nils-herrmann/clean_scirepeval huggingface dataset:
Developing product recall capability through supply chain quality management
Year: 2020

Supply chain quality management (SCQM) has been viewed as a critical method for a manufacturer's management of product recalls. This study aims to empirically investigate the impact of SCQM practices on product recall capability using a sensemaking perspective. We adopt a multi method approach by combining case study and quantitative survey methods. This study selects three manufacturers from the food, automobile and pharmaceutical industries to conduct an explorative case study. The findings reveal that product recall capability includes tracking and traceability and formal process, and the manufacturers use quality management teamwork, supplier qualification and supplier involvement as the key SCQM practices. A conceptual framework of the relationships between SCQM practices and product recall capability is developed based on the findings of the case study. The hypotheses are empirically tested using structural equation modelling, bootstrapping method and data collected from 400 manufacturers in China. We find that quality management teamwork and supplier qualification are positively associated with product recall capability. Quality management teamwork is positively associated with supplier qualification and involvement. In addition, supplier qualification partially mediates the effect of quality management teamwork and fully mediates the effect of supplier involvement on product recall capability.
Impact of different placement depths on the crestal bone level of immediate versus delayed placed platform switched implants.
Venue: Journal of cranio maxillo facial surgery official publication of the European Association for Cranio Maxillo Facial Surgery
Year: 2018

The preservation of peri implant bone is one requirement for long term success of dental implants. The purpose of this study was to evaluate the impact of subcrestal placement on the crestal bone level of immediate versus delayed placed implants after loading.  In this retrospective study, data of 159 patients who received 330 implants was analyzed. Implants were placed subcrestally, crestally or supracrestally into fresh sockets or healed sites. Vertical bone level height was assessed radiographically and implants were followed up annually. The influence of patient and implant related risk factors for peri implant bone loss was evaluated using a linear mixed model.  Depth of implant placement was significantly correlated with peri implant bone loss (P 0.001, 95% CI) Least effective loss of crestal bone was determined when implants were placed between 1 mm and 1.99 mm subcrestally. Smoking significantly enhanced the risk of peri implant bone loss (P 0.04, 95% CI) Immediate implant placement was not positively correlated with peri implant bone loss (P 0.51, 95% CI) CONCLUSION Within the limits of this study, implant placement 1.08 mm subcrestally may be recommendable in order to avoid supracrestal expositions of platform switched titanium implants over time.
Shakespeare's Women and the Fin de Siecle
Year: 2016

Scholarship on Victorian productions of Shakespeare typically isolates Shakespeare from the rest of the repertory. My thesis illuminates how late Victorian performances of Shakespeare and contemporary Victorian drama conditioned each other. I re interrogate iconoclastic performances of Shakespeare's heroines to reveal actresses' performance networks, showing how actresses' movements between fin de siecle roles created consonances between ostensibly antithetical areas of the repertoire. The performances and receptions of British actresses with high cultural capital reveal Shakespeare's interventions into fin de siecle debates on gender and sexuality. Highlighting female performance genealogies, I offer the first narrative of women's acting traditions in Shakespeare. I explore actresses' commercial strategising, celebrity personae, theatrical innovations and contributions to Shakespearean hermeneutics. The thesis draws on significant unpublished archival material, including from private collections. Chapter One examines how the ostensibly puritanical Madge Kendal and Royal mistress Lillie Langtry used the role of Rosalind (As You Like It) within a portfolio of self promotional strategies, inscribing their professional legitimacy and dramatising different sexual identities. Chapter Two explores how Terry's Lady Macbeth (1888 9) interpreted as a loving wife, challenged theatrical semiotics, contemporary ideals of marriage, and perceptions of 'good' and 'bad' women. Chapter Three, on Mrs Patrick Campbell, demonstrates the success of her movements between the 'sex problem play' and Shakespeare, revealing how her Shakespeare reception reflected fin de siecle concerns as the unwell body and mind, the figure of Salome, and the child as both a sexual object and potentially suicidal. Chapter Four, on Terry's Imogen (Cymbeline) discusses Shakespearean actresses' contribution to ideas of national character and queenship, as Queen Victoria's reign neared its end, including specific milestones such as the 1897 Diamond Jubilee. Chapter Five examines Shakespeare's intersections with the 'New Woman' commodity culture and politics, as suffragists co opted Shakespeare as a 'suffrage' playwright, with The Winter's Tale's Paulina as their icon.
Context in Human Emotion Perception for Automatic Affect Detection: A Survey of Audiovisual Databases
Venue: 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)
Year: 2019

