Miracle-dz/UniFAR-FTUs huggingface dataset:
Heterogeneous adaptive component-based applications with Adaptive.Net

Adaptation to changing environmental conditions is a major challenge for most distributed applications. The service-oriented programming paradigm leads to an increasing number of applications that are not only meant to provide services through standard user-interfaces hosted on desktop computers, but are to be accessible from small mobile devices as well. The integration of the different programming environments on desktop (i.e.; Windows) and mobile computers (i.e.; Java Micro Editions - J2ME) puts an extra burden on the programmer of this kind of applications. In addition, unstable conditions caused by modern infrastructures for mobile applications and varying properties of computational devices have to be considered during runtime of the application. Dynamic reconfiguration provides a powerful mechanism for adaptive computing. Within this paper, we elaborate on the extension of our previously developed Adaptive.Net framework towards CORBA and Java. With the introduction of new connector types, our framework is able to provide seamless support for adaptive, heterogeneous applications based on . Net, Java, and CORBA. In context of our framework, applications consist of components which interact via so-called connectors. The component/connector model allows for mediating between component frameworks (Java, .Net) as well as between communication protocols (CORBA, .Net Remoting, sockets, etc.). Within the paper we give an overview of our adaptation framework Adaptive.Net, that includes a monitoring infrastructure, a reconfiguration platform and tools for building adaptive applications. Using a proof-of-concept application, we experimentally evaluate our connector architecture and study interoperability of Java, CORBA, and . Net objects.
A Performance Analysis of Long-Term Archiving Techniques

A challenge for digital archives managing long lived data, such as medical records and land registers, is to guarantee long-term authenticity, integrity, and datedness. Although some techniques have been proposed that provide these security goals, most proposals lack a corresponding performance analysis. Thus, in this paper we provide an analytical analysis of the performance of several proposals. Following, to see the impact of different approaches on the runtime, we implemented the most promising schemes and compared them with respect to their required storage space and verification time. Furthermore, the identified computational bottlenecks of the techniques are presented and corresponding improvements are indicated. Finally, we show how to select a long-term archiving scheme and the appropriate key sizes based on trust assumptions and the number of documents to be archived.
Effect of Minor Amendments of Patient’s Position on the Accuracy of Linear Measurements Yielded from Cone Beam Computed Tomography

Statement of Problem: Image distortion in intra and extra-oral radiographs are an unavoidable phenomenon. Patient's positional changes from the routine alignments is an important issue for this unwanted alteration, Therefore the accuracy of the dimensional measurements will be affected. Purpose: Our purpose is to find out the effect of minor changes (possibly happening in the clinic) in the position of a human dry skull on the accuracy of the measurements acquired by Cone Beam Computed Tomography (CBCT). Materials and Method: In this study, 3 locations on the skull were pointed with radio- opaque markers. Imaging process with Kodak 9000 CBCT was performed in standard and 10 analytically miss- oriented positions. Then 2 distances were measured between the centers of markers. Later, these measurements were compared with the standard position values. Results: There was not any imperative difference in the measurements of the 10 altered positions yielded in this study with standard position values. Conclusion: According to our results, apparently, the accuracy of linear measurements in CBCT images is endorsed by unintentional small changes in the patient’s position during the projections.
STRUCTURAL SIMULATION OF DISTRIBUTEDCOMPUTATIONS USING CHRONOLOG ( MC )

Chronolog(MC) is a logic programming language based on a linear-time temporal logic with multiple granularity of time. In this logic, all formulas can be clocked and are allowed to be deened on local clocks. Therefore the language is exible and it is suitable for modeling and specifying those systems where the notion of dynamic change is central. This paper presents a knowledge-based modeling methodology for the speciication of distributed computations with Chronolog(MC). The methodology combines trajectory and structural simulation methods together to describe a simulation system, and it develops a mod-eling formalism to represent the initial structural representation of a system as well as a method to use in determining the next representation of the structure. This methodology can be used for building a simulation environment for distributed computations, which provides an integration of modeling formalism, modeling environment, knowledge-base management and processing of the model in simulation.
Determining value in a complex service setting

