Miracle-dz/UniFAR-FTUs huggingface dataset:
The Reinforcing Effects of Fox News ∗

In recent decades, cable television has expanded Americans’ choices for televised news substantially. This paper examines whether access to a more conservative news source— the Fox News cable channel—influences vote intentions. According to prior media effects research, the most likely impact of Fox News access is to reinforce voters’ predispositions and thus to polarize public opinion. To test that possibility with individual-level data, we identify local Fox News availability for 22,592 respondents to the 2000 National Annenberg Election Survey. Using aggregate-level voting data, DellaVigna and Kaplan (2007) finds a pro-Republican effect of Fox News access that is largest in Democratic communities. In contrast, we find an average treatment effect indistinguishable from zero. Yet we also find a sizable effect on the vote intentions of Republicans and pure independents. Consistent with a long tradition of media effects studies, access to Fox News reinforces Republican loyalties without persuading Democrats to vote against their party. ∗We are grateful to Jens Hainmueller, Danny Hayes, Gabriel Lenz, Jonathan Mummolo, and Paul Musgrave for helpful comments. We also acknowledge the tireless research assistance of Christopher Duffner, Patrick Gavin, Lindsay Pettingill, Matt Rogers, and Will Tamplin. Ken Winneg of the Annenberg Public Policy Center facilitated our access to restricted data from the 2000 NAES. We also thank Stefano DellaVigna and Ethan Kaplan for publicly posting their town-level Fox News availability data. A previous draft of this paper was presented at the D.C. Area American Politics Workshop at George Washington University. †Assistant Professor, Department of Government, Georgetown University, 681 ICC, Washington, DC 20057, dh335@georgetown.edu. ‡Assistant Professor, Public Policy Institute and Department of Government, Georgetown University, 100 Old North Hall, Washington, DC 20057, jml89@georgetown.edu.
An explanation-based, visual debugger for one-way constraints

This paper describes a domain-specific debugger for one-way constraint solvers. The debugger makes use of several new techniques. First, the debugger displays only a portion of the dataflow graph, called a <i>constraint slice</i>, that is directly related to an incorrect variable. This technique helps the debugger scale to a system containing thousands of constraints. Second, the debugger presents a visual representation of the solver's data structures and uses color encodings to highlight changes to the data structures. Finally, the debugger allows the user to point to a variable that has an unexpected value and ask the debugger to suggest reasons for the unexpected value. The debugger makes use of information gathered during the constraint satisfaction process to generate plausible suggestions. Informal testing has shown that the explanatory capability and the color coding of the constraint solver's data structures are particularly useful in locating bugs in constraint code.
Ensemble Methods with Voting Protocols Exhibit Superior Performance for Predicting Cancer Clinical Endpoints and Providing More Complete Coverage of Disease-Related Genes

In genetic data modeling, the use of a limited number of samples for modeling and predicting, especially well below the attribute number, is difficult due to the enormous number of genes detected by a sequencing platform. In addition, many studies commonly use machine learning methods to evaluate genetic datasets to identify potential disease-related genes and drug targets, but to the best of our knowledge, the information associated with the selected gene set was not thoroughly elucidated in previous studies. To identify a relatively stable scheme for modeling limited samples in the gene datasets and reveal the information that they contain, the present study first evaluated the performance of a series of modeling approaches for predicting clinical endpoints of cancer and later integrated the results using various voting protocols. As a result, we proposed a relatively stable scheme that used a set of methods with an ensemble algorithm. Our findings indicated that the ensemble methodologies are more reliable for predicting cancer prognoses than single machine learning algorithms as well as for gene function evaluating. The ensemble methodologies provide a more complete coverage of relevant genes, which can facilitate the exploration of cancer mechanisms and the identification of potential drug targets.
Kaxiras’s Porphyrin: DFT Modeling of Redox-Tuned Optical and Electronic Properties in a Theoretically Designed Catechol-Based Bioinspired Platform

A detailed computational investigation of the 5,6-dihydroxyindole (DHI)-based porphyrin-type tetramer first described by Kaxiras as a theoretical structural model for eumelanin biopolymers is reported herein, with a view to predicting the technological potential of this unique bioinspired tetracatechol system. All possible tautomers/conformers, as well as alternative protonation states, were explored for the species at various degrees of oxidation and all structures were geometry optimized at the density functional theory (DFT) level. Comparison of energy levels for each oxidized species indicated a marked instability of most oxidation states except the six-electron level, and an unexpected resilience to disproportionation of the one-electron oxidation free radical species. Changes in the highest energy occupied molecular orbital (HOMO)–lowest energy unoccupied molecular orbital (LUMO) gaps with oxidation state and tautomerism were determined along with the main electronic transitions: more or less intense absorption in the visible region is predicted for most oxidized species. Data indicated that the peculiar symmetry of the oxygenation pattern pertaining to the four catechol/quinone/quinone methide moieties, in concert with the NH centers, fine-tunes the optical and electronic properties of the porphyrin system. For several oxidation levels, conjugated systems extending over two or more indole units play a major role in determining the preferred tautomeric state: thus, the highest stability of the six-electron oxidation state reflects porphyrin-type aromaticity. These results provide new clues for the design of innovative bioinspired optoelectronic materials.
A novel extracellular low‐temperature active phytase from Bacillus aryabhattai RS1 with potential application in plant growth

