Miracle-dz/UniFAR-FTUs huggingface dataset:
ELECTRON–ION RECOMBINATION OF Fe x FORMING Fe ix AND OF Fe xi FORMING Fe x: LABORATORY MEASUREMENTS AND THEORETICAL CALCULATIONS

We have measured electron–ion recombination for Fe9+ forming Fe8+ and for Fe10+ forming Fe9+ using a merged beams arrangement at the TSR heavy-ion storage ring in Heidelberg, Germany. The measured merged beams recombination rate coefficients (MBRRC) for relative energies from 0 to 75 eV are presented, covering all dielectronic recombination (DR) resonances associated with 3s → 3p and 3p → 3d core transitions in the spectroscopic species Fe x and Fe xi, respectively. We compare our experimental results to state-of-the-art multiconfiguration Breit–Pauli (MCBP) calculations and find significant differences. Poor agreement between the measured and theoretical resonance structure is seen for collision energies below 48 eV for Fe x and below 35 eV for Fe xi. The integrated resonance strengths, though, are in reasonable agreement. At higher energies, good agreement is seen for the resonance structure but for the resonance strengths theory is significantly larger than experiment by a factor of ≈ 1.5 (2) for Fe x (Fe xi). From the measured MBRRC, we have extracted the DR contributions and transform them into plasma recombination rate coefficients (PRRCs) for astrophysical plasmas with temperatures in the range of 102–107 K. This range spans across the regimes where each ion forms in photoionized or in collisionally ionized plasmas. For both temperature regimes, the experimental uncertainties are 25% at a 90% confidence level. As expected based on predictions from active galactic nucleus observations as well as our previous laboratory and theoretical work on M-shell iron, the formerly recommended DR data severely underestimated the rate coefficient at temperatures relevant for photoionized gas. At these temperatures relevant for photoionized gas, we find agreement between our experimental results and MCBP theory. This is somewhat surprising given the poor agreement in MBRRC resonance structure. At the higher temperatures relevant for collisionally ionized gas, the MCBP calculations yield an Fe xi DR rate coefficient that is significantly larger than the experimentally derived one. We present parameterized fits to our experimentally derived DR PRRC for ease of inclusion into astrophysical modeling codes.
Using Metafeatures to Increase the Effectiveness of Latent Semantic Models in Web Search

In web search, latent semantic models have been proposed to bridge the lexical gap between queries and documents that is due to the fact that searchers and content creators often use different vocabularies and language styles to express the same concept. Modern search engines simply use the outputs of latent semantic models as features for a so-called global ranker. We argue that this is not optimal, because a single value output by a latent semantic model may be insufficient to describe all aspects of the model's prediction, and thus some information captured by the model is not used effectively by the search engine. To increase the effectiveness of latent semantic models in web search, we propose to create metafeatures-feature vectors that describe the structure of the model's prediction for a given query-document pair and pass them to the global ranker along with the models? scores. We provide simple guidelines to represent the latent semantic model's prediction with more than a single number, and illustrate these guidelines using several latent semantic models. We test the impact of the proposed metafeatures on a web document ranking task using four latent semantic models. Our experiments show that (1) through the use of metafeatures, the performance of each individual latent semantic model can be improved by 10.2% and 4.2% in NDCG scores at truncation levels 1 and 10; and (2) through the use of metafeatures, the performance of a combination of latent semantic models can be improved by 7.6% and 3.8% in NDCG scores at truncation levels 1 and 10, respectively.
Improved Release and Metabolism of Flavonoids by Steered Fermentation Processes: A Review

This paper provides an overview on steered fermentation processes to release phenolic compounds from plant-based matrices, as well as on their potential application to convert phenolic compounds into unique metabolites. The ability of fermentation to improve the yield and to change the profile of phenolic compounds is mainly due to the release of bound phenolic compounds, as a consequence of the degradation of the cell wall structure by microbial enzymes produced during fermentation. Moreover, the microbial metabolism of phenolic compounds results in a large array of new metabolites through different bioconversion pathways such as glycosylation, deglycosylation, ring cleavage, methylation, glucuronidation and sulfate conjugation, depending on the microbial strains and substrates used. A whole range of metabolites is produced, however metabolic pathways related to the formation and bioactivities, and often quantification of the metabolites are highly underinvestigated. This strategy could have potential to produce extracts with a high-added value from plant-based matrices.
A new perspective on the socialness in bug triaging: a case study of the eclipse platform project

