Miracle-dz/UniFAR-FTUs huggingface dataset:
How does firms' perceived competition affect technological innovation in Luxembourg?

This paper revisits the competition-innovation relationship using an unbalanced panel of enterprise data stemming from four waves of the Luxembourgish innovation survey for the period 2002-2010. We estimate by full-information maximum likelihood a nonlinear dynamic simultaneous-equations model with pseudo-fixed effects using four measures of perceived competition and three indicators of innovation and find that firms whose main market is characterised by rapid obsolescence of products are more likely to spend on innovation and to introduce product or process innovations. We also find that these firms also often consider their main market to be characterised by rapidly-changing technologies where higher competition also implies higher innovation.
X-Ray Emission from the Double Pulsar System J0737–3039

We report on a 10 ks observation of the double pulsar system J0737-3039 obtained with the Chandra X-Ray Observatory's Advanced CCD Imaging Spectrometer. We detect the system as a point source with coordinates (J2000.0) R.A. = 07h37m51. ˢ23, decl. = -30°39'40. ″9, making this the first double neutron star system to be detected at X-ray energies. Only 77 source counts are detected. The data are represented satisfactorily by a power-law spectrum with photon index Γ = 2.9 ± 0.4. The inferred 0.2-10 keV luminosity is ≈2 × 1030 ergs s-1 for a distance of 0.5 kpc. We do not detect any significant variability with orbital phase in these data, which span one full orbit. These results are consistent with the X-ray emission originating solely from the magnetosphere of the energetic A pulsar, with an efficiency for conversion of rotational energy to X-rays in this band of ~0.04%, although we cannot exclude other possibilities.
Filter Design and Performance Evaluation for Fingerprint Image Segmentation

Fingerprint recognition plays an important role in many commercial applications and is used by millions of people every day, e.g. for unlocking mobile phones. Fingerprint image segmentation is typically the first processing step of most fingerprint algorithms and it divides an image into foreground, the region of interest, and background. Two types of error can occur during this step which both have a negative impact on the recognition performance: ‘true’ foreground can be labeled as background and features like minutiae can be lost, or conversely ‘true’ background can be misclassified as foreground and spurious features can be introduced. The contribution of this paper is threefold: firstly, we propose a novel factorized directional bandpass (FDB) segmentation method for texture extraction based on the directional Hilbert transform of a Butterworth bandpass (DHBB) filter interwoven with soft-thresholding. Secondly, we provide a manually marked ground truth segmentation for 10560 images as an evaluation benchmark. Thirdly, we conduct a systematic performance comparison between the FDB method and four of the most often cited fingerprint segmentation algorithms showing that the FDB segmentation method clearly outperforms these four widely used methods. The benchmark and the implementation of the FDB method are made publicly available.
Non-Parametric Determination of Real-Time Lag Structure between Two Time Series: The 'Optimal Thermal Causal Path' Method

We introduce a novel non-parametric methodology to test for the dynamical time evolution of the lag-lead structure between two arbitrary time series. The method consists of constructing a distance matrix based on the matching of all sample data pairs between the two time series. Then, the lag-lead structure is searched for as the optimal path in the distance matrix landscape that minimizes the total mismatch between the two time series, and that obeys a one-to-one causal matching condition. To make the solution robust to the presence of a large amount of noise that may lead to spurious structures in the distance matrix landscape, we generalize this optimal search by introducing a fuzzy search by sampling over all possible paths, each path being weighted according to a multinomial logit or equivalently Boltzmann factor proportional to the exponential of the global mismatch of this path. We present the efficient transfer matrix method that solves the problem and test it on simple synthetic examples to demonstrate its properties and usefulness compared with the standard running-time cross-correlation method. We then apply our 'optimal thermal causal path' method to the question of the lag-dependence between the US stock market and the treasury bond yields and confirm our earlier results on an arrow of the stock markets preceding the Federal Reserve Funds' adjustments, as well as the yield rates at short maturities in the period 2000-2003. Our application of this technique to inflation, inflation change, GDP growth rate and unemployment rate unearths non-trivial lag relationships: the GDP changes lead inflation especially since the 1980s, inflation changes leads GDP only in the 1980 decade, and inflation leads unemployment rates since the 1970s. In addition, our approach seems to detect multiple competing lag structures in which one can have inflation leading GDP with a certain lag time and GDP feeding back/leading inflation with another lag time.
An Approach to Find Maximal Disjoint Paths with Reliability and Delay Constraints