Bacillus aryabhattai RS1 isolated from rhizosphere produced an extracellular, low temperature active phytase. The cultural conditions for enzyme production were optimized to obtain 35 U mL−1 of activity. Purified phytase had specific activity and molecular weight of 72.97 U mg−1 and ∼40 kDa, respectively. The enzyme was optimally active at pH 6.5 and 40°C and was highly specific to phytate. It exhibited higher catalytic activity at low temperature, retaining over 40% activity at 10°C. Phytase was more thermostable in presence of Ca2+ ion and retained 100% residual activity on preincubation at 20–50°C for 30 min. Partial phytase encoding gene, phyB (816 bp) was cloned and sequenced. The encoded amino acid sequence (272 aa) contained two conserved motifs, DA[A/T/E]DDPA[I/L/V]W and NN[V/I]D[I/L/V]R[Y/D/Q] of β‐propellar phytase and had lower sequence homology with other Bacillus phytases, indicating its novelty. Phytase and the bacterial inoculum were effective in improving germination and growth of chickpea seedlings under phosphate limiting condition. Moreover, the potential applications of the enzyme with relatively high activity at lower temperatures (20–30°C) could also be extended to aquaculture and food processing. © 2017 American Institute of Chemical Engineers Biotechnol. Prog. , 33:633–641, 2017
The IS-BioBank project

Advances of high throughput technologies have yielded the possibility to investigate human cells of healthy and morbid ones at different levels. Consequently, this has made possible the discovery of new biological and biomedical data and the proliferation of a large number of databases. In this paper, we describe the IS-BioBank (Integrated Semantic Biological Data Bank) proposal. It consists of the realization of a framework for enabling the interoperability among different biological data sources and for ultimately supporting expert users in the complex process of extraction, navigation and visualization of the precious knowledge hidden in such a huge quantity of data. In this framework, a key role has been played by the Connectivity Map, a databank which relates diseases, physiological processes, and the action of drugs. The system will be used in a pilot study on the Multiple Myeloma (MM).
Nonlinear camera response functions and image deblurring

This paper investigates the role that nonlinear camera response functions (CRFs) have on image deblurring. In particular, we show how nonlinear CRFs can cause a spatially invariant blur to behave as a spatially varying blur. This can result in noticeable ringing artifacts when deconvolution is applied even with a known point spread function (PSF). In addition, we show how CRFs can adversely affect PSF estimation algorithms in the case of blind deconvolution. To help counter these effects, we introduce two methods to estimate the CRF directly from one or more blurred images when the PSF is known or unknown. While not as accurate as conventional CRF estimation algorithms based on multiple exposures or calibration patterns, our approach is still quite effective in improving deblurring results in situations where the CRF is unknown.
"Kernelized" Self-Organizing Maps for Structured Data

The suitability of the well known kernels for trees, and the lesser known SelfOrganizing Map for Structures for categorization tasks on structured data is investigated in this paper. It is shown that a suitable combination of the two approaches, by defining new kernels on the activation map of a Self-Organizing Map for Structures, can result in a system that is significantly more accurate for categorization tasks on structured data. The effectiveness of the proposed approach is demonstrated experimentally on a relatively large corpus of XML formatted data.
Community detection in complex networks using flow simulation

Community detection and analysis is an important part of studying the organization of complex systems in real world, and it's extensively applied on many fields. Recently, many of existing algorithms are not effective or the results are unstable. In this paper, a new method of community testing is proposed by us based on the conception of flow field. In our approach, each node is represented as a field source and has a tendency to forward data to the connected nodes with highest field strength, after some iterations the nodes with same data information form a community. It is evaluated by us for the approach on some synthetic and real-world networks whose community structures are known. It is demonstrated that the approach performs wellin effectiveness and robustness.
Modulation of spinal inhibitory reflexes depends on the frequency of transcutaneous electrical nerve stimulation in spastic stroke survivors

