Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing Test-Defect Coverage Information to Support Analytical Reasoning and Testing

Software testing is an essential activity in all software projects. The key issue in testing is determining the sufficiency of tests and, traditionally this has been done by using the Software Reliability Growth Models (SRGMs). However, SRGMs are not applicable when there are no stabilization phases as required by most software reliability models. Test-Defect Coverage Analytics Model (TDCAM) has been proposed to address this problem. This paper proposes the application of visual analytic techniques as an approach for supporting informed decision making in deciding the sufficiency of tests. Visual analytics research considers interactive visualization as the common platform for combining various computational data analysis techniques to support the analytical reasoning process. We presented four visual representations of TDCAM to demonstrate how analytical models have been applied to indicate the adequacy of tests in relation to sufficient and efficient test coverage. The techniques provide an effective and generally applicable test estimation on the basis of a general trend that higher test coverage correlates with higher probability of detecting more defects.
Data Skew Profiling using HPCC Systems

Over the last few decades, there has been a tremendous increase in the volume of data available for analysis in various domains. Although processing power has scaled up as well, it is well known that the rate of increase of data far supersedes the higher processing capabilities of modern processors. The natural consequence to the advent of big data was distribution of data across multiple nodes to facilitate not only storage but also parallel processing. The advent of the age of large volumes of data came to be known as the era of big data. The distribution of data among various machines posed a fundamental problem in big data as well as distributed computing: The impact of data skew. We worked on a project to profile data skew on a multi-computing cluster. This paper summarizes our efforts and findings. We use HPCC Systems, a modern big data management and analysis tool. In this project, we analyze the impact of differently skewed data distributions on the most common database operations, namely, NORMALIZE, DENORMALIZE, JOIN, SORT, TABLE, and PROJECT using a set of queries, and analyzing their runtimes.
Robust Detection of Cyberbullying in Social Media

The potentially detrimental effects of cyberbullying have led to the development of numerous automated, data–driven approaches, with an emphasis on classification accuracy. Cyberbullying, as a form of abusive online behavior, although not well–defined, is a repetitive process, i.e., a sequence of aggressive messages sent from a bully to a victim over a period of time with the intent to harm the victim. Existing work has focused on aggression (i.e., using profanity to classify toxic comments independently) as an indicator of cyberbullying, disregarding the repetitive nature of this harassing process. However, raising a cyberbullying alert immediately after an aggressive comment is detected can lead to a high number of false positives. At the same time, three key practical challenges remain unaddressed: (i) detection timeliness, which is necessary to support victims as early as possible, (ii) scalability to the staggering rates at which content is generated in online social networks, (iii) reliance on high quality annotations from human experts for training of highly accurate supervised classifiers. To overcome the challenges associated with cyberbullying detection in online social networks, my PhD thesis focuses on a novel formulation of the online classification problem as sequential hypothesis testing that seeks to drastically reduce the number of features used while maintaining high classification accuracy. To reduce the dependency on labeled datasets, I seek to develop efficient semisupervised methods that extrapolate from a small seed set of expert annotations. Preliminary results are very encouraging, showing significant improvements over the state–of–the–art.
Association of Household Income With Life Expectancy and Cause-Specific Mortality in Norway, 2005-2015.

