nils-herrmann/clean_scirepeval huggingface dataset:
STANDARDIZATION OR ADAPTATION IN COSMETICS WEBSITES MARKETING AN EMPIRICAL STUDY.
Year: 2011

The websites marketing is becoming an important tool both for multinationals and SMEs, in their effort to internationalizing their business. This study focuses on the international opportunities that are present within the European markets. The paper aims at identifying the degree of websites marketing standardization vs. adaptation, as a marketing tool for cosmetic products. Moreover, the study examines in a comparative manner the standardization strategy of multinationals and small and medium enterprises (SMEs) leaders in European markets, for different cosmetic cathegories. The evaluation of online advertising standardization is based on the modified Model for Testing Advertising Standardization, developed by Whitelock and Chung. The web sites degree of localizations are analyzed based upon 98 criteria, as resulted from an adapted methodology of ProfNet Institut fur Internet Marketing, Munster (Germany) The sample includes the 101 leaders from European markets. The research outcomes reflect a standardized websites marketing policy for SMEs and localized for multinationals. Also, for perfumes, dental care products and toiletry, European cosmetic leaders implement standardized websites marketing policies and balanced for the other cosmetics categories. The hypothesis concerning a strong correlation between standardization and handling dimension was supported.
Empowering News Recommendation with Pre trained Language Models
Venue: SIGIR
Year: 2021

Personalized news recommendation is an essential technique for online news services. News articles usually contain rich textual content, and accurate news modeling is important for personalized news recommendation. Existing news recommendation methods mainly model news texts based on traditional text modeling methods, which is not optimal for mining the deep semantic information in news texts. Pre trained language models (PLMs) are powerful for natural language understanding, which has the potential for better news modeling. However, there is no public report that shows PLMs have been applied to news recommendation. In this paper, we report our work on pre trained language models empowered news recommendation (PLM NR) Offline experimental results on both monolingual and multilingual news recommendation datasets show that leveraging PLMs for news modeling can effectively improve the performance of news recommendation. Our PLM NR models have been deployed to the Microsoft News platform, and online flight results show that they can achieve significant performance gains in both English speaking and global markets.
SspABCD SspE is a phosphorothioation sensing bacterial defence system with broad anti phage activities
Venue: Nature Microbiology
Year: 2020

Bacteria have evolved diverse mechanisms to fend off predation by bacteriophages. We previously identified the Dnd system, which uses DndABCDE to insert sulfur into the DNA backbone as a double stranded phosphorothioate (PT) modification, and DndFGH, a restriction component. Here, we describe an unusual SspABCD SspE PT system in Vibrio cyclitrophicus Escherichia coli and Streptomyces yokosukanensis which has distinct genetic organization, biochemical functions and phenotypic behaviour. SspABCD confers single stranded and high frequency PTs with SspB acting as a nickase and possibly introducing nicks to facilitate sulfur incorporation. Strikingly, SspABCD coupled with SspE provides protection against phages in unusual ways: (1) SspE senses sequence specific PTs by virtue of its PT stimulated NTPase activity to exert its anti phage activity, and (2) SspE inhibits phage propagation by introducing nicking damage to impair phage DNA replication. These results not only expand our knowledge about the diversity and functions of DNA PT modification but also enhance our understanding of the known arsenal of defence systems. SspABCD SspE is a widespread bacterial defence system against phage infection, in which SspABCD is responsible for introducing phosphorothioate modifications and SspE serves as a nickase that cleaves foreign DNA.
Effectiveness of self supervised pre training for speech recognition
Venue: ArXiv
Year: 2019

