Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of multiple conformations of the E-domain of 5S rRNA from Escherichia coli in solution and in crystals by NMR spectroscopy

NMR spectroscopy of the E-domain fragment of Escherichia coli 5S rRNA indicates that this molecule exists in solution as either a stem-loop or as a duplex with two U-U base pairs in the bulge region. At temperatures below 27 degrees C, interconversion between the monomeric and dimeric forms in solution occurs on a time scale of weeks and allows the preparation of samples on which NMR structure determinations can be carried out on predominantly monomeric or dimeric species. The NMR results obtained provide comparison data for the distinction between A- and B-form E.coli 5S rRNA and for the possible kinetics of conversion between these forms. NMR evidence is presented that the duplex form also exists in crystals and suggestions are made for means to obtain stem-loop conformations of E-domain and other small RNA stem-loop sequences in crystals.
Compositional Verification of Timing Constraints for Embedded Real-Time Systems

In real-time software, not only computation errors but also timing errors can cause system failures, which eventually result in significant physical damages or threats to human life. To efficiently guarantee the timely execution of expected functions, it is necessary to clearly specify and formally verify timing requirements before performing detailed system design. This paper proposes a compositional approach to specifying and verifying timing requirements for real-time systems in a systematic manner. We specify both requirements and specification of a system using Modular TER nets, an extension of TER nets, to support timing analysis in a compositional way. By incrementally composing the requirement model and the specification model, we can check timing anomalies in requirements and the specification model. Key-Words: Timing constraints, real-time systems, timing verification, compositional analysis
Indri : A language-model based search engine for complex queries ( extended version )

Search engines are a critical tool for intelligence analysis. A number of innovations for search have been introduced since research with an emphasis on analyst needs began in the TIPSTER project. For example, the Inquery search engine introduced support for specification of complex queries in a probabilistic inference network framework. Recent research on language model-ing has led to the development of Indri, a search engine that combines the best features of inference nets and language modeling in an architecture designed for large-scale applications. In this paper, we describe the Indri system and show how the query language is designed to support modern language technologies. We also present results demonstrating that Indri is both effective and efficient.
Leverage and limitations of the EU's influence in the eastern neighbourhood : a study of compliance with the EU's justice and home affairs' standards in Georgia, Moldova and Ukraine

When the European Neighbourhood Policy (ENP) was launched in 2004 expectations of its potential were low because it lacks the ability to offer EU membership as an incentive, which was found to be pivotal for the EU to have influence in the Central and Eastern European Countries (CEECs). Nevertheless, progress reports have demonstrated that some convergence toward the EU standards has taken place in the neighbouring countries. This research seeks to understand under which conditions compliance takes place, what explains the variation in (non)compliance with the EU standards in the area of Justice and Home Affairs (JHA) and what influence does the EU have. It examines formal and behavioural compliance with the EU action plan recommendations in the area of border guard reform, readmission agreement, asylum and refugee protection, and criminalisation of human trafficking in Georgia, Moldova and Ukraine. The three states have all expressed interest in EU membership, but they vary in their potential to be considered as candidates and in their identification with the EU. Rather than assuming that the EU’s influence is low in the neighbourhood because it cannot offer a certain membership incentive, this research studies the problem by focusing on a combination of explanatory factors drawn from rational choice and sociological/constructivist institutionalism both at the macro level (strength of membership prospect and identification with the EU) and at the issue-specific levels. The research demonstrates that the EU’s influence is differential and dependent on domestic, external and issue-specific conditions. The results indicate that the EU is capable of eliciting influence in the JHA area without a certain EU membership prospect. However, when the country perceives that there is a possibility to accede to the EU, compliance with the EU standards has been more even across the four issue areas and at the formal and behavioural levels.
Path Planning for Mobile Beacon Nodes in Localization for Wireless Sensor Networks

Abstract A path planning for mobile beacon nodes is presented based on the node localization problem of WSN. The beacon nodes define the unknown node position by using ranging method of RSSI. By analyzing defects of a static trajectory, random trajectory, the beacon nodes move to the maximum coverage of unlocated nodes. The simulation result demonstrates that this algorithm obtains good localization performance and can be well adapted to the WSN node localization problem.
Settler Sovereignty: Jurisdiction and Indigenous People in America and Australia, 1788–1836

* Introduction *1. Jurisdiction, Territory and Sovereignty in Empire *2. Pluralism as Policy *3. Indigenous Jurisdiction and Spatial Order *4. Legality and Lawlessness *5. The Limits of Jurisdiction *6. Farmbrough's Fathoming and Transitions in Georgia *7. Lego'me and Territoriality in New South Wales *8. Perfect Settler Sovereignty * Conclusion
Factors Affecting Labor Supply Decisions and Retirement Income

