Miracle-dz/UniFAR-FTUs huggingface dataset:
A multiple case study on the impact of pair programming on product quality

Pair programming is a programming technique in which two programmers use one computer to work together on the same task. There is an ongoing debate over the value of pair programming in software development. The current body of knowledge in this area is scattered and unorganized. Review shows that most of the results have been obtained from experimental studies in university settings. Few, if any, empirical studies exist, where pair programming has been systematically under scrutiny in real software development projects. Thus, its proposed benefits remain currently without solid empirical evidence. This paper reports results from four software development projects where the impact of pair programming on software product quality was studied. Our empirical findings appear to offer contrasting results regarding some of the claimed benefits of pair programming. They indicate that pair programming may not necessarily provide as extensive quality benefits as suggested in literature, and on the other hand, does not result in consistently superior productivity when compared to solo programming.
Understanding COBOL systems using inferred types

In a typical COBOL program, the data division consists of 50% of the lines of code. Automatic type inference can help to understand the large collections of variable declarations contained therein, showing how variables are related based on their actual usage. The most problematic aspect of type inference is pollution, the phenomenon that types become too large, and contain variables that intuitively should not belong to the same type. The aim of the paper is to provide empirical evidence for the hypothesis that the use of subtyping is an effective way for dealing with pollution. The main results include a tool set to carry out type inference experiments, a suite of metrics characterizing type inference outcomes, and the conclusion that only one instance of pollution was found in the case study conducted.
L1-Graph Based Neighborhood Preserving Embedding with an Application to Face Recognition

Neighborhood Preserving Embedding (NPE) is a famous graph-oriented dimension deduction algorithm, which has got lots of successful applications in computer vision field. Just as all the graph-oriented algorithms, the effectiveness of the NPE greatly relies on whether a suitable graph can be constructed. While the traditional graph construction method has some intrinsic weaknesses, especially when the face appearance exist large changes resulting from illumination, expression and pose. L1-graph method is a parameter-free unsupervised graph construction method and is more robust to noise and outliers than the traditional graph construction method. Combining the merits of L1-graph and NPE, this paper proposes a L1-graph based Neighborhood Preserving Embedding (L1GNPE) method which can promote the robustness and discriminative ability of NPE. Extensive experiments conducted on several popular face databases show that the L1GNPE method outperforms the traditional NPE method under unsupervised conditions.
INTEGRAL observations of the blazar Mrk 421 in outburst Results of a multi-wavelength campaign

Context. If one wants to understand the physics of blazars, better simultaneous observations are important at all wavelengths, so it was fortunate that a ToO observation of the TeV-emitting blazar Mrk 421 with INTEGRAL could be triggered in June 2006 by an increase in the RXTE count rate to more than 30 mCrab. The source was then observed with all INTEGRAL instruments, with the exception of the spectrometer SPI, for a total exposure of 829 ks. During this time several outbursts were observed by IBIS and JEM- X. Multiwavelength observations were immediately triggered, and the source was observed at radio, optical, and X-ray wavelengths up to TeV energies. Aims. The data obtained during these observations were analysed with respect to time variability, time lags, correlated vari ability, and spectral evolution and then compiled in aFspectrum. Methods. The observations of the different instruments/telescopes were analysed with the usual correlation and time-analysis methods. The spectral analysis of the X-ray data was performed with XSPEC. Results. Four strong flares at X-rays were observed that were not seen a t other wavelengths (partially because of missing data). From the fastest rise in the X-rays, an upper limit could be derived to the extension of the emission region. A time lag between high-energy and low-energy X-rays was observed, which allowed an estimation of the magnetic-field strength. The spectr al analysis of the X-rays revealed a slight spectral hardening of the low-energy (3-∼43 keV) spectral index. The hardness-ratio analysis of the Swift-XRT (0.2 - 10 keV) data indicated a small correlation with the intensity; i. e. , a hard-to-soft evolution was obser ved. At the energies of IBIS/ISGRI (20 - 150 keV), such correlations are less obvious. A multiwavelength spectrum was composed and the X-ray and bolometric luminosities calculated. Conclusions. The observed flaring activity of Mrk 421 is mainly visible at X -rays. It is found that the spectral change with intensity is small. But at least one flare showed a completely di fferent spectral behaviour than the other flares, so one can con clude that each blob of relativistic-moving electrons has its own individu al physical environment that leads to different emission characteristics. From a fit of a leptonic emission model to the data, one finds that the observed variability may be due to a varying effi ciency of particle acceleration.
Change Blindness in the Absence of a Visual Disruption

