nils-herrmann/clean_scirepeval huggingface dataset:
Biological function and molecular mechanism of piRNA in cancer
Venue: Practical laboratory medicine
Year: 2019

Cancer is the second leading cause of death globally. piRNAs, which are a novel type of identified small noncoding RNA (ncRNA) play a crucial role in cancer genomics. In recent years, a relatively large number of studies have demonstrated that several piRNA are aberrantly expressed in various kinds of cancers including gastric cancer, bladder cancer, breast cancer, colorectal cancer and Lung cancer and may probably serve as a novel therapeutic target and biomarker for cancer treatment. The present review summarized current advances in our knowledge of the roles of piRNAs in cancer.
Autonomous Driving without a Burden: View from Outside with Elevated LiDAR
Venue: 2019 IEEE 89th Vehicular Technology Conference (VTC2019 Spring)
Year: 2019

The current autonomous driving architecture places a heavy burden in signal processing for the graphics processing units (GPUs) in the car. This directly translates into battery drain and lower energy efficiency, crucial factors in electric vehicles. This is due to the high bit rate of the captured video and other sensing inputs, mainly due to Light Detection and Ranging (LiDAR) sensor at the top of the car which is an essential feature in autonomous vehicles. LiDAR is needed to obtain a high precision map for the vehicle AI to make relevant decisions. However, this is still a quite restricted view from the car. This is the same even in the case of cars without a LiDAR such as Tesla. The existing LiDARs and the cameras have limited horizontal and vertical fields of visions. In all cases it can be argued that precision is lower, given the smaller map generated. This also results in the accumulation of a large amount of data in the order of several TBs in a day, the storage of which becomes challenging. If we are to reduce the effort for the processing units inside the car, we need to uplink the data to edge or an appropriately placed cloud. However, the required data rates in the order of several Gbps are difficult to be met even with the advent of 5G. Therefore, we propose to have a coordinated set of LiDARaEUR(tm)s outside at an elevation which can provide an integrated view with a much larger field of vision (FoV) to a centralized decision making body which then sends the required control actions to the vehicles with a lower bit rate in the downlink and with the required latency. The calculations we have based on industry standard equipment from several manufacturers show that this is not just a concept but a feasible system which can be implemented.The proposed system can play a supportive role with existing autonomous vehicle architecture and it is easily applicable in an urban area.
What is Dramatic Recitation
Year: 2015

This article examines the literary evidence for recitations of drama in first and early second century C.E.Rome. It begins by contextualizing the practice of recitatio, and thereafter focuses on the central question of how a solo speaker could recite a play so as to render it intelligible for his audience. Two solutions suggested by extant sources are voice and gesture; it is possible that the individuals reciting plays either altered their intonation or inserted specific movements to signify a change of character. Although both of these solutions are tentative, they indicate nonetheless that dramatic recitation involved elements of performance.
A water based and metal free dye solar cell exceeding 7% efficiency using a cationic poly(3,4 ethylenedioxythiophene) derivative+
Venue: Chemical science
Year: 2020

A green, efficient and stable solar cell based only on water and safe and cheap elements of the periodic table is proposed in this work, finally consolidating (also from a sustainability viewpoint) the concept of "artificial photosynthesis" studied for decades by the scientific community. The concept of dye sensitized solar cells is re proposed here with a metal free organic dye, an iodine based electrolyte in a 100% aqueous environment and a new cathode (cationic PEDOT) synthesized for the first time with the aim of inhibiting the repulsion between the anions of redox couples and the PEDOT:PSS matrix commonly used as the counter electrode. This elegant setup leads to a record efficiency of 7.02% the highest value ever obtained for a water based solar cell and, in general, for a photovoltaic device free of both organic solvents and expensive/heavy metals.
A deep bidirectional long short term memory based multi scale approach for music dynamic emotion prediction
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2016

Music Dynamic Emotion Prediction is a challenging and significant task. In this paper, We adopt the dimensional valence arousal (V A) emotion model to represent the dynamic emotion in music. Considering the high context correlation among the music feature sequence and the advantage of Bidirectional Long Short Term Memory (BLSTM) in capturing sequence information, we propose a multi scale approach, Deep BLSTM (DBLSTM) based multi scale regression and fusion with Extreme Learning Machine (ELM) to predict the V A values in music. We achieved the best performance on the database of Emotion in Music task in MediaEval 2015 compared with other submitted results. The experimental results demonstrated the effectiveness of our novel proposed multi scale DBLSTM ELM model.
Substrate Integrated Magneto Electric Dipole Antenna for 5G Wi Fi
Venue: IEEE Transactions on Antennas and Propagation
Year: 2015