Importance Examining causes of death and making comparisons across countries may increase understanding of the income-related differences in life expectancy. Objectives To describe income-related differences in life expectancy and causes of death in Norway and to compare those differences with US estimates. Design and Setting A registry-based study including all Norwegian residents aged at least 40 years from 2005 to 2015. Exposures Household income adjusted for household size. Main Outcomes and Measures Life expectancy at 40 years of age and cause-specific mortality. Results In total, 3 041 828 persons contributed 25 805 277 person-years and 441 768 deaths during the study period (mean [SD] age, 59.3 years [13.6]; mean [SD] number of household members per person, 2.5 [1.3]). Life expectancy was highest for women with income in the top 1% (86.4 years [95% CI, 85.7-87.1]) which was 8.4 years (95% CI, 7.2-9.6) longer than women with income in the lowest 1%. Men with the lowest 1% income had the lowest life expectancy (70.6 years [95% CI, 69.6-71.6]), which was 13.8 years (95% CI, 12.3-15.2) less than men with the top 1% income. From 2005 to 2015, the differences in life expectancy by income increased, largely attributable to deaths from cardiovascular disease, cancers, chronic obstructive pulmonary disease, and dementia in older age groups and substance use deaths and suicides in younger age groups. Over the same period, life expectancy for women in the highest income quartile increased 3.2 years (95% CI, 2.7-3.7), while life expectancy for women in the lowest income quartile decreased 0.4 years (95% CI, -1.0 to 0.2). For men, life expectancy increased 3.1 years (95% CI, 2.5-3.7) in the highest income quartile and 0.9 years (95% CI, 0.2-1.6) in the lowest income quartile. Differences in life expectancy by income levels in Norway were similar to differences observed in the United States, except that life expectancy was higher in Norway in the lower to middle part of the income distribution in both men and women. Conclusions and Relevance In Norway, there were substantial and increasing gaps in life expectancy by income level from 2005 to 2015. The largest differences in life expectancy between Norway and United States were for individuals in the lower to middle part of the income distribution.
Price Elasticity of Bushmeat Demand in the Greater Serengeti Ecosystem: Insights for Managing the Bushmeat Trade

Rural households across the tropics rely on bushmeat hunting to fulfil their subsistence and cash income needs. As human populations grow, and urban market demand drives commercial trade, hunting is often unsustainable, compromising community long-term food security and wildlife conservation objectives. Scarce information about the effectiveness of different intervention options hampers design of informed management strategies to reduce bushmeat hunting while simultaneously safeguarding community’s food security. Here we examine the potential of interventions aimed at reducing bushmeat demand by evaluating the own- and cross-price elasticities, i.e. how consumers respond to changes in the price of bushmeat and the price of five substitutes – beef, chicken, lamb, goatmeat and fish. We conducted stated preference surveys, complemented by a socio-economic survey using the Poverty Environment Network protocol in 452 households in 21 villages in the Greater Serengeti Ecosystem in Tanzania. Using random intercept Poisson regression models, we find significant and elastic negative own-price elasticities of bushmeat demand and significant positive cross-price elasticities except for goat and fish. The significant (all at the 0.01 level) own-price elasticities ranges from -1.099 when bushmeat is paired with beef to -0.718 when bushmeat is paired with fish while the significant cross-price elasticities ranges from 0.128 when bushmeat is paired with beef to 0.590 when bushmeat is paired with lamb suggesting that most cross-price relations were highly inelastic. Variation between districts was considerable and depended on substitutes included in the model. Estimated elasticities were modified by socio-economic covariates including ethnicity, household size, household income, household Tropical Livestock Units ownership, household land ownership and distance to nearest protected area boundary, Lake Victoria and nearest road. Overall, we find mixed support for the hypothesis that interventions the price of bushmeat and decreasing that of its substitutes will reduce bushmeat demand. The effectiveness of demand reducing interventions should increase if complemented by other policy interventions, e.g., interventions that increase the opportunity cost of hunting, by providing alternative income generation opportunities for hunters.
IRF1 Maintains Optimal Constitutive Expression of Antiviral Genes and Regulates the Early Antiviral Response

Viral defense at mucosal sites depends on interferons (IFN) and IFN stimulated genes (ISGs), either of which may be constitutively expressed to maintain an “antiviral state” (AVS). However, the mechanisms that govern the AVS are poorly defined. Using a BEAS-2B respiratory epithelial cell line deficient in IRF1, we demonstrate higher susceptibility to infection with vesicular stomatitis virus (VSV) and influenza virus. IRF1-mediated restriction of VSV is IFN-independent, as blockade of types I and III IFNs and JAK-STAT signaling before infection did not affect VSV infection of either parent or IRF1 KO cells. Transcriptome analysis revealed that IRF1 regulates constitutive expression of ~300 genes, including antiviral ISGs: OAS2, BST2, and RNASEL and knockdown of any of these IRF1-dependent genes increased VSV infection. Additionally, IRF1 enhances rapid expression of IFNβ and IFNλ after stimulation with poly I:C and also regulates ISG expression. Mechanistically, IRF1 enhances recruitment of BRD4 to promotor-enhancer regions of ISGs for rapid expression and maintains levels of histone H3K4me1 for optimal constitutive expression. Finally, IRF1 also regulates constitutive expression of TLR2 and TLR3 and promotes signaling through these pattern recognition receptors (PRR). These data reveal multiple roles for IRF1 toward effective anti-viral responses by maintaining IFN-independent constitutive expression of anti-viral ISGs and supporting early IFN-dependent responses to PRR stimulation.
Raspberry as a Source for the Development of Drosophila suzukii Attractants: Laboratory and Commercial Polytunnel Trials