Findings from studies of visual memory and change detection have revealed a surprising inability to detect large changes to scenes from one view to the next (‘change blindness’). When some form of disruption is introduced between an original and modified display, observers often fail to notice the change. This disruption can take many forms (eg an eye movement, a flashed blank screen, a blink, a cut in a motion picture, etc) with similar results. In all cases, the changes are sufficiently large that, were they to occur instantaneously, they would consistently be detected. Prior research on change blindness was predicated on the assumption that, in the absence of a visual disruption, the signal caused by the change would draw attention, leading to detection. In two experiments, we demonstrate that change blindness can occur even in the absence of a visual disruption. In one experiment, subjects actually detected more changes with a disruption than without one. When changes are sufficiently gradual, the visible change signal does not seem to draw attention, and large changes can go undetected. The findings are discussed in the context of metacognitive beliefs about change detection and the strategic decisions those beliefs entail.
A Stochastic Model for Context-Aware Anomaly Detection in Indoor Location Traces

Rapid growth in the development of real-time location system solutions has led to an increased interest in indoor location-aware services, such as hospital asset management. Although there are extensive studies in the literature on the analysis of outdoor location traces, the studies of indoor location traces are less touched and fragmented. To that end, in this paper, we provide a focused study of indoor location traces collected by the sensors attached to medical devices in a hospital environment. Along this line, we first introduce some unique properties of these indoor location traces. We show that they can capture the movement patterns of the medical devices, which are tightly coupled with the work flow in the controlled hospital environment. Based on this observation, we propose a stochastic model for context-aware anomaly detection in indoor location traces, which exploits the hospital work flow and models the movements of medical devices as transitions in finite state machines. In detail, we first develop a density-based method to identify the hotspots filled with high-level abnormal activities in the indoor environment. The discovered hotspots serve as the context for nearby trajectories. Then, we introduce an N-gram based method for measuring the degree of anomaly based on the detected hotspots, which is able to predict the missing events possibly due to the devices being stolen. Besides, to address the noisy nature of the indoor sensor networks, we also propose an iterative algorithm to estimate the transition probabilities. This algorithm allows to effectively recover the missing location records which are critical for the abnormality estimation. Finally, the experimental results on the real-world date sets validate the effectiveness of the proposed context-aware anomaly detection method for identifying abnormal events.
Disturbed acid-base transport: an emerging cause of hypertension

Genome-wide association studies and physiological investigations have linked alterations in acid-base transporters to hypertension. Accordingly, Na+-coupled HCO−3-transporters, Na+/H+-exchangers, and anion-exchangers have emerged as putative mechanistic components in blood pressure disturbances. Even though hypertension has been studied extensively over the last several decades, the cause of the high blood pressure has in most cases not been identified. Renal, cardiovascular, and neuronal dysfunctions all seem to play a role in hypertension development but their relative importance and mutual interdependency are still being debated. Multiple functional and structural alterations have been described in patients and animals with hypertension but it is typically unclear whether they are causes or consequences of hypertension or represent mechanistically unrelated associations. Perturbed blood pressure regulation has been demonstrated in several animal models with disrupted expression of acid-base transporters; and reciprocally, disturbed acid-base transport function has been described in hypertensive individuals. In addition to regulating intracellular and extracellular pH, Na+-coupled HCO−3-transport, Na+/H+-exchange, and anion-exchange also contribute to water and electrolyte balance in cells and systemically. Since acid-base transporters are widely expressed, alterations in transport activities likely affect multiple cell and organ functions, and it is a significant challenge to determine the mechanisms linking perturbed acid-base transport function to hypertension. It is the purpose of this review to evaluate the current evidence for involvement of acid-base transporters in hypertension development and discuss the cellular and integrative mechanisms, which may link changes in acid-base transport to blood pressure disturbances.
Optimal Dynamic Promotion and the Knapsack Problem for Perishable Items (Extended Abstract)