In this communication, a new technique tapered H shaped ground, is proposed to reduce the thickness of a magneto electric (ME) dipole antenna. By employing the proposed technique, the antenna height of the ME dipole antenna is reduced from 0.25 to 0.11 l0 (where l0 is the wavelength of 5.5 GHz) This new antenna structure can be easily realized by the multi layer printed circuit board (PCB) technology, which is low cost and easy to fabricate. Measured results show that this antenna has an impedance bandwidth of 18.74% for VSWR 2 (4.98 to 6.01 GHz) Stable radiation patterns with low back radiation and low cross polarization radiation are achieved across the entire operating bandwidth for 5G Wi Fi.
The diagnosis and management of rhinitis: an updated practice parameter.
Venue: The Journal of allergy and clinical immunology
Year: 2008

These parameters were developed by the Joint Task Force on Practice Parameters, representing the American Academy of Allergy, Asthma Immunology; the American College of Allergy, Asthma and Immunology; and the Joint Council of Allergy, Asthma and Immunology. The American Academy of Allergy, Asthma Immunology (AAAAI) and the American College of Allergy, Asthma and Immunology (ACAAI) have jointly accepted responsibility for establishing "The diagnosis and Management of Rhinitis: An Updated Practice Parameter." This is a complete and comprehensive document at the current time. The medical environment is a changing environment, and not all recommendations will be appropriate for all patients. Because this document incorporated the efforts of many participants, no single individual, including those who served on the Joint Task Force, is authorized to provide an official AAAAI or ACAAI interpretation of these practice parameters. Any request for information about or an interpretation of these practice parameters by the AAAAI or ACAAI should be directed to the Executive Offices of the AAAAI, the ACAAI, and the Joint Council of Allergy, Asthma and Immunology. These parameters are not designed for use by pharmaceutical companies in drug promotion.
Negative Electronic Word of Mouth in Corporate Social Responsibility Online Communication: A Case Study of a Cosmetics Company
Year: 2018

Corporate Social Responsibility (CSR) as a stakeholder oriented concept, requires companies to be interactive with stakeholders. CSR communication, therefore, is recommended to be dialogical despite their fear of negative conversations with stakeholders. This thesis aims at understanding how a cosmetics company which is well known for actively engaging in CSR handles negative eWOM in CSR online communication with consumers. The research purpose is to understand emerged negative eWOM in CSR online communication with consumers and how it is handled by the case company for dialogical communication. The theoretical framework was build combining CSR communication research and negative eWOM management research. Inductive research approach and single case study method is used in this study. This study collected and analysed computermediated data as consumers' negative feedbacks and company's responses from the company's Facebook fan page. The results of this study indicate that negative eWOM can be handled with structural and strategic approach. Different types of emerged negative eWOM were handled with different strategies which could be either responsive or non responsive. The chosen strategy acted as a guide for response construction in order for desired strategic outcomes. Responsiveness and tone of language is also important when responding to negative eWOM. Overall, the company took active participation in CSR online communication with consumers in order to solve consumers' challenges and to project its CSR reputation.
A profile of MPA students' perceptions of online learning: What MPA students value in online education and what they think would improve online learning experiences
Year: 2020

What do MPA students value in online education and what do they think would improve online learning experiences in an MPA program? Ironically, few studies have tried to derive more than a couple of factors in a single study. Integrating the key concepts from across the literature, the perceptions about an array of quality factors were identified and studied both quantitatively and qualitatively with a survey of 160 MPA students. The results distinguish and rank seven factors affecting students' perceptions of quality online education in a theoretically coherent framework. Those factors are: basic online modality, teaching presence, instructional support, interactive online modality, social presence, cognitive presence, and trust in the online teaching system. The overall impressions of online learning examined include the degree of online acceptance, the likelihood of taking online classes, and the effects of instructional skill.
STUDY OF THE ANTIBACTERIAL AND ANTIFUNGAL EFFECT OF THE TRAGOPOGON DUBIUS SCOP ASTERACEAE AQUEOUS EXTRACTS
Year: 2017

The aim of this study was to determine the antibacterial and antifungal effect of two aqueous extracts obtained from different vegetal products of Tragopogon dubius Scop. species: Tragopogoni dubiusi radix and Tragopogoni dubiusi cauli et folium. Two aqueous extracts of different concentrations were obtained and tested on three bacterial strains (Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, Streptococcus mutans identified in saliva) and one fungal strain (Candida albicans ATCC 10231) In the case of Candida albicans, none of the two tested aqueous extracts of different concentrations had any inhibitory effect, which means they are not antifungal; on the other hand, strains of Staphylococcus aureus, Escherichia coli and Streptococcus mutans are sensible to the tested extracts. The results indicate that the two tested extracts have a moderate bacteriostatic effect.
Recursos didacticos virtuales en proyectos de ciencias naturales en periodo de confinamiento por COVID 19
Year: 2020