This paper explores how social relationships among developers impact on the efficiency of bug fixes. From the case study of the Eclipse Platform project, we found that (1) past achievements of bug triaging by particular pairs of assignors and fixers do not necessarily impact on the time to fix bugs, (2) rather, the time required to fix a bug can depend on who assigns the bug fixing task to a fixer. These findings would imply that we need to not only consider "who should fix this bug? " but also take into account a fixer's perspective "who should assign this bug? " or "who should ask to whom? ", in order to better support the bug triaging process.
High preoperative CA 15-3 concentrations predict adverse outcome in node-negative and node-positive breast cancer: study of 600 patients with histologically confirmed breast cancer.

BACKGROUND CA 15-3 is the most widely used serum marker in breast cancer. Currently, its main uses are in the surveillance of patients with diagnosed disease and monitoring the treatment of patients with advanced disease. METHODS Preoperative CA 15-3 concentrations were measured prospectively in 600 patients with histologically confirmed breast cancer. Marker concentrations were related to patient outcome by both univariate and multivariate analysis. RESULTS After a median follow-up of 6.27 years, patients with high preoperative concentrations of CA 15-3 (>30 units/L) had a significantly shorter overall survival pattern than those with low concentrations. As a prognostic factor, CA 15-3 was independent of tumor size, axillary node status, and patient age. As well as being prognostic in the total population of patients, CA 15-3 also predicted outcome in different subgroups of patients, including those with both node-negative and node-positive disease, those who were both estrogen receptor (ER)-negative and ER-positive, and those younger and older that 50 years of age. CA 15-3 was also predictive of outcome irrespective of the type of adjuvant therapy administered, i.e., whether adjuvant hormone therapy, adjuvant chemotherapy, or radiotherapy was administered. CONCLUSION Assay of CA 15-3 is a relatively inexpensive, convenient, and noninvasive method for evaluating prognosis in newly diagnosed breast cancer patients.
An Empirical Investigation of the Effect of Advanced Web Technologies on Product Returns

Internet retailers have been making significant investments in advanced technologies, e.g., zoom, color swatch, and alternative photos, that are capable of providing detailed product-related information and, thereby mitigating the lack of “touch-and-feel,” which, in turn, is expected to lower product returns. However, a clear understanding of the impact of the use of these technologies on product returns is still lacking. This exploratory study attempts to fill this gap by using several econometric models to unravel the relationship between product-related technology usage and product returns. Our unique and rich dataset allows us to measure technology usage at the product level for each consumer. The results show that zoom usage has a negative and weakly significant coefficient, suggesting that a higher use of the zoom technology leads to fewer returns. Color swatch, on the other hand, does not seem to have any impact on product returns. Surprisingly, we find that the use of alternative photos increases the likelihood of returns. Thus, our findings show that different technologies have different effects on product returns. Interestingly, with a higher use of alternative photos, loyal consumers are more likely to return, whereas the effect on non-loyal consumers is insignificant. We provide plausible explanations for all these findings based on the extant literature on customer satisfaction. We also conduct a number of tests to ensure the robustness of the findings.
Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome, which makes them impractical in many real applications, especially when many state conditions and model couplings need to be studied. To overcome this problem, it is proposed to substitute RTMs through surrogate meta-models also named emulators. Emulators approximate the functioning of RTMs through statistical learning regression methods, and can open many new applications because of their computational efficiency and outstanding accuracy. Emulators allow fast global sensitivity analysis (GSA) studies on advanced, computationally expensive RTMs. As a proof-of-concept, three machine learning regression algorithms (MLRAs) were tested to function as emulators for the leaf RTM PROSPECT-4, the canopy RTM PROSAIL, and the computationally expensive atmospheric RTM MODTRAN5. Selected MLRAs were: kernel ridge regression (KRR), neural networks (NN) and Gaussian processes regression (GPR). For each RTM, 500 simulations were generated for training and validation. The majority of MLRAs were excellently validated to function as emulators with relative errors well below 0.2%. The emulators were then put into a GSA scheme and compared against GSA results as generated by original PROSPECT-4 and PROSAIL runs. NN and GPR emulators delivered identical GSA results, while processing speed compared to the original RTMs doubled for PROSPECT-4 and tripled for PROSAIL. Having the emulator-GSA concept successfully tested, for six MODTRAN5 atmospheric transfer functions (outputs), i.e., direct and diffuse at-surface solar irradiance ( E d i f , E d i r ), direct and diffuse upward transmittance ( T d i r , T d i f ), spherical albedo (S) and path radiance ( L 0 ), the most accurate MLRA’s were subsequently applied as emulator into the GSA scheme. The sensitivity analysis along the 400–2500 nm spectral range took no more than a few minutes on a contemporary computer—in comparison, the same analysis in the original MODTRAN5 would have taken over a month. Key atmospheric drivers were identified, which are on the one hand aerosol optical properties, i.e., aerosol optical thickness (AOT), Angstrom coefficient (AMS) and scattering asymmetry variable (G), mostly driving diffuse atmospheric components, E d i f and T d i f ; and those affected by atmospheric scattering, L 0 and S. On the other hand, as expected, AOT, AMS and columnar water vapor (CWV) in the absorption regions mostly drive E d i r and T d i r atmospheric functions. The presented emulation schemes showed very promising results in replacing costly RTMs, and we think they can contribute to the adoption of machine learning techniques in remote sensing and environmental applications.
Weight Rotation Technique for PAPR Reduction in OFDM