Senior managers in retail industry make important decisions upon assortment planning, product pricing, and product promotion. While product assortment is a strategic decision taken over a long-term planning period (Kok et al., 2006), the latter two are both strategic and tactical: they can be used in dayto-day marketing decisions to dynamically adjust to demand variations. Within the food retail industry, the necessity, frequency, and complexity of pricing and promotion decisions are further magnified by perishability of food products. There is a strong need by retail managers for a “soft”marketing tool, whichwould dynamically allow them to improve sales and revenues, yet not altering product prices. For, dynamic pricing models may prescribe to change prices too often or in an “unsystematic” fashion, which contradicts discrete-time decision making, implementation costs, and retail brand image strategy. In addition, the price reduction must usually be done over all units of the product, thus losing possible profit from customers willing to pay the original, higher price. Furthermore, dynamic pricing results in a trade-off between markdowns and stockouts, since markdowns may damage producers, while stockouts may damage retailers. We design a revenue management model, in which demand is stimulated by moving a number of product units to a promotion space, rather than by price changes. Thus, we address the problem of filling a promotion location with limited space to maximize the expected revenue, which we have termed the Knapsack Problem for Perishable Items (KPPI). Examples of the promotion space include shelves close to the cash register, promotion kiosks, or a depot used for selling via the Internet. We solve the KPPI using a problem decomposition into single product unit subproblems. A natural mathematical setting for the KPPI subproblems is the restless bandit model (cf. Whittle, 1988; NinoMora, 2002), a fundamental stochastic model for resolving a trade-off between exploration and exploitation in an optimal fashion. In our model the bandits (perishable items) are restless, because they can get sold regardless of being in the knapsack or not, the time horizon is finite, and we are to select more than one item for the knapsack, which is allowed to be filled partially, due to the heterogeneity of the items. Each product unit is assigned a promotion priority index, which captures the opportunity cost of promotion, as a function of its price, lifetime, expected demand, and expected promotion power. These indices are then used for each item as objective-function value coefficients in a (classic) knapsack problem, whose solution yields a well-performing heuristic for the KPPI. We thus mix up two models: the restless bandit problem and the knapsack problem.
Music Making as a Tool for Promoting Brain Plasticity across the Life Span

Playing a musical instrument is an intense, multisensory, and motor experience that usually commences at an early age and requires the acquisition and maintenance of a range of skills over the course of a musician’s lifetime. Thus, musicians offer an excellent human model for studying the brain effects of acquiring specialized sensorimotor skills. For example, musicians learn and repeatedly practice the association of motor actions with specific sound and visual patterns (musical notation) while receiving continuous multisensory feedback. This association learning can strengthen connections between auditory and motor regions (e.g., arcuate fasciculus) while activating multimodal integration regions (e.g., around the intraparietal sulcus). We argue that training of this neural network may produce cross-modal effects on other behavioral or cognitive operations that draw on this network. Plasticity in this network may explain some of the sensorimotor and cognitive enhancements that have been associated with music training. These enhancements suggest the potential for music making as an interactive treatment or intervention for neurological and developmental disorders, as well as those associated with normal aging.
Country Risk Assessment; A Behavioural Perspective

Over the last 40 years the concept of judgment and decision making received increasing attention from both scholars and the professional field. It started in the beginning of the ‘70’s of the previous century when Kahneman and Tversky published a number of papers (Tversky and Kahneman, 1971, Kahneman and Tversky, 1972, Kahneman and Tversky, 1973) where they presented their heuristics and biases approach to judgment and decision making under uncertainty. Ever since Kahneman and Tversky published their results in the beginning of the 1970’s “the heuristics and biases program […] spread beyond academic psychology, affecting theory and research across a range of disciplines including economics, law, medicine, and political science” (Gilovich & Griffin, 2002). Although the applicability of the heuristics and biases approach is tested in a number of fields (for instance medicine and law) there are still a lot of disciplines that need to be studied. This book presents the process of judgment and decision making within one specific discipline: country risk assessment when executed by decision makers in small and medium sized enterprises when assessing international business opportunities.
Additional file 12

Pletcher et al. (2002) PMID: 12007414 1,312 genes with age-related changes in expression. We received information on the probe sets that showed age-related changes in gene expression from the corresponding author of this paper. The results were from an updated analysis, and a slightly larger set of significant genes were identified than was reported in the original paper. Using the annotation file provided to accompany the expression array used in the study we converted probe sets to FlyBase gene IDs ("FBgn"), ignoring any probe sets lacking FBgn. FBgn were then updated to current FBgn using FlyBase (http://flybase.org/static_pages/downloads/IDConv.html, accessed 30 December 2015). Subsequently, we retained only those unique genes with a one-to-one relationship between current and former FBgn (differences among annotation releases cause a small minority of putative open reading frames to be merged or split as annotations improve).
Cyclooxygenase‐2 and 5‐lipoxygenase converging functions on cell proliferation and tumor angiogenesis: implications for cancer therapy

Cyclooxygenase (COX) and lipoxygenase (LO) metabolic pathways are emerging as key regulators of cell proliferation and neo‐angiogenesis. COX and LO inhibitors are being investigated as potential anticancer drugs and results from clinical trials seem to be encouraging. In this article we will review evidence of COX‐2 and 5‐LO involvement in cancer pathobiology, propose a model of integrated control of cell proliferation by these enzymes, and discuss the pharmacologic implications of this model. —Romano, M. , Clària, J. Cyclooxygenase‐2 and 5‐lipoxygenase converging functions on cell proliferation and tumor angiogenesis: implications for cancer therapy. FASEB J. 17, 1986–1995 (2003)
Psychiatric Consultation Record Retrieval Using Scenario-Based Representation and Multilevel Mixture Model

