nils-herrmann/clean_scirepeval huggingface dataset:
A morphological and phylogenetic evaluation of Marasmius sect. Globulares (Globulares Sicci complex) with nine new taxa from the Neotropical Atlantic Forest
Venue: Persoonia
Year: 2020

The largest and most recently emended Marasmius sect. Globulares (Globulares Sicci complex) has increased in number of species annually while its infrasectional organization remains inconclusive. During forays in remnants of the Atlantic Rainforest in Brazil, 24 taxa of Marasmius belonging to sect. Globulares were collected from which nine are herein proposed as new: Marasmius altoribeirensis, M. ambicellularis, M. hobbitii, M. luteoolivaceus, M. neotropicalis, M. pallidibrunneus, M. pseudoniveoaffinis, M. rhabarbarinoides and M. venatifolius. We took this opportunity to evaluate sect. Globulares sensu Antonin Noordel. in particular, combining morphological examination and both single and multilocus phylogenetic analyses using LSU and ITS data, including Neotropical samples to a broader and more globally distributed sampling of over 200 strains. Three different approaches were developed in order to better use the genetic information via Bayesian and Maximum Likelihood analyses. The implementation of these approaches resulted in: i) the phylogenetic placement of the new and known taxa herein studied among the other taxa of a wide sampling of the section; ii) the reconstruction of improved phylogenetic trees presenting more strongly supported resolution especially from intermediate to deep nodes; iii) clearer evidence indicating that the series within sect. Sicci and sect. Globulares in the traditional concept are non monophyletic by this more stringent evaluation; and iv) the existence of several monophyletic suprespecific groups equivalent to the stirpes of Singer clusters of morphologically similar species. These two latter points corroborate with findings of previous studies implementing analyses with the entire genus. Based on these results, we proposed a new infrasectional classification elevating Singer's concept of stirpes to series. Thirteen new series, the emendation of three extant series and three subsections gathering these series based on the major clades are proposed.
Propagation characteristics of Gaussian beams in plasma sheath turbulence
Year: 2017

In this study, the new fractal model and power spectrum of plasma sheath turbulence are established based on the fractal dimensions in hypersonic turbulence that were measured through experiments. The expression for beam spot size, scintillation index, angle of arrival fluctuation, and beam wander are obtained from the power spectrum. Finally, the propagation characteristics of a Gaussian beam in a turbulent plasma sheath are simulated. The authors' results indicate that plasma sheath turbulence can lead to amplitude and phase variations. A larger variance in the plasma sheath turbulence causes a more evident refractive index fluctuation and a greater effect on the Gaussian beam propagation characteristics. On the contrary, a larger Reynolds number reduces the effect of the plasma sheath turbulence on the Gaussian beam. This new power spectral model is fundamental to understanding Gaussian beam propagation in plasma sheath turbulence and may provide a reference for the imaging and communication system under the effect of plasma sheath turbulence.
Model of Entrepreneurship Financial Activity of the Transnational Company Based on Intellectual Technology
Year: 2020

In order to ensure the sustainable competitiveness of multinational corporations in an integrated and at the same time segmented and diversified global financial market, it is first and foremost important to determine their mission and strategy, which have particularities for universal, specialized, niche, international bank oriented clients. Based on the principles of functionality, uniqueness and collegiality, necessary competence and conflict of interest, taking into account prevailing business processes and environmental factors, organizational structures of transnational banks are developed, the main types of which are linear functional, divisional, mixed. Corresponding to the modern trends of global financial business and entrepreneurship, the methodology of organizational modeling is a multilevel organizational business model of a transnational bank with organizational and functional (business, functions, structure) technological (IT landscape, IT infrastructure, services) process role, regulatory, service, quantitative subsystems. The Bank's organizational design format introduces and develops a profile of its innovative, team, client oriented, productive corporate culture. In today's global banking, comprehensive programs for improving business ecosystems with creative management tools are being updated.
Synthesis of silver loaded ZnO nanorods and their enhanced photocatalytic activity and photoconductivity study.
Venue: Photochemical photobiological sciences Official journal of the European Photochemistry Association and the European Society for Photobiology
Year: 2019

