Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bermuda Triangle?: A Review of Method Application and Triangulation in User Experience Evaluation

User experience (UX) evaluation is a growing field with diverse approaches. To understand the development since previous meta-review efforts, we conducted a state-of-the-art review of UX evaluation techniques with special attention to the triangulation between methods. We systematically selected and analyzed 100 papers from recent years and while we found an increase of relevant UX studies, we also saw a remaining overlap with pure usability evaluations. Positive trends include an increasing percentage of field rather than lab studies and a tendency to combine several methods in UX studies. Triangulation was applied in more than two thirds of the studies, and the most common method combination was questionnaires and interviews. Based on our analysis, we derive common patterns for triangulation in UX evaluation efforts. A critical discussion about existing approaches should help to obtain stronger results, especially when evaluating new technologies.
Detection Is Better Than Cure: A Cloud Incidents Perspective

Cloud providers use automated watchdogs or monitors to continuously observe service availability and to proactively report incidents when system performance degrades. Improper monitoring can lead to delays in the detection and mitigation of production incidents, which can be extremely expensive in terms of customer impacts and manual toil from engineering resources. Therefore, a systematic understanding of the pitfalls in current monitoring practices and how they can lead to production incidents is crucial for ensuring continuous reliability of cloud services. In this work, we carefully study the production incidents from the past year at Microsoft to understand the monitoring gaps in a hyperscale cloud platform. We conduct an extensive empirical study to answer: (1) What are the major causes of failures in early detection of production incidents and what are the steps taken for mitigation, (2) What is the impact of failures in early detection, (3) How do we recommend best monitoring practices for different services, and (4) How can we leverage the insights from this study to enhance the reliability of the cloud services. This study provides a deeper understanding of existing monitoring gaps in cloud platforms, uncover interesting insights and provide guidance for best monitoring practices for ensuring continuous reliability.
LazyCow: A Lightweight Crowdsourced Testing Tool for Taming Android Fragmentation

Android fragmentation refers to the increasing variety of Android devices and operating system versions. Their number make it impossible to test an app on every supported device, resulting in many device compatibility issues and leading to poor user experiences. To mitigate this, a number of works that automatically detect compatibility issues have been proposed. However, current state-of-the-art techniques can only be used to detect specific types of compatibility issues (i.e., compatibility issues caused by API signature evolution), i.e., many other essential categories of compatibility issues are still unknown. For instance, customised OS versions on real devices and semantic OS modifications could result in severe compatibility issues that are difficult to detect statically. In order to address this research gap and facilitate the prospect of taming Android frag- mentation through crowdsourced efforts, we propose LazyCow, a novel, lightweight, crowdsourced testing tool. Our experimental results involving thousands of test cases on real Android devices demonstrate that LazyCow is effective at autonomously identifying and validating API-induced compatibility issues. The source code of both client side and server side are all made publicly available in our artifact package. A demo video of our tool is available at https://www.youtube. com/watch? v=_xzWv_mo5xQ.
Heterogeneous Testing for Coverage Profilers Empowered with Debugging Support

Ensuring the correctness of code coverage profilers is crucial, given the widespread adoption of code coverage for various software engineering tasks. Existing validation techniques, such as differential testing and metamorphic testing, have shown effectiveness in uncovering bugs in coverage profilers. However, these techniques have limitations as they primarily rely on homogeneous sources, i.e., different coverage profilers or the profilers themselves, for validation. In this paper, we propose Decov, a novel heterogeneous testing technique, to validate coverage profilers using the information provided by debuggers as a heterogeneous source. Coverage profilers record execution counts for each source line in the program, while debuggers monitor hit counts for each source line when running the program in debug mode. Our key insight is that the execution counts obtained from coverage profilers should align with the hit counts monitored by debuggers, without conflicts. Decov constructs multiple heterogeneous relations and utilizes them to uncover bugs in coverage profilers. Through experiments on Gcov and LLVM-cov, two widely used code coverage profilers, we discovered 21 new bug reports, with 19 of them directly confirmed by developers. Notably, developers have resolved 5 bugs in the latest trunk version. Decov serves as a simple yet effective coverage profiler validator and offers a complementary approach to existing techniques.
CAmpactor: A Novel and Effective Local Search Algorithm for Optimizing Pairwise Covering Arrays