Psychiatric consultation record retrieval attempts to help people to efficiently and effectively locate the consultation records relevant to their depressive problems. Consultation records can also make people aware that they are not alone, because many individuals have suffered from the same or similar problems. Additionally, people can understand how to alleviate their depressive symptoms according to recommendations from health professionals. To achieve this goal, this paper proposes the use of a scenario-based representation, i.e., a symptom-based structural representation, to capture the depressive symptoms and their semantic relations, such as cause-effect and temporal relations, for understanding users' queries clearly. The symptoms and relations are identified from semantic mining and analysis of consultation records. The multilevel mixture model is adopted to estimate the relevance of queries and consultation records based on the structural information. Experimental results show that the proposed approach achieves higher precision than does a term-based flat representation. An experiment is also conducted to examine the effect of error propagation resulting from incorrect identification of symptoms and relations. Experimental results demonstrate that combining different approaches can improve the retrieval robustness.
The effects of tactile feedback and movement alteration on interaction and awareness with digital embodiments

Collaborative tabletop systems can employ direct touch, where people's real arms and hands manipulate objects, or indirect input, where people are represented on the table with digital embodiments. The input type and the resulting embodiment dramatically influence tabletop interaction: in particular, the touch avoidance that naturally governs people's touching and crossing behavior with physical arms is lost with digital embodiments. One result of this loss is that people are less aware of each others' arms, and less able to coordinate actions and protect personal territories. To determine whether there are strategies that can influence group interaction on shared digital tabletops, we studied augmented digital arm embodiments that provide tactile feedback or movement alterations when people touched or crossed arms. The study showed that both augmentation types changed people's behavior (people crossed less than half as often) and also changed their perception (people felt more aware of the other person's arm, and felt more awkward when touching). This work shows how groupware designers can influence people's interaction, awareness, and coordination abilities when physical constraints are absent.
The Influence of α-Lipoic Acid and Garlic Administration on Biomarkers of Oxidative Stress and Inflammation in Rabbits Exposed to Oxidized Nutrition Oils

We hypothesized that addition of substances with antioxidant activity could decrease the concentrations of biomarkers of oxidative stress and inflammatory process, thus inhibiting nonalcoholic steatohepatitis development. We investigated the influence of α-lipoic acid (ALA) and garlic administration on the development of adverse changes in rabbit liver and serum under oxidative stress conditions induced with HFD from oxidized oils. We determined 8-hydroxy-2′-deoxyguanosine (8OHdG) and malondialdehyde (MDA) in liver homogenates, total oxidant status (TOS), lipid peroxides (LOO) and tumor necrosis factor alpha (TNFα) in blood serum, and TNFα and IL-1α genes expression in liver. The results indicate that the intake of dietary ALA and garlic was significantly associated with decreases of 8OHdG and MDA levels in rabbits' liver tissue as well as TOS and LOO levels in rabbits' serum. Similarly, TNFα and IL-1α gene expressions were suppressed due to ALA and garlic supplementation. The histopathological analysis confirmed that HFD results in liver disorder leading to steatosis. This adverse effect of HFD was ameliorated by the supplementation of ALA and garlic. The obtained results indicate a beneficial effect of ALA and garlic administration by reducing the oxidative stress intensity and the levels of some proinflammatory cytokines in rabbits fed HFD.
Towards a more effective method for analyzing mobile eye-tracking data: integrating gaze data with object recognition algorithms

In this paper we present the outlines of a new project that aims at developing and implementing effective new methods for analyzing gaze data collected with mobile eye-tracking devices. More specifically, we argue for the integration of object recognition algorithms from vision engineering, such as invariant region matching techniques, in gaze analysis software. We present a series of arguments why an object-based approach may provide a significant surplus, in terms of analytical precision, flexibility, additional application areas and cost efficiency, to the existing systems that use predefined areas of analysis. In order to test the actual analytical power of object recognition algorithms for the analysis of gaze data recorded in the wild, we develop a series of test cases in different real world situations, including shopping behavior, navigation, handling and usability of mobile systems. By setting up these case studies in close collaboration with key players in the relevant fields (retailers, signage consultants, market and user-experience research, and developers of eye-tracking hard- and software), we will be able to sketch an accurate picture of the pros and cons of the proposed method in comparison to current analytical practice.
A Type System for Unstructured Locking that Guarantees Deadlock Freedom without Imposing a Lock Ordering

Deadlocks occur in concurrent programs as a consequence of cyclic resource acquisition between threads. In this paper we present a novel type system that guarantees deadlock freedom for a language with references, unstructured locking primitives, and locks which are implicitly associated with references. The proposed type system does not impose a strict lock acquisition order and thus increases programming language expressiveness.