Recently, multipaths solutions have been proposed to improve the quality-of-service (QoS) in communication networks (CN). Peng and Shen algorithm (PSA) was proposed to generate lamdaDP/DC – the maximum edge-disjoint-path-set with minimal cost subject to a delay constraint, for lamda≤2. This paper introduces a different and equally important problem, lamdaDP/DR, to obtain the maximal edge-disjoint-path-set with maximum reliability subject to a given delay constraint, for lambda≤1. lamdaDP/DR is applicable to time critical applications that require non-compromised time delay while demanding maximum system reliability. In this paper we show how lamdaDP/DR is different from lamdaDP/DC, and propose an approximate algorithm similar to the Lagrange-relaxation based PSA to solve the problem. Our simulations on three randomly generated CNs show that our polynomial time algorithm produced lamdaDP/DR with comparable optimality to that obtained using the NP-hard brute-force approach.
ACUTE EFFECT ON POWER OUTPUT OF ALTERNATING AN AGONIST AND ANTAGONIST MUSCLE EXERCISE DURING COMPLEX TRAINING

The efficient coordination of agonist and antagonist muscles is one of the important early adaptations in resistance training responsible for large increases in strength. Weak antagonist muscles may limit speed of movement; consequently, strengthening them leads to an increase in agonist muscle movement speed. However, the effect of combining agonist and antagonist muscle exercises into a power training session has been largely unexplored. The purpose of this study was to determine if a training complex consisting of contrasting agonist and antagonist muscle exercises would result in an acute increase in power output in the agonist power exercise. Twenty-four college-aged rugby league players who were experienced in combined strength and power training served as subjects for this study. They were equally assigned to an experimental (Antag) or control (Con) group and were no different in age, height, body mass, strength, or maximal power. Power output was assessed during bench press throws with a 40-kg resistance (BT P40) with the Plyometric Power System training device. After warming up, the Con group performed the BT P40 tests 3 minutes apart to determine if any acute augmentation to power output could occur without intervention. The Antag group also performed the BT P40 tests; however, an intervention strategy of a set of bench pulls, which is an antagonistic action to the bench throw, was performed between tests to determine if this would acutely affect power output during the second BT P40 test. Although the power output for the Con group remained unaltered between test occasions, the significant 4.7% increase for the Antag group indicates that a strategy of alternating agonist and antagonist muscle exercises may acutely increase power output during complex power training. This result may affect power training and specific warm-up strategies used in ballistic sports activities, with increased emphasis placed upon the antagonist muscle groups.
THE UPPER ATMOSPHERE OF HD17156b

HD17156b is a newly found transiting extrasolar giant planet that orbits its G-type host star in a highly eccentric orbit (e ∼ 0.67) with an orbital semimajor axis of 0.16 AU. Its period, 21.2 Earth days, is the longest among the known transiting planets. The atmosphere of the planet undergoes a 27-fold variation in stellar irradiation during each orbit, making it an interesting subject for atmospheric modeling. We have used a three-dimensional model of the upper atmosphere and ionosphere for extrasolar gas giants in order to simulate the progress of HD17156b along its eccentric orbit. Here we present the results of these simulations and discuss the stability, circulation, and composition of its upper atmosphere. Contrary to the well-known transiting planet HD209458b, we find that the atmosphere of HD17156b is unlikely to undergo fast hydrodynamic escape at any point along the orbit, even if the upper atmosphere is almost entirely composed of atomic hydrogen and H+, and infrared cooling by H+3 ions is negligible. The nature of the upper atmosphere is sensitive to the composition of the thermosphere, and in particular to the mixing ratio of H2, as the availability of H2 regulates radiative cooling. In light of different simulations we make specific predictions about the thermosphere–ionosphere system of HD17156b that can potentially be verified by observations.
Spinal Plasticity and Behavior: BDNF-Induced Neuromodulation in Uninjured and Injured Spinal Cord

