Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of mobile applications through a feedback-based quality assurance approach

With an approach for mobile application development that is based on developing a minimal set of functions in order to realize a minimum viable product (MVP), it is possible to put a product on the market within a short amount of time. Nevertheless, this beneficial short time to market often involves poor quality of the developed application. Currently, the elicitation, analysis, and processing of user feedback are unfocused and take too much time and effort to mitigate the poor quality of the application. Hence, we outline an approach aimed at tailored quality assurance as part of MVP development, which enables and expands the benefits of MVP by providing a semi-automated feedback elicitation, analysis, and processing framework. This is intended to raise the effectiveness and efficiency of early user feedback consideration during further development in order to assure the quality and acceptance of a minimalistically developed mobile application.
On the Use of Real-Time Maude for Architecture Description and Verification: A Case Study

Real-Time Maude is an executable rewriting logic language particularly well suited for the specification of object-oriented open and distributed real time systems. In this paper we explore the possibility of using Real-Time Maude as a formal notation for software architecture description and verification of real time systems. The system model is composed of two kinds of descriptions: static and dynamic. The static description consists in identifying the different elements composing the architecture, while the dynamic description is the definition of the rules governing the system behaviour in terms of the possible actions allowed. The correspondence between software architecture concepts and the Real-Time Maude concepts are developed for this purpose. The step towards verifying system architecture is realized by applying Real-Time Maude simulation and analysis techniques to the described model and the properties that must be satisfied. An example is used to illustrate our proposal and to compare it with other architecture description languages.
U-TEL: a tool for eliciting user task models from domain experts

Eliciting user-task models is a thorny problem in modelbased user interface design, and communicating domainspecific knowledge from an expert to a knowledge engineer is a continuing problem in knowledge acquisition. We devised a task elicitation method that capitalizes on a domain expert’s ability to describe a task in plain English, and on a knowledge engineer’s skills to formalize it. The method bridges the gap between the two by helping the expert refine the description and by giving the engineer clues to its structure. We implemented and evaluated an interactive tool called the User-Task Elicitation Tool (U-TEL) to elicit user-task models from domain experts based on our methodology. Via direct manipulation, U-TEL provides capabilities for word processing, keyword classification, and outline refinement, By using U-TEL, domain experts can refine a textual specification of a user task into a basic user-task model suitable for use in model-based interface development environments. Our evaluation shows that U-TEL can be used effectively by domain experts with or without a background in programming or interface modeling, and that the tool can be a key element in promoting user-centered interface design in model-based systems.
Length and GC Content Variability of Introns among Teleostean Genomes in the Light of the Metabolic Rate Hypothesis

A comparative analysis of five teleostean genomes, namely zebrafish, medaka, three-spine stickleback, fugu and pufferfish was performed with the aim to highlight the nature of the forces driving both length and base composition of introns (i.e., bpi and GCi). An inter-genome approach using orthologous intronic sequences was carried out, analyzing independently both variables in pairwise comparisons. An average length shortening of introns was observed at increasing average GCi values. The result was not affected by masking transposable and repetitive elements harbored in the intronic sequences. The routine metabolic rate (mass specific temperature-corrected using the Boltzmann's factor) was measured for each species. A significant correlation held between average differences of metabolic rate, length and GC content, while environmental temperature of fish habitat was not correlated with bpi and GCi. Analyzing the concomitant effect of both variables, i.e., bpi and GCi, at increasing genomic GC content, a decrease of bpi and an increase of GCi was observed for the significant majority of the intronic sequences (from ∼40% to ∼90%, in each pairwise comparison). The opposite event, concomitant increase of bpi and decrease of GCi, was counter selected (from <1% to ∼10%, in each pairwise comparison). The results further support the hypothesis that the metabolic rate plays a key role in shaping genome architecture and evolution of vertebrate genomes.
The metaheuristic GRASP as an upper bound for a branch and bound algorithm in a scheduling problem with non-related parallel machines and sequence-dependent setup times

This paper approaches a scheduling problem with parallel non-related machines, sequencedependent setup times, due dates, weighted jobs and eligibility constraints. A branch and bound algorithm (B&B) is developed and a solution provided by the metaheuristic GRASP is used as an upper bound. Instances are generated and solved by the B&B. The results are compared to the solutions found by the MILP solver XPRESS. The algorithm is shown experimentally to perform very well for problems with up to 17 jobs. A conclusion is shown, and new tests for the full article are proposed.
Modeling Sovereign Yield Spreads: A Case Study of Russian Debt

We construct a model for pricing sovereign debt that accounts for the risks of both default and restructuring, and allows for compensation for illiquidity. Using a new and relatively efficient method, we estimate the model using Russian dollar-denominated bonds. We consider the determinants of the Russian yield spread, the yield differential across different Russian bonds, and the implications for market integration, relative liquidity, relative expected recovery rates, and implied expectations of different default scenarios.
Eye-Tracking Metrics in Software Engineering