Purpose – The purpose of this paper is to capture the richness of customer perceived value by determining its benefit and cost dimensions in a complex service setting. Perceived value is argued as equivalent to value-in-use; that is value that emerges for or is created by the customer. Design/methodology/approach – A series of in-depth interviews was conducted with a diverse group of clients of financial planning services as well as with financial planners in Australia. Findings – Six benefit and four cost dimensions of complex service are identified, namely expertise, education, motivation, support, relationship and convenience benefits, as well as monetary, time and effort, emotional and lifestyle costs. The results also indicate proposed outcomes of these dimensions, along with relevant moderators, leading to a broad conceptual framework for future empirical validation. Originality/value – This study contributes to the sparse conceptual development of value perceptions, or value-in-use, in a complex service context. In particular, the authors identify the benefit and cost dimensions, specifically addressing aspects of value that are linked to the long-term relationship between provider and customer. The authors also develop a conceptual model of value, including both outcomes and situational moderators of the various value dimensions. Finally, the conceptualization of perceived value is discussed with respect to the value co-creation literature.
Cost of Capital and the Role of Institutional Ownership

We examine the relationship between the institutional ownership and the cost of capital. Using firm-level data for the period from 1990 to 2006, we find that changes in dedicated (transient) ownership generally lower (increase) the investee’s cost of capital. Dividing the data into highversus low-leverage investees, we find that highly levered investees benefit the most from an increase in dedicated ownership. Overall, the results suggest that ownership changes made by dedicated institutional investors can lower the investee’s cost of financing. We used different methods to check the robustness of our results.
Wavelength Variation Approach in Single Mode-Multimode-Single Mode Optical Fiber as a Bending Sensor

Multimode interference in optical waveguides has interesting self-imaging properties, which have extensively been investigated and utilized in many integrated optical devices. Multimode interference has also been explored in optical fibers in order to realize fiber devices, including sensors. A basic structure of these devices has been the Single mode –Multimode – Single mode (SMS) fiber section concatenation. This dissertation describes theoretical and numerical investigations on multimode interference (MMI) devices using a single mode-multimode-single mode (SMS) fiber structure for possible use as bending sensor using wavelength variation technique. Several aspects of the SMS edge filters have been investigated, including the effect of bending the SMS fiber cores due to fabrication tolerances, polarization dependence, and temperature dependence. These aspects can impair the performance of a wavelength measurement system. There are several approaches which have been proposed and demonstrated to achieve high resolution and accuracy of wavelength measurement. Bending effects due to the splicing process on the spectral characteristics of SMS fiber structure are investigated experimentally with the help of MATLAB. A limit for the tolerable of the cores of an SMS fiber structure based sensor is proposed, beyond which the fiber spectral performance degrades unacceptably. We use Wavelength variation approach by which we can measure the bending more accurately in optical waveguide, as compare to recent sensors. Due to the power loss the power transmission is decreases and efficiency also reduces. So by wavelength variation approach we developed an efficient spectrometer capable of performing a wide variety of coherent multidimensional measurements at optical wavelengths. In this approach we fixed the power and calculate the variation in the wavelength to sense the bending accurately. We apply our algorithm for performing several comparison considerations which shows the performance of our algorithm which is better in comparison to the previous work.
Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.
A Survey of Ontology Learning Procedures

Ontologies constitute an approach for knowledge representation that can be shared establishing a shared vocabulary for different applications and are also the backbone of the Semantic Web. Thus a fast and efficient ontology development is a requirement for the success of many knowledge based systems and for the Semantic Web itself. However, ontology development is a difficult and time consuming task. Ontology learning is an approach for the problem of knowledge acquisition bottleneck that aims at reducing the cost of ontology construction through the development of automatic methods for the extraction of knowledge about a specific domain and its representation in an ontology like structure. This paper provides a discussion on existing ontology learning techniques and the state of the art of the field.
A Critical Literacy Case Study: The Journey from Pre-service Exploration to In-service Implementation

I am submitting herewith a dissertation written by Wendy Beth Meller entitled “A Critical Literacy Case Study: The Journey from Pre-service Exploration to In-service Implementation. ” I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Education.
Effects of Semantic Features on Machine Learning-Based Drug Name Recognition Systems: Word Embeddings vs. Manually Constructed Dictionaries