We compare self supervised representation learning algorithms which either explicitly quantize the audio data or learn representations without quantization. We find the former to be more accurate since it builds a good vocabulary of the data through vq wav2vec  to enable learning of effective representations in subsequent BERT training. Different to previous work, we directly fine tune the pre trained BERT models on transcribed speech using a Connectionist Temporal Classification (CTC) loss instead of feeding the representations into a task specific model. We also propose a BERT style model learning directly from the continuous audio data and compare pre training on raw audio to spectral features. Fine tuning a BERT model on 10 hour of labeled Librispeech data with a vq wav2vec vocabulary is almost as good as the best known reported system trained on 100 hours of labeled data on testclean, while achieving a 25% WER reduction on test other. When using only 10 minutes of labeled data, WER is 25.2 on test other and 16.3 on test clean. This demonstrates that self supervision can enable speech recognition systems trained on a near zero amount of transcribed data.
224th ENMC International Workshop: Clinico sero pathological classification of immune mediated necrotizing myopathies Zandvoort, The Netherlands, 14 16 October 2016
Venue: Neuromuscular Disorders
Year: 2018

224th ENMC International Workshop: Clinico sero pathological classification of immune mediated necrotizing myopathies Zandvoort, The Netherlands, 14 16 October 2016 Yves Allenbach Andrew L. Mammen Olivier Benveniste Werner Stenzel on behalf of the Immune Mediated Necrotizing Myopathies Working Group 3 a Department of Internal Medicine, Pitie Salpetriere Hospital, AP HP Sorbonne university, Paris, France b National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, USA c Department of Neuropathology, Charite Universitatsmedizin, Berlin, Germany
A Digital Twin Method for Automated Behavior Analysis of Large Scale Distributed IoT Systems
Venue: 2019 14th Annual Conference System of Systems Engineering (SoSE)
Year: 2019

The behavior of a large scale distributed IoT system is often hard to verify and validate. The reasons include: 1) the specification is often unclear, ambiguous and incomplete resulting in misunderstandings and undesired behavior. 2) It is almost impossible for a human to reason about the correctness of a system consisting of thousands of components. 3) It is very hard to observe all related components when trying to solve a problem because the system is geographically distributed over large areas. A digital twin capturing the system operational behavior will be of great help to assist a human in detecting behavioral anomalies and reasoning about root causes. This paper proposes a method to develop digital twins for automated behavior analysis of large scale distributed IoT systems. We present a real life use case of a smart office lighting system for which the method was successfully applied. The developed digital twin was used for anomaly detection and reasoning in a semi automated root cause analysis (RCA) approach.
La robotica creativa para el desarrollo de la cultura Maker inclusiva en la ensenanza fundamental: caso Escuela Municipal de Capistrano de Abreu, en Sao Paulo, Brasil
Year: 2020

This analysis on creative robotics presents a case study in which the inclusive culture Maker is integrated into learning at the Capistrano de Abreu basic education institution, in Sao Paulo, Brazil. The strategies and educational actions based on educational planning and training for teachers are disclosed. The results and contributions of this study make suggestions for educators and school systems to achieve digital inclusion through creative robotics, the Maker movement, and elements of Design Thinking. These educational tools promote the protagonism of the student and enhance their capacities in the midst of a needy community, which mostly has little access to information technology and digital communication in their social contexts.
Surface Modification of Poly (ether ether ketone) with a Medlite C6 (ND YAG Q Switched) Skin Treatment Laser
Venue: Journal of Macromolecular Science, Part B
Year: 2019

Poly ether ether ketone (PEEK) a synthetic polymer, is expected to be useful as a biomaterial due to its appropriate mechanical, chemical, and biocompatibility properties. However, this polymer is biologically inert, requiring surface modification to improve its adhesion to bone cells for use as a bone substrate. Surface properties, such as roughness and hydrophilicity, are important factors in the adhesion of biomaterials to the surrounding tissue; therefore, in this study, laser treatment was performed for surface modification. The aim of the research described here was to investigate the effect of two laser parameters, fluency and wavelength, on the surface roughness and hydrophilicity to determine the optimum parameters for improving surface adhesion. The surface topography and average roughness (Ra) were investigated by atomic force microscopy (AFM) Surface morphology was also observed with an optical microscope, and the hydrophilicity of the surfaces was investigated with static contact angle tests. The results obtained showed that the samples treated at the wavelength of 532 nm with fluency of 8 J/cm2, compared to fluencies of 4 and 12 J/cm2, showed improved surface properties. However, in terms of radiation wavelength, the wavelength of 1064 nm at these three fluencies showed the most promising results for enhancing the surface properties of PEEK for bone implant applications.
Deep vein thrombosis
Venue: British Medical Journal
Year: 2018