The increasing demand for software customization has led to the development of highly configurable systems. Combinatorial interaction testing (CIT) is an effective method for testing these types of systems. The ultimate goal of CIT is to generate a test suite of acceptable size, called a t-wise covering array (CA), where t is the testing strength. Pairwise testing (i.e., CIT with t=2) is recognized to be the most widely-used CIT technique and has strong fault detection capability. In pairwise testing, the most important problem is pairwise CA generation (PCAG), which is to generate a pairwise CA (PCA) of minimum size. However, existing state-of-the-art PCAG algorithms suffer from the severe scalability challenge; that is, they cannot tackle large-scale PCAG instances effectively, resulting in PCAs of large sizes. To alleviate this challenge, in this paper we propose CAmpactor, a novel and effective local search algorithm for compacting given PCAs into smaller sizes. Extensive experiments on a large number of real-world, public PCAG instances show that the sizes of CAmpactor's generated PCAs are around 45% smaller than the sizes of PCAs constructed by existing state-of-the-art PCAG algorithms, indicating its superiority. Also, our evaluation confirms the generality of CAmpactor, since CAmpactor can reduce the sizes of PCAs generated by a variety of PCAG algorithms.
Analyzing High-Risk Emergency Areas with GIS and Neural Networks: The Case of Athens, Greece

Any analysis of health service problems facing the world today must consider that these problems exist in a geographic context. This fact has led to an increased need for accurate and current information to support emergency planning and decision making. In this article we combine geographic information systems (GIS) and neural networks for performing health emergency assessments and generating hazard maps that show areas that are potentially at high risk for emergencies. Through the use of neural networks we predict the location of future emergency events. On these events we use a kernel density estimator to create maps of areas that have a high risk for future emergencies. As a result, emergency services will know in advance where there is a high possibility of an emergency event occurring and can formulate a response, thus improving incident management and health planning. For example, the service can locate ambulances in places near the expected emergency cases, minimizing response time. The approach was tested in stroke-event analysis in the city of Athens, Greece.
Statfier: Automated Testing of Static Analyzers via Semantic-Preserving Program Transformations

Static analyzers reason about the behaviors of programs without executing them and report issues when they violate pre-defined desirable properties. One of the key limitations of static analyzers is their tendency to produce inaccurate and incomplete analysis results, i.e., they often generate too many spurious warnings and miss important issues. To help enhance the reliability of a static analyzer, developers usually manually write tests involving input programs and the corresponding expected analysis results for the analyzers. Meanwhile, a static analyzer often includes example programs in its documentation to demonstrate the desirable properties and/or their violations. Our key insight is that we can reuse programs extracted either from the official test suite or documentation and apply semantic-preserving transformations to them to generate variants. We studied the quality of input programs from these two sources and found that most rules in static analyzers are covered by at least one input program, implying the potential of using these programs as the basis for test generation. We present Statfier, a heuristic-based automated testing approach for static analyzers that generates program variants via semantic-preserving transformations and detects inconsistencies between the original program and variants (indicate inaccurate analysis results in the static analyzer). To select variants that are more likely to reveal new bugs, Statfier uses two key heuristics: (1) analysis report guided location selection that uses program locations in the reports produced by static analyzers to perform transformations and (2) structure diversity driven variant selection that chooses variants with different program contexts and diverse types of transformations. Our experiments with five popular static analyzers show that Statfier can find 79 bugs in these analyzers, of which 46 have been confirmed.
Who's Afraid of Conflict? The Mobilizing Effect of Conflict Framing in Campaign News Schuck,

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Emotional and Functional Challenge in Core and Avant-garde Games

Digital games are a wide, diverse and fast developing art form, and it is important to analyse games that are pushing the medium forward to see what design lessons can be learned. However, there are no established criteria to determine which games show these more progressive qualities. Grounded theory methodology was used to analyse language used in games reviews by critics of both ‘core gamer’ titles and those titles with more avant-garde properties. This showed there were two kinds of challenge being discussed — emotional and functional which appear to be, at least partially, mutually exclusive. Reviews of ‘core’ and ‘avantgarde’ games had different measures of purchase value, primary emotions, and modalities of language used to discuss the role of audiovisual qualities. Emotional challenge, ambiguity and solitude are suggested as useful devices for eliciting emotion from the player and for use in developing more ’avant-garde’ games, as well as providing a basis for further lines of inquiry. Author
Mining Resource-Operation Knowledge to Support Resource Leak Detection

Resource leaks, which are caused by acquired resources not being released, often result in performance degradation and system crashes. Resource leak detection relies on two essential components: identifying potential Resource Acquisition and Release (RAR) API pairs, and subsequently analyze code to uncover instances where the corresponding release API call is absent after an acquisition API call. Yet, existing techniques confine themselves to an incomplete pair pool, either pre-defined manually or mined from project-specific code corpus, thus limiting coverage across libraries/APIs and po- tentially overlooking latent resource leaks. In this work, we propose to represent resource-operation knowledge as abstract resource acquisition/release operation pairs (Abs-RAR pairs for short), and present a novel approach called MiROK to mine such Abs-RAR pairs to construct a better RAR pair pool. Given a large code corpus, MiROK first mines Abs-RAR pairs with rule-based pair expansion and learning-based pair identification strategies, and then instantiates these Abs-RAR pairs into concrete RAR pairs. We implement MiROK and apply it to mine RAR pairs from a large code corpus of 1,454,224 Java methods and 20,000 Maven libraries. We then perform an extensive evaluation to investigate the mining effectiveness of MiROK and the practical usage of its mined RAR pairs for supporting resource leak detection. Our results show that MiROK mines 1,313 new Abs-RAR pairs and instantiates them into 6,314 RAR pairs with a high precision (i.e., 93.3%). In addition, by feeding our mined RAR pairs, existing approaches detect more resource leak defects in both online code examples and open-source projects
Size of the Bimodality by using Trapezoidal Rule

