief and post-traumatic growth. A total of 414 adults, ages 18 to 66 years, who were bereaved for 2 years or less, completed a battery of self-report questionnaires. Results of a Gender (2) by Age (4) analysis of variance test showed few differences, overall. Small, significant gender differences were detected for current grief, with women expressing more grief than men. A main effect of age was also observed for grief, with emerging adults reporting less grief than middle-aged adults. A series of moderation models were conducted whereby the effects of gender and age on the relation between grief and post-traumatic growth were examined. Results showed small but significant moderation effects of gender, but not age. Results are discussed in terms of the need for more precision in the research examining post-traumatic growth, including the need for theoretical foundations rooted in both feminist and lifespan theories.