Abstract Neurophysiological studies in healthy subjects suggest that increased spinal inhibitory reflexes from the tibialis anterior (TA) muscle to the soleus (SOL) muscle might contribute to decreased spasticity. While 50 Hz is an effective frequency for transcutaneous electrical nerve stimulation (TENS) in healthy subjects, in stroke survivors, the effects of TENS on spinal reflex circuits and its appropriate frequency are not well known. We examined the effects of different frequencies of TENS on spinal inhibitory reflexes from the TA to SOL muscle in stroke survivors. Twenty chronic stroke survivors with ankle plantar flexor spasticity received 50-, 100-, or 200-Hz TENS over the deep peroneal nerve (DPN) of the affected lower limb for 30 min. Before and immediately after TENS, reciprocal Ia inhibition (RI) and presynaptic inhibition of the SOL alpha motor neuron (D1 inhibition) were assessed by adjusting the unconditioned H-reflex amplitude. Furthermore, during TENS, the time courses of spinal excitability and spinal inhibitory reflexes were assessed via the H-reflex, RI, and D1 inhibition. None of the TENS protocols affected mean RI, whereas D1 inhibition improved significantly following 200-Hz TENS. In a time-series comparison during TENS, repeated stimulation did not produce significant changes in the H-reflex, RI, or D1 inhibition regardless of frequency. These results suggest that the frequency-dependent effect of TENS on spinal reflexes only becomes apparent when RI and D1 inhibition are measured by adjusting the amplitude of the unconditioned H-reflex. However, 200-Hz TENS led to plasticity of synaptic transmission from the antagonist to spastic muscles in stroke survivors.
Syrphidae (Diptera) from the Greek island of Lesvos, with description of two new species

The results of the hoverfly (Syrphidae) collection by the ‘Malloch Society’ on the Greek island of Lesvos are presented.Fieldwork took place from February to March 2006 and from May to June 2010. An account of 66 species from 28 generais provided including two species new to science, five species new to Greece and data for several rarely recorded species.We describe Eumerus armatus Ricarte and Rotheray sp. nov., a medium size species with red abdomen. We also describe Sphiximorpha hiemalis Ricarte, Nedeljkovic and Hancock sp. nov., a hairy species with distinctive colour and pollinositypatterns and abdomen shape. The female of Eumerus claripennis Coe, 1957 is described and the male genitalia are figured.The majority of species encountered belonged to the typically Mediterranean genera Eumerus (8 spp.), Merodon (16 spp.)and Paragus (6 spp.). Approximately 71% of the recorded species also occur in Turkey. This supports the idea that West Mediterranean and Anatolian faunas overlap in Lesvos.
Consistent sets of lines with no colorful incidence

We consider incidences among colored sets of lines in $\mathbb{R}^d$ and examine whether the existence of certain concurrences between lines of $k$ colors force the existence of at least one concurrence between lines of $k+1$ colors. This question is relevant for problems in 3D reconstruction in computer vision.
Pattern Search in Temporal Social Networks

Due to the wide availability of social media and the wide range of real-life and human-centered applications, social networks have become an attractive research area. However, the temporal aspect of relations between entities in a social network has been widely ignored. We argue that the temporal aspect of social networks is the key to understand interactions and other phenomena happening in these networks and should thus be considered more closely. In this work we address the problem of pattern search in temporal social networks, thus finding all occurrences of a temporal pattern in a large temporal social network. As a first step, we define a temporal pruning criterion, which allows to quickly reduce the search space of candidates. Then, we present an index structure which allows to quickly find the occurrences of simple temporal network structures, from which more complex query structures can be derived from. Our experimental evaluation on a real-world temporal social network shows the effectiveness of our pruning approach and our proposed index structures, reducing the search-time for small temporal patterns by many orders of magnitude.
Beamforming System Combined with Quasi-Orthogonal Space-Time Block Coding

A beamforming system combined with fourbranch space-time block encoder is proposed. This leads to higher system performance and system flexibility in that the number of transmit antennas is not limited unlike transmit diversity system. Our system shows mainly three interesting results. First, diversity gain from space-time block coding (STBC) and beamforming gain are observed. Second the effect of angular spread leads to performance improvement as angular spread increase up to some threshold. It indicates that in the case of rich scattering environments such as indoor cases, we can expect the effect of our system to be more reliable. Finally, we can improve system performance while the code rate is preserved.
Increased mediator complex subunit 15 expression is associated with poor prognosis in hepatocellular carcinoma

Mediator complex subunit 15 (MED15) is a coactivator involved in the regulated transcription of RNA polymerase II-dependent genes and serves an oncogenic role in numerous types of cancer. However, the expression and function of MED15 in hepatocellular carcinoma (HCC) remain unknown. In the present study, the aim was to investigate the expression and clinical significance of MED15 in HCC. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemical analysis revealed that MED15 mRNA and protein levels were significantly upregulated in HCC tissues compared with those in the corresponding adjacent non-tumor liver tissues. Furthermore, analyzing data from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and GSE14520 datasets revealed a significant correlation between MED15 expression and the tumor size (P=0.033), Barcelona Clinic Liver Cancer stage (P=0.031), α-fetoprotein levels (P=0.002) and metastasis risk (P=0.001). Furthermore, patients with high MED15 expression levels had a shorter survival time compared with those with low MED15 expression levels (P<0.05). Univariate and multivariate analyses further revealed that MED15 may be an independent prognostic factor for the overall survival of HCC patients (hazard ratio, 1.762; 95% confidence interval, 1.077–2.882; P<0.05). In addition, MED15 expression was positively associated with hypoxia-inducible factor 1α expression in the TCGA-LIHC and GSE14520 datasets (P<0.01). In conclusion, the data reported in the present study indicated that MED15 is overexpressed in HCC and may represent a novel prognostic biomarker for patients with HCC.
User-guided Repairing of Inconsistent Knowledge Bases

