Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaboration and informal hierarchy in innovation teams: Product introductions in entrepreneurial ventures

Funding information Texas A&M University; University of Washington Abstract Research Summary: Although stars may be particularly innovative, building teams to collaborate with them can be difficult. Coordinating efforts between stars and non-stars may be especially complex in new venture, which rely on informal hierarchy to manage organizational tasks. We investigate how a venture's success at introducing new products may be influenced by the extent to which company founders and star performers are involved in co-developing new technologies. By analyzing innovation teams within a sector of the medical device industry from 1986 to 2007, we find that combining both star inventors and founder-inventors on a venture's innovation team may limit product introductions. Our results highlight the importance of organizational design in managing coordination and resource allocation in a venture setting and suggest important boundary conditions when stars may impede, rather than benefit, innovation. Managerial Summary: Designing an innovation team can be challenging for new ventures. While the presence of a technologically proficient founder or highly accomplished inventor can significantly bolster a new venture's innovation Received: 30 June 2017 Revised: 14 June 2019 Accepted: 18 June 2019
Disposal of waste materials at the bottom of pit lakes

Mine pits have been used as sites for disposal of wastes from mining, ore milling and refinery, oil sand processing, by-products of acid mine drainage (AMD) neutralisation, ashes of coal combustion in power plants or even industrial wastes. In several cases, pit lakes formed after disposal of the waste materials. In other cases, the disposal went on after formation of a pit lake or was even conducted in order to neutralise the pit lake. However, the deposition of waste in surface water is not allowed in many countries. The purpose of the paper is to contribute to the discussion how to handle such existing waste deposits. In order to reach that goal, the paper gives a brief overview over processes relevant for the transport of substances from the waste into the main water body of pit lakes. Examples and experiences from Germany and from international literature are presented. The presented examples and the literature show that there are advantages and disadvantages accompanying subaqueous disposal of waste. In general, the stability of the conditions inside the deposited waste and at its interface with its aqueous environment is a main prerequisite for successful long term storage of waste below a water cover. In this respect, meromixis is usually helpful. Risks such as long term change of conditions inside and around the waste deposits and the pit lakes, as groundwater contamination or as toxication of aquatic life have to be evaluated carefully and site specifically. However, there are no scientifically reasonable arguments for a general preclusion of the subaqueous disposal of waste in pit lakes.
Dependency modeling for information fusion with applications in visual recognition

While many pattern recognition algorithms have been developed in the last forty years, classifying images/videos in practical applications still faces the challenges of self/mutual occlusions, clustered backgrounds, illumination variations, etc. In order to improve the recognition performance, many systems are designed by fusing multiple complementary features for various classification tasks. This thesis addresses the independent assumption issue in the fusion process and proposes two novel frameworks for dependency modeling. Under some mild assumptions, the first approach uses a linear combination of posterior probabilities to model the feature dependency. Based on the linear combination property, this thesis proposes a Linear Classifier Dependency Modeling (LCDM) method for classifier level fusion. Under the linear dependency modeling framework, this thesis shows that more information about the class label is available in feature level, so LCDM is generalized to feature level and the Linear Feature Dependency Model (LFDM) is proposed. Since it is almost impossible to verify whether the assumptions in existing methods are valid in practice applications, fusion method with less demanding assumption should give better performance. In the second approach, this thesis develops an Analytic Dependency Model (ADM) for score level fusion without the assumptions in existing fusion algorithms. With the proposed ADM, this thesis gives an equivalent condition to the independent assumption from probabilistic properties of marginal distributions. Since the ADM may contain infinite number of undeter-
Senior academics as key negotiators in the implementation of impact policies in the social sciences and humanities