This study investigates size of the bimodality to illustrate the gap between two modes/peaks in a bimodal distribution. To get this goal, one of the definite integral (i.e. Trapezoidal rule) is used on the mixture of normals (the mixture of one normal and the second one standard normal) with the selected parameter values of mean, mixing proportion and standard deviation. From the results, an increase of size of bimodality is identified if mean increases while all other parameters remain constant. A similar situation of increasing pattern of bimodality size has been observed when parametric values of mixing proportion increases (varies) while keeping other parameter values constant. However, a fraction changed is revealed in the size of bimodality if values of mean and mixing proportion are kept constant while standard deviation varies.
The Influences Between E-Service Quality Toward Positive and Opposition Brand Referral in Malaysia

Telecommunication sector is one of the drivers in the new digitalization era by providing the basis for business expansion and flow of investment through the communication. In Malaysia, this sector had faced some of the challenge regarding the customer perception which led the industry facing some negative brand referral and directed the brand evangelism failed to develop. Therefore, this research aims to identify the influences between e-service quality dimension consist of responsiveness, ease of use, privacy & security, functionality, reliability, efficiency towards the positive brand referrals as well as oppositional brand referrals. Through quantitative analysis, questionnaires were distributed, and the answers were analyzed. Based on the analysis conducted, it was found that reliability, functionality, and ease of use significantly contributed in predicting the positive brand referral. While reliability, privacy, and functionality significantly supported in predicting the oppositional brand referral in Malaysia.
Elevated SLC40A1 impairs cardiac function and exacerbates mitochondrial dysfunction, oxidative stress, and apoptosis in ischemic myocardia

Iron homeostasis is crucial for optimal cardiac function. Iron deficiency and overload have been linked to the development of cardiomyopathy and heart failure (HF) via intricate mechanisms. Although the crucial role of SLC40A1 in iron metabolism by facilitating the efflux of cellular iron has been confirmed, its specific molecular functions in cardiovascular diseases remain poorly understood. In this study, we generated mice with inducible cardiomyocyte-specific overexpression of SLC40A1 for the first time. The overexpression of SLC40A1 in the cardiomyocytes of adult mice resulted in significant iron deficiency, leading to mitochondrial dysfunction, oxidative stress, and apoptosis, subsequently resulting in the development of fatal HF. Notably, SLC40A1 upregulation was observed in the ischemic region during the initial phase of myocardial infarction (MI), contributing to iron loss in the cardiomyocytes. Conversely, the cardiomyocyte-specific knockdown of SLC40A1 improved cardiac dysfunction after MI by enhancing mitochondrial function, suppressing oxidative stress, and reducing cardiomyocytes apoptosis. Mechanistically, Steap4 interacted with SLC40A1, facilitating SLC40A1-mediated iron efflux from cardiomyocytes. In short, our study presents evidence for the involvement of SLC40A1 in the regulation of myocardial iron levels and the therapeutic benefits of cardiomyocyte-specific knockdown of SLC40A1 in MI in mice.
University of Birmingham A season for all things

Phenology plays an important role in many human–nature interactions, but these seasonal patterns are often overlooked in conservation. Here, we provide the first broad exploration of seasonal patterns of interest in nature across many species and cultures. Using data from Wikipedia, a large online encyclopedia, we analyzed 2.33 billion pageviews to articles for 31,751 species across 245 languages. We show that seasonality plays an important role in how and when people interact with plants and animals online. In total, over 25% of species in our data set exhibited a seasonal pattern in at least one of their language-edition pages, and seasonality is significantly more prevalent in pages for plants and animals than it is in a random selection of Wikipedia articles. Pageview seasonality varies across taxonomic clades in ways that reflect observable patterns in phenology, with groups such as insects and flowering plants having higher seasonality than mammals. Differences between Wikipedia language editions are significant; pages in languages spoken at higher latitudes exhibit greater seasonality overall, and species seldom show the same pattern across multiple language editions. These results have relevance to conservation policy formulation and to improving our understanding of what drives human interest in biodiversity.
Two Types of Liquid Phase Separation lnduced by Soft Centrifugation in Aqueous Ethyl Acetate Using Ethanol as Cosolvent

