Miracle-dz/UniFAR-FTUs huggingface dataset:
ReUML: a UML Profile for Modeling and Verification of Reactive Systems

The Unified Modeling Language, has become effectively the standard modeling language for analysis and design of software systems. However, despite achievements in defining semi-formal semantics, with a combination of OCL constraints and textual descriptions of the UML semantics, UML is still an informal language. This paper introduces a tool for developing correct models of distributed and reactive systems using UML and Rebeca. Rebeca is an actor- based modeling language supported by a formal verification tool. This approach can bridge the gap between software development and formal verification by allowing users to develop their systems using UML and yet getting advantage of formal verification support of Rebeca tools and theory. In this way, we combine two separate approaches to modeling by adding verification step to software development lifecycle. Furthermore, this can make a contribution to defining rigorous semantics for UML diagrams and to provide tool support for verification of these diagrams.
A Review Approach to Detecting Violations of Consistency between Specification and Program Structures

The application of specification-based program verification techniques (e.g., black-box testing, formal proof) faces strong challenges in practice when the gap between the structure of a specification and that of its program is large. This paper describes a view-based program review approach to addressing these challenges. The essential idea of the approach is first to derive comparable views from the specification and program, and then detect and eliminate the violations of structural consistency in the program views on the basis of a set of criteria. We also developed a prototype tool to support the review approach, and conducted a case study to assess the effectiveness of the approach.
Comparison of Antioxidant Properties of Water and Ethanol Extracts Obtained from Dried Boxthorn (Lycium chinensis) Fruit

Antioxidant activities of W and E extracts obtained from dried boxthorn (Lycium chinensis) fruit were measured based on DPPH radical scavenging and reducing powers, and their relationships with total phenolics, flavonoid content, and antioxidant activity were investigated. A linear correlation among antioxidant activity, total phenolics, and flavonoid content was observed in concentration-dependent mode. Both extracts showed > 95% DPPH radical-scavenging activity and the higher reducing power of 3200 ppm at the same concentration. The antioxidant potential of both extracts were compared with those of commercial antioxidants such as BHA, BHT, TBHQ, ferulic acid, and α-tocopherol using H2O2 scavenging activity, inhibition of linoleic acid peroxidation, inhibition of hemolysis of rat erythrocyte induced by peroxyl radicals, and inhibition of Fe2+-induced lipid peroxidation using rat brain tissue. In the H2O2 scavenging activity, E extract showed a comparable significant antioxidant power, comparable to commercial antioxidants, and no signifi-cant difference (P > 0.05) was found between W and E extracts on inhibition of the linoleic acid peroxidation. Whereas W extract exhibited a significant power in the hemolysis of rat erythrocytes, none was observed in E extract. In the Fe-induced lipid peroxidation using rat brain tissue, no significant difference (P > 0.05) was found between both ex-tracts, showing a comparable activity with those of synthetic antioxidants. Both W and E extracts of dried boxthorn (Lycium chinensis) fruit may have a potential as natural antioxidants to replace synthetic antioxidants.
Pyrosequencing-Based Analysis of the Microbiome Associated with the Horn Fly, Haematobia irritans

The horn fly, Haematobia irritans, is one of the most economically important pests of cattle. Insecticides have been a major element of horn fly management programs. Growing concerns with insecticide resistance, insecticide residues on farm products, and non-availability of new generation insecticides, are serious issues for the livestock industry. Alternative horn fly control methods offer the promise to decrease the use of insecticides and reduce the amount of insecticide residues on livestock products and give an impetus to the organic livestock farming segment. The horn fly, an obligatory blood feeder, requires the help of microflora to supply additional nutrients and metabolize the blood meal. Recent advancements in DNA sequencing methodologies enable researchers to examine the microflora diversity independent of culture methods. We used the bacterial 16S tag-encoded FLX-titanium amplicon pyrosequencing (bTEFAP) method to carry out the classification analysis of bacterial flora in adult female and male horn flies and horn fly eggs. The bTEFAP method identified 16S rDNA sequences in our samples which allowed the identification of various prokaryotic taxa associated with the life stage examined. This is the first comprehensive report of bacterial flora associated with the horn fly using a culture-independent method. Several rumen, environmental, symbiotic and pathogenic bacteria associated with the horn fly were identified and quantified. This is the first report of the presence of Wolbachia in horn flies of USA origin and is the first report of the presence of Rikenella in an obligatory blood feeding insect.
Semi-supervised training of Least Squares Support Vector Machine using a multiobjective evolutionary algorithm