Dieser Artikel basiert auf der Arbeit von COST Action 15137, dem Europaischen Netzwerk fur Forschungsevaluierung in der SSH (ENRESSH) und wird von COST (Europaische Zusammenarbeit in Wissenschaft und Technologie) unterstutzt. In diesem Papier verfolgen wir zwei Hauptziele. Zunachst uberprufen wir die relevante Literatur und prasentieren sie anhand eines theoretischen Rahmens, der strukturelle Perspektiven und die Berucksichtigung individueller Handlungsspielraume miteinander verbindet, um ein besseres Verstandnis fur die Rolle von Hochschullehrern in den Sozial- und Geisteswissenschaften (SSH) bei der Umsetzung der verschiedenen Politiken, die die Produktion, die Verbreitung und die Evaluierung von Forschung betreffen, einschlieslich der wirkungsbezogenen Politiken zu erhalten. Tatsachlich kann die Verhandlungsmacht der Wissenschaftler in Bezug auf die Wirkungsagenda - wie sie derzeit von europaischen politischen Entscheidungstragern gefordert wird (siehe z. B. Europaische Kommission 2018) und die Auswirkungen auf Politik, Wirtschaft sowie Umwelt und Gesellschaft - nicht isoliert betrachtet werden und wie ihre Wahrnehmung und Haltung gegenuber den allgemeinen politischen Veranderungen, die sich auf die Praxis der akademischen Forschung auswirken, sind. Zweitens diskutieren wir einige vorlaufige Ergebnisse der Interviews, die wir im Rahmen der COST ENRESSH-Aktion mit 16 in acht europaischen Landern tatigen hochrangigen Soziologen durchgefuhrt haben, wobei wir uns auf deren Wahrnehmung und Einstellung zur Wirkungsagenda konzentrieren.
Mapping severe fire potential across the contiguous United States

The Fire Severity Mapping System (FIRESEV) project is an effort to provide critical information and tools to fire managers that enhance their ability to assess potential ecological effects of wildland fire. A major component of FIRESEV is the development of a Severe Fire Potential Map (SFPM), a geographic dataset covering the contiguous United States (CONUS) that quantifies the potential for wildland fires to burn with higher severity should they occur (Dillon et al 2011a). We developed this map using empirical observations and statistical models to relate biophysical conditions at the time and location of a fire to the resulting severity. For our purposes, burn severity refers to the degree to which aboveground biomass has been altered as expressed in the change between preand post-fire satellite imagery (Lentile et al 2006). Our aim in creating the SFPM is to explore the relationships between site characteristics and burn severity (Dillon et al 2011b) and to provide land managers with a tool that can forecast the potential severity of future fires.
Principal Component Analysis of Blast Furnace Drainage Patterns

Monitoring and control of the blast furnace hearth is critical to achieve the required production levels and adequate process operation, as well as to extend the campaign length. Because of the complexity of the draining, the outflows of iron and slag may progress in different ways during tapping in large blast furnaces. To categorize the hearth draining behavior, principal component analysis (PCA) was applied to two extensive sets of process data from an operating blast furnace with three tapholes in order to develop an interpretation of the outflow patterns. Representing the complex outflow patterns in low dimensions made it possible to study and illustrate the time evolution of the drainage, as well as to detect similarities and differences in the performance of the tapholes. The model was used to explain the observations of other variables and factors that are known to be affected by, or affect, the state of the hearth, such as stoppages, liquid levels, and tap duration.
Quantifying Structural Transformations from Redox Reactions in TiO2

TiO2 anatase nanoparticles have shown interesting properties as ultraviolet (UV) light photocatalysts for water and air remediation as well as for solar water splitting. Understanding the structural changes that take place during photocatalysis is critical to developing structure-reactivity relations for these applications. Oxygen vacancies are believed to play an important role in surface reactivity. The structure of TiO2 nanoparticles has been investigated with in situ atomic resolution transmission electron microscopy (TEM) [1,2]. In these experiments, a low electron flux was used to prevent structural damage, however, this results in a poor signal-to-noise ratio. Differentiating intensity fluctuations due to shot noise from fluctuations associated with defect-induced structural changes is crucial and challenging, and the interpretation of the point defect structure can only be accomplished through a detailed comparison with theory. Here, computational methods based on molecular dynamics (MD) and density functional theory (DFT) are employed to construct defect models of TiO2, which are employed in image simulations to interpret experimental observations.
Automatic Tag Recommendation for Web 2.0 Blogosphere by Extracting Keywords from Similar Blogs

