Miracle-dz/UniFAR-FTUs huggingface dataset:
SURVIVAL RATES OF CASSIN'S AND RHINOCEROS AUKLETS AT TRIANGLE ISLAND, BRITISH COLUMBIA

Abstract We estimated survival of Cassin's Auklet (Ptychoramphus aleuticus) and Rhinoceros Auklet (Cerorhinca monocerata) from recapture rates during 1994–1997. For both species, a two “age”-class model provided the best fit. Estimates of local adult survival were significantly lower for Cassin's Auklet (0.672 ± 0.047) than for Rhinoceros Auklet (0.829 ± 0.095). Our estimate of survival appears lower than that required for the maintenance of a stable population of Cassin's Auklets. The available information indicates that a low survival rate and a declining population at Triangle Island are plausible, particularly given the recent large scale oceanographic changes which have occurred in the North Pacific Ocean. Nevertheless, additional mark-recapture data and indexes of population size are required to rigorously demonstrate population declines at the world's largest Cassin's Auklet colony.
Promoter-distal RNA polymerase II binding discriminates active from inactive CCAAT/ enhancer-binding protein beta binding sites

Transcription factors (TFs) bind to thousands of DNA sequences in mammalian genomes, but most of these binding events appear to have no direct effect on gene expression. It is unclear why only a subset of TF bound sites are actively involved in transcriptional regulation. Moreover, the key genomic features that accurately discriminate between active and inactive TF binding events remain ambiguous. Recent studies have identified promoter-distal RNA polymerase II (RNAP2) binding at enhancer elements, suggesting that these interactions may serve as a marker for active regulatory sequences. Despite these correlative analyses, a thorough functional validation of these genomic co-occupancies is still lacking. To characterize the gene regulatory activity of DNA sequences underlying promoter-distal TF binding events that co-occur with RNAP2 and TF sites devoid of RNAP2 occupancy using a functional reporter assay, we performed cis-regulatory element sequencing (CRE-seq). We tested more than 1000 promoter-distal CCAAT/enhancer-binding protein beta (CEBPB)-bound sites in HepG2 and K562 cells, and found that CEBPB-bound sites co-occurring with RNAP2 were more likely to exhibit enhancer activity. CEBPB-bound sites further maintained substantial cell-type specificity, indicating that local DNA sequence can accurately convey cell-type–specific regulatory information. By comparing our CRE-seq results to a comprehensive set of genome annotations, we identified a variety of genomic features that are strong predictors of regulatory element activity and cell-type–specific activity. Collectively, our functional assay results indicate that RNAP2 occupancy can be used as a key genomic marker that can distinguish active from inactive TF bound sites.
Harmonizing Music the Boltzmann Way

Abstract Music harmonization has long been recognized as a highly intellectual process. Musicologists have studied music pieces by great composers and formulated a number of symbolic rules. However, these rules usually form only a set of heuristics and may not be absolutely precise. In this paper, we demonstrate how to train a Boltzmann machine to capture these syntactic rules and use it to construct an effective Boltzmann machine (EBM) to harmonize some unseen pieces. We have also incorporated ways to apply absolute constraints to the completion process. Our experiments demonstrate that using an EBM, ‘good’ harmonies can be non-deterministically synthesized along with a relative measure of their quality.
Wheat Storage Proteins : ISOLATION AND CHARACTERIZATION OF THE GLIADIN MESSENGER RNAs.

A total RNA extract was prepared from developing wheat seeds using guanidine-HCl to eliminate endogenous RNase activity. The RNA preparation, substantially free of protein, carbohydrate and DNA, was chromatographed on either a poly uridylic acid-agarose or poly guanylic acid-agarose column to yield a gliadin-enriched mRNA fraction. Only slight differences were observed for the products synthesized in a wheat germ cell-free translation system when either poly adenylic acid-enriched or cytosine-rich RNA was used as a template. These results are consistent with the high proline content of the gliadins and indicate that a large proportion of the mRNA activity in these RNA preparations is directed toward gliadin synthesis. After a second affinity chromatography step, the gliadin-enriched mRNA fraction was fractionated by two cycles on sucrose-density gradient centrifugation under denaturing conditions. The RNA sedimented as a broad band with a peak at 14S and a shoulder at the 11S region of the sucrose gradient. RNA from the peak 14S fraction translated predominantly the two major gliadin polypeptides which had molecular weights of 34,000 and 36,000. Analysis of the 14S RNA by methylmercury hydroxide-agarose gel electrophoresis revealed the presence of a predominant RNA species with a molecular size of 415,000 (1,200 nucleotides).
Towards a Dependency-Based PropBank of General Finnish