Brain-derived neurotrophic factor (BDNF) is a member of the neurotrophic factor family of signaling molecules. Since its discovery over three decades ago, BDNF has been identified as an important regulator of neuronal development, synaptic transmission, and cellular and synaptic plasticity and has been shown to function in the formation and maintenance of certain forms of memory. Neural plasticity that underlies learning and memory in the hippocampus shares distinct characteristics with spinal cord nociceptive plasticity. Research examining the role BDNF plays in spinal nociception and pain overwhelmingly suggests that BDNF promotes pronociceptive effects. BDNF induces synaptic facilitation and engages central sensitization-like mechanisms. Also, peripheral injury-induced neuropathic pain is often accompanied with increased spinal expression of BDNF. Research has extended to examine how spinal cord injury (SCI) influences BDNF plasticity and the effects BDNF has on sensory and motor functions after SCI. Functional recovery and adaptive plasticity after SCI are typically associated with upregulation of BDNF. Although neuropathic pain is a common consequence of SCI, the relation between BDNF and pain after SCI remains elusive. This article reviews recent literature and discusses the diverse actions of BDNF. We also highlight similarities and differences in BDNF-induced nociceptive plasticity in naïve and SCI conditions.
Effects of Yoga on Psychological Health, Quality of Life, and Physical Health of Patients with Cancer: A Meta-Analysis

Yoga is one of the most widely used complementary and alternative medicine therapies to manage illness. This meta-analysis aimed to determine the effects of yoga on psychological health, quality of life, and physical health of patients with cancer. Studies were identified through a systematic search of seven electronic databases and were selected if they used a randomized controlled trial design to examine the effects of yoga in patients with cancer. The quality of each article was rated by two of the authors using the PEDro Scale. Ten articles were selected; their PEDro scores ranged from 4 to 7. The yoga groups compared to waitlist control groups or supportive therapy groups showed significantly greater improvements in psychological health: anxiety (P = .009), depression (P = .002), distress (P = .003), and stress (P = .006). However, due to the mixed and low to fair quality and small number of studies conducted, the findings are preliminary and limited and should be confirmed through higher-quality, randomized controlled trials.
The Changing Portrayal of Adolescents in the Media Since 1950

INTRODUCTION: MASS MEDIA AND THE SOCIALIZATION OF ADOLESCENTS SINCE WORLD WAR II PART 1 THE EMERGENCE AND EVOLUTION OF A YOUTH CULTURE IN THE MEDIA 1. Understanding the "Jackpot Market": Media, Marketing and the Rise of the American Teenager 2. "Still Talking about my Generation! ": The Representation of Youth in Popular Music 3. Music Videos: Media of the Youth, by the Youth, for the Youth PART 2. PORTRAYAL OF ADOLESCENTS AND INFLUENTIAL BEHAVIORS 4. It Matters What Young People Watch: Health Risk Behaviors Portrayed in Top-Grossing Movies Since 1950 5. Adolescent Gender Role Portrayals in the Media: 1950 to the Present 6. Adolescent Body Image and Eating in the Media: Trends and Implications for Adolescent Health 7. African Americans, Latinos, Asians, and Native Americans in the Media: Implications for Adolescents 8. Adolescents and Television Violence 9. Tobacco Portrayals in US Advertising and Entertainment Media 10. The Changing Portrayal of Alcohol Use in Television Advertising 11. From Twin Beds to Sex at Your Fingertips: Teen Sexuality in Movies, Music, Television, and the Internet, 1950 to 2005 PART 3. EVOLVING FORMS OF MEDIA INFLUENCE 12. The Games, They are a-Changin': Technological Advancements in Video Games and Implications for Effects on Youth 13. Adolescents and the Internet PART 4. POLICY IMPLICATIONS FOR HEALTHY ADOLESCENT DEVELOPMENT 14. Policy Interventions 15. Conclusions
Measurement of Stock Market Volatility through ARCH and GARCH Models: A Case Study of Karachi Stock Exchange