Several commercial products and home-made attractants have been developed for monitoring and mass-trapping of the spotted wing drosophila, Drosophila suzukii. Growers in Mexico have adopted an attractant based on a fermenting mixture of raspberry pulp and sucrose, with anecdotally promising results. We compared the capture rates of traps baited with raspberry pulp + sucrose with captures from a range of alternative attractants. Raspberry pulp alone or with sucrose was more attractive than apple cider vinegar (ACV) or SuzukiiTrap and similar to baker’s yeast + sucrose in laboratory cage studies. Synthetic raspberry aroma (0.1–10% concentration), in water or mixed with ACV, did not improve capture rates in the laboratory. Traps baited with raspberry + sucrose or ACV had similar captures of D. suzukii in raspberry or blackberry polytunnels in Michoacán, Mexico. Raspberry + sucrose baited traps captured significantly higher numbers of other drosophilid species, leading to higher total numbers of captured flies (all species), which may explain why Mexican growers favor the raspberry-based attractant. The commercial products SuzukiiTrap and Z-Kinol had lower captures than ACV in polytunnels, although SuzukiiTrap had the highest selectivity in captures of D. suzukii (81% of flies captured). A two-component trap (2C trap) baited with ACV + ethanol as the drowning solution and raspberry pulp + sucrose or baker’s yeast + sucrose in a ventilated tube device was markedly more effective than the trap currently used by growers. We conclude that raspberry pulp + sucrose is as effective for the attraction of D. suzukii as ACV under commercial polytunnel conditions. The 2C trap performed better than the transparent cup trap currently used by berry producers in Mexico.
New measurement of the relativistic Doppler shift in neon.

The Doppler free two photon transition from the metastable 1S{sub 5} to 4S{sub 1}{prime}{double_prime} in neon was measured for both a fast beam ({approx}120 keV) and a slow thermal beam. The transition frequencies for each beam were measured independently relative to a hyperfine component of a nearby I{sub 2} reference line. The absolute frequency shift between the two beams was obtained. This measurement of the relativistic Doppler shift verifies the time dilation effect to an accuracy of 2.3 ppm which represents a more than 10 fold improvement over previous measurements.
Assessing the Influence of Water Constituents on the Radiative Heating of Laptev Sea Shelf Waters

The presence of optically active water constituents is known to attenuate the light penetration in the ocean and impact the ocean heat content. Here, we investigate the influence of coloured dissolved organic matter (CDOM) and total suspended matter (TSM) on the radiative heating of the Laptev Sea shelf waters. The Laptev Sea region is heavily influenced by the Lena River, one of the largest river systems in the Arctic region. We simulate the radiative heating by using a coupled atmosphere-ocean radiative transfer model (RTM) and \textit{in situ} measurements from the TRANSDRIFT XVII expedition carried out in September 2010. The results indicate that CDOM and TSM have significant influence on the energy budget of the Laptev Sea shelf waters, absorbing most of the solar energy in the first \replaced{two meters}{2 m} of the water column. In the station with the highest CDOM absorption (a\textsubscript{CDOM}(443) = 1.77 m\textsuperscript{-1}) \replaced{$\sim$43}{42.6}\% more energy is absorbed in the surface layer compared to the station with the lowest a\textsubscript{CDOM}(443) ($\sim$0.2 m\textsuperscript{-1}), which translates to an increased \replaced{radiative}{radiant} heating rate of \replaced{$\sim$0.6}{0.57}\textdegree{}C\deleted[remark=]{/day}. The increased absorbed energy by the water constituents also implies in increased sea ice melt rate and changes in the surface heat fluxes to the atmosphere. By \replaced{using}{combining} satellite remote sensing and RTM we \replaced{quantify}{present} the spatial distribution of the radiative heating in the Laptev Sea for a typical summer day. The tools developed here \added[remark=]{(the combined use of satellite remote sensing, RT modeling and \textit{in situ} observations)} and tested in our case study can be used to improve the parameterizations of coupled atmosphere-ocean models to assess the \replaced{role}{feedback} of the ocean \added[remark=]{in the effect of} Arctic \replaced{a}{A}mplification.
Effect of AuPd Bimetal Sensitization on Gas Sensing Performance of Nanocrystalline SnO2 Obtained by Single Step Flame Spray Pyrolysis