Herein, we synthesized ZnO nanorods using a solvothermal reaction technique at 200 degC for 24 h, and the prepared ZnO nanorods were decorated with silver (Ag) nanoparticles to enhance their photocatalytic activity. The Ag nanoparticles were photochemically deposited on the ZnO rods with varying molar concentrations (from 0.5 to 10 mol% and their various physicochemical properties were studied. The prepared material was characterised using different spectroscopic techniques. XRD revealed the formation of a highly crystalline hexagonal phase of ZnO. For a higher silver loading >5 mol% separate peaks corresponding to cubic silver were observed in the XRD pattern. The photoluminescence spectra of the Ag/ZnO nanostructures show two distinct peaks at 390 and 500 nm; interestingly, the PL intensity of the ZnO emission peak at 500 nm decreases with an increase in the silver concentration. The diffuse reflectance spectra of Ag/ZnO indicate absorbance at 380 nm due to ZnO and a slight hump at 440 nm that corresponds to silver nanoparticles. The FE SEM and TEM analysis indicates the formation of a hexagonal rod like morphology, with the lengths of the rods ranging from around 50 to 200 nm and a diameter of around 30 nm. TEM also confirms the presence of Ag nanoparticles with sizes in the range of 20 to 30 nm on the surface of the ZnO nanorods. The photocatalytic activity of the Ag/ZnO nanostructures was evaluated by following the degradation of methylene blue (MB) dye under a 400 W mercury vapour lamp. ZnO with 10 mol% Ag loading shows the highest photocatalytic activity as compared to the 0.5, 1 5 mol% Ag ZnO catalysts. The observed apparent rate constant for the photocatalytic MB degradation using 10 mol% Ag ZnO (Kapp 6.01 x 10 2 min 1) was six times that of pure ZnO (Kapp 1.09 x 10 2 min 1) A gradual increase in the photocatalytic activity of Ag/ZnO was observed with an increase in the silver concentration. The photocurrent response of the prepared Ag ZnO nanostructures was examined by a photoconductivity study. Moreover, the photocatalytic performance of the sample was correlated with the photoconductivity of the samples. The photoconductivity of the samples was stable, and the photoconductivity of 10 mol% Ag ZnO was almost 20 times that of pure ZnO, resulting in a higher photocatalytic activity.
Household installation of solar panels Motives and barriers in a 10 year perspective
Year: 2018

This article compares what homeowners identified as motives and barriers for installing photovoltaic panels in Sweden in 2008 2009 and in 2014 2016. Earlier research has provided snapshots of existing barriers and motives, but not analyzed changes over time, as is done here. Between 2008 and 2014, the PV market in Sweden changed profoundly, with the introduction of subsidies and changes in rules, making it easier for households to sell electricity they produce. At the same time, regulations have increased for the households.
Communication, cooperation conflict in quorum sensing bacteria
Year: 2012

The scientific community has gathered an extremely detailed and sophisticated understanding of the genetic and molecular underpinnings of microbial communication. How these microbial communication systems arise and are maintained over evolutionary time scales however has received relatively little attention. Some major questions remain unanswered such as; what is the function of small diffusible molecules? How does population structure affect the dynamics of social communication and what is the link between the ecology of communication and the virulence of a pathogenic population? Borrowing concepts from evolutionary theory can help to unravel these fundamental questions in the context of microbial communication as it has done in other taxa displaying social behaviours. In addition microbial model organisms in which molecular and genetic tools are abundant lend enormous power to empirical tests of evolutionary theory. This work combines both of these in an attempt to understand the evolution of bacterial communication using the model organism Pseudomonas aeruginosa and its well characterised Quorum Sensing systems. Specifically the focus is in three areas. Firstly this study reveals that the stability of bacterial signalling is vulnerable to perturbations in cost and benefit and genetic conflict. Secondly this study finds that spatial structure (biofilm vs planktonic) influences the outcome of social competition over signalling and reduces population viability. Thirdly this study finds that interspecific and intraspecific competition over public goods impose divergent selective pressures on communication.
Will they, or Won't they? Examining patients' vaccine intention for flu and COVID 19 using the Health Belief Model
Venue: Research in Social and Administrative Pharmacy
Year: 2020