Recent policy has focused on alleviating poverty among the elderly, with varying degrees of success. Gains to some subsets of the elderly population have come at the expense of others. A component of the policy debate has been identifying factors which might influence labor force participation decisions and the effects such decisions will have on retirement income and its adequacy for a growing elderly population. While models of retirement behavior are becoming increasingly sophisticated, most fail to capture key elements such as expectations and uncertainty. This is in part due to the reduced form nature of policy experiments; parameters are estimated under a current policy and used to predict effects of an alternative scenario. Such an approach implicitly assumes that the only difference in the alternative setting is the change in policy and does not adequately account for endogeneity of decisions and responses to these changes. This paper reviews factors affecting the labor supply decision, their interactions with and implications for subsequent retirement income, and identifies important methods and data requirements necessary to model complicated dynamic behavior more accurately.
Retrieval from Noisy E-Discovery Corpus in the Absence of Training Data

OCR errors hurt retrieval performance to a great extent. Research has been done on modelling and correction of OCR errors. However, most of the existing systems use language dependent resources or training texts for studying the nature of errors. Not much research has been reported on improving retrieval performance from erroneous text when no training data is available. We propose a novel algorithm for detecting OCR errors and improving retrieval performance on an E-Discovery corpus. Our contribution is two-fold : (1) identifying erroneous variants of query terms for improvement in retrieval performance, and (2) presenting a scope for a possible error-modelling in the erroneous corpus where clean ground truth text is not available for comparison. Our algorithm does not use any training data or any language specific resources like thesaurus. It also does not use any knowledge about the language except that the word delimiter is blank space. The proposed approach obtained statistically significant improvements in recall over state-of-the-art baselines.
A scalable high-performance active network node

Active networking in environments built to support link rates up to several gigabits per second poses many challenges. One such challenge is that the memory bandwidth and individual processing power of the router's microprocessors limit the total available processing power of a router. In this article we identify and describe three components, which promise a high-performance active network solution. This implements the key features typical to active networking, such as automatic protocol deployment and application specific processing, and it is suitable for a gigabit environment. First, we describe the hardware of the active network node (ANN), a scalable high-performance platform based on off-the-shelf CPUs connected to a gigabit ATM switch backplane. Second, we introduce the ANN's modular, extensible, and highly efficient operating system (NodeOS). Third, we describe an execution environment running on top of the NodeOS, which implements a novel large-scale active networking architecture called distributed code caching.
Universitt at Dortmund on a Markovian Process Algebra on a Markovian Process Algebra

Process algebras extended by a concept to present timing behaviour have been very recently proposed as a good modelling tool for the combined analysis of qualitative and quantitative system behaviour. We introduce a a process algebra including exponentially distributed time delays and a systematic approach to compute the underlying labelled transition system and continuous time Markov process. In particular it can be shown that the compositional operations on the level of the algebra can be directly translated in composi-tional operations to build the state space and generator matrix of the underlying Markov process. In the approach it is possible to deene and prove very naturally equivalence relations covering quantitative aspects which are congruence relations according to composition operators.
Speech Emotion Recognition for Affective Human-Robot Interaction

We evaluate the performance of a speech emotion recognition method for affective human-robot interaction. In the proposed method, emotion is classified into 6 classes: Angry, bored, happy, neutral, sad, and surprised. After applying noise reduction and speech detection, we obtain a feature vector for an utterance from statistics of phonetic and prosodic information. The phonetic information includes log energy, shimmer, formant frequencies, and Teager energy; the prosodic information includes pitch, jitter, and rate of speech. Then a pattern classifier based on Gaussian support vector machines decides the emotion class of the utterance. To simulate a human-robot interaction situation, we record speech commands and dialogs uttered at 2m away from a microphone. Experimental results show that the proposed method achieves the classification accuracy of 58.6% while listeners give 60.4% with the reference labels given by speakers’ intention. On the other hand, the proposed method shows the classification accuracy of 51.2% with the reference labels given by the listeners’ majority decision.
New power allocation methods for AF relay assisted OFDM cognitive radio networks with outdated CSI

In this paper, we investigate optimal and suboptimal power allocation schemes for amplify-and-forward (AF) relay assisted OFDM-based cognitive radio (CR) transmission. Due to channel feedback delay, the available channel state information (CSI) between the secondary and primary users is considered as an outdated but correlated version of the actual instantaneous CSI.We develop an optimal power allocation scheme to maximize the instantaneous capacity of the CR transmission assuming that the primary users are subject to average interference constraints, and the CR transmitters are subject to maximum transmit power constraint. A suboptimal scheme with reduced complexity has also been investigated and compared with the uniform loading algorithm. Numerical results confirm that the proposed optimal power loading scheme achieves on average, 60% capacity improvement than the uniform loading algorithm. Also the proposed suboptimal scheme outperforms the uniform loading approach and can be used as a less complex alternative for optimal power allocation with about 10% (on average) capacity degradation.
Identification and characterization of the bovine immunodeficiency-like virus tat gene