Semantic features are very important for machine learning-based drug name recognition (DNR) systems. The semantic features used in most DNR systems are based on drug dictionaries manually constructed by experts. Building large-scale drug dictionaries is a time-consuming task and adding new drugs to existing drug dictionaries immediately after they are developed is also a challenge. In recent years, word embeddings that contain rich latent semantic information of words have been widely used to improve the performance of various natural language processing tasks. However, they have not been used in DNR systems. Compared to the semantic features based on drug dictionaries, the advantage of word embeddings lies in that learning them is unsupervised. In this paper, we investigate the effect of semantic features based on word embeddings on DNR and compare them with semantic features based on three drug dictionaries. We propose a conditional random fields (CRF)-based system for DNR. The skip-gram model, an unsupervised algorithm, is used to induce word embeddings on about 17.3 GigaByte (GB) unlabeled biomedical texts collected from MEDLINE (National Library of Medicine, Bethesda, MD, USA). The system is evaluated on the drug-drug interaction extraction (DDIExtraction) 2013 corpus. Experimental results show that word embeddings significantly improve the performance of the DNR system and they are competitive with semantic features based on drug dictionaries. F-score is improved by 2.92 percentage points when word embeddings are added into the baseline system. It is comparative with the improvements from semantic features based on drug dictionaries. Furthermore, word embeddings are complementary to the semantic features based on drug dictionaries. When both word embeddings and semantic features based on drug dictionaries are added, the system achieves the best performance with an F-score of 78.37%, which outperforms the best system of the DDIExtraction 2013 challenge by 6.87 percentage points.
Generation of boron-deficiency-tolerant tomato by overexpressing an Arabidopsis thaliana borate transporter AtBOR1

Nutrient deficiency in soil poses a widespread agricultural problem. Boron (B) is an essential micronutrient in plants, and its deficiency causes defects in both vegetative and reproductive growth in various crops in the field. In Arabidopsis thaliana, increased expression of a major borate transporter gene AtBOR1 or boric acid channel gene AtNIP5;1 improves plant growth under B-deficient conditions. In this study, we examined whether high expression of a borate transporter gene increases B accumulation in shoots and improves the growth of tomato plant, a model of fruit-bearing crops, under B-deficient conditions. We established three independent transgenic tomato plants lines expressing AtBOR1 using Agrobacterium-mediated transformation of tomato (Solanum lycopersicum L. cv. Micro-Tom). Reverse transcription-polymerase chain reaction (RT-PCR) analysis confirmed that two lines (Line 1 and Line 2) more strongly expressed AtBOR1 than Line 3. Wild-type plants and the transgenic plants were grown hydroponically under B-sufficient and B-deficient conditions. Wild-type and Line 3 (weakly expressing transgenic line) showed a defect in shoot growth under B-deficient conditions, especially in the development of new leaves. However, seedlings of Line 1 and Line 2, the transgenic lines showing strong AtBOR1 expression, did not show the B-deficiency phenotype in newly developing leaves. In agreement with this phenotype, shoot biomass under low-B conditions was higher in the strongly expressing AtBOR1 line. B concentrations in leaves or fruits were also higher in Line 2 and Line 1. The present study demonstrates that strong expression of AtBOR1 improved growth in tomato under B-deficient conditions.
Fuzzy Learning Vector Quantization based on Fuzzy k-Nearest Neighbor Prototypes

In this paper, a new competition strategy for learning vector quantization is proposed. The simple competitive strategy used for learning vector quantization moves the winning prototype which is the closest to the newly given data pattern. We propose a new learning strategy based on k-nearest neighbor prototypes as the winning prototypes. The selection of several prototypes as the winning prototypes guarantees that the updating process occurs more frequently. The design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the proposed learning strategy.
Optimal grouping and user ordering for sequential group detection in synchronous CDMA

The sequential group detection technique is a generalization of the decision feedback detector: in the latter, users are successively demodulated and cancelled one-by-one, while in the former this basic operation is performed simultaneously on groups of users. The computational complexity of a group decision feedback detector (GDFD) is exponential in the largest size of the groups; thus instead of using the partition of users as design parameters, choosing the "maximum group size" is more reasonable in practice. Given the maximum group size, a grouping algorithm is proposed. It is shown that the proposed grouping algorithm maximizes the asymptotic symmetric energy (ASE) of the multiuser detection system. Furthermore, based on a set of lower bounds on the asymptotic group symmetric energy (AGSE) of the GDFD, it is shown that the proposed grouping algorithm, in fact, maximizes the AGSE lower bound for every group of users. Together with a fast computational method based on branch-and-bound, the theoretical analysis of the grouping algorithm enables the offline estimation of the computational cost and the performance of GDFD. Simulation results are presented to verify the theoretical results.
A Multi-Resolution, Full-Colour Spatial Gamut Mapping Algorithm