In this work, we present the first results of a project aiming at a Finnish Proposition Bank, an annotated corpus of semantic roles. The annotation is based on an existing treebank of Finnish, the Turku Dependency Treebank, annotated using the well-known Stanford Dependency scheme. We describe the use of the dependency treebank for PropBanking purposes and show that both annotation layers present in the treebank are highly useful for the annotation of semantic roles. We also discuss the specific features of Finnish influencing the development of a PropBank as well as the methods employed in the annotation, and finally, we present preliminary evaluation of the annotation quality.
Gender Composition and Small-Group Learning in Fourth-Grade Mathematics

Fourth graders (N = 112; 50 boys and 62 girls) from 4 classrooms participated in research on students' affective experiences and achievement outcomes in small-group learning in mathematics. Teachers designed and implemented a study that examined students' reported affective experiences in small groups associated with individual gender and group gender configuration. Students' reported experiences and achievement were assessed after each of 6 lessons and again after a 10-day delay. In general, students' reported personal experiences changed with increased exposure to their small group and were differently-adaptively-reconstructed upon delayed reflection. There were no results associated with individual student gender; group gender configuration emerged as an important dimension in students' reported helping behavior and affective experiences. Considerations based upon these and other results are offered that might be useful for teachers as they plan, enact, or reflect on their experiences with small-group learning.
Indoor Positioning Using Ultrawideband and Inertial Measurements

In this paper, we present an approach to combine measurements from inertial sensors (accelerometers and gyroscopes) with time-of-arrival measurements from an ultrawideband (UWB) system for indoor positioning. Our algorithm uses a tightly coupled sensor fusion approach, where we formulate the problem as a maximum a posteriori (MAP) problem that is solved using an optimization approach. It is shown to lead to accurate 6-D position and orientation estimates when compared to reference data from an independent optical tracking system. To be able to obtain position information from the UWB measurements, it is imperative that accurate estimates of the UWB receivers' positions and their clock offsets are available. Hence, we also present an easy-to-use algorithm to calibrate the UWB system using a maximum-likelihood (ML) formulation. Throughout this work, the UWB measurements are modeled by a tailored heavy-tailed asymmetric distribution to account for measurement outliers. The heavy-tailed asymmetric distribution works well on experimental data, as shown by analyzing the position estimates obtained using the UWB measurements via a novel multilateration approach.
DataViewer : A Scene Graph Based Visualization Library

This article outlines the capabilities of a scientific visualization toolkit called DataViewer, and compares it to analogous software. DataViewer was originally designed for the construction of the visualization part of certain computational steering packages, and consequently it is particularly straightforward to closely couple DataViewer with numerical calculations. Rendering is performed through a high-level scene graph which facilitates the easy construction of complex visualizations. DataViewer differs from other such libraries by allowing complex geometrical objects, which efficiently encapsulate large amounts of data, to be used as nodes in the scene graph. Graphics hardware access is through the OpenGL API.
Theoretically Optimal Datalog Rewritings for OWL 2 QL Ontology-Mediated Queries

We show that, for OWL2QL ontology-mediated queries with (i) ontologies of bounded depth and conjunctive queries of bounded treewidth, (ii) ontologies of bounded depth and bounded-leaf tree-shaped conjunctive queries, and (iii) arbitrary ontologies and bounded-leaf tree-shaped conjunctive queries, one can construct and evaluate nonrecursive datalog rewritings by, respectively, LOGCFL, NL and LOGCFL algorithms, which matches the optimal combined complexity.
5D extremal rotating black holes and CFT duals

Kerr/CFT correspondence has been recently applied to various types of 5D extremal rotating black holes. A common feature of all such examples is the existence of two chiral CFT duals corresponding to the U(1) symmetries of the near horizon geometry. In this paper, by studying the moduli space of the near horizon metric of five-dimensional extremal black holes which are asymptotically flat or AdS, we realize an SL(2, ) modular group which is a symmetry of the near horizon geometry. We show that there is a lattice of chiral CFT duals corresponding to the moduli points identified under the action of the modular group. The microscopic entropy corresponding to all such CFTs is equivalent and is in agreement with the Bekenstein–Hawking entropy.
The Influence of the Tone of Feedback Prompts on the Learning Behavior and Satisfaction of University Students in a Multiple Cue Probablility Learning Task

The Influence of the Tone of Feedback Prompts on the Learning Behavior and Satisfaction of University Students in a Multiple Cue Probability Learning Task by Sebastian Thomas 11 Previous research has shown that feedback tone affects users' perceptions of computer systems. This study tested the generality of this finding and explored possible interactions of feedback tone with feedback validity and user gender. The task was a multiple cue probability learning (MCPL) problem. Experiment 1 was used to establish an appropriate level of task difficulty and ensure the effectiveness of cognitive feedback. In Experiment 2, cognitive feedback validity and feedback tone were manipulated as within-subjects variables. Women improved substantially over blocks of trials in both tone conditions whereas men improved only in the polite condition. Most women preferred polite feedback whereas most men preferred the opposite. These results extend the range of tasks in which feedback tone has been shown to affect users' reactions to interfaces. These results suggest dissociation between performance and preference as men improved more with polite feedback although they preferred direct feedback.
Loosely Coupling Java Algorithms and XML Parsers: a Performance-Oriented Study

