Miracle-dz/UniFAR-FTUs huggingface dataset:
The ATP-Binding Cassette Transporter ABCB19 Regulates Postembryonic Organ Separation in Arabidopsis

The phytohormone auxin plays a critical role in plant development, including embryogenesis, organogenesis, tropism, apical dominance and in cell growth, division, and expansion. In these processes, the concentration gradient of auxin, which is established by polar auxin transport mediated by PIN-FORMED (PIN) proteins and several ATP-binding cassette/multi-drug resistance/P-glycoprotein (ABCB/MDR/PGP) transporters, is a crucial signal. Here, we characterized the function of ABCB19 in the control of Arabidopsis organ boundary development. We identified a new abcb19 allele, abcb19-5, which showed stem-cauline leaf and stem-pedicel fusion defects. By virtue of the DII-VENUS marker, the auxin level was found to be increased at the organ boundary region in the inflorescence apex. The expression of CUP-SHAPED COTYLEDON2 (CUC2) was decreased, while no obvious change in the expression of CUC3 was observed, in abcb19. In addition, the fusion defects were greatly enhanced in cuc3 abcb19-5, which was reminiscent of cuc2 cuc3. We also found that some other organ boundary genes, such as LOF1/2 were down-regulated in abcb19. Together, these results reveal a new aspect of auxin transporter ABCB19 function, which is largely dependent on the positive regulation of organ boundary genes CUC2 and LOFs at the postembryonic organ boundary.
Strategies for Logic Programming

Logic programs consist of formulas of mathematical logic and various proof-theoretic techniques can be used to design and analyse execution models for such programs. We brieey review the main problems, which are questions that are still elusive in the design of logic programming languages, from a proof-theoretic point of view. Existing strategies which lead to the various languages are all rather sophisticated and involve complex manipulations of proofs. All are designed for analysis on paper by a human and many of them are ripe for automation. We aim to perform the automation of some aspects of strategies for logic programming language, in order to assist in the design of these languages. In this paper we describe the rst steps towards the design of such an automatic analysis tool. We investigate the usage of particular proof manipulations for the analysis of logic programming strategies. We propose a more precise speciication of sequent calculi inference rules that we use as a framework for the generalisation and automation-oriented speciication of the permutation process.
Nonlinear and magneto-optical transmission studies on magnetic nanofluids of non-interacting metallic nickel nanoparticles

Oxide free stable metallic nanofluids have the potential for various applications such as in thermal management and inkjet printing apart from being a candidate system for fundamental studies. A stable suspension of nickel nanoparticles of ∼ 5 nm size has been realized by a modified two-step synthesis route. Structural characterization by x-ray diffraction and transmission electron microscopy shows that the nanoparticles are metallic and are phase pure. The nanoparticles exhibited superparamagnetic properties. The magneto-optical transmission properties of the nickel nanofluid (Ni-F) were investigated by linear optical dichroism measurements. The magnetic field dependent light transmission studies exhibited a polarization dependent optical absorption, known as optical dichroism, indicating that the nanoparticles suspended in the fluid are non-interacting and superparamagnetic in nature. The nonlinear optical limiting properties of Ni-F under high input optical fluence were then analyzed by an open aperture z-scan technique. The Ni-F exhibits a saturable absorption at moderate laser intensities while effective two-photon absorption is evident at higher intensities. The Ni-F appears to be a unique material for various optical devices such as field modulated gratings and optical switches which can be controlled by an external magnetic field.
Novel virtual moving sound-based spatial auditory brain-computer interface paradigm

This paper reports on a study in which a novel virtual moving sound-based spatial auditory brain-computer interface (BCI) paradigm is developed. Classic auditory BCIs rely on spatially static stimuli, which are often boring and difficult to perceive when subjects have non-uniform spatial hearing perception characteristics. The concept of moving sound proposed and tested in the paper allows for the creation of a P300 oddball paradigm of necessary target and non-target auditory stimuli, which are more interesting and easier to distinguish. We present a report of our study of seven healthy subjects, which proves the concept of moving sound stimuli usability for a novel BCI. We compare online BCI classification results in static and moving sound paradigms yielding similar accuracy results. The subject preference reports suggest that the proposed moving sound protocol is more comfortable and easier to discriminate with the online BCI.
The Spicy system: towards a notion of mapping quality