What you need to know Deep vein thrombosis (DVT) commonly affects the lower limb, with clot formation beginning in a deep calf vein and propagating proximally.1 It is a common venous thromboembolic (VTE) disorder with an incidence of nearly 1.6 per 1000 inhabitants a year.234 The rate of involvement of particular sites varies: distal veins 40% popliteal 16% femoral 20% common femoral 20% and iliac veins 4%.1 Certain medical conditions listed in box 1 increase the likelihood of clot formation in the deep veins. Upper limb DVT represents less than 10% of all DVT, and central venous catheters are the main risk factor.7 Venocaval thromboses are rare and are associated with malignancy, compression, and vascular  This article provides an overview for non specialists on initial approach to patients with suspected DVT. Box 1 DVT risk factors56 Transient risk factors Persistent risk factors Unprovoked VTERETURN TO TEXT Sources and selection criteria We searched Medline and Cochrane databases for clinical trials, systematic reviews, and meta analyses relevant to the diagnosis and management of DVT. Search terms included "deep vein thrombosis,"
Optimizing Attention for Sequence Modeling via Reinforcement Learning.
Venue: IEEE transactions on neural networks and learning systems
Year: 2021

Attention has been shown highly effective for modeling sequences, capturing the more informative parts in learning a deep representation. However, recent studies show that the attention values do not always coincide with intuition in tasks, such as machine translation and sentiment classification. In this study, we consider using deep reinforcement learning to automatically optimize attention distribution during the minimization of end task training losses. With more sufficient environment states, iterative actions are taken to adjust attention weights so that more informative words receive more attention automatically. Results on different tasks and different attention networks demonstrate that our model is of great effectiveness in improving the end task performances, yielding more reasonable attention distribution. The more in depth analysis further reveals that our retrofitting method can help to bring explainability for baseline attention.
The psychological contract: A missing link between safety climate and safety behaviour on construction sites
Venue: Safety Science
Year: 2019

The relationship between safety climate and safety behaviour is well established in construction, however, the way safety plans and actions of top management translate to the workforce is still unclear. Considering the influence of supervisors' behaviour on workers' safety behaviour and conceptualizing safety through the lens of the 'Psychological Contract' (PC) it is argued that 'Psychological Contract of Safety' (PCS) could be a vital factor to explain how workers attach meaning to supervisor behaviour at construction sites and prioritise safety issues. Previous research suggests that (1) safety climate is based on perception of workers regarding safety and (2) PCS is based on perceived mutual obligations between workers and supervisors. As a result, if PCS or mutual obligations between workers and supervisors are fulfilled, then safety behaviour of the workers will be positively influenced. A model depicting the PCS as an alternative intervention in understanding how safety climate factors influence workers' safety behaviour is presented. Using Structural Equation Modelling (SEM) the model of the PCS is validated. The model explains how construction safety is influenced by the mutual safety obligations between supervisor and workers.
Orthognathic surgery with two segment le fort i and sagittal split ramus osteotomies of open bite deformity in an amelogenesis imperfecta patient via virtual planning: A case report
Venue: Nigerian journal of clinical practice
Year: 2020