The adoption of XML to represent any kind of data and documents, even complex and huge, is becoming a matter of fact. However, interfacing algorithms and applications with XML Parsers requires to adapt algorithms and applications: event-based SAX Parsers need algorithms that react to events generated by the parser. But parsing/loading XML documents provides poor performance (if compared to reading flat files): therefore, several researches are trying to address this problem by improving the parsing phase, e.g., by adopting condensed or binary representations of XML documents. This paper deals with the other side of the coin, i.e., the problem of coupling algorithms with XML Parsers, in a way that does not require to change the active (polling-based) nature of many algorithms and provides acceptable performance during execution; this problem becomes even more important when we consider Java algorithms, that usually are less efficient than C or C++ algorithms. This paper presents a study about the problem of loosely coupling Java algorithms with XML Parsers. The coupling is loose because the algorithm should be unaware of the particular interface provided by parsers. We consider several coupling techniques, and we compare them by analyzing their performance. The evaluation leads us to identify the coupling techniques that perform better, depending on the specific algorithm’s needs and application scenario.
Game Theoretic Modeling of Malicious Users in Collaborative Networks

If a network is to operate successfully, its users need to collaborate. Collaboration takes the form of following a network protocol and involves some resource expenditure on the part of the user. Therefore, users cannot automatically be expected to follow the protocol if they are not forced to. The situation is exacerbated by the presence of malicious users whose objective is to damage the network and increase the cost incurred by the legitimate users. The legitimate users are, at least initially, unaware of the type (legitimate or malicious) of the other users. Our contribution is a model for the strategic interaction of legitimate and malicious users as described above. The model is based on repeated graphical games with incomplete information. We describe and analyze two specific instantiations, aiming to demonstrate the modeliquests expressive power and tractability. The main benefit we see from using game theory for this essentially security problem is the ability to bound the damage caused by the malicious users.
Dispersal barriers and isolation among deep‐sea mussel populations (Mytilidae: Bathymodiolus) from eastern Pacific hydrothermal vents

Deep‐sea hydrothermal vent species are widely dispersed among habitat islands found along the global mid‐ocean ridge system. We examine factors that affect population structure, gene flow and isolation in vent‐endemic mussels of the genus Bathymodiolus from the eastern Pacific Ocean. Mussels were sampled from localities including the Galapagos Rift (GAR, 0°48′ N; 86°10′ W) and the East Pacific Rise (EPR, 13° N to 32° S latitude) across a maximum distance of 4900 km. The sampled range crossed a series of topographical features that interrupt linear aspects of the ridge system, and it encompassed regions of strong cross‐axis currents that could impede along‐axis dispersal of mussel larvae. Examinations of mitochondrial DNA sequences and allozyme variation revealed significant barriers to gene flow along the ridge axis. All populations from the GAR and EPR from 13° N to 11° S were homogeneous genetically and appeared to experience unimpeded high levels of interpopulational gene flow. In contrast, mussels from north and south of the Easter Microplate were highly divergent (4.4%), possibly comprising sister‐species that diverged after formation of the microplate ≈ 4.5 Ma. Strong cross‐axis currents associated with inflated bathymetry of the microplate region may reinforce isolation across this region.
Common visual pattern discovery via spatially coherent correspondences

We investigate how to discover all common visual patterns within two sets of feature points. Common visual patterns generally share similar local features as well as similar spatial layout. In this paper these two types of information are integrated and encoded into the edges of a graph whose nodes represent potential correspondences, and the common visual patterns then correspond to those strongly connected subgraphs. All such strongly connected subgraphs correspond to large local maxima of a quadratic function on simplex, which is an approximate measure of the average intra-cluster affinity score of these subgraphs. We find all large local maxima of this function, thus discover all common visual patterns and recover the correct correspondences, using replicator equation and through a systematic way of initialization. The proposed algorithm possesses two characteristics: 1) robust to outliers, and 2) being able to discover all common visual patterns, no matter the mappings among the common visual patterns are one to one, one to many, or many to many. Extensive experiments on both point sets and real images demonstrate the properties of our proposed algorithm in terms of robustness to outliers, tolerance to large spatial deformations, and simplicity in implementation.
Responsible innovation, the art and craft of anticipation

Anticipation is required for anticipatory governance and generally considered to be a cornerstone of responsible innovation, but is it necessarily anticipation of the future? In regard to emerging technologies, responsible research and innovation appear to call for judgments of what these technologies might or will effect in the future. The paper questions this assumption by clarifying the meaning and scope of anticipation. One can learn to anticipate what can happen in the world as we know it. But emerging technologies are thought to change the world in relevant ways which is why the question of the future is raised in the first place. Though anticipation does not reach as far as a changed world in the future, this is not necessary for anticipatory governance or for anticipation as part of responsible research and innovation.
Analysis of Base-Position Error Rate of Next-Generation Sequencing to Detect Tumor Mutations in Circulating DNA.