The twindemic of influenza and COVID 19 places pharmacists in a position of high impact to inform and manage vaccination uptake. Given prior vaccine hesitancy in the US and the current high impact of COVID 19 on the population, it is imperative to understand and address factors that drive perceptions and intention to get vaccinated.  The objectives of the study were to 1) determine impact of the COVID 19 pandemic on influenza vaccine uptake, on patient perceptions of vaccinations, vaccine intention, and health behaviors and 2) determine vaccine intention through the Health Belief Model.  An IRB approved prospective Qualtrics based survey was administered online to eligible respondents: non pregnant panel respondents 18 years or older within the United States who could independently complete the entire questionnaire in English. Data analyses included descriptive statistics, psychometric analyses of the 5C and CoBQ tools, one way ANOVA to compare demographic groups and vaccine intention items with survey scores, and mapping and path analysis of the HBM with one added domain (Decision Making Determinant, DMD) Results 525 respondents completed the survey from October 23 29, 2020. Respondents aged 18 49, making less than $20,000 or an undisclosed income, and not having anyone close to them directly affected by COVID 19 showed a significant, negative impact of COVID 19 on health behavior and a significantly lower vaccine acceptance. The 5C and CoBQ showed moderately strong reliability. Mapping for the HBM revealed significant correlations between all modifying factors with Individual Perceptions except for Race/Ethnicity. Of the Individual Perceptions, Perceived Benefits .114) and Perceived Barriers .307) significantly predicted DMD and directly impacted Vaccine Intention. DMD was not a significant mediator of Vaccination Intention.  Vaccination messaging should focus on a simple yet balanced view of benefits and risks, targeting those under age 50 and living in low income households, to motivate uptake of influenza and COVID 19 vaccines.
Resilience assessment of the lithium supply chain in China under impact of new energy vehicles and supply interruption
Year: 2020

The development of new energy vehicles had a huge impact on lithium demand under the framework of the lithium supply chain, and geopolitical changes have increased the risk of lithium supply interruption. Does the lithium supply chain have the coping ability under the demand impact of new energy vehicles and the risk of supply interruption? Can some improvement measures improve the coping ability of the lithium supply chain? In this paper, the system dynamic modeling is used method to evaluate the supply chain resilience; make the price, supply and demand systems be the three resilient mechanisms of the lithium supply chain; and set demand impact, supply interrupt, and three enhancement measures as the model scenes. The simulation results show that the lithium supply chain is less resilient under the impact of new energy vehicles. Furthermore, the resilience of the lithium supply chain is good under the risk of short term supply interruption, but worse under long term supply interruption. Finally, promoting a design for recycling has the most obvious improvement in coping ability with the lithium supply chain, with reserve stockpile and drawdown focused more on adjusting supply chain fluctuations and; material substitution has only a slight improvement in supply chain resilience.
Semi Automated SVG Programming via Direct Manipulation
Venue: UIST
Year: 2016

Direct manipulation interfaces provide intuitive and interactive features to a broad range of users, but they often exhibit two limitations: the built in features cannot possibly cover all use cases, and the internal representation of the content is not readily exposed. We believe that if direct manipulation interfaces were to (a) use general purpose programs as the representation format, and (b) expose those programs to the user, then experts could customize these systems in powerful new ways and non experts could enjoy some of the benefits of programmable systems. In recent work, we presented a prototype SVG editor called Sketch n Sketch that offered a step towards this vision. In that system, the user wrote a program in a general purpose lambda calculus to generate a graphic design and could then directly manipulate the output to indirectly change design parameters (i.e. constant literals) in the program in real time during the manipulation. Unfortunately, the burden of programming the desired relationships rested entirely on the user. In this paper, we design and implement new features for Sketch n Sketch that assist in the programming process itself. Like typical direct manipulation systems, our extended Sketch n Sketch now provides GUI based tools for drawing shapes, relating shapes to each other, and grouping shapes together. Unlike typical systems, however, each tool carries out the user's intention by transforming their general purpose program. This novel, semi automated programming workflow allows the user to rapidly create high level, reusable abstractions in the program while at the same time retaining direct manipulation capabilities. In future work, our approach may be extended with more graphic design features or realized for other application domains.
Incremental Learning Based Adaptive Object Recognition for Mobile Robots
Venue: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2018

3D visual understanding of the surrounding environment is vital for successful mobile robotic tasks such as autonomous navigation or general object interaction. However, current systems have limited perceptual capabilities in the sense that they are not very well adaptable to unknown environments. Human operators, on the other hand, are experts in adapting to previously unknown information. Hence, human robot teaming in which the human helps the robot to adapt to new environments and the robot assists in automated object recognition to efficiently feed the control environment of the operator is advantageous. In this work, we propose an object recognition and localization system for mobile robots, based on deep learning, and we study the adaptation of the resulting robotic perception to a new environment. We propose two methods to teach the robot a new object category: using prior knowledge and using limited operator input. We conducted several experiments to show the feasibility of proposed methods.
Disgust, creatureliness and the accessibility of death related thoughts
Year: 2007