This paper proposes a novel approach to automatic tag recommendation for weblogs/blogs. It makes use of collective intelligence extracted from Web 2.0 collaborative tagging as well as word semantics to learn how to predict the best set of tags to use, using a Vector Space Model (VSM), comparing similar blogs from the web and statistical methods. Tags are popular means of annotating and organizing content on the web, from photos, videos and music to blogs. Unfortunately, tagging is just a manual process and limited to the users’ own knowledge and experience. There may be more accurate or popular tags to describe the same content. Collaborative tagging is a recent technology that creates collective intelligence by observing how different users tag similar content. Our research makes use of this collective intelligence to automatically generate tag suggestions to blog authors based on the semantic content of blog entries. Key-Words: Web 2.0, Blog, Collaborative Tagging, Intelligent Systems.
An Automatic Segmentation of T2-FLAIR Multiple Sclerosis Lesions

Multiple sclerosis diagnosis and patient follow-up can be helped by an evaluation of the lesion load in MRI sequences. A lot of automatic methods to segment these lesions are available in the literature. The MICCAI workshop Multiple Sclerosis (MS) lesion segmentation Challenge 08 allows to test and compare these algorithms. This paper presents a method designed to detect hyperintense signal area on T2-FLAIR sequence and its results on the Challenge test data. The proposed algorithm uses only three conventional MRI sequences: T1, T2 and T2-FLAIR. First, images are cropped, spatially unbiased and skull-stripped. A segmentation of the brain into its different compartments is performed on the T1 and the T2 sequences. From these segmentations, a threshold for the T2-FLAIR sequence is automatically computed. Then postprocessing operations select the most plausible lesions in the obtained hyperintense signals. Global result on the test data (80/100) is close to the inter-expert variability (90/100).
Electromagnetic wave scattering from locally perturbed periodic inhomogeneous layers

We consider the scattering problem for locally perturbed periodic penetrable dielectric layers, which is formulated in terms of the full vector‐valued time‐harmonic Maxwell's equations. By assuming a non‐periodic right‐hand side, or, a perturbation in the permittivity, one cannot reduce the problem to one periodic cell in the classical way. In this article we present a method to solve such scattering problems. For that, we apply the Floquet‐Bloch transform to derive a coupled family of quasi‐periodic problems and solve the individual quasi‐periodic problems by combining some standard methods with technical calculations. This approach works as long as we stay away from the singularities in the quasi‐periodicity of the Calderon operator, which we use for the boundary condition. The challenge is to prove the unique existence of the solutions for the quasi‐periodicities inside the one‐dimensional set for which the quasi‐periodic differential operator is singular. The idea to tackle this problem is to construct a limit solution by letting the quasi‐periodicity converge to a singularity while decomposing the quasi‐periodic differential operator using the Sherman‐Morrison‐Woodbury formula. Additionally, we show regularity results of the Floquet‐Bloch transformed solution to the perturbed problem on the unbounded domain with respect to the quasi‐periodicity mode. These results, i.e., contribute to a numerical method to approximate the solution to the unbounded domain problem, which we will describe in a forthcoming work.
Field-Induced Deformation and Structure Changes in a Magnetic Polymersome: Many-Particle Simulation

Coarse-grained molecular dynamics simulation is performed to analyse structure and deformation response of a magnetic polymersome – a submicron hollow capsule whose membrane is made of amphiphilic block-copolymer, and the intramembrane space is filled with magnetic nanoparticles. The major prospects of these objects are related to controlled drug release. The developed many-particle model is used to calculate equilibrium magnetized configurations of polymersomes with different intensity of magnetic interparticle coupling. The analysis of those data reveals that under external magnetic field, an initially spherical capsule stretches along the field direction assuming a spheroid-like shape. This behaviour is caused by the field-driven tendency of the nanoparticles to aggregate inside the polymersome membrane. At weak interparticle magnetic interaction no extended chains are observed. Accordingly, the deformation and density redistribution are relatively small. In a polymersome with strong interparticle coupling the nanoparticles self-organize in long chains aligned with the field, and this induces considerable elongation of the polymersome along with accumulation of the majority of the nanoparticles in the “equatorial” zone of the membrane of the capsule.
Dealing with uncertainty in agent-based models for short-term predictions