3Abstarct: This paper examines the presence of volatility at the Karachi Stock Exchange (KSE) through the use of Autoregressive Conditional Heteroskedacity (ARCH) and Generalized Autoregressive Conditional Heteroskedacity (GARCH) models introduced by Engle (1982), Bollerslev (1986) and Nelson (1991). The data has been acquired from the website of KSE and State Bank of Pakistan and analysis is with the use of Minitab, Excel and other computer packages. In this paper, a long-time series data analysis of two Indexes namely;‘KSE-100 Index’ and ‘All shares index’ has been used first time in this emerging stock exchange. The empirical result confirms the presence of high volatility at Karachi Stock Exchange through- out the study period.
The luminosity dependence of clustering and higher order correlations in the PSCz survey

We investigate the spatial clustering of galaxies in the PSCz galaxy redshift survey, as revealed by the two-point correlation function, the luminosity mark correlations and the moments of counts-in-cells. We construct volume-limited subsamples at different depths and search for a luminosity dependence of the clustering pattern. We find no statistically significant effect in either the two-point correlation function or the mark correlations and so we take each subsample (of different characteristic luminosity) as representing the same statistical process. We then carry out a counts-in-cells analysis of the volume-limited subsamples, including a rigorous error calculation based on the recent theory of Szapudi, Colombi & Bernardeau. In this way, we derive the best estimates to date of the skewness and kurtosis of IRAS galaxies in redshift space. Our results agree well with previous measurements in both the parent angular catalogue and the derived redshift surveys. This is in contrast with smaller, optically selected surveys, where there is a discrepancy between the redshift space and projected measurements. Predictions from cold dark matter theory, obtained using the recent semi-analytical model of galaxy formation of Benson et al., provide an excellent description of our clustering data.
On the Role of Uncertainty in the Risk-Incentives Tradeoff

We use a simple agency model to clarify and characterize the various avenues through which changes in the level of uncertainty impact the optimal strength of linear incentives. Instead of attempting to characterize different "types" of uncertainty, which has been the approach in the literature so far, we base our characterization on the link between uncertainty and the agent's action choice. We then use this characterization to provide conditions under which the relationship between uncertainty and incentives can be positive and relate it back to the existing models in the literature.
When Elephants Fly: Differential Sensitivity of Right and Left Inferior Frontal Gyri to Discourse and World Knowledge

Both local discourse and world knowledge are known to influence sentence processing. We investigated how these two sources of information conspire in language comprehension. Two types of critical sentences, correct and world knowledge anomalies, were preceded by either a neutral or a local context. The latter made the world knowledge anomalies more acceptable or plausible. We predicted that the effect of world knowledge anomalies would be weaker for the local context. World knowledge effects have previously been observed in the left inferior frontal region (Brodmann's area 45/47). In the current study, an effect of world knowledge was present in this region in the neutral context. We also observed an effect in the right inferior frontal gyrus, which was more sensitive to the discourse manipulation than the left inferior frontal gyrus. In addition, the left angular gyrus reacted strongly to the degree of discourse coherence between the context and critical sentence. Overall, both world knowledge and the discourse context affect the process of meaning unification, but do so by recruiting partly different sets of brain areas.
Double Whammy – How ICT Projects are Fooled by Randomness and Screwed by Political Intent