Support Vector Machines (SVMs) are considered state-of-the-art learning machines techniques for classification problems. This paper studies the training of SVMs in the special case of problems in which the raw data to be used for training purposes is composed of both labeled and unlabeled data - the semi-supervised learning problem. This paper proposes the definition of an intermediate problem of attributing labels to the unlabeled data as a multiobjective optimization problem, with the conflicting objectives of minimizing the classification error over the training data set and maximizing the regularity of the resulting classifier. This intermediate problem is solved using an evolutionary multiobjective algorithm, the SPEA2. Simulation results are presented in order to illustrate the suitability of the proposed technique.
In vitro and In vivo Models Analyzing von Hippel-Lindau Disease-Specific Mutations

Mutations in the von Hippel-Lindau (VHL) tumor suppressor gene cause tissue-specific tumors, with a striking genotype-phenotype correlation. Loss of VHL expression predisposes to hemangioblastoma and clear cell renal cell carcinoma, whereas specific point mutations predispose to pheochromocytoma, polycythemia, or combinations of hemangioblastoma, renal cell carcinoma, and/or pheochromocytoma. The VHL protein (pVHL) has been implicated in many cellular activities including the hypoxia response, cell cycle arrest, apoptosis, and extracellular matrix remodeling. We have expressed missense pVHL mutations in Vhl−/− murine embryonic stem cells to test genotype-phenotype correlations in euploid cells. We first examined the ability of mutant pVHL to direct degradation of the hypoxia inducible factor (HIF) subunits HIF1α and HIF2α. All mutant pVHL proteins restored proper hypoxic regulation of HIF1α, although one VHL mutation (VHLR167Q) displayed impaired binding to Elongin C. This mutation also failed to restore HIF2α regulation. In separate assays, these embryonic stem cells were used to generate teratomas in immunocompromised mice, allowing independent assessment of the effects of specific VHL mutations on tumor growth. Surprisingly, teratomas expressing the VHLY112H mutant protein displayed a growth disadvantage, despite restoring HIFα regulation. Finally, we observed increased microvessel density in teratomas derived from Vhl−/− as well as VHLY112H, VHLR167Q, and VHLR200W embryonic stem cells. Together, these observations support the hypothesis that pVHL plays multiple roles in the cell, and that these activities can be separated via discrete VHL point mutations. The ability to dissect specific VHL functions with missense mutations in a euploid model offers a novel opportunity to elucidate the activities of VHL as a tumor suppressor.
Manipulation of gold colloidal nanoparticles with atomic force microscopy in dynamic mode: influence of particle–substrate chemistry and morphology, and of operating conditions

One key component in the assembly of nanoparticles is their precise positioning to enable the creation of new complex nano-objects. Controlling the nanoscale interactions is crucial for the prediction and understanding of the behaviour of nanoparticles (NPs) during their assembly. In the present work, we have manipulated bare and functionalized gold nanoparticles on flat and patterned silicon and silicon coated substrates with dynamic atomic force microscopy (AFM). Under ambient conditions, the particles adhere to silicon until a critical drive amplitude is reached by oscillations of the probing tip. Beyond that threshold, the particles start to follow different directions, depending on their geometry, size and adhesion to the substrate. Higher and respectively, lower mobility was observed when the gold particles were coated with methyl (–CH3) and hydroxyl (–OH) terminated thiol groups. This major result suggests that the adhesion of the particles to the substrate is strongly reduced by the presence of hydrophobic interfaces. The influence of critical parameters on the manipulation was investigated and discussed viz. the shape, size and grafting of the NPs, as well as the surface chemistry and the patterning of the substrate, and finally the operating conditions (temperature, humidity and scan velocity). Whereas the operating conditions and substrate structure are shown to have a strong effect on the mobility of the particles, we did not find any differences when manipulating ordered vs random distributed particles.
Boosting Expert Ensembles for Rapid Concept Recall

Many learning tasks in adversarial domains tend to be highly dependent on the opponent. Predefined strategies optimized for play against a specific opponent are not likely to succeed when employed against another opponent. Learning a strategy for each new opponent from scratch, though, is inefficient as one is likely to encounter the same or similar opponents again. We call this particular variant of inductive transfer a concept recall problem. We present an extension to AdaBoost called ExpBoost that is especially designed for such a sequential learning tasks. It automatically balances between an ensemble of experts each trained on one known opponent and learning the concept of the new opponent. We present and compare results of Exp-Boost and other algorithms on both synthetic data and in a simulated robot soccer task. ExpBoost can rapidly adjust to new concepts and achieve performance comparable to a classifier trained exclusively on a particular opponent with far more data.
Joint Turbo Frequency Domain Equalization and Carrier Synchronization