Water/ethyl acetate/ethanol is widely used as a "green" extractant system. We show that 2 different types of phase separation can be induced upon centrifugation in this ternary system using ethanol as a cosolvent of water and ethyl acetate: centrifuge-induced criticality and centrifuge-induced emulsification. The expected composition profiles of samples after centrifugation can be represented by bent lines in a ternary phase diagram when gravitational energy is added to the free energy of mixing. The experimental equilibrium composition profiles behave qualitatively as expected and can be predicted using a phenomenological theory of mixing. The concentration gradients are small except near the critical point, as expected for small molecules. Nevertheless, they are usable when accompanied by temperature cycles. These findings open new possibilities of centrifugal separation, even if control is delicate during temperature cycles. These schemes are accessible
Hydrological model comparison and assessment: criteria from catchment scales and temporal resolution

ABSTRACT This study examines the performance of three hydrological models, namely the artificial neural network (ANN) model, the Hydrologiska Byråns Vattenbalansavdelning-D (HBV-D) model, and the Soil and Water Integrated Model (SWIM) over the upper reaches of the Huai River basin. The assessment is done by using databases of different temporal resolution and by further examining the applicability of SWIM for different catchment sizes. The results show that at monthly scale the performance of the ANN model is better than that of HBV-D and SWIM. The ANN model can be applied at any temporal scale as it establishes an artificial precipitation–runoff relationship for various time scales by only using monthly precipitation, temperature and runoff data. However, at daily scale the performance of both HBV-D and SWIM are similar or even better than the ANN model. In addition, the performance of SWIM at a small catchment size (less than 10 000 km2) is much better than at a larger catchment size. In view of climate change modelling, HBV-D and SWIM might be integrated in a dynamical atmosphere-water-cycle modelling rather than the ANN model due to their use of observed physical links instead of artificial relations within a black box. Editor D. Koutsoyiannis; Associate editor D. Hughes
Safe Talar Tunnel Placement During Reconstruction of the Deep Layer of the Deltoid Ligament: A Comparison of 4 Different Anatomic Landmarks on the Lateral Malleolus

Background: Deltoid ligament reconstruction of the ankle can be considered when the ruptured ligament is insufficient for direct repair. Purpose: To compare the safety of talar tunnels oriented toward 4 different anatomic landmarks on the lateral malleolus during reconstruction of the deep layer of the deltoid ligament (DDL). Study Design: Descriptive laboratory study. Methods: A total of 30 computed tomography scans of the ankle joint in healthy adults were collected to generate 3-dimensional models. Virtual talar tunnels with a diameter of 5 mm and with different lengths (20.0, 25.0, and 30.0 mm) were created from the talar insertion of the DDL and were oriented toward the talar neck as well as the most anterior, the most distal, and the most posterior points of the distal fibula. The minimal safe distance (MSD) of a drilling route was calculated for the tunnels, and the safe distance from the end of the tunnel to the bone surface was measured for each tunnel. The nonpaired Student t test was used to detect differences among the safe distances of the 4 different bone tunnels. Results: For the 20.0-mm tunnels, the safe distance of the tunnel oriented toward the talar neck (5.90 ± 1.16 mm) did not meet the MSD (6.0 mm). For the 25.0-mm tunnels, the safe distances of the tunnels oriented toward the talar neck (4.53 ± 1.13 mm) and the anterior point of the fibula (5.91 ± 1.52 mm) did not meet the MSD (6.9 mm). Conclusion: Tunnels that were 5 mm in diameter and 20.0 and 25.0 mm in length, oriented toward the most distal or most posterior point of the distal fibula, were safe for DDL reconstruction. Clinical Relevance: Knowledge of safe talar tunnel placement is important, especially to avoid bone surface penetration during DDL reconstruction.
Coupled Evaluation of Below- and Aboveground Energy and Water Cycle Variables from Reanalysis Products over Five Flux Tower Sites in the United States

AbstractReanalysis products are widely used to study the land–atmosphere exchanges of energy, water, and carbon fluxes and have been evaluated using in situ data above or below ground. Here, measurements for several years at five flux tower sites in the United States (with a total of 315 576 h of data) are used for the coupled evaluation of both below- and aboveground processes from three global reanalysis products and six global land data assimilation products. All products show systematic errors in precipitation, snow depth, and the timing of the melting and onset of snow. Despite the biases in soil moisture, all products show significant correlations with observed daily soil moisture for the periods with unfrozen soil. While errors in 2-m air temperature are highly correlated with errors in skin temperature for all sites, the correlations between skin and soil temperature errors are weaker, particularly over the sites with seasonal snow. While net short- and longwave radiation flux errors have opposite.