Agent-based models (ABMs) are gaining traction as one of the most powerful modelling tools within the social sciences. They are particularly suited to simulating complex systems. Despite many methodological advances within ABM, one of the major drawbacks is their inability to incorporate real-time data to make accurate short-term predictions. This paper presents an approach that allows ABMs to be dynamically optimized. Through a combination of parameter calibration and data assimilation (DA), the accuracy of model-based predictions using ABM in real time is increased. We use the exemplar of a bus route system to explore these methods. The bus route ABMs developed in this research are examples of ABMs that can be dynamically optimized by a combination of parameter calibration and DA. The proposed model and framework is a novel and transferable approach that can be used in any passenger information system, or in an intelligent transport systems to provide forecasts of bus locations and arrival times.
Linear Regression Model for Predicting Daily PM2.5 Using VIIRS-SNPP and MODIS-Aqua AOT

Small-sized particulates (PM2.5) are very dangerous if inhaled by humans. The measurement of the particle concentration is carried out by the highly variable AQMS. Several studies have shown a positive relationship between aerosol optical thickness to surface PM2.5. The study aims to predict PM2.5 from Aerosol Optical Thickness using Linear Regression Model in Indonesia. The aerosol optical thickness is obtained from the VIIRS sensor on the SNPP satellite and from the MODIS sensor on the Aqua satellite. Linear regression model for predicting daily PM2.5 using AOT VIIRS SNPP is PM2.5=56.683*AOT-3.807 with r=0.7. Linear regression model for predicting daily PM2.5 using AOT MODIS-Aqua is PM2.5=104.3*AOT+1.0118 with r=0.7.
Evaluation of Stream and Wetland Restoration Using UAS-Based Thermal Infrared Mapping

Large-scale wetland restoration often focuses on repairing the hydrologic connections degraded by anthropogenic modifications. Of these hydrologic connections, groundwater discharge is an important target, as these surface water ecosystem control points are important for thermal stability, among other ecosystem services. However, evaluating the effectiveness of the restoration activities on establishing groundwater discharge connection is often difficult over large areas and inaccessible terrain. Unoccupied aircraft systems (UAS) are now routinely used for collecting aerial imagery and creating digital surface models (DSM). Lightweight thermal infrared (TIR) sensors provide another payload option for generation of sub-meter-resolution aerial TIR orthophotos. This technology allows for the rapid and safe survey of groundwater discharge areas. Aerial TIR water-surface data were collected in March 2019 at Tidmarsh Farms, a former commercial cranberry peatland located in coastal Massachusetts, USA (41°54′17″ N 70°34′17″ W), where stream and wetland restoration actions were completed in 2016. Here, we present a 0.4 km2 georeferenced, temperature-calibrated TIR orthophoto of the area. The image represents a mosaic of nearly 900 TIR images captured by UAS in a single morning with a total flight time of 36 min and is supported by a DSM derived from UAS-visible imagery. The survey was conducted in winter to maximize temperature contrast between relatively warm groundwater and colder ambient surface environment; lower-density groundwater rises above cool surface waters and thus can be imaged by a UAS. The resulting TIR orthomosaic shows fine detail of seepage distribution and downstream influence along the several restored channel forms, which was an objective of the ecological restoration design. The restored stream channel has increased connectivity to peatland groundwater discharge, reducing the ecosystem thermal stressors. Such aerial techniques can be used to guide ecological restoration design and assess post-restoration outcomes, especially in settings where ecosystem structure and function is governed by groundwater and surface water interaction.
Educational differentials in domain specific physical activity by ethnicity, age, and gender: findings from over 44,000 participants in The UK Household Longitudinal Study (2013-2015)