An important aspect of human emotion perception is the use of contextual information to understand others' feelings even in situations where their behavior is not very expressive or has an emotionally ambiguous meaning. For technology to successfully detect affect, it must mimic this human ability when analyzing audiovisual input. Databases upon which machine learning algorithms are trained should capture the context of social interactions as well as the behavior expressed in them. However, there is a lack of consensus about what constitutes relevant context in such databases. In this article, we make two contributions towards overcoming this challenge: (a) we identify two principal sources of context for emotion perceptions based on psychological theory, and (b) we provide an overview of how each of these has been considered in published databases covering social interactions. Our results show that a similar set of contextual features are present across the reviewed databases. Between all the different databases researchers seem to have taken into account a set of contextual features reflecting the sources of context seen in psychological theory. However, within individual databases, these features are not yet systematically varied. This is problematic because it prevents them from being used directly as resources for the modeling of context sensitive affect detection. Based on our findings, we suggest improvements for the future development of affective databases.
Rapid Development of Activated Carbon and ZnO Nanoparticles via Green Waste Conversion Using Avocado Fruit Peel Powder and its High Performance Efficiency in Aqueous Dye Removal Application
Venue: Journal of Inorganic and Organometallic Polymers and Materials
Year: 2019

The present study focused to evaluate the utility of avocado fruit peel waste material for the development of activated carbon and ZnO nanoparticles for water treatment applications. Green synthesized activated carbon and ZnO nanoparticles using avocado fruit peel as a substrate was characterized using different techniques including FESEM, TEM, EDX, XRD and FTIR. In addition, further investigation was carried out to find their efficiency of its application for removal of selective dyes such as Congo red, Crystal violet, Saffranin, Methylene orange and Malachite green in aqueous solution through adsorption and photocatalytic activity respectively. 99.9% dye removal was observed in the column experiment condition, where, 100 mg L 1 concentrations of selective dye solutions were passed through the column (7.9 x 1.2 cm) filled with 50 mg of synthesized activated carbon at the flow rate of 6 drops/min. Green synthesized ZnO nanoparticles exhibited efficient photocatalytic activity of 70 98% against above mentioned selective dyes under the sunlight irradiation for the experimental condition which contains 20 mg of ZnO NPs and 50 mL (30 mg L 1) of each dye solution. Further studies are recommended to elucidate the detailed mechanism of this avocado fruit peel powder in proposed materials conversion and using these materials as an agent for dye removal applications.
Steklov Spectral Geometry for Extrinsic Shape Analysis
Venue: ACM Trans. Graph.
Year: 2019

We propose using the Dirichlet to Neumann operator as an extrinsic alternative to the Laplacian for spectral geometry processing and shape analysis. Intrinsic approaches, usually based on the Laplace Beltrami operator, cannot capture the spatial embedding of a shape up to rigid motion, and many previous extrinsic methods lack theoretical justification. Instead, we consider the Steklov eigenvalue problem, computing the spectrum of the Dirichlet to Neumann operator of a surface bounding a volume. A remarkable property of this operator is that it completely encodes volumetric geometry. We use the boundary element method (BEM) to discretize the operator, accelerated by hierarchical numerical schemes and preconditioning; this pipeline allows us to solve eigenvalue and linear problems on large scale meshes despite the density of the Dirichlet to Neumann discretization. We further demonstrate that our operators naturally fit into existing frameworks for geometry processing, making a shift from intrinsic to extrinsic geometry as simple as substituting the Laplace Beltrami operator with the Dirichlet to Neumann operator.
Deep reinforcement learning applied to the k server problem
Venue: Expert Syst. Appl.
Year: 2019

The reinforcement learning paradigm has been shown to be an effective approach in solving the k server problem. However, this approach is based on the Q learning algorithm, being subjected to the curse of dimensionality problem, since the action value function (Q function) grows exponentially with the increase in the number of states and actions. In this work, a new algorithm based on the deep reinforcement learning paradigm is proposed. For this, the Q function is defined by a multilayer perceptron neural network that extracts the information of the environment from images that encode the dynamics of the problem. The applicability of the proposed algorithm is illustrated in a case study in which different nodes and servers problem configurations are considered. The agents behavior is analyzed during the training phase and its efficiency is evaluated from performance tests that quantify the quality of the generated server displacement policies. The results obtained provide a new algorithm promising view as an alternative solution to the k server problem.
Programming Self Assembly of DNA Origami Honeycomb Two Dimensional Lattices and Plasmonic Metamaterials.
Venue: Journal of the American Chemical Society
Year: 2016

Scaffolded DNA origami has proven to be a versatile method for generating functional nanostructures with prescribed sub 100 nm shapes. Programming DNA origami tiles to form large scale 2D lattices that span hundreds of nanometers to the micrometer scale could provide an enabling platform for diverse applications ranging from metamaterials to surface based biophysical assays. Toward this end, here we design a family of hexagonal DNA origami tiles using computer aided design and demonstrate successful self assembly of micrometer scale 2D honeycomb lattices and tubes by controlling their geometric and mechanical properties including their interconnecting strands. Our results offer insight into programmed self assembly of low defect supra molecular DNA origami 2D lattices and tubes. In addition, we demonstrate that these DNA origami hexagon tiles and honeycomb lattices are versatile platforms for assembling optical metamaterials via programmable spatial arrangement of gold nanoparticles (AuNPs) into cluster and superlattice geometries.
PPCoin: Peer to Peer Crypto Currency with Proof of Stake
Year: 2012