BACKGROUND Detecting single-nucleotide variations and insertions/deletions in circulating tumor DNA is challenging because of their low allele frequency. The clinical use of circulating tumor DNA to characterize tumor genetic alterations requires new methods based on next-generation sequencing. METHODS We developed a method based on quantification of error rate of each base position [position error rate (PER)]. To identify mutations, a binomial test was used to compare the minor-allele frequency to the measured PER at each base position. This process was validated in control samples and in 373 plasma samples from patients with lung or pancreatic cancer. RESULTS Minimal mutated allele frequencies were 0.003 for single-nucleotide variations and 0.001 for insertions/deletions. Independent testing performed by droplet digital PCR (n = 231 plasma samples) showed strong agreement with the base-PER method (κ = 0.90). CONCLUSIONS Targeted next-generation sequencing analyzed with the base-PER method represents a robust and low cost method to detect circulating tumor DNA in patients with cancer.
Issues in the pharmacological treatment of obsessive–compulsive disorder

Aims: Obsessive–compulsive disorder (OCD) preferentially responds to a class of antidepressants called serotonin reuptake inhibitors (SRI). This review discusses certain issues unique to pharmacological treatment of OCD: choice of SRI, dose and duration of treatment, options after first failed SRI trial and treatment of SRI non‐responders.
The Terminal Design of the Energy Self-Sufficiency Internet of Things

As quite a potential technology, the Internet of Things is bound to experience a widespread application in a few years. This paper will conduct an in-depth study on the terminal of Internet of Things. Through studying the general architecture of the Internet of Things, according to its application requirements and technical conditions, the paper analyze the factors affecting the development of the Internet of Things, then adopts the module design to design the universal terminal structure of the Internet of Things. Since the energy consumption is a core issue in the wireless sensor network design, the level of energy management strategy will continue to improve with the development of wireless sensor networks. The paper proposes the energy management system based on energy collection. The paper also initially achieves a system which can provide energy permanently to the Internet of Things using solar energy and lithium batteries.
A comprehensive comparison of general RNA–RNA interaction prediction methods

RNA–RNA interactions are fast emerging as a major functional component in many newly discovered non-coding RNAs. Basepairing is believed to be a major contributor to the stability of these intermolecular interactions, much like intramolecular basepairs formed in RNA secondary structure. As such, using algorithms similar to those for predicting RNA secondary structure, computational methods have been recently developed for the prediction of RNA–RNA interactions. We provide the first comprehensive comparison comprising 14 methods that predict general intermolecular basepairs. To evaluate these, we compile an extensive data set of 54 experimentally confirmed fungal snoRNA–rRNA interactions and 102 bacterial sRNA–mRNA interactions. We test the performance accuracy of all methods, evaluating the effects of tool settings, sequence length, and multiple sequence alignment usage and quality. Our results show that—unlike for RNA secondary structure prediction—the overall best performing tools are non-comparative energy-based tools utilizing accessibility information that predict short interactions on this data set. Furthermore, we find that maintaining high accuracy across biologically different data sets and increasing input lengths remains a huge challenge, causing implications for de novo transcriptome-wide searches. Finally, we make our interaction data set publicly available for future development and benchmarking efforts.
Applied Time Series Analysis for the Social Sciences

McCleary and Hay have made time series analysis techniques -- the Box-Jenkins or ARIMA methods -- accessible to the social scientist. Rejecting the dictum that time series analysis requires substantial mathematical sophistication, the authors take a clearly written, step-by-step approach. They describe the logic behind time series analysis, and its possible applications in impact assessment, causal modelling and forecasting, multivariate time series and parameter estimation.
Why women enter into entrepreneurship: an explanatory model

Develops a model of the factors that motivate women to start their own businesses. Qualitative research involving 25 French women entrepreneurs were used to explore case study situations. The research identified a number of situations that relate to women’s decisions to become entrepreneurs, namely “dynastic compliance”, “no other choice”, “entrepreneurship by chance”, “natural succession”, “forced entrepreneurship”, “informed entrepreneur” and “pure entrepreneur”. The findings do not reinforce the assumption that a majority of women become entrepreneurs for reasons of necessity and identified antecedents to the generalised “push”, “pull” and environmental motives.