The prevalence of overall physical inactivity remains high, particularly amongst socioeconomically disadvantaged groups. It is unclear however if such inequalities vary systematically by age, sex, or ethnicity, and if there are differing effects across physical activity (PA) domains.We used data from a nationally representative survey of the UK, Understanding Society, with information on educational attainment (our indicator of socioeconomic position), PA and demographics collected in 2013-2015 (N= 44,903). Logistic regression analyses were conducted to test associations of education with three different PA domains (active travel, occupational and leisure time). To examine modification of the associations between education and physical activity in each domain by sex, age and ethnicity, we tested two-way interaction terms (education x ethnicity; education x sex; education x age). Lower educational attainment was associated with higher active transportation and occupational physical activity, but lower weekly leisure-time activity. These associations were modified by sex, ethnicity, and age. For example, education-related differences in active travel were larger for females (difference in predicted probability of activity between highest and lowest educational groups: −10% in females, (95% CI: −11.9, 7.9) −3% in males (−4.8, −0.4). The education-related differences in occupational activity were larger among males −35% (−36.9, −32.4) than females −17% (−19.4, −15.0). Finally, education related differences in moderate to vigorous leisure time activity varied most substantially by ethnicity; for example, differences were 17% (16.2, 18.7) for White individuals compared with 6% (0.6, 11.6) for Black individuals.Educational differences in PA vary by domain, and are modified by age, sex, and ethnicity. A better understanding of physically inactive sub-groups may aid development of tailored interventions to increase activity levels and reduce health inequalities.
Deposition of tungsten nitride thin films on Si, Zr and Stainless steel substrates using Plasma focus

The present research is motivated by the hard coatings on the substrate which improves the wear resistance that extends the working life of substrate material. Industrially, hard coatings are being used in automotive engine accessories, turbine blades, cutting and machining tools. Due to remarkable and desired mechanical, tribological and electronic properties of tungsten nitride thin films, these coatings are being applied in industry as well as for engineering purposes. The present research work reports the successful attempt to synthesis tungsten nitride films on Si, Zr and stainless steel substrates. Synthesis of WN/a-Si3N4, W-Zr-N and nano-crystalline tungsten nitride thin films on Si and Stainless steel substrates using Mather-Type plasma focus device. Tungsten nitride thin films have been synthesized on different substrates using various deposition techniques but the use of plasma focus technique is one of the prospective hybrid deposition methods that provides high deposition rate, deposition under reactive nature, good adhesion in small time, simple and economical technique for deposition purpose. The results of these experiments show the successful growth of tungsten based nitride thin films using plasma focus device of energy 3.3 kJ. The following four types of different experiments were performed. In the first experiment, WN/a-Si3N4 thin films were synthesized by utilizing the energetic ion/electron species emanated from hot, dense pinched plasma column in UNU/ICTP plasma focus operated with nitrogen gas. Structural, chemical, morphological and mechanical properties of synthesized films were studied using Xray diffraction (XRD), X-ray Photoelectron Spectroscopic (XPS), Field Emission Scanning Electron Microscopy (FESEM) and nano-indentation respectively. XRD spectra show WN2, W2N, W7N6, WSi2 phases on exposed samples. XPS results confirmed the chemical bonding of W-Si-N in synthesized films. FESEM micrographs showed uniform granular structure of synthesized WN/a-Si3N4 thin films. Surface morphology of synthesized thin films showed that increase in focus shots strong effects on the grain size due to change in ion energy flux. Nanoindentation results show the significant increase in hardness with increase in focus shots with maximum hardness of 23.5±1 GPa was observed for 45 focus shots. In the second experiment, nano-structure thin film of tungsten nitride was deposited onto Si-substrate at room temperature using Mather type plasma focus (3.3 kJ) machine. The substrate was exposed against 10, 20, 30 and 40 deposition shots