From an existential terror management theory perspective, disgusting stimuli are threatening to human beings because they make salient people's vulnerability to death. Two studies were designed to assess this proposition by measuring implicit death related ideation after individuals were presented with stimuli that either were or were not disgusting, under conditions in which the similarities of humans to other animals or the uniquely human aspects of people were made salient. In Study 1, in which rather extreme disgust eliciting pictures were used, disgusting stimuli led to higher death thought accessibility than neutral pictures regardless of whether or not participants had previously been primed with similarities between humans and other animals. In Study 2, in which milder verbal disgust eliciting stimuli were used, disgusting stimuli led to heightened death thought accessibility only when human animal similarities were first primed. Implications for the regulation and humanization of the human body and its functions are discussed.
Trajectory Optimization for Cellular Enabled UAV With Connectivity Outage Constraint
Venue: IEEE Access
Year: 2020

This paper studies the trajectory optimization problem of a single cellular enabled unmanned aerial vehicle (UAV) taking into account the outage performance of the entire trajectory. To provide real time control, it is critical for UAV to maintain reliable connectivity with the ground base station (GBS) We first consider the connectivity outage performance, which is defined as the sum of the time duration of the outage performance not meeting a predefined threshold during the entire UAV mission. Then we formulate a trajectory optimization problem to minimize the mission completion time, while ensuring a sum constraint of the connectivity outage performance. We show that the connectivity outage constraint can be transformed into a flying area constraint. Since the formulated problem is NP hard, a low complexity method is proposed to solve the problem by finding the shortest path in an undirected weighted graph with enlarged GBS coverage. Simulation results demonstrate the superiority of the proposed scheme over other state of the art schemes, in terms of trajectory length and computational complexity.
Improving Community Involvement and Citizenship among Elementary School Students through Service Learning Experiences.
Year: 2007

This Action Research Project was designed to increase student awareness and involvement of socio economic differences and how the children can make a difference in their community. Service learning projects were non existent at the Academy causing the young children to miss out on learning experiences that would teach them how to make a difference in their community while also making real world connections to the curriculum. Donation collections for people in need were previously implemented as community service projects in the elementary school but these activities did not teach children about actively conducting services and understanding socio economic differences apparent in society that can be tied in with the classroom curriculum. The writer implemented a service learning program for the kindergarten students that involved the children reading books to earn money they were to save to purchase books for children in need at a neighboring public school. The children communicated with the children in need through pen pal letters. Both groups of children learned how they are similar in many ways regardless of their living situations. They discussed different books they liked which helped the students at the Academy select the books they would purchase for the children in need. Once the children collected their money and purchased the books, a kindergarten book wrapping day was created. The students all took part in decorating white paper to use as homemade wrapping paper for the books. A pre project and post project interview were administrated to the kindergartners using the same questions for both interviews to track the changes in perspective and maturity the students underwent after completing the service learning project. Analysis of the data indicated that service learning projects result in more meaningful learning experiences for young children as opposed to donation collections or an absence of any form of humanitarian education. The children gained an understanding of socio economic differences and learned how they can make an impact on their communities by helping people in need. Student responses to interview questions before and after the service learning project was implemented reveal increasing maturity and understanding of how the students can help people in need and be upstanding citizens in their communities. Improving Community 3 Table of
TensorFlow on State of the Art HPC Clusters: A Machine Learning use Case
Venue: 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
Year: 2019

The recent rapid growth of the data flow programming paradigm enabled the development of specific architectures, e.g. for machine learning. The most known example is the Tensor Processing Unit (TPU) by Google. Standard data centers, however, still can not foresee large partitions dedicated to machine learning specific architectures. Within data centers, the High Performance Computing (HPC) clusters are highly parallel machines targeting a broad class of compute intensive workflows, as such they can be used for tackling machine learning challenges. On top of this, HPC architectures are rapidly changing, including accelerators and instruction sets other than the classical x86 CPUs. In this blurry scenario, identifying which are the best hardware/software configurations to efficiently support machine learning workloads on HPC clusters is not trivial. In this paper, we considered the workflow of TensorFlow for image recognition. We highlight the strong dependency of the performance in the training phase on the availability of arithmetic libraries optimized for the underlying architecture. Following the example of Intel leveraging the MKL libraries for improving the TensorFlow performance, we plugged the Arm Performance Libraries into TensorFlow and tested on an HPC cluster based on Marvell ThunderX2 CPUs. Also, we performed a scalability study on three state of the art HPC clusters based on different CPU architectures, x86 Intel Skylake, Arm v8 Marvell ThunderX2, and PowerPC IBM Power9.