A cDNA clone of the bovine immunodeficiency-like virus (BIV) trans-activator gene (tat) was identified and characterized. The tat cDNA clone was generated by splicing, and on the basis of sequence analysis, the Tat protein was found to be encoded entirely by the first exon. It is 103 amino acids in size and shares sequence homology with the human immunodeficiency virus (HIV) Tat. The BIV tat clone can trans activate the BIV promoter effectively, as measured by the expression of the bacterial chloramphenicol acetyltransferase gene, when transfected into bovine cells. Besides activating the BIV promoter, the BIV Tat can also trans activate the HIV promoter effectively. It is possible that BIV Tat and HIV Tat employ similar mechanisms in trans activation of the viral long terminal repeat-directed gene expression.
Automatic Extraction of Personal Experiences from Patients' Blogs: A Case Study in Chronic Obstructive Pulmonary Disease

People with long-term illness such as chronic obstructive pulmonary disease (COPD) often use social media to document and share information, opinions and their experiences with others. Analysing the self-reported experiences of patients shared online has the potential to help medical researchers gain insight into some of the key issues affecting patients. However, the scale of health conversation taking place online poses considerable challenges to traditional content analysis. In this paper, we present a system which automates extraction of patient statements which refer to a personal experience. We applied a crowd sourcing methodology to create a set of 1770 annotated sentences from blog posts written by COPD patients. Our machine learning approach trained on lexical features successfully extracted sentences about patient experience with 93% precision and 80% recall (F-measure: 86%). Automatic annotation of sentences about patient experience can facilitate subsequent content analysis by highlighting the most relevant sentences to this particular problem.
12 Watching the Brain Comprehend Discourse

When the first author (Morton Ann Gernsbacher) was in graduate school, she once sat in on an undergraduate entry-level cognition course to see how one of the department’s best teachers conveyed the excitement and exquisiteness of cognitive psychology to an audience of 19-year-olds. This professor began the first day by posing the following challenge: Imagine that you were sent to some faraway planet, and your mission on this planet was to discern the workings of a mysterious—at least to you—structure, what here on earth we might call a building. However, you were prohibited or otherwise unable to enter the structure. How would you discern what work went on inside the structure? With guidance, the students arrived at recommendations such as to first carefully observe what entered the structure, and then carefully observe what exited the structure, and from those observations infer what work must go on inside the structure. Thus, if one saw sheet metal, rubber, and glass entering the structure and one observed Subaru vehicles leaving the structure, one might infer something different than if one saw denim cloth, thread, and zippers entering the structure and men’s blue jeans coming out. At this point the professor skillfully introduced some of the rudimentary concepts of experimental design: How, if clever enough, one might manipulate certain aspects of the input to the structure while controlling as many extraneous variables as possible, then measure qualitatively or quantitatively the output and thereby allow sharper inferences of what type of work went on inside the structure. At this point students suggested other covert techniques, for example, sneaking in at night or some time when their presence would not be detected—in other words, observing the structure “at rest. ” Trying to obtain a blueprint or floor plan of the structure was also suggested. Even bombing a section of the structure to see how that affects the output (an idea not so far
A Novel Data-Mining Approach Leveraging Social Media to Monitor Consumer Opinion of Sitagliptin

A novel data mining method was developed to gauge the experience of the drug Sitagliptin (trade name Januvia) by patients with diabetes mellitus type 2. To this goal, we devised a two-step analysis framework. Initial exploratory analysis using self-organizing maps was performed to determine structures based on user opinions among the forum posts. The results were a compilation of user's clusters and their correlated (positive or negative) opinion of the drug. Subsequent modeling using network analysis methods was used to determine influential users among the forum members. These findings can open new avenues of research into rapid data collection, feedback, and analysis that can enable improved outcomes and solutions for public health and important feedback for the manufacturer.
Potent Risk Factor for Aneurysm Formation: Termination Aneurysms of the Anterior Communicating Artery and Detection of A1 Vessel Asymmetry by Flow Dilution