We introduce the Spicy system, a novel approach to the problem of automatically selecting the best mappings among two data sources. Known schema mapping algorithms rely on value correspondences -- i.e. correspondences among semantically related attributes -- to produce complex transformations among data sources. Spicy brings together schema matching and mapping generation tools to further automate this process. A key observation, here, is that the quality of the mappings is strongly influenced by the quality of the input correspondences. To address this problem, Spicy adopts a three-layer architecture, in which a schema matching module is used to provide input to a mapping generation module. Then, a third module, the mapping verification module, is used to check candidate mappings and choose the ones that represent better transformations of the source into the target. At the core of the system stands a new technique for comparing the structure and actual content of trees, called structural analysis. Experimental results show that our mapping discovery algorithm achieves both good scalability and high precision in mapping selection.
Civil society and democracy : a reader

PREFACE INTRODUCTION PART I CONCEPTUALIZING CIVIL SOCIETY: MODES OF CIVIL SOCIETY, THE IDEA OF CIVIL SOCIETY, RETHINKING THE PUBLIC SPHERE A CONTRIBUTION OF THE CRITIQUE OF ACTUALLY EXISTING DEMOCRACY, CIVIL SOCIETIES LIBERALISM AND THE MORAL USES OF PLURALISM, BOWLING IN THE BRONX THE UNCIVIL INTERSTICES BETWEEN CIVIL AND POLITICAL SOCIETY, BEYOND THE NATION? OR WITHIN? , CIVIL SOCIETY CULTURAL POSSIBILITY OF A MODERN IDEAL, CIVIL SOCIETY AND ITS INSTITUTIONS, CIVIL SOCIETY AND ITS AVATARS, CIVIL SOCIETY OR THE STATE WHAT HAPPENED TO CITIZENSHIP? , THE CIVIL AND THE POLITICAL IN CIVIL SOCIETY PART II CIVIL SOCIETY AND DEMOCRACY: EMPIRICAL INVESTIGATIONS: IN SEARCH OF CIVIL SOCIETY MARKET REFORM AND SOCIAL CHANGE IN CONTEMPORARY CHINA, CIVIL SOCIETY AND OTHER POLITICAL POSSIBILITIES IN SOUTHEAST ASIA, CIVIL SOCIETY, CONTESTATION AND CITIZEN ACTION IN INDIA, THE COFFEE HOUSE AND THE ASHRAM, GANDHI, CIVIL SOCIETY AND THE PUBLIC SPHERES, DEMOCRACY, SOCIAL CAPITAL AN D CI VIL SOCIETY IN INDIA, ETHNIC CONFLICT AND CIVIL SOCIETY - INDIA AND BEYOND
A new multi-human detection algorithm using an IR-UWB radar system

This paper presents a multi-human detection algorithm using an impulse radio ultra-wideband (IR-UWB) radar system. The algorithm operates in a similar manner to the conventional clean algorithm that has mainly been used for estimating a channel impulse response (CIR) by computing deconvolution from the clutter subtracted received signal. Unlike the clean algorithm, the algorithm attempts to divide the clutter subtracted received signal into a number of coherent clusters so that the detection success rate of the multi-humans can be improved without a priori knowledge of the number of existing humans. The algorithm performs quite well in dense multipath environments that take place almost always in practice. The validity of the algorithm is demonstrated by successfully tracking the distances of randomly walking people using a commercial IR-UWB radar system. The detection error rate is also discussed based on the normalized histogram obtained from the experimentally measured data.
A framework to support spatial, temporal and thematic analytics over semantic web data