The cost-benefit analysis formulates the holy trinity of objectives of project management - cost, schedule, and benefits. As our previous research has shown, ICT projects deviate from their initial cost estimate by more than 10% in 8 out of 10 cases. Academic research has argued that Optimism Bias and Black Swan Blindness cause forecasts to fall short of actual costs. Firstly, optimism bias has been linked to effects of deception and delusion, which is caused by taking the inside-view and ignoring distributional information when making decisions. Secondly, we argued before that Black Swan Blindness makes decision-makers ignore outlying events even if decisions and judgements are based on the outside view. Using a sample of 1,471 ICT projects with a total value of USD 241 billion - we answer the question: Can we show the different effects of Normal Performance, Delusion, and Deception? We calculated the cumulative distribution function (CDF) of (actual-forecast)/forecast. Our results show that the CDF changes at two tipping points - the first one transforms an exponential function into a Gaussian bell curve. The second tipping point transforms the bell curve into a power law distribution with the power of 2. We argue that these results show that project performance up to the first tipping point is politically motivated and project performance above the second tipping point indicates that project managers and decision-makers are fooled by random outliers, because they are blind to thick tails. We then show that Black Swan ICT projects are a significant source of uncertainty to an organisation and that management needs to be aware of.
Path-consistent safety in mixed human-robot collaborative manufacturing environments

In order to improve production flexibility, it is widely agreed that future working environments will be populated by both humans and robot manipulators, sharing the same workspace. This scenario introduces a series of safety issues which are uncommon in industrial settings where physical separation of robot areas is typically enforced. While several approaches for safe human-robot interaction exist, none of them can be easily integrated with production constraints. This paper discusses the composition of safety constraints with production ones. An algorithm is derived in order to maximize productivity, while guaranteeing a safe separation distance of the robot from the human. Experimental results showing the effectiveness of the approach in a typical industrial setting are also discussed.
pH sensitive CdS–iron oxide fluorescent–magnetic nanocomposites

There has been great interest in the use of nanoparticles for imaging, particularly in multimodal applications (e.g., combination of MRI and fluorescence). Yet creating particles with multiple functionalities has been challenging. Here, we report the synthesis of pH sensitive, fluorescent–magnetic, nanocomposites created through a simple aqueous procedure. Separately synthesized superparamagnetic iron oxide nanoparticles and mercaptopropionic acid (MPA)-coated CdS quantum dots were crosslinked using 3-mercaptopropyl trimethoxysilane (MPS) as a bifunctional linker to yield CdS–iron oxide conjugates. Conjugates formed clusters of 0.1–1.0 µm diameter, with the smallest observed particle diameter ∼50 nm. Particle solubility and photoluminescent (PL) intensity were sensitive to solution pH, with the highest PL intensity and stability obtained at pH values <3.0 and MPS:Cd:Fe ratios of 1:10:1. pH sensitivity is believed to result from changes in nanoparticle solubility within the silica-based matrix. Given these unique properties, this material might find application in separation, pH sensitive detection (e.g., endosomal tracking) and biosensing.
Quantitative Magnetization Transfer Imaging of Human Cervical Spinal Cord at 3 T

Introduction: The goal of this study was to determine the feasibility of performing quantitative magnetization transfer (qMT) at high resolution in the spinal cord on clinical 3T systems. While magnetization transfer (MT) imaging has been used to assess brain tissue microstructure, similar studies in the human spinal cord have been limited. This can largely be attributed to the difficulties associated with imaging the spinal cord, which include: i) high resolution demands (cord diameter ≈ 1.5 cm), ii) motion (CSF pulsation and respiration), and iii) susceptibility gradients (bone/tissue interfaces). Despite these difficulties, MT has been characterized in the spinal cord via the magnetization transfer ratio normalized to the CSF (MTCSF), a measure that has been shown to be sensitive to myelination changes in patients with adrenomyeloneuropathy (AMN) [1,2]. Unfortunately, MTCSF is also sensitive to changes in tissue relaxation times and flow effects in CSF, making it difficult to discriminate between myelin and inflammation effects. To alleviate this sensitivity, quantitative MT (qMT) approaches have been proposed. Previous work at 1.5T [3] has indicated that the ratio of the macromolecular to free water pool sizes, or pool size ratio (PSR), may be sensitive to myelination changes in the spinal cord. Given the resolution demands of imaging the spinal cord, qMT studies of the spinal cord would presumably benefit from the increased SNR at 3T; however, such studies are hampered by the fact that SAR scales according the field strength squared. To address these issues, we have developed a protocol for high resolution qMT imaging of the cervical spinal cord at 3T and here we report data acquired in healthy subjects.