Eye-tracking studies are getting more prevalent in software engineering. Researchers often use different metrics when publishing their results in eye-tracking studies. Even when the same metrics are used, they are given different names, causing difficulties in comparing studies. To encourage replications and facilitate advancing the state of the art, it is important that the metrics used by researchers be clearly and consistently defined in the literature. There is therefore a need for a survey of eye-tracking metrics to support the (future) goal of standardizing eye-tracking metrics. This paper seeks to bring awareness to the use of different metrics along with practical suggestions on using them. It compares and contrasts various eye-tracking metrics used in software engineering. It also provides definitions for common metrics and discusses some metrics that the software engineering community might borrow from other fields.
Refinement of analgesia following thoracotomy and experimental myocardial infarction using the Mouse Grimace Scale

What is the central question of this study? There is an ethical imperative to optimize analgesia protocols for laboratory animals, but this is impeded by our inability to recognize pain reliably. We examined whether the Mouse Grimace Scale (MGS) provides benefits over a standard welfare scoring system for identifying a low level of pain in the frequently used murine surgical model of myocardial infarction. What is the main finding and its importance? Low‐level pain, responsive to analgesia, was detected by MGS but not standard methods. In this model, most of the pain is attributable to the thoracotomy, excepted in mice with very large infarcts. This approach represents a model for assessing postsurgical analgesia in rodents.
PIVoT: Project insights and Visualization Toolkit

An in-process view into a software development project's health is critical for its success. However, in services organizations, a typical software development team employs a heterogeneous set of tools based on client requirements through the different phases of the software project. The use of disparate tools with non-compatible outputs makes it very difficult to extract one coherent picture of the project's health and status. Existing project management tools either work at the process layer and rely on manually entered information, or are activity centric, without a holistic view. In this paper, we present PIVoT, a metric-based framework for automated, non-invasive, and in-process data collection and analysis in heterogeneous software project environments, that provides rich, multi-dimensional insights into the project's health and trajectory. Here, we introduce the different analyses, insights and metrics, and discuss their usage in typical software projects.
Sketch-based path design

We present Drive, a system for the conceptual layout of 3D path networks. Our sketch-based interface allows users to efficiently author path layouts with minimal instruction. Our system incorporates some new and noteworthy components. We present the break-out lens, a novel widget for interactive graphics, inspired by break-out views used in engineering visualization. We also make three contributions specific to path curve design: First, we extend our previous work to fit aesthetic paths to sketch strokes with constraints, using piecewise clothoid curves. Second, we determine the height of paths above the terrain using a constraint optimization formulation of the occlusion relationships between sketched strokes. Finally, we illustrate examples of terrain sensitive path construction in the context of road design: automatically removing foliage, building bridges and tunnels across topographic features and constructing road signs appropriate to the sketched paths.
Predictive Modeling Using a Somatic Mutational Profile in Ovarian High Grade Serous Carcinoma

Purpose Recent high-throughput sequencing technology has identified numerous somatic mutations across the whole exome in a variety of cancers. In this study, we generate a predictive model employing the whole exome somatic mutational profile of ovarian high-grade serous carcinomas (Ov-HGSCs) obtained from The Cancer Genome Atlas data portal. Methods A total of 311 patients were included for modeling overall survival (OS) and 259 patients were included for modeling progression free survival (PFS) in an analysis of 509 genes. The model was validated with complete leave-one-out cross-validation involving re-selecting genes for each iteration of the cross-validation procedure. Cross-validated Kaplan-Meier curves were generated. Cross-validated time dependent receiver operating characteristic (ROC) curves were computed and the area under the curve (AUC) values were calculated from the ROC curves to estimate the predictive accuracy of the survival risk models. Results There was a significant difference in OS between the high-risk group (median, 28.1 months) and the low-risk group (median, 61.5 months) (permutated p-value <0.001). For PFS, there was also a significant difference in PFS between the high-risk group (10.9 months) and the low-risk group (22.3 months) (permutated p-value <0.001). Cross-validated AUC values were 0.807 for the OS and 0.747 for the PFS based on a defined landmark time t = 36 months. In comparisons between a predictive model containing only gene variables and a combined model containing both gene variables and clinical covariates, the predictive model containing gene variables without clinical covariates were effective and high AUC values for both OS and PFS were observed. Conclusions We designed a predictive model using a somatic mutation profile obtained from high-throughput genomic sequencing data in Ov-HGSC samples that may represent a new strategy for applying high-throughput sequencing data to clinical practice.
Fast camera fingerprint search algorithm for source camera identification