In this paper we propose Weight Rotation Technique for peak to- average power ratio (PAPR) reduction in OFDM systems. It is based on selected mapping (SLM) algorithm. The main drawback of the conventional SLM technique is its high signal processing complexity due to the use of multiple inverse fast Fourier transform (IFFT) operations per OFDM block. In the proposed PAPR reduction is based on a preset threshold value and the phase sequence is modified accordingly. Simulation results show that this technique gives a performance close to SLM technique with considerable reduction in complexity.
Non-invasive assessment of myocardial ischaemia by using low amplitude oscillations of the conventional ECG signals (ECG dispersion mapping) during percutaneous coronary intervention

Objective — The HeartVueTM 6S System is a recently developed novel technology that may provide non-invasive assessment of myocardial ischaemia by analysing low amplitude oscillations of the conventional ECG signals (ECG dispersion mapping). The available data to validate this new technology is limited.Therefore we performed a prospective study to assess the HeartVueTM 6S System for the detection of myocardial ischaemia during coronary occlusion in patients undergoing percutaneous coronary intervention (PCI). Methods — A total of 101 patients undergoing cardiac catheterization were prospectively enrolled. HeartVueTM 6S System ECG dispersion mapping was obtained at baseline, and during the first balloon inflation and at the end of the procedure if PCI was performed. Parameters provided by the HeartVueTM 6S System were analysed. Results — Fifty patients who underwent PCI comprised the final study population.The mean age was 63.7 ± 10 years and 58% were men. In 58% of cases the indication was acute coronary syndrome. In 98% of patients, PCI was successful. There were significant differences in the G7+G9 values between the first inflation and the end of the procedure, which reflect changes in ventricular depolarization (P= 0.02 by Wilcoxon signed rank test). Conclusions — The HeartVueTM 6S System may have potential for a non-invasive assessment of ischaemia in patients with suspected coronary artery disease. Larger studies are warranted to confirm these preliminary findings.
Towards a Self-Adaptive Super-node P2P Overlay Based on Information Exchange