Amelogenesis imperfecta (AI) is an enamel defect and is often associated with the anterior open bite (AOB) and transverse maxillary deficiency. It is known that in such cases when AI and AOB appeared together, posterior maxillary impaction with or without bilateral mandibular ramus osteotomies is a frequently preferred treatment option. Virtual planning is more reliable rather than the conventional model surgery planning, especially for complicated cases. Usage area of virtual 3D anatomical models reconstructed from Cone Beam Computed Tomography (CBCT) data is expanding day by day for both diagnosis and surgical planning. The aim of this study is to present a patient with AI and AOB and transverse maxillary deficiency and management of this case with virtually planned two segment Le fort I and sagittal split ramus osteotomies followed by prosthetic rehabilitation.
A Computational Approach with Biological Evaluation: Combinatorial Treatment of Curcumin and Exemestane Synergistically Regulates DDX3 Expression in Cancer Cell Lines
Venue: Biomolecules
Year: 2020

DDX3 belongs to RNA helicase family that demonstrates oncogenic properties and has gained wider attention due to its role in cancer progression, proliferation and transformation. Mounting reports have evidenced the role of DDX3 in cancers making it a promising target to abrogate DDX3 triggered cancers. Dual pharmacophore models were generated and were subsequently validated. They were used as 3D queries to screen the InterBioScreen database, resulting in the selection of curcumin that was escalated to molecular dynamics simulation studies. In vitro anti cancer analysis was conducted on three cell lines such as MCF 7, MDA MB 231 and HeLa, which were evaluated along with exemestane. Curcumin was docked into the active site of the protein target (PDB code 2I4I) to estimate the binding affinity. The compound has interacted with two key residues and has displayed stable molecular dynamics simulation results. In vitro analysis has demonstrated that both the candidate compounds have reduced the expression of DDX3 in three cell lines. However, upon combinatorial treatment of curcumin (10 and 20 mM) and exemestane (50 mM) a synergism was exhibited, strikingly downregulating the DDX3 expression and has enhanced apoptosis in three cell lines. The obtained results illuminate the use of curcumin as an alternative DDX3 inhibitor and can serve as a chemical scaffold to design new small molecules.
Clique percolation
Venue: Random Struct. Algorithms
Year: 2009

Derenyi, Palla and Vicsek introduced the following dependent percolation model, in the context of finding communities in networks. Starting with a random graph G generated by some rule, form an auxiliary graph G whose vertices are the k cliques of G, in which two vertices are joined if the corresponding cliques share k 1 vertices. They considered in particular the case where G G(n, p) and found heuristically the threshold function p p(n) above which a giant component appears in G. Here we give a rigorous proof of this result, as well as many extensions. The model turns out to be very interesting due to the essential global dependence present in G. 1 Cliques sharing vertices Fix k 2 and 1 l k 1. Given a graph G, let G be the graph whose vertex set is the set of all copies of Kk in G, in which two vertices are adjacent if the corresponding copies of Kk share at least l vertices. Starting from a random graph G G(n, p) our aim is to study percolation in the corresponding graph G p i.e. to find for which values of p there is a 'giant' component in G k,l p containing a positive fraction of the vertices of G p For l k 1, this question was proposed by Derenyi, Palla and Vicsek  motivated by the study of 'communities' in real world networks, but independent of the motivation, we consider it to be an extremely natural question in the theory of random graphs. Indeed, it is perhaps the most natural example of dependent percolation arising out of the model G(n, p) As we shall see in a moment, it is not too hard to guess the answer; simple heuristic derivations based on the local analysis of G p were given in  and by Palla, Derenyi and Vicsek  (For a survey of related work see  Note, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge CB3 0WB, UK University of Memphis, Memphis TN 38152, USA Research supported in part by NSF grants DMS 0505550, CNS 0721983 and CCF0728928, and ARO grant W911NF 06 1 0076 Mathematical Institute, University of Oxford, 24 29 St Giles' Oxford OX1 3LB, UK
An Empirical Investigation on Ownership Characteristics, Activities of the Audit Committee, and Audit Fees in Companies Listed on Indonesia Stock Exchange
Year: 2015