To determine the source camera of a query image, the fingerprint from the query image needs to be compared with the fingerprints in the reference fingerprint database. Traditionally, the query fingerprint is compared with these reference fingerprints one by one in sequence. For a large database, however, such a brute-force search is inefficient and time-consuming. How to accurately locate the correct fingerprint in the reference fingerprint database is thus becoming a crucial problem for commercial applications of source camera identification. So far there have been few studies in literature addressing this problem. In this work, we propose a new solution to fast fingerprint search. We first store the information of the reference fingerprint digests in the separate-chaining hash table, and then introduce a new rule to select the candidate reference fingerprint digests before performing the correlation. The selection rule is incarnated with the search priority vector. Experimental results have shown that the proposed algorithm outperforms current algorithms.
Perceptron Training for a Wide-Coverage Lexicalized-Grammar Parser

This paper investigates perceptron training for a wide-coverage CCG parser and compares the perceptron with a log-linear model. The CCG parser uses a phrase-structure parsing model and dynamic programming in the form of the Viterbi algorithm to find the highest scoring derivation. The difficulty in using the perceptron for a phrase-structure parsing model is the need for an efficient decoder. We exploit the lexicalized nature of CCG by using a finite-state supertagger to do much of the parsing work, resulting in a highly efficient decoder. The perceptron performs as well as the log-linear model; it trains in a few hours on a single machine; and it requires only a few hundred MB of RAM for practical training compared to 20 GB for the log-linear model. We also investigate the order in which the training examples are presented to the online perceptron learner, and find that order does not significantly affect the results.
Combining Lidar and Synthetic Aperture Radar Data to Estimate Forest Biomass: Status and Prospects

Research activities combining lidar and radar remote sensing have increased in recent years. The main focus in combining lidar-radar forest remote sensing has been on the retrieval of the aboveground biomass (AGB), which is a primary variable related to carbon cycle in land ecosystems, and has therefore been identified as an essential climate variable. In this review, we summarize the studies combining lidar and radar in estimating forest AGB. We discuss the complementary use of lidar and radar according to the relevance of the added value. The most promising prospects for combining lidar and radar data are in the use of lidar-derived ground elevations for improving large-area biomass estimates from radar, and in upscaling of lidar-based AGB data across large areas covered by spaceborne radar missions.
The Selfie Generation: Examining the Relationship Between Social Media Use and Early Adolescent Body Image

Social media use among adolescents continues to increase each year. This cross-sectional study explored how the amount of time spent using social media and the frequency of specific behaviors on social media, namely, behaviors that involve self-objectification, were related to body surveillance and body shame among a sample of early adolescents (N = 142; 43 boys and 99 girls, X ¯ a g e = 12.44 years, SDage = 0.61). Utilizing self-report measures, three types of social media were examined: Twitter, Facebook, and Instagram. Analyses indicated that greater levels of self-objectifying social media use predicted greater body shame among youth, and this was mediated by an associated increase in body surveillance. This mediation was moderated by self-monitoring and gender, such that the mediating role of body surveillance was stronger among girls and adolescents who are particularly focused on others for approval (i.e., high in self-monitoring). Implications of these findings are discussed.
Protective Efficacy of Cross-Reactive CD8+ T Cells Recognising Mutant Viral Epitopes Depends on Peptide-MHC-I Structural Interactions and T Cell Activation Threshold

Emergence of a new influenza strain leads to a rapid global spread of the virus due to minimal antibody immunity. Pre-existing CD8+ T-cell immunity directed towards conserved internal viral regions can greatly ameliorate the disease. However, mutational escape within the T cell epitopes is a substantial issue for virus control and vaccine design. Although mutations can result in a loss of T cell recognition, some variants generate cross-reactive T cell responses. In this study, we used reverse genetics to modify the influenza NP336–374 peptide at a partially-solvent exposed residue (N->A, NPN3A mutation) to assess the availability, effectiveness and mechanism underlying influenza-specific cross-reactive T cell responses. The engineered virus induced a diminished CD8+ T cell response and selected a narrowed T cell receptor (TCR) repertoire within two Vβ regions (Vβ8.3 and Vβ9). This can be partially explained by the H-2DbNPN3A structure that showed a loss of several contacts between the NPN3A peptide and H-2Db, including a contact with His155, a position known to play an important role in mediating TCR-pMHC-I interactions. Despite these differences, common cross-reactive TCRs were detected in both the naïve and immune NPN3A-specific TCR repertoires. However, while the NPN3A epitope primes memory T-cells that give an equivalent recall response to the mutant or wild-type (wt) virus, both are markedly lower than wt->wt challenge. Such decreased CD8+ responses elicited after heterologous challenge resulted in delayed viral clearance from the infected lung. Furthermore, mice first exposed to the wt virus give a poor, low avidity response following secondary infection with the mutant. Thus, the protective efficacy of cross-reactive CD8+ T cells recognising mutant viral epitopes depend on peptide-MHC-I structural interactions and functional avidity. Our study does not support vaccine strategies that include immunization against commonly selected cross-reactive variants with mutations at partially-solvent exposed residues that have characteristics comparable to NPN3A.
The lower mass function of the young open cluster Blanco 1: from 30 M_(Jup) to 3 M_☉