P2P topology design is a hot topic because it is very important for solving the problems such as deficiency in scalability and effectivity of unstructured P2P overlays. A good topology can greatly improve the performance of search algorithm. The paper proposes a self-adaptive Super-node Overlay Based on Information Exchange called SOBIE. The super-node selection in the SOBIE is different from the general super-node selections which only consider physical capabilities such as bandwidth, CPU processing ability, storage space, and etc. The SOBIE selects the super-nodes by considering the aggregation of the delay, distance, especially the information exchange frequency, exchange time and query similarity. The SOBIE also detects the free-riders and forces them to quit the system. Through experimental simulations, we prove that the SOBIE has better performance than random or standard super-node P2P topologies in terms of file query success rate, the average query hops, and the total number of query messages.
Relevance Propagation Model for Large Hypertext Documents Collections

Web search engines have become indispensable in our daily life to help us finding the information we need. Several search tools, for instance Google, use links to select the matching documents against a query. In this paper, we propose a new ranking function that combines content and link rank based on propagation of scores over links. This function propagates scores from source pages to destination pages in relation with query terms. We assessed our ranking function with experiments over two test collections WT10g and GOV. We conclude that propagating link scores according to query terms provides significant improvement for information retrieval.
A Tale of Two Macroeconomic Issues: Public Spending and Households’ Preferences

This paper tries to explain how political/bureaucratic corruption in India affects households’ preferences of consumption-leisure, consumption-saving and consumption-demand of real balances decisions in a typical economy, dominated by the informal sector, and modeled in an open-economy New Keynesian Dynamic Stochastic General Equilibrium (NK DSGE) style with micro-foundations. The study incorporates the enormously important informal sector, as the lion’s share of Indian workforce is employed in this sector. It also does not keep the degree of political/bureaucratic corruption out, as thriving corruption has engulfed the entire nation. A theoretical model based on a representative household’s utility function comprising consumption, public consumption, real balances and labor supply (production) subject to its budget constraint is developed and solved. The paper shows, theoretically, that public spending on consumption, government transfer, political/bureaucratic corruption/embezzlement in public spending on consumption and political/bureaucratic corruption/embezzlement in government transfer do not affect households’ preferences of optimal consumption-saving decision (optimal intertemporal consumption decision), optimal consumption-leisure decision (optimal consumption-labor supply decision) and optimal consumption-demand of real balances decision.
Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain.
Using Cyclic Scheduling to Generate Believable Behavior in Games

Video game virtual characters should interact with the player, each other, and the environment. However, the cost of scripting complex behaviors becomes a bottleneck in content creation. Our goal is to help game designers to more easily populate their open world with background characters that exhibit more believable behaviors. We use a cyclic scheduling model that generates dynamic schedules for the daily lives of virtual characters. The scheduler employs a tiered behavior architecture where behavior components are modular and reusable. This research validates the designer usability of an implementation of this model. We present the results of a user study that evaluates the scheduling system versus manual scripting based on three metrics of behavior creation: behavior completeness, behavior correctness and behavior implementation time. The results indicate that the behavior architecture produces more reliable behaviors and improves designer efficiency which will reduce the cost of generating more believable character behaviors.
Pain assessment in children undergoing venipuncture: the Wong–Baker faces scale versus skin conductance fluctuations

The aim of this study was to evaluate the efficacy of the subjective Wong–Baker faces pain rating scale (WBFS) and of the objective skin conductance fluctuation (SCF) test in assessing pain in children undergoing venipuncture. One-hundred and fifty children (aged 5–16 years) entered the study. All underwent venipuncture at the antecubital fossa to collect blood specimens for routine testing in the same environmental conditions. After venipuncture, the children indicated their pain intensity using the WBFS, whereas the number of SCFs was recorded before, during and after venipuncture. So, pain level was measured in each child with WBFS and SCF. We found that the level of WBFS-assessed pain was lower in all children, particularly those above 8 years of age, than SCF-assessed pain (p < 0.0001). Moreover, the number of SCFs was significantly higher during venipuncture than before or after venipuncture (p < 0.0001). At multivariate regression analysis, age and previous experience of venipuncture influenced the WBFS (β = −1.81, p < 0.001, and β = −0.86, p < 0.001, respectively) but not SCFs. In conclusion, although both procedures can be useful for research and clinical practice, our findings show that WBFS was affected by age and previous venipuncture, whereas SCF produced uniform data. If verified in other studies, our results should be taken into account when using these tools to evaluate pain in children.