Improvement of sensitivity, lower detection limits, stability and reproducibility of semiconductor metal oxide gas sensor characteristics are required for their application in the fields of ecological monitoring, industrial safety, public security, express medical diagnostics, etc. Facile and scalable single step flame spray pyrolysis (FSP) synthesis of bimetal AuPd sensitized nanocrystalline SnO2 is reported. The materials chemical composition, structure and morphology has been studied by XRD, XPS, HAADFSTEM, BET, ICP-MS techniques. Thermo-programmed reduction with hydrogen (TPR-H2) has been used for materials chemical reactivity characterization. Superior gas sensor response of bimetallic modified SnO2 towards wide concentration range of reducing (CO, CH4, C3H8, H2S, NH3) and oxidizing (NO2) gases compared to pure and monometallic modified SnO2 is reported for dry and humid gas detection conditions. The combination of facilitated oxygen molecule spillover on gold particles and electronic effect of Fermi level control by reoxidizing Pd-PdO clusters on SnO2 surface is proposed to give rise to the observed enhanced gas sensor performance.
Anomaly Event Detection for Sensor Networks on Apriori Algorithms and Subjective Logic

Aiming at the challenges that anomaly events are difficult to be characterized and heterogeneous nodes can not cooperate directly in sensor network, a novel anomaly detection method for sensor networks is proposed in this paper. We use Apriori algorithm to mine the sample data and find the mapping from the events to sensing data, which provides the rule for the detection. In the detection, the node first find the suspicious event, and the relevant nodes cooperate to validate it. To fuse the detection result of heterogeneous nodes, we first map the results to subjective logic opinions, and generate reasonable and comprehensive conclusions with its fusion rules. Our analysis shows that our solution is able to refine the range of node detection events, improve detection efficiency and generate detection results reasonably.
Tau Inclusions in Alzheimer's, Chronic Traumatic Encephalopathy and Pick's Disease. A Speculation on How Differences in Backbone Polarization Underlie Divergent Pathways of Tau Aggregation

Tau-related dementias appear to involve specific to each disease aggregation pathways and morphologies of filamentous tau assemblies. To understand etiology of these differences, here we elucidate molecular mechanism of formation of tau PHFs based on the PMO theory of misfolding and aggregation of pleiomorphic proteins associated with neurodegenerative diseases. In this model, fibrillization of tau is initiated by the coupled binding and folding of the MTB domains that yields antiparallel homodimers, in analogy to folding of split inteins. The free energy of binding is minimized when the antiparallel alignment brings about backbone-backbone H-bonding between the MTBD segments of similar “strand” propensities. To assess these propensities, a function of the NMR shielding tensors of the Cα atoms is introduced as the folding potential function FPi; the Cα tensors are obtained by the quantum mechanical modeling of protein secondary structure (GIAO//B3LYP/D95**). The calculated FPi plots show that the “strand” propensities of the MBTD segments, and hence the homodimer's register, can be affected by the relatively small changes in the environment's pH, as a result of protonation of MBTD's conserved histidines. The assembly of the antiparallel tau dimers into granular aggregates and their subsequent conversion into the parallel cross-β structure of paired helical filaments is expected to follow the same path as the previously described fibrillization of Aβ. Consequently, the core structure of the nascent tau fibril is determined by the register of the tau homodimer. This model accounts for the reported differences in (i) fibril-core structure of in vivo and in vitro filaments, (ii) cross-seeding of isoforms, (iii) effects of reducing/non-reducing conditions, (iv) effects of PHF6 mutations, and (v) homologs' aggregation properties. The proposed model also suggests that in contrast to Alzheimer's and chronic traumatic encephalopathy disease, the assembly of tau prions in Pick's disease would be facilitated by a moderate drop in pH that accompanies e.g., transit in the endosomal system, inflammation response or an ischemic injury.
WCET Analysis meets Virtual Prototyping: Improving Source-Level Timing Annotations