Spatial and temporal data are critical components in many applications. This is especially true in analytical applications ranging from scientific discovery to national security and criminal investigation. The analytical process often requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. This dissertation proposes a framework built around the RDF data model for analysis of thematic, spatial and temporal relationships between named entities. We present a spatiotemporal modeling approach that uses an upper-level ontology in combination with temporal RDF graphs. A set of query operators that use graph patterns to specify a form of context are formally defined, and an extension of the W3C-recommended SPARQL query language to support these query operators is presented. We also describe an efficient implementation of the framework that extends a state-of-the-art commercial database system. We demonstrate the scalability of our approach with a performance study using both synthetic and real-world RDF datasets of over 25 million triples.
Analysis of Alternative Keyboards Using Learning Curves

Objective : To quantify learning percentages for alternative keyboards (chord, contoured split, Dvorak, and split fixed angle) and understand how physical, cognitive, and perceptual demand affect learning. Background: Alternative keyboards have been shown to offer ergonomic benefits over the conventional, single-plane QWERTY keyboard design, but productivity-related challenges may hinder their widespread acceptance. Method: Sixteen participants repeatedly typed a standard text passage using each alternative keyboard. Completion times were collected and subsequent learning percentages were calculated. Participants were asked to subjectively rate the physical, cognitive, and perceptual demands of each keyboard, and these values were then related to the calculated learning percentages. Results: Learning percentage calculations revealed the percentage for the split fixed-angle keyboard (90.4%) to be significantly different ( p < .05) from the learning percentages for the other three keyboards (chord, 77.3%; contour split, 76.9%; Dvorak, 79.1%). The average task completion time for the conventional QWERTY keyboard was 40 s, and the average times for the fifth trial on the chord, contoured split, Dvorak, and split fixed-angle keyboards were 346, 69, 181, and 42 s, respectively. Conclusions: Productivity decrements can be quickly regained for the split fixed-angle and contour split keyboard but will take considerably longer for Dvorak and chord keyboards. The split fixed-angle keyboard involved physical learning, whereas the others involved some combination of physical and cognitive learning, a result supported by the subjective responses. Application: Understanding the changes in task performance time that come with learning can provide additional information for a cost-benefit analysis when considering the implementation of ergonomic interventions.
Drug Solubility: Importance and Enhancement Techniques

Solubility, the phenomenon of dissolution of solute in solvent to give a homogenous system, is one of the important parameters to achieve desired concentration of drug in systemic circulation for desired (anticipated) pharmacological response. Low aqueous solubility is the major problem encountered with formulation development of new chemical entities as well as for the generic development. More than 40% NCEs (new chemical entities) developed in pharmaceutical industry are practically insoluble in water. Solubility is a major challenge for formulation scientist. Any drug to be absorbed must be present in the form of solution at the site of absorption. Various techniques are used for the enhancement of the solubility of poorly soluble drugs which include physical and chemical modifications of drug and other methods like particle size reduction, crystal engineering, salt formation, solid dispersion, use of surfactant, complexation, and so forth. Selection of solubility improving method depends on drug property, site of absorption, and required dosage form characteristics.
Quantitative Relationship between Transmitter Release and Calcium Current at the Calyx of Held Synapse

A newly developed deconvolution method (Neher and Sakaba, 2001) allowed us to resolve the time course of neurotransmitter release at the calyx of Held synapse and to quantify some basic aspects of transmitter release. First, we identified a readily releasable pool (RRP) of synaptic vesicles. We found that the size of the RRP, when tested with trains of strong stimuli, was constant regardless of the exact stimulus patterns, if stimuli were confined to a time interval of ∼60 msec. For longer-lasting stimulus patterns, recruitment of new vesicles to the RRP made a substantial contribution to the total release. Second, the cooperativity of transmitter release as a function of Ca2+ current was estimated to be 3–4, which confirmed previous results (Borst and Sakmann, 1999; Wu et al., 1999). Third, an initial small Ca2+ influx increased the efficiency of Ca2+ currents in subsequent transmitter release. This type of facilitation was blocked by a high concentration of EGTA (0.5 mm). Fourth, the release rates of synaptic vesicles at this synapse turned out to be heterogeneous: once a highly Ca2+-sensitive population of vesicles was consumed, the remaining vesicles released at lower rates. These components of release were more clearly separated in the presence of 0.5 mm EGTA, which prevented the buildup of residual Ca2+. Conversely, raising the extracellular Ca2+ concentration facilitated the slower population such that its release characteristics became more similar to those of the faster population under standard conditions. Heterogeneous release probabilities are expected to support the maintenance of synaptic transmission during high-frequency stimulation.
Modelling Macroeconomic and Distributional Impacts of Stabilization and Adjustment Packages: Current Literature and Challenges