This study examines the effect of ownership characteristics and activities of the audit committee to audit fee. This study also uses control variables which include free cash flow, liquidity ratios, profitability ratios, solvency ratios, firm size, market to book value of equity, and audits quality of manufacture companies in Indonesia Stock Exchange in the year 2010 2012 are used as the population in this study. Data collection method used was purposive sampling. The statistical methods used to analyze the data are the multiple linear regression and results obtained indicate that managerial ownership, audit committee activity, firm size, liquidity ratios, profitability ratios affect audit fees. Meanwhile, institutional ownership, free cash flow, solvency ratio, and market to book value of equity do not affect the audit fees significantly.
MEC Empowered Non Terrestrial Network for 6G Wide Area Time Sensitive Internet of Things
Venue: ArXiv
Year: 2021

In the upcoming sixth generation (6G) era, the demand for constructing a wide area time sensitive Internet of Things (IoT) keeps increasing. As conventional cellular technologies are hard to be directly used for wide area timesensitive IoT, it is beneficial to use non terrestrial infrastructures including satellites and unmanned aerial vehicles (UAVs) where a non terrestrial network (NTN) can be built under the cell free architecture. Driven by the timesensitive requirements and uneven distribution of IoT devices, the NTN is required to be empowered by mobile edge computing (MEC) while providing oasis oriented on demand coverage for the devices. Nevertheless, communication and MEC systems are coupled with each other under the influence of complex propagation environment in the MECempowered NTN, which makes it hard to orchestrate the resources. In this paper, we propose a process oriented framework to design the communication and MEC systems in a time division manner. Under this framework, the largescale channel state information (CSI) is used to characterize the complex propagation environment with an affordable cost, where a non convex latency minimization problem is formulated. After that, the approximated problem is given and it can be decomposed into subproblems. These subproblems are further solved in an iterative way. Simulation results demonstrate the superiority of the proposed process oriented scheme over other algorithms. These results also indicate that the payload deployments of UAVs should be appropriately predesigned to improve the efficiency of resource use. Furthermore, the results imply that it is advantageous to integrate NTN with MEC for wide area time sensitive IoT. Index Terms Cell free, mobile edge computing, non terrestrial networks, sixth generation, wide area time sensitive IoT.
The neo.nEURO.network Hypothermia Randomized Controlled Trial
Venue: Pediatrics
Year: 2010

In this issue of Pediatrics Simbruner et al1 report results of the neo.nEURO.network study of hypothermia for infants with hypoxic ischemic encephalopathy (HIE) They enrolled infants of =36 weeks' gestational age with clinical and electrophysiological evidence of HIE and randomly assigned them to targeted temperature reduction (33.5degC rectal temperature [range: 33degC 34degC] or a control group (37degC rectal temperature [range: 36.5degC 37.5degC] The study design shared features with previously published trials of this intervention; entry criteria were those of the CoolCap trial,2 target temperature was identical to that of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)3 and Total Body Hypothermia (TOBY)4 trials, and a manually controlled cooling blanket (Tecotherm TS 200 [Tec Com, Munich, Germany] was used as it was in the TOBY trial. All the trials, including the neo.nEURO.network trial, maintained targeted temperature for 72 hours followed by rewarming at a rate of =0.5degC/hour. The neo.nEURO.network used morphine in both study arms; the TOBY trial used sedation for distressed infants, but the percentage of infants so treated was not reported.4 The primary outcome of death or Address correspondence to Abbot R. Laptook, MD, Department of Pediatrics, Women Infants Hospital of Rhode Island, 101 Dudley St, Suite 1100, Providence, RI 02905. E mail: alaptook{at}wihri.org
Commentary: What makes a life go well? Moral functioning and quality of life measurement in neurodevelopmental disorders reflections on Jonsson et al. (2017)
Venue: Journal of child psychology and psychiatry, and allied disciplines
Year: 2017

Jonsson et al.'s excellent review of the literature on quality of life (QoL) and childhood mental and behavioural disorders (Jonsson et al. highlights the need for studies that utilise child self reported QoL, in contrast to parent or proxy QoL measures, and further challenges the field to develop QoL measures that 'put the child's own views and priorities first'