nils-herrmann/clean_scirepeval huggingface dataset:
Offloading in Cloud and Fog Hybrid Infrastructure Using iFogSim
Venue: 2020 10th International Conference on Cloud Computing, Data Science Engineering (Confluence)
Year: 2020

The information and communication technology has witnessed unprecedented changes with the introduction of IoT and the implementation of IoT applications is mainly dependant on cloud services like compute, storage, networking, etc. Fog computing has been introduced as a complement to the cloud infrastructure because in near future demands of the IoT devices will exceed the capabilities of the cloud. Our work focuses on the efficient utilization of the Cloud Fog resources by distributing the application modules among Fog devices and cloud data centers. Placing the application modules on Fog devices improves performance parameters like response time, latency, energy consumption, etc. We have proposed two load balancing algorithms whose performance has been evaluated on the iFogSim simulator and their performance has been compared with the cloud only approach. Our approach is generic which can be used in the vast majority of IoT applications.
Contextual understanding of microservice architecture: current and future directions
Venue: SIAP
Year: 2018

Current industry trends in enterprise architectures indicate movement from Service Oriented Architecture (SOA) to Microservices. By understanding the key differences between these two approaches and their features, we can design a more effective Microservice architecture by avoiding SOA pitfalls. To do this, we must know why this shift is happening and how key SOA functionality is addressed by key features of the Microservice based system. Unfortunately, Microservices do not address all SOA shortcomings. In addition, Microservices introduce new challenges. This work provides a detailed analysis of the differences between these two architectures and their features. Next, we describe both research and industry perspectives on the strengths and weaknesses of both architectural directions. Finally, we perform a systematic mapping study related to Microservice research, identifying interest and challenges in multiple categories from a range of recent research.
[Effect of acupuncture at the anterior oblique parietotemporal line on gray matter remodeling in patients with hemiplegia of cerebral infarction]
Venue: Zhen ci yan jiu Acupuncture research
Year: 2020

To observe the intervention effect of acupuncture at the anterior oblique parietotemporal line on gray matter remodeling in patients with hemiplegia of cerebral infarction based on voxel based morphology (VBM) and to reveal the advantages and central effect sites of scalp acupuncture for hemiplegia of cerebral infarction.  A total of 18 patients with hemiplegia of cerebral infarction in the right basal ganglia and 18 healthy subjects were enrolled and T1 structural scan was performed. The patients were randomly divided into scalp acupuncture group and non scalp acupuncture group, with 9 patients in each group. SPSS20.0 was used to analyze the degree of neurological deficit (NIHSS) before and after treatment, and SPM8 software package was used to compare the change in gray matter after treatment between the two groups, the difference in gray matter between patients and healthy subjects.  After treatment, the scalp acupuncture group had a significant reduction in NIHSS (P<0.05) while the non scalp acupuncture group had no significant change in NIHSS (P>0.05) the scalp acupuncture group had a significantly lower NIHSS than the non scalp acupuncture group after treatment (P<0.05) Compared with the healthy subjects, the patients with cerebral infarction had a voxel increase of gray matter in the bilateral cerebellum; after 2 weeks of treatment, the scalp acupuncture group had a voxel increase of gray matter in the motor related cortex (such as the cerebellum, the anterior cingulate, the basal nucleus, and the medial frontal gyrus) and some parts of the sensory cortex, while the non scalp acupuncture group had a slight voxel increase of gray matter in few brain regions which were not associated with motor. After treatment, the scalp acupuncture group had a voxel increase in the brain regions of the basal ganglia, mainly the lenticular nucleus and the claustrum. Compared with the non scalp acupuncture group after treatment, the scalp acupuncture group had a greater gray matter increase in the brain regions mainly in the bilateral cerebellar cortex.  Acupuncture at the anterior oblique parietotemporal line can promote neurological function recovery in patients with hemiplegia, possibly by promoting gray matter remodeling in the motor centers of the extrapyramidal system (mainly the bilateral cerebellum and the contralateral basal ganglia) and some parts of the sensory cortex and inducing functional compensation in corresponding brain regions.
Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity.
Venue: Cell reports
Year: 2014

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre and post neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.
Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks
Year: 2020

The volatility of wind power generations could significantly challenge the economic and secure operation of combined electricity and heat networks. To tackle this challenge, this paper proposes a framework of optimal dispatch with distributed electric heating storage based on a correlation based long short term memory prediction model. The prediction model of distributed electric heating storage is developed to model its behavior characteristics which are obtained by the auto correlation and correlation analysis with external factors including weather and time of use price. An optimal dispatch model of combined electricity and heat networks is then formulated and resolved by a constraint reduction technique with clustering and classification. Our method is verified through numerous simulations. The results show that, compared with the state of the art techniques of support vector machine and recurrent neural networks, the mean absolute percentage error with the proposed correlation based long short term memory can be reduced by 1.009 and 0.481 respectively. Compared with conventional method, the peak wind power curtailment with dispatching distributed electric heating storage is reduced by nearly 30% and 50% in two cases respectively.
The unsung benefits of wholesale competition to electric utility customers who forgo retail competition
Year: 2017

Electricity deregulation came in two parts: wholesale and retail. While wholesale competition has lowered system costs, the verdict on retail choice is less