Repairing techniques for relational databases have leveraged in- tegrity constraints to detect and then resolve errors in the data. User guidance has started to be employed in this setting to avoid a prohibitory exploration of the search space of solutions. In this pa- per, we present a user-guided repairing technique for Knowledge Bases (KBs) enabling updates suggested by the users to resolve errors. KBs exhibit more expressive constraints with respect to relational tables, such as tuple-generating dependencies (TGDs) and negative rules (a form of denial constraints). We consider TGDs and a notable subset of denial constraints, named contra- diction detecting dependencies (CDDs). We propose user-guided polynomial-delay algorithms that ensure the repairing of the KB in the extreme cases of interaction among these two classes of constraints. To the best of our knowledge, such interaction is so far unexplored even in repairing methods for relational data. We prove the correctness of our algorithms and study their feasibility in practical settings. We conduct an extensive experimental study on synthetically generated KBs and a real-world inconsistent KB equipped with TGDs and CDDs. We show the practicality of our proposed interactive strategies by measuring the actual delay time and the number of questions required in our interactive framework.
Constant-Time Predictive Distributions for Gaussian Processes

One of the most compelling features of Gaussian process (GP) regression is its ability to provide well-calibrated posterior distributions. Recent advances in inducing point methods have sped up GP marginal likelihood and posterior mean computations, leaving posterior covariance estimation and sampling as the remaining computational bottlenecks. In this paper we address these shortcomings by using the Lanczos algorithm to rapidly approximate the predictive covariance matrix. Our approach, which we refer to as LOVE (LanczOs Variance Estimates), substantially improves time and space complexity. In our experiments, LOVE computes covariances up to 2,000 times faster and draws samples 18,000 times faster than existing methods, all without sacrificing accuracy.
Plants with possible psychoactive effects used by the Krahô Indians, Brazil.

OBJECTIVE In spite of the richness of the Brazilian biodiversity, no phytomedicines have been developed from this flora with the purpose of being used in psychiatric treatments. The objective of the present study was to document the use of plants with possible psychoactive effects in rituals performed by the Krahô Indians, who live in the cerrado savannahs biome in the central region of Brazil. Also, the present data were compared with the data obtained during a review of the literature on the use of psychoactive plants by 25 Brazilian indigenous groups. METHOD The study was carried out during two years of fieldwork during which anthropological and botanical methods were employed. RESULTS Seven local shamans were interviewed and they indicated 98 formulas, consisting of 45 plant species that appear to have psychoactive properties and were used in 25 different treatments. Some of the psychoactive properties were "prevention of madness", "stimulant effect", "tranquilizing effect", "prevention of tremors", "longer sleeping period", "open mind" and "induction of sleep". This article also describes the review of literature, which recorded 58 plants that may have psychoactive effects used by 25 Brazilian Indian cultures. CONCLUSION The treatment of psychological/psychiatric disorders based on the plants used by the Krahô Indians is very rich. It is also observed among other Brazilian indigenous groups. Future phytochemical and pharmacological studies on these plants may develop new medicines to treat psychiatric disorders.
Effective protection of fish on inshore coral reefs depends on the scale of mangrove-reef connectivity

Connectivity is an important consideration in conservation, but is rarely quantified when assessing marine reserve performance. Mangrove-reef connectivity is known to enhance reserve effectiveness when habitats are close together (< 250 m apart). Coral reefs are, however, often farther from mangroves, making it difficult to integrate mangrove-reef connectivity into conservation more widely. To determine if connectivity affects reserve performance beyond 250 m, we examined effects on reef fish in Hervey Bay, Queensland, Australia. Reserves affected fish assemblages and enhanced the abundances of harvested species and key functional groups on reefs within 500 m of mangroves (about 10 times greater inside reserves), but not on isolated reefs. Connectivity can affect reserve performance over broader distances than previously shown. We suggest that connectivity effects on inshore reef fish may simply be amplified on reefs located closest to adjacent mangroves, provided those reefs are within the migratory capabilities of fish. Mangrove-reef connectivity should be viewed as an important conservation target and may be broadly incorporated into reserve design by prioritizing the protection of seascapes where mangroves and reefs are closest.