Structural adjustment policy packages sponsored by the IMF and the World Bank are a combination of monetary, fiscal and trade measures intended to curb inflation, improve the balance of payments, and foster economic growth. From a brief discussion of a typical structural adjustment policy package and the debate about its macroeconomic and distributional impacts, we derive a list of desirable characteristics for an adequate model thereof. Upon reviewing the literature on the issue, we see beginnings of a consensus on how to construct the sectoral structure of the real side of the economy and the formation of relative prices, and effective tools for analyzing distributional impacts also on population groups different from those used in formulating the model. However, the views on the proper relationship (in particular, directions of causality) between credit, prices, and real output are sharply divided between the monetarist and the structuralist school, with only one model allowing for an endogenous switch between the two corresponding modes of behavior. We also find that current methodologies are not very useful for representing the behavior of the economy prior to the achievement of the hypothetical equilibrium, thus not allowing for calibration of model behavior to time series and potentially resulting in low quality of parameter estimation. Furthermore, currently used formalisms for representation of stock-flow relationships involving capital account transactions are quite unwieldy, requiring the model builder to manually keep track of accounting identities and thus unnecessarily increasing the effort of model building.
An imbalanced data classification method based on automatic clustering under-sampling

Classification of imbalanced datasets has become one of the most challenging problems in big data mining. Because the number of positive samples is far less than the negative samples, low accuracy and poor generalization performance and some other defects always go with learning process of traditional algorithms. Ensemble construction algorithm is an important method to handle this problem. Especially, the ensemble construction algorithm based on random under-sampling or clustering can effectively improve the performance of classification. However, the former causes information loss easily and the latter increases complexity. In this paper, we propose ACUS, an improved ensemble algorithm based on automatic clustering and under-sampling. ACUS conducts clustering first according to the weight of samples, and then it constructs balanced-distributed dataset which consists of a certain percentage of the majority class and all of the minority class from each cluster. With Adaboost algorithm construction, these datasets are used to get an ensemble classifier. Experimental results demonstrate the advantages of our proposed algorithm in terms of accuracy, simplicity and high stability.
SAT Based Automated Test Case Generation For MUMCUT Coverage

MUMCUT is a criterion for testing Boolean specifications. The traditional test case generation methods for this problem are based on approximate approaches. The efficiency of these algorithms depend on the designers’ experience on this coverage. In this paper, the authors apply SAT based method to solve this problem. Two SAT solvers, walksat and zChaff, are employed to generate approximate and optimal test case set respectively. The experimental results show that the two SAT methods are efficient.
Metal-insulator transition in a generalized Hubbard model with correlated hopping at half-filling

In the present paper the metal-insulator transition is studied in a generalized Hubbard model with correlated hopping at half-filling and zero temperature. Single-particle Green function and energy spectrum of the electron system are calculated. The expressions for the energy gap width and the concentration of polar states (holes or doublons) are obtained. The conditions for metallic and insulating states are found.
Geometric Deformation by Merging a 3D-Object with a Simple Shape