In this paper we propose a synchronization method to compensate for the effect of frequency offset and phase noise generated by local oscillator instabilities for a Turbo Frequency Domain Equalizer (TFDE). TFDE is considered as an efficient equalization method which benefits from both good performance of iterative systems and reasonable complexity due to performing equalization in the frequency domain. We propose a joint turbo equalization and synchronization method in which the feedback information, generated iteratively by the decoder, is used for synchronization. As iterations continue, if the feedback information becomes more reliable, the performance of the synchronization method is continually improved. We propose two methods based on different criteria when the system suffers from only frequency offset. We also suggest a method based on Maximum A Posteriori (MAP) criterion in the presence of both frequency offset and phase noise which can be considered as a decision directed phase lock loop. These methods achieve considerable performance improvement with reasonable complexity.
A comparison between cystatin C, plasma creatinine and the Cockcroft and Gault formula for the estimation of glomerular filtration rate.

BACKGROUND In clinical practice, the glomerular filtration rate (GFR) is often estimated from plasma creatinine. Several studies have shown cystatin C (cys C) to be a better parameter for the diagnosis of impaired renal function. No data are available, however, on the performance of cys C in follow-up of patients, compared with creatinine. Also, comparisons of cys C with the Cockcroft and Gault (C&G) formula for estimation of GFR are few. METHODS Plasma samples were obtained from 93 consecutive patients seen for GFR determination and from 30 patients with diabetes mellitus type 2, of whom 23 were investigated a second time after 2 years. GFR was determined with [125I]iothalamate. Plasma creatinine was determined enzymatically and the creatinine clearance calculated according to C&G. Cys C was measured with a particle-enhanced immunonephelometric method. RESULTS GFR correlated with 1/cys C (r = 0.873) as well as with C&G (r = 0.876). The area under the curve (AUC) of the receiver operating curves (ROCs), a measure of diagnostic accuracy, for cys C (0.931) and C&G (0.938) were equal (P = 0.815) and both better than the creatinine AUC (0.848; P = 0.006). Bland and Altman analysis showed that the simple formula GFR = -4.32 + 80.35 x 1/cys C, derived from our data, gave more accurate (P < 0.0001) and more precise (P = 0.024) GFR estimates than obtained with the C&G formula. The day-to-day variation (biological +analytical) for cys C was small (3.1%, SD 2.51%) in diabetic patients. In the follow-up study in diabetic patients, cys C was the parameter which had the best correlation (r = 0.66) with changes in GFR. CONCLUSIONS Cys C shows a high correlation with GFR. With a very simple formula, cys C gives a good estimate of GFR, more accurate and precise than C&G. Because biological variation is low, cys C gives also a good assessment of GFR changes during follow-up. Cys C is the preferred endogenous parameter for GFR.
Context-Aware Augmented Reality Authoring Tool in Digital Ecosystem

In this paper, we propose a context-aware authoring tool which users make virtual contents in-situ. In order to realize, three essential components are defined and some technical challenges are reviewed. We expect that the contents will be adaptive and responsible to dynamic environment. It will be applicable for many industries such as book publication, in-situ simulation and so on.
Random walks based modularity: application to semi-supervised learning

Although criticized for some of its limitations, modularity remains a standard measure for analyzing social networks. Quantifying the statistical surprise in the arrangement of the edges of the network has led to simple and powerful algorithms. However, relying solely on the distribution of edges instead of more complex structures such as paths limits the extent of modularity. Indeed, recent studies have shown restrictions of optimizing modularity, for instance its resolution limit. We introduce here a novel, formal and well-defined modularity measure based on random walks. We show how this modularity can be computed from paths induced by the graph instead of the traditionally used edges. We argue that by computing modularity on paths instead of edges, more informative features can be extracted from the network. We verify this hypothesis on a semi-supervised classification procedure of the nodes in the network, where we show that, under the same settings, the features of the random walk modularity help to classify better than the features of the usual modularity. Additionally, the proposed approach outperforms the classical label propagation procedure on two data sets of labeled social networks.
Adult attachment and coping style in students with elevated mood