BACKGROUND AND PURPOSE: There is a high incidence of intracranial aneurysms of the AcomA suggesting the possibility of an anatomic risk factor. There also exists an association of termination-type aneurysms with anatomic variations of 1 anterior cerebral artery trunk (A1) as the exclusive or dominant supply to both pericallosal arteries (A2). This yields the hypotheses of aneurysm formation from straight jets of A1 blood. MATERIALS AND METHODS: The anatomy and contrast filling of A1 and A2 segments and AcomAs were studied for a subset of cases entered into the Cerecyte Coil Trial for patients with AcomA (n = 105) and other aneurysms (n = 123) that were selected from imaging available at the Cerecyte Core Trial angiographic Core Lab. These cases were analyzed for A1 vessel dominance by measurement of the vessel diameter and dilution of angiographic contrast agent in A2s due to the differential flow source on selective angiography. A control group without aneurysms was assessed anatomically, using a large sequential CTA series (n = 159), acquired during acute stroke assessment. RESULTS: A1 dominance configuration is strongly associated with the presence of AcomA aneurysms for patients with intracranial aneurysms (odds ratio, 17.8). This association is also present compared with the incidence of A1 dominance in the large sequential control series of patients without aneurysms undergoing CTA for other reasons (odds ratio, 7.5). Outflow dilution of selective angiographic images augments anatomic information. CONCLUSIONS: A flow-based assessment of contrast flowing from the A1 to the A2 segments after injection pressure is superior to an A1 diameter based categorization when A1 vessel diameters are not strikingly different. The anatomic variant of asymmetric A1 configurations likely facilitates the development of AcomA aneurysms by flow stresses, providing further evidence to support the role of biophysical factors in intracranial aneurysm development.
Plasma Membrane-Located Purine Nucleotide Transport Proteins Are Key Components for Host Exploitation by Microsporidian Intracellular Parasites

Microsporidia are obligate intracellular parasites of most animal groups including humans, but despite their significant economic and medical importance there are major gaps in our understanding of how they exploit infected host cells. We have investigated the evolution, cellular locations and substrate specificities of a family of nucleotide transport (NTT) proteins from Trachipleistophora hominis, a microsporidian isolated from an HIV/AIDS patient. Transport proteins are critical to microsporidian success because they compensate for the dramatic loss of metabolic pathways that is a hallmark of the group. Our data demonstrate that the use of plasma membrane-located nucleotide transport proteins (NTT) is a key strategy adopted by microsporidians to exploit host cells. Acquisition of an ancestral transporter gene at the base of the microsporidian radiation was followed by lineage-specific events of gene duplication, which in the case of T. hominis has generated four paralogous NTT transporters. All four T. hominis NTT proteins are located predominantly to the plasma membrane of replicating intracellular cells where they can mediate transport at the host-parasite interface. In contrast to published data for Encephalitozoon cuniculi, we found no evidence for the location for any of the T. hominis NTT transporters to its minimal mitochondria (mitosomes), consistent with lineage-specific differences in transporter and mitosome evolution. All of the T. hominis NTTs transported radiolabelled purine nucleotides (ATP, ADP, GTP and GDP) when expressed in Escherichia coli, but did not transport radiolabelled pyrimidine nucleotides. Genome analysis suggests that imported purine nucleotides could be used by T. hominis to make all of the critical purine-based building-blocks for DNA and RNA biosynthesis during parasite intracellular replication, as well as providing essential energy for parasite cellular metabolism and protein synthesis.
Error Link Detection and Correction in Wikipedia

The hyperlink structure of Wikipedia forms a rich semantic network connecting entities and concepts, enabling it as a valuable source for knowledge harvesting. Wikipedia, as crowd-sourced data, faces various data quality issues which significantly impacts knowledge systems depending on it as the information source. One such issue occurs when an anchor text in a Wikipage links to a wrong Wikipage, causing the error link problem. While much of previous work has focused on leveraging Wikipedia for entity linking, little has been done to detect error links. In this paper, we address the error link problem, and propose algorithms to detect and correct error links. We introduce an efficient method to generate candidate error links based on iterative ranking in an Anchor Text Semantic Network. This greatly reduces the problem space. A more accurate pairwise learning model was used to detect error links from the reduced candidate error link set, while suggesting correct links in the same time. This approach is effective when data sparsity is a challenging issue. The experiments on both English and Chinese Wikipedia illustrate the effectiveness of our approach. We also provide a preliminary analysis on possible causes of error links in English and Chinese Wikipedia.
Hybrid TDOA/AOA Geometrical Positioning Schemes for MS Location Estimation

Abstract To achieve more accurate measurements of the MS location, it is possible to integrate many kinds of schemes. In this paper we combine time difference of arrival (TDOA) from three base stations (BSs) and angle of arrival (AOA) information at the serving BS to give location estimation of the MS. Based on the non-line-of-sight (NLOS) environments and the knowledge of NLOS error statistics is not obtained, the proposed methods utilize the TDOA hyperbolas and the AOA line to find all the possible intersections to locate the mobile station (MS). Different NLOS models were used to evaluate the proposed methods. Simulation results that the proposed methods provide better location accuracy comparing with Taylor series algorithm (TSA) and least square (LS) method.