La investigacion tiene por objetivo analizar los recursos didacticos virtuales planificados para el abordaje de proyectos educativos de ciencias naturales en periodo de confinamiento por COVID 19. Generandose un trabajo de tipo descriptivo no experimental, con una poblacion conformada por 30 docentes de la Unidad Educativa San Francisco Sales, ubicado en la Provincia de Manabi Ecuador, siendo la muestra constituida por 6 docentes quienes cumplieron con los criterios de inclusion. Los resultados se abordaron desde las areas: Recursos didacticos audiovisuales en redes sociales, Aulas virtuales, Metodo de aprendizaje, Plataformas de ciencias naturales. Los recursos didacticos virtuales proyectados por los docentes para ser implementados en el proyecto educativo de ciencias naturales, son idoneos para promover un aprendizaje significativo en los estudantes, sin embargo, es necesario contar con un proceso de capacitacion tanto para profesores como discentes con la finalidad de evitar inconvenientes que perjudiquen el aprendizaje, asi como el rendimiento escolar.
Ultra Broadband, Fabrication Tolerant Optical Coupler for Arbitrary Splitting Ratio Using Particle Swarm Optimization Algorithm
Venue: IEEE Photonics Journal
Year: 2020

This work presents a design approach of multi segment directional couplers with ultra broadband flat spectra and benign fabrication tolerance on the silicon nitride platform. Using particle swarm optimization, we optimize design parameters of multiple coupling regions and asymmetric decoupling regions in the multi segment couplers, and synthesize optimized structures for the intended power splitting ratio over optical telecommunication O, S, E, and C bands. To efficiently model the device with many structural parameters, each part of the fundamental structure is separately modelled by the most efficient method, including effective index method, coupled mode theory, and transfer matrix method to construct the high dimensional design space. By choosing a proper evaluation function, the optimized couplers achieve flat spectra with less than 2% fluctuation over ~300 nm spectrum for 50%/50%,30%/70% and 10%/90% splitting ratios, which is well verified by 3D FDTD. We also discuss performance degradation caused by fabrication variations and offer a general strategy to enhance fabrication tolerance for the broadband optical couplers with asymmetric decoupling regions.
ASEAN Child Face Recognition System with FaceNet
Year: 2019

Page 1 of 8 Abstract Current researches show that deep learning is the state of art techniques in machine learning which outperform the human level performance. It is also the popular technique which gives high accuracy in computer vision. Face recognition is one of the ongoing researches in biometric authentication and identification system. In this paper, we develop ASEAN child face recognition system using FaceNet. We use FaceNet as feature extractions, dlib as preprocessing and classifier as K Nearest Neighbors (KNN) FaceNet produces 128 embeddings per face as feature vectors and calculate Euclidean distance between faces in order to measure face similarity. The proposed system achieves state of art face recognition performance on ASEAN child face dataset with high accuracy.
Parallelizing a finite element solver in computational hemodynamics
Venue: Int. J. High Perform. Comput. Appl.
Year: 2018

In the last 20 years, a new approach has emerged to investigate the physiopathology of circulation. By merging medical images with validated numerical models, it is possible to support doctors' decision making process. The iCardioCloud project aims at establishing a computational framework to perform a complete patient specific numerical analysis, specially oriented to aortic diseases (like dissections or aneurysms) and to deliver a compelling synthesis. The project can be considered a pioneering example of a Computer Aided Clinical Trial: i.e. a comprehensive analysis of patients where the level of knowledge extracted by traditional measures and statistics is enhanced through the massive use of numerical modeling. From a computer engineering point of view, iCardioCloud faces multiple challenges. First, the number of problems to solve for each patient is significantly huge this is typical of computational fluid dynamics (CFD) and it requires parallel methods. In addition, working in a clinical environment demands efficiency as the timeline requires rapid quantitative answers (as may happen in an emergency scenario) It is therefore mandatory to employ high end parallel systems, such as large clusters or supercomputers. Here we discuss a parallel implementation of an application within the iCardioCloud project, built with a black box approach i.e. by assembling and configuring existing packages and libraries and in particular LifeV, a finite element library developed to solve CFD problems. The goal of this paper is to describe the software architecture underlying LifeV and to assess its performance and the most appropriate parallel paradigm. This paper is an extension of a previous work presented at the PBio 2015 Conference. This revision extends the description of the software architecture and discusses several new serial and parallel optimizations to the application. We discuss the introduction of hybrid parallelism in order to mitigate some performance problems previously experienced.
The Neural Correlates of Consciousness
Venue: Annals of the New York Academy of Sciences
Year: 2008