A multi–resolution, full–colour spatial gamut mapping algorithm (GMA) is proposed in this paper. Its aim is to maintain as much of an original image’s overall, and in particular spatial, information as possible within the limits of a reproduction medium’s gamut. First, the original image is decomposed into different spatial frequency bands. Second, lightness compression and initial gamut mapping are applied to the lowest frequency band image. Third, the next higher frequency band is added to the gamut mapped image and the result is processed by subsequent gamut mapping transformations. The third step is repeated until the highest frequency band is reached. The effect of this algorithm is that intra–image differences in the original image are well maintained in the gamut mapped reproduction. A psychophysical experiment is then described whose results show that this algorithm is in the pair of most accurate GMAs and can outperform all other algorithms tested here for images which are less accurately reproduced by all GMAs.
MILES: A Medium resolution INT Library of Empirical Spectra

A new stellar library developed for stellar population synthesis modeling is presented. The library consist of 985 stars spanning a large range in atmospheric parameters. The spectra were obtained at the 2.5m INT telescope and cover the range (cid:21)(cid:21) 3525–7500 ˚A at 2.3 ˚A (FWHM) spectral resolution. The spectral resolution, spectral type coverage, ﬂux calibration accuracy and number of stars represent a substantial improvement over previous libraries used in population synthesis models.
XMM–Newton spectroscopy of high-redshift quasars

We present XMM-Newton X-ray spectra and optical photometry of four high-redshift (z = 2.96-3.77) quasars, [HB89] 0438-436, [HB89] 2000-330, [SP89] 1107+487 and RX J122135.6+280613; of these four objects, the first two are radio-loud and the last two are radio-quiet. Model fits require only a power law with Galactic absorption in each case; additional intrinsic absorption is also needed for [HB89] 0438-436 and RX J122135.6+280613. The spectra are hard (Γ ∼ 1.7 for [HB89] 0438-436, [HB89] 2000-330 and ∼1.4 for RX J122135.6+280613), with the exception of [SP89] 1107+487, which is softer (r ∼ 2.0); the combined Galactic and intrinsic absorption of lower-energy X-rays in the last of the sources is much less significant than in the other three. The two intrinsically unabsorbed sources have greater optical fluxes relative to the X-ray contributions at the observed energies. While there is no need to include reflection or iron line components in the models, our derived upper limits (99 per cent confidence) on these parameters are not stringent; the absence of these features, if confirmed, may be explained in terms of the high power-law contribution and/or a potentially lower albedo as a result of the low disc temperature. However, we note that the power-law spectrum can be produced via mechanisms other than the Comptonization of accretion disc emission by a corona; given that all four of these quasars are radio sources at some level, we should also consider the possibility that the X-ray emission originates, at least partially, in a jet.
Structural analysis of the principal immunodominant domain of the feline immunodeficiency virus transmembrane glycoprotein

In the transmembrane envelope glycoprotein (TM) of lentiviruses, including human immunodeficiency virus type 1 (HIV-1) and feline immunodeficiency virus (FIV), two cysteine residues, conserved in most retroviruses, are thought to form a loop containing five to seven amino acids. These elements make up a B-cell epitope recognized by nearly 100% of sera from infected patients or animals, designated the principal immunodominant domain (PID). The PID amino acid sequences are highly conserved between isolates of the same lentivirus but are unrelated, except for the two cysteines, when divergent lentiviruses are compared. The aim of this study was to analyze the relationship between amino acid sequence in the PID and envelope function. We introduced two kinds of mutations in the PID of FIV: mutations which impeded the formation of a loop and mutations which substituted the sequence of FIV with the corresponding sequences from other lentiviruses, HIV-1, visna virus, and equine infectious anemia virus. We analyzed antibody recognition, processing, and fusogenic properties of the modified envelopes, using two methods of Env expression: a cell-free expression system and transfection of a feline fibroblast cell line with gag-pol-deleted FIV proviruses. Most mutations in the PID of FIV severely affected envelope processing and abolished syncytium formation. Only the chimeric envelope containing the HIV-1 PID sequence was correctly processed and maintained the capacity to induce syncytium formation, although less efficiently than the wild-type envelope. We computed three-dimensional structural models of the PID, which were consistent with mutagenesis data and confirmed the similarity of FIV and HIV-1 PID structures, despite their divergence in amino acid sequence. Considering these results, we discussed the respective importance of selection exerted by functional requirements or host antibodies to explain the observed variations of the PIDs in lentiviruses.