In this paper we discuss the problem of relating machine instructions to source level constructs, and how it has been addressed in the domains of Virtual Prototyping (VP) and Worst-Case Execution Time (WCET) analysis. It has been handled in different ways, although the goals and requirements between both domains are not far from another. This paper shows that there exists a mutual benefit in exchanging solutions between the two research domains, by demonstrating the applicability and utility of VP methods for WCET analysis, and highlighting their shortcomings. After an evaluation of existing methods, we carefully rework and combine them to a sound and generic mapping algorithm for source-level WCET analysis. As a result, we obtain WCET estimates that outperform classic binary analyzers especially under moderate compiler optimization. Our approach is based on hierarchical flow matching, control-dependency- and dominator-homomorphic maps, and dominator lumping to soundly fill the gaps in the mapping. WCET estimation is performed using Model Checking, which maximally exploits the information available in the source, and highlights remaining weaknesses in the mapping methods. Last but not least, we discuss further chances of synergy between both research communities which could enable support for more complex microarchitectures with caches, pipelines and speculative execution in both source-level WCET analysis and VP.
Joint attention and object learning in 5-and 7-month-old infants

We examined the effects of joint attention for object learning in 5- and 7-month-old infants. Infants interacted with an adult social partner who taught them about a novel toy in two conditions. In the Joint Attention condition, the adult spoke about the toy while alternating gaze between the infant and the toy, while in the Object Only condition, the adult looked to the toy and to a spot on the ceiling, but never at the infant. In the test trials following each social interaction, we presented infants with the ‘familiarization’ toy and a novel toy, and monitored looking times to each object. We found that 7-month-olds looked significantly longer to the novel toy following the Joint Attention relative to the Object Only condition, while 5-month-old infants did not show a significant difference across conditions. We interpret these results to suggest that joint attention facilitated 7-month-old infants’ encoding of information about the familiarization object. Implications for the ontogeny of infant learning in joint attention contexts are discussed. Copyright # 2007 John Wiley & Sons, Ltd.
An in-vivo study on placental transfer of naproxen in early human pregnancy.

BACKGROUND Naproxen is one of the most common non-steroidal anti-inflammatory drugs used by women of reproductive age. Naproxen is known to be teratogenic in animals. The aim of this study was to investigate the placental transfer of naproxen in the first trimester of human pregnancy, and to determine the amount of the drug in different embryonic compartments. METHODS Twenty-eight patients who requested surgical termination of pregnancy in the first trimester were given two oral 500 mg doses of naproxen before the surgical procedure. Four biological samples, maternal venous blood, coelomic fluid, amniotic fluid and fetal tissue, were collected from each patient for drug analyses by high performance liquid chromatography. RESULTS Naproxen was detected in all samples. The mean (+/- SD) concentrations were 69.5 +/- 12.2 microg/ml, 6.4 +/- 2.4 microg/g, 1.85 +/- 1.03 microg/ml and 0.14 +/- 0.11 microg/ml in maternal serum, fetal tissue, coelomic fluid and amniotic fluid respectively. The mean amniotic fluid/maternal drug ratio and fetal/maternal drug ratio were 0.002 (range 0.0005-0.0064) and 0.092 (range 0.022-0.155) respectively. There was a positive correlation between the fetal drug concentration (r = 0.59, P = 0.001), amniotic fluid drug concentration (r = 0.47, P = 0.013), amniotic fluid/maternal ratio (r = 0.536, P = 0.003) and fetal/maternal ratio (r = 0.72, P < 0.001) with advancing gestational age. CONCLUSIONS Although naproxen can cross the placenta readily in the first trimester of human pregnancy, only a small amount was present in fetal tissues. Since there is no information on whether this small amount of naproxen would be teratogenic or not, women of reproductive age who are taking naproxen regularly should be warned of the possible fetal side-effects.