Deformation techniques are often used to model the shape of geometric objects This paper presents a new geometric deformation technique allowing local deformation of the shape of an object by merging the object with a simple D shape sphere ellipsoid Two kinds of e ects can be obtained the simple shape is used to produce either a bump or a dent on the object The object is deformed so that it includes or it embeds the simple shape In order to deform the object the D space where it lies is continuously deformed so that the object is bumped and the shape of the bump corresponds to the simple D shape If the surfaces of both the original object and the simple shape are smooth continuously di erentiable the surface of the deformed object is also smooth Moreover topological properties of the object are unchanged and the volume variation of the deformed object is controlled by the volume delimited by the simple shape An interactive deformation tool based on this tech nique is presented It comprises a convex D shape and a center a D point included in the shape The user can interactively control the deformation by changing the parameters of the tool shape and the position of the tool center Control of the para meters is particularly intuitive
Antibacterial activity of Kedrostis foetidissima ( Jacq )

Medicinal plants are the nature s gift to human beings to make disease free healthy life. In India different extracts are used for the treatment of various diseases. Total 50% modern drugs are of natural products origin and as such these natural products play an important role in the drug development pharmaceutical industry. Use of plant as a source of medicine has been inherited and is an important component of the health care system (Hidayathulla et al., 2011). Several antibiotics used for the treatment of human infections, which have limited antimicrobial spectrum. Medicinal plants are the backbone of traditional medicine and the antibacterial activity of plant extract is due to different chemical agent in antimicrobial compounds (Arulmozhi et al., 2007). Last ten years the peace of development of new antimicrobial drugs has slowed down while the prevalence of resistance has increased astronomically (Hugo et al., 1984). Ethanobotanical records suggest that plants are the sleeping against of pharmaceutical industry (Irobi et al., 1996). Antimicrobial properties of medicinal plants are being increasingly reported from different parts of the world ( Saxena , 1997). It has been reported that the higher plants have shown to be a potential source for the new antimicrobial agents (Mitschern et al., 1987). ISSN: 2319-7706 Volume 2 Number 4 (2013) pp. 104-107 http://www.ijcmas. com
ATGPS using real value logic simulation

In terms of Automatic Test Pattern Generation System, we proposed a new algorithm which employs real value logic simulation, but gate output value calculation method is quite different from Cheng and Agrawal's in order to realize high fault coverage and process acceleration. Moreover, we implemented our algorithm on parallel processor and could yield high speed processing. Compared with Cheng and Agrawal algorithm, acceleration is about 4× with 100(%) fault coverage. And acceleration is more than 5× using parallel processor moreover.
Sovereign Debt Restructuring and Debt Sustainability: An Analysis of Recent Cross-country Experience

Restoring a country's debt to a sustainable path after a sovereign debt restructuring is key to ensuring a credible and durable exit from the crisis. In recent years, a number of countries have restructured their sovereign liabilities, either following a default, or preemptively, to avoid a default. This Occasional Paper takes stock of the experiences of some of these countries--Argentina, the Dominican Republic, Ecuador, Moldova, Pakistan, Russia, Ukraine, and Uruguay--with debt-restructuring operations, with a view to assessing the outcomes and whether debt sustainability has been restored. The emphasis of the study is on sovereign debt owed to private creditors.
Discovering Regularity Patterns of Mobility Practices through Mobile Phone Data

This article addresses the issue of analyzing and mapping mobility practices by using different kinds of mobile phone network data, which provide geo-located information on mobile phone activity at a high spatial and temporal resolution. It will present and discuss major findings and drawbacks, based on an application carried out on the Milan urban region (Lombardy, Northern Italy) and suggest possible implications for policies.
Supporting Keyword Selection in Generating Earth Science Metadata

Vast amounts of earth science data have been stored and managed in various projects. Because earth science requires considerable experience and expertise, we generally generate metadata for earth science datasets. In such metadata, keyword information is important. Controlled keywords such as GCMD Science Keyword are used for metadata. However, selection of suitable keywords is not easy. We propose methods to suggest keywords from summary texts of datasets. We considered simple string matching and inferring by Labeled LDA, and apply them to the actual earth science metadata.