Aims. We performed a deep wide field optical survey of the young (~100−150 Myr) open cluster Blanco 1 to study its low mass population well down into the brown dwarf regime and estimate its mass function over the whole cluster mass range. Methods. The survey covers 2.3 square degrees in the I and z-bands down to I ≃ z ≃ 24 with the CFH12K camera. Considering two different cluster ages (100 and 150 Myr), we selected cluster member candidates on the basis of their location in the (I, I − z) CMD relative to the isochrones, and estimated the contamination by foreground late-type field dwarfs using statistical arguments, infrared photometry and low-resolution optical spectroscopy. Results. We find that our survey should contain about 57% of the cluster members in the 0.03−0.6 M_☉ mass range, including 30–40 brown dwarfs. The candidate’s radial distribution presents evidence that mass segregation has already occured in the cluster. We took it into account to estimate the cluster mass function across the stellar/substellar boundary. We find that, between 0.03 M_☉ and 0.6 M_☉, the cluster mass distribution does not depend much on its exact age, and is well represented by a single power-law, with an index α = 0.69 ± 0.15. Over the whole mass domain, from 0.03 M_☉ to 3 M_☉, the mass function is better fitted by a log-normal function with m_0 = 0.36 ± 0.07 M_☉ and σ = 0.58 ± 0.06. Conclusions. Comparison between the Blanco 1 mass function, other young open clusters’ MF, and the galactic disc MF suggests that the IMF, from the substellar domain to the higher mass part, does not depend much on initial conditions. We discuss the implications of this result on theories developed to date to explain the origin of the mass distribution.
Generic criticality of community structure in random graphs

We examine a community structure in random graphs of size n and link probability p/n determined with the Newman greedy optimization of modularity. Calculations show that for p<1 communities are nearly identical with clusters. For p=1 the average sizes of a community s(av) and of the giant community s(g) show a power-law increase s(av)∼n(α') and s(g)∼n(α). From numerical results we estimate α'≈0.26(1) and α≈0.50(1) and using the probability distribution of sizes of communities we suggest that α'=α/2 should hold. For p>1 the community structure remains critical: (i) s(av) and s(g) have a power-law increase with α'≈α<1 and (ii) the probability distribution of sizes of communities is very broad and nearly flat for all sizes up to s(g). For large p the modularity Q decays as Q∼p(-0.55), which is intermediate between some previous estimations. To check the validity of the results, we also determine the community structure using another method, namely, a nongreedy optimization of modularity. Tests with some benchmark networks show that the method outperforms the greedy version. For random graphs, however, the characteristics of the community structure determined using both greedy and nongreedy optimizations are, within small statistical fluctuations, the same.
Answering Opinion Questions with Random Walks on Graphs

Opinion Question Answering (Opinion QA), which aims to find the authors' sentimental opinions on a specific target, is more challenging than traditional fact-based question answering problems. To extract the opinion oriented answers, we need to consider both topic relevance and opinion sentiment issues. Current solutions to this problem are mostly ad-hoc combinations of question topic information and opinion information. In this paper, we propose an Opinion PageRank model and an Opinion HITS model to fully explore the information from different relations among questions and answers, answers and answers, and topics and opinions. By fully exploiting these relations, the experiment results show that our proposed algorithms outperform several state of the art baselines on benchmark data set. A gain of over 10% in F scores is achieved as compared to many other systems.
I=2 Pion scattering length with improved actions on anisotropic lattices

ππ scattering length in the I=2 channel is calculated within quenched approximation using improved gauge and improved Wilson fermion actions on anisotropic lattices. The results are extrapolated towards the chiral, infinite volume and continuum limit. This result improves our previous result on the scattering length. In the chiral, infinite volume and continuum limit, we obtain , which is consistent with the result from Chiral Perturbation Theory, the experiment and results from other lattice calculations.
Criteria to measure the quality of TVAR estimation for audio signals

An audio signal can be represented by a Time-Varying Auto-Regressive (TVAR) model, whose parameters can be estimated by a particle filter. Since the original parameters are unavailable for real signals, an evaluation of the estimation may be traditionally performed through indirect criteria such as the SNR of the signal denoised by a Kalman filter based on the TVAR estimated model or through a statistical analysis based on the observation. We propose a new evaluation method based on the statistical characterization of the output of the inverse TVAR estimated model. The proposed criteria are much more suitable and coherent when correlated to the direct criterion (cepstral distance), which is related to the estimated TVAR parameters.