This review examines recent advances in the study of brain correlates of consciousness. First, we briefly discuss some useful distinctions between consciousness and other brain functions. We then examine what has been learned by studying global changes in the level of consciousness, such as sleep, anesthesia, and seizures. Next we consider some of the most common paradigms used to study the neural correlates for specific conscious percepts and examine what recent findings say about the role of different brain regions in giving rise to consciousness for that percept. Then we discuss dynamic aspects of neural activity, such as sustained versus phasic activity, feedforward versus reentrant activity, and the role of neural synchronization. Finally, we briefly consider how a theoretical analysis of the fundamental properties of consciousness can usefully complement neurobiological studies.
Material intelligence as a driver for value creation in IoT enabled business ecosystems
Year: 2018

The purpose of this study is to identify and discuss the role of intelligent materials in the emergence of new business models based on the Internet of Things (IoT) The study suggests new areas for further research to better understand the influences of material intelligence on the business models in industry wide service ecosystems.  The study uses data from an earlier study of intelligent materials in the steel industry networks. The insights are based on 34 qualitative interviews among 15 organizations in the industry. The data are reanalyzed for this study.  The observations from the steel industry show how material intelligence can be harnessed for value creation in IoT based business ecosystems. The results suggest that not all "things" connected to the IoT need to be intelligent, if information related to the things are collected, stored and shared for collaborative value creation among the actors involved in the business ecosystem.  The study discusses how IoT deployments allow businesses to benefit from the velocity and variety of information associated with things and guides future research to study the ways in which value is created through IoT enabled business models.  Rather than focusing on improving the efficiency of the supply network, the study presents new paths for competitive advantages in the new IoT ecosystems.  The study contributes to the mounting research on the IoT by identifying and discussing the critical aspects of how IoT can transform business models and supply networks within end to end ecosystems.
3D numerical optimisation of an asymmetric orifice in the surge tank of a high head power plant
Year: 2011

In this presented work, the results of 3D numerical investigations will be utilized to improve the 1Dnumerical calculation of water hammer and surge tanks of high head power plants. Usually, tabular values are used to quantify local head losses as a first approach. For existing high head power plants, the coefficients can be calibrated based on measurements. In a planning stage, physical laboratory tests and 3D numerical simulations provide an alternative to assess loss quantities. In case of the presented work, a 3D simulation using ANSYS CFX is carried out to calculate the local head loss coefficients. Furthermore, the investigated orifice is optimised for stationary and non stationary cases. The present investigations on an asymmetric orifice, which is located in an elbow and part of a restricted entry surge tank, have shown that the local loss coefficient for the numerical simulations is higher than the simplified theoretic approach (tabular value) The findings using a 3D numerical approach are in agreement with earlier laboratory experiments. Thus, the numerical method was applied to optimise the orifice geometry with respect to the asymmetric effects of the orifice and to minimise the construction costs.
External and internal labour flexibility in Spain: a substitute or complementary effect on firm performance?
Year: 2008

The contingent perspective in strategic human resource management maintains that it is necessary to observe the interaction between human resource practices by encouraging external and internal labour flexibility. An issue still to be resolved is whether this fit leads to a complementary or substitute effect on firm performance. In order to contribute to this debate, we examine how the relationship between external labour flexibility and firm performance is moderated by the degree of internal labour flexibility. To do this, we use the Survey on Business Strategies of the Ministry of Industry, Tourism and Trade on a sample of 1,403 Spanish industrial firms. The results show the existence of a substitute effect between the two types of labour flexibility. Using them simultaneously does not lead to greater benefits for firms.
A deep learning approach for proactive multi cloud cooperative intrusion detection system
Venue: Future Gener. Comput. Syst.
Year: 2019

The last few years have witnessed the ability of cooperative cloud based Intrusion Detection Systems (IDS) in detecting sophisticated and unknown attacks associated with the complex architecture of the Cloud. In a cooperative setting, an IDS can consult other IDSs about suspicious intrusions and make a decision using an aggregation algorithm. However, undesired delays arise from applying aggregation algorithms and also from waiting to receive feedback from consulted IDSs. These limitations render the decisions generated by existing cooperative IDS approaches ineffective in real time, hence making them unsustainable. To face these challenges, we propose a machine learning based cooperative IDS that efficiently exploits the historical feedback data to provide the ability of proactive decision making. Specifically, the proposed model is based on a Denoising Autoencoder (DA) which is used as a building block to construct a deep neural network. The power of DA lies in its ability to learn how to reconstruct IDSs' feedback from partial feedback. This allows us to proactively make decisions about suspicious intrusions even in the absence of complete feedback from the IDSs. The proposed model was implemented in GPU enabled TensorFlow and evaluated using a real life dataset. Experimental results show that our model can achieve detection accuracy up to 95%