Background The psychological wellbeing of individuals may be disrupted through experiencing periods of elevated mood, known as mania. Identifying processes which may be used to predict the onset of mania may be helpful in the development of more specialised psychological interventions. The research explores the cognitive processes which may contribute to the development of elevated mood episodes. Methods The research addresses this question through a review of the literature which is used to inform the current investigation. The study considers how coping style and attachment style may be used to predict the onset of elevated mood in undergraduate and postgraduate university students (n=100). Participants completed the Relationship Questionnaire (RQ; Bartholomew and Horowitz, 1991), the Brief COPE (Carver, 1997) and the Goldberg Mania Questionnaire (GMQ: Goldberg, 1993). Regression analyses were conducted to explore the data. The reflective paper highlights some of the methodological limitations, clinical implications and ethical considerations of the study. Results The literature review revealed that cognitions such as positive rumination, specific beliefs about the self and a positive cognitive style were implicated in the development of manic experiences. The empirical study found that a preoccupied attachment style, and coping strategies of denial distraction and humour were significant predictors of elevated mood. Discussion The clinical implications regarding how the results may inform clinical practice through psychological interventions such as cognitive behavioural therapy are discussed. Limitations included the cross sectional design methodology, the use of online questionnaires and difficulties in generalisation. Conclusions Attachment style and coping strategies may be used to predict the onset of elevated moods. This may be useful for the development of new psychological interventions in mania. The thesis provides further clarification regarding psychological factors involved in the development of mania and identifies possible new areas for further exploration.
Study of Dementia in Swedish Twins

The Study of Dementia in Swedish Twins is a study of dementia in a defined population of twins. The goals included estimating heritability of Alzheimer's disease and identifying risk and protective factors in twin pairs discordant for the disease. The data, including not only diagnoses and age of onset but also extensive information about potential environmental risk factors, are now archived as Study ICPSR 25963 at National Archive for Computerized Data on Aging, Inter-university Consortium for Political and Social Research, at the University of Michigan, and available for researchers to use. Up to the time of archiving, 215 cases of dementia have been identified from a base sample of 2,394 individuals.
Fast generation of cylindrical panoramic views from free-hand video sequences

We report on a fast algorithm for the generation of cylindrical panoramic views from hand-held video sequences. Due to its high processing speed the algorithm is suited for hardware implementation into next generation video- and photo cameras. This enables the user to easily create immersive views from simple pan shots of variable quality. The individual processing steps within the algorithm are described in detail. Final results of the video to panorama conversion process along with an an outlook on how to further improve the method when implemented in consumer grade video- and photo cameras are given at the end of this paper.
Fuzzy Vault for Face Based Cryptographic Key Generation

This paper presents a method for changeable cryptographic key generation using face biometrics signal. A previously introduced scheme, fuzzy vault, is utilized for secure binding of randomly generated key with extracted biometrics features. The major technical difficulty is to map noisy biometrics representation to the exactly correct key. In this paper, the proposed method is based on 2-dimensional quantization of distance vectors between biometrics features and pairs of random vectors. A windowing process is applied to tolerate the variations of biometrics signals. Further, we also introduce a two-factor scheme, where the quantized distance vectors are generated with user-dependent random vectors. By integrating a second factor, both the biometrics and the key are changeable, and zero error rate can be obtained.
Factor Structure of the WAIS-R Italian Version Compared with American and British Solutions

The WAIS-R was administered to a sample of 180 young Italian adults (aged 19 to 35 years). A principal components analysis was conducted on the 11 subtests to investigate the factor structure. According to the criteria of extraction, one- and three-factor solutions are discussed. The oblique rotation provided evidence for three correlated factors, 1: Verbal, 2: Perceptual Organization, and 3: Freedom from Distractibility. However, to compare Italian results with those obtained in the USA and UK, an orthogonal rotation was performed. High coefficients of congruence point to similarity of factor loading matrices in all three countries.
Vantage: Scalable and efficient fine-grain cache partitioning

Cache partitioning has a wide range of uses in CMPs, from guaranteeing quality of service and controlled sharing to security-related techniques. However, existing cache partitioning schemes (such as way-partitioning) are limited to coarse-grain allocations, can only support few partitions, and reduce cache associativity, hurting performance. Hence, these techniques can only be applied to CMPs with 2-4 cores, but fail to scale to tens of cores. We present Vantage, a novel cache partitioning technique that overcomes the limitations of existing schemes: caches can have tens of partitions with sizes specified at cache line granularity, while maintaining high associativity and strong isolation among partitions. Vantage leverages cache arrays with good hashing and associativity, which enable soft-pinning a large portion of cache lines. It enforces capacity allocations by controlling the replacement process. Unlike prior schemes, Vantage provides strict isolation guarantees by partitioning most (e.g. 90%) of the cache instead of all of it. Vantage is derived from analytical models, which allow us to provide strong guarantees and bounds on associativity and sizing independent of the number of partitions and their behaviors. It is simple to implement, requiring around 1.5% state overhead and simple changes to the cache controller. We evaluate Vantage using extensive simulations. On a 32-core system, using 350 multi programmed workloads and one partition per core, partitioning the last-level cache with conventional techniques degrades throughput for 71 % of the workloads versus an unpartitioned cache (by 7% average, 25% maximum degradation), even when using 64-way caches. In contrast, Vantage improves throughput for 98% of the workloads, by 8% on average (up to 20%), using a 4-way cache.