A peer to peer crypto currency design derived from Satoshi Nakamoto's Bitcoin. Proof of stake replaces proof of work to provide most of the network security. Under this hybrid design proof of work mainly provides initial minting and is largely non essential in the long run. Security level of the network is not dependent on energy consumption in the long term thus providing an energyefficient and more cost competitive peer to peer crypto currency. Proof of stake is based on coin age and generated by each node via a hashing scheme bearing similarity to Bitcoin's but over limited search space. Block chain history and transaction settlement are further protected by a centrally broadcasted checkpoint mechanism.
Facile in situ solution synthesis of SnSe/rGO nanocomposites with enhanced thermoelectric performance
Year: 2020

Constructing nanostructured composite architectures has been considered as an effective strategy to reduce the lattice thermal conductivity (kL) and enhance the dimensionless figure of merit (ZT) of thermoelectric materials. Herein, a series of SnSe/reduced graphene oxide (rGO) x (x 0.1, 0.3, 0.5, 0.7 wt% nanocomposites are controllably synthesised in situ via a facile single step bottom up solution method, where rGO nanosheets are incorporated intimately into the SnSe matrix. Nanocompositing performs two key functions: (i) significantly reducing the lattice thermal conductivity of the material, which can be attributed to enhanced phonon scattering from high density SnSe/rGO interfaces, and (ii) improving the electrical conductivity over the low temperature range, as result of an increased carrier concentration. The subsequent thermoelectric performance of SnSe/rGO sintered pellets has been optimised by tuning the rGO mass fraction, with SnSe/rGO 0.3 achieving kL 0.36 W m 1 K 1 at 773 K (cutting the kL of SnSe by 33% to yield a maximum ZT of 0.91 at 823 K (representing a ~47% increase compared to SnSe) This study provides a new pathway to improve the thermoelectric performance of polycrystalline SnSe by way of engineering metal chalcogenide/rGO composite architectures at the nanoscale.
Oncoplastic breast surgery versus conventional breast conserving surgery: a comparative retrospective study
Venue: ANZ journal of surgery
Year: 2019

In addition to conventional breast conserving surgery (BCS) oncoplastic breast surgery (OBS) is an operation technique that strives simultaneously to increase oncological safety and patient's satisfaction. It is the combination of the best proven techniques in plastic surgery with surgery for breast cancer. In a growing number of indications, OBS overcomes the limit of conventional BCS by allowing larger resection volumes while avoiding deformities. The aim of our retrospective study (2012 2014) was to compare oncological outcomes of OBS versus BCS.
A review of critical success factors (CSFs) for executive information system (EIS) development in education domain
Year: 2017

This study reviews the critical success factors (CSFs) of executive information systems (EIS) development for education domain. EIS is the information system that can integrate internal and external information, which allows executives formulate plans, explain the indicators, determine organisation performance, mapping productivity and make strategic decision making. Although the implementation of the EIS can be complying using the standard system development life cycle (SDLC) model, the CSFs that affect its development is important to identify to the success of its initiative. Previous studies have examined various CSF to the success of EIS implementation, but explanation the significant of CSF based on the findings in education EIS development needs to discuss further. The study was accomplished through content analysis approaches based on the previous findings on CSF framework in education EIS development study done by the author. The results explained the review of CSF components discovered, (1) organisational contexts, (2) human resources, (3) development activities, and (4) EIS as a product. These findings potentially used as a reference to the continuing development of education EIS or the development of EIS in any organisation that possess management background similar as an education field.
Impacto de procesos de Bienestar Estudiantil en el mejoramiento de la calidad educativa de Universidad Laica Eloy Alfaro de Manabi, Extension Chone
Year: 2018

La problematica se centro en identificar las debilidades del accionar de los departamentos de Bienestar Estudiantil en el pais, con vistas a publicar un documento que sirva para recomendar acciones de fortalecimiento de los procesos de estas areas de las instituciones de educacion superior, por ello se planteo como objetivo general determinar el impacto de los procesos de Bienestar Estudiantil en el mejoramiento de la calidad educativa de la Universidad Laica Eloy Alfaro de Manabi, Extension Chone; para lo cual se utilizo el metodo cuantitativo mediante encuestas a los estudiantes universitarios. Se obtuvo como resultado limitaciones en el proceso debido a las limitaciones de personal y de recursos, que generan insatisfaccion de los estudiantes, quienes esperan que este departamento les solucione sus problemas de salud fisica, mental, emocional, defienda sus derechos y les otorgue apoyo economico para sus estudios
Exploring the effect of Airbnb hosts' attachment and psychological ownership in the sharing economy
Venue: Tourism Management
Year: 2019

Previous research on the sharing economy has not typically focused on organizational structure and its management in spite of the fact that the essence of recent peer to peer business practices is the collaboration of online platforms and sharable assets owned by market peers. This paper critically examines a theoretical model to explore how these market partners engage in this platform organization and how their perceptions of attachment and ownership are established within the new organizational structure. The results of structural equation modeling applied to 224 Airbnb hosts indicate that attachment to a platform firm plays a vital role in achieving a sense of psychological ownership that ultimately influences citizenship behaviors toward the organization as well as toward peer hosts. The results suggest that the newly formed structure should acknowledge an establishing mechanism of attachment and psychological ownership in partnering with individual service providers in its operational management.
Exploring Factors for Improving Low Resolution Face Recognition
Venue: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2019

State of the art deep face recognition approaches report near perfect performance on popular benchmarks, e.g. Labeled Faces in the Wild. However, their performance deteriorates significantly when they are applied on low quality images, such as those acquired by surveillance cameras. A further challenge for low resolution face recognition for surveillance applications is the matching of recorded low resolution probe face images with high resolution reference images, which could be the case in watchlist scenarios. In this paper, we have addressed these problems and investigated the factors that would contribute to the identification performance of the state of the art deep face recognition models when they are applied to low resolution face recognition under mismatched conditions. We have observed that the following factors affect performance in a positive way: appearance variety and resolution distribution of the training dataset, resolution matching between the gallery and probe images, and the amount of information included in the probe images. By leveraging this information, we have utilized deep face models trained on MS Celeb 1M and fine tuned on VGGFace2 dataset and achieved state of the art accuracies on the SCFace and ICB RW benchmarks, even without using any training data from the datasets of these benchmarks.
Interference reduction of high energy noise for modal parameter identification of offshore wind turbines based on iterative signal extraction
Venue: Ocean Engineering
Year: 2019

An iterative noise extraction and elimination method is proposed, to solve the difficulty of modal parameter identification caused by contaminated high energy components in measured signals. The approach is based on the idea that if only the high energy noise is extracted and eliminated accurately, modal parameter identification can be improved significantly by using the remaining (filtered) signal. A theoretical development is that a general form of noises is considered, i.e. they can be purely harmonic or damped, which implies noises from machine vibration or other unknown sources can be taken into account. The advantage of this approach is that only one significant, relatively noisy component is extracted at each iteration, i.e. only the most reliable component is extracted each time, so more accurate high energy noise elimination is expected. To demonstrate the accuracy of the proposed method, a numerical signal with one high energy noisy component is used. Numerical results show that the approach can extract and eliminate high energy noise at 2.1 Hz accurately by setting a small model order. A special case is the noisy component as a harmonic, which means the traditional Fourier transform can be applied. However, one can conclude that the proposed method outperforms the Fourier transform due to its limitation of fixed frequency resolution. To further investigate the effectiveness of the approach, an experiment on a steel offshore platform is conducted, and experimental results indicate that when measured raw data is used, only the first mode can be identified; if filtered data is used by employing the proposed method, the first two modes can be identified with improved damping ratio estimation. Finally, sea test data from an offshore wind turbine in operating conditions are used, results show that the first mode with a frequency of 0.3592 Hz and a damping ratio of 0.0151 are successfully identified, while no reasonable parameters can be obtained by employing the stochastic subspace identification method, even when the used model order reaches 300.
Challenges of Commercial Aquaponics in Europe: Beyond the Hype
Year: 2020

In recent years, aquaponics has been receiving increased interest globally as a commercial food production technology and aquaponics start up companies have been formed in most European countries. Between 2014 and 2018, the European funded COST Action FA1305 "The EU Aquaponics Hub Realising Sustainable Integrated Fish and Vegetable Production for the EU" created a strong network of researchers and entrepreneurs. However, surveys show that the aquaponic production in Europe is still very limited, and very few companies are economically viable. In order to obtain insights into the barriers to early development of commercial aquaponics, two surveys were carried out one in Europe, which included France, and one in France alone, with a different protocol. Henceforth, for simplicity, the former will be referred to as Europe and the latter as France. The results reveal that the development of commercial aquaponics has hit the level of "disillusionment" caused by numerous challenges facing commercial food production. As the understanding of the processes involved in aquaponics is increasing, it will be very interesting to follow the developments in the field over the coming years in order to ascertain whether aquaponics will follow the phases outlined by the "Gartner's Hype Cycle" and thus proceed to become an established technology, or whether it will remain an "one hit wonder" and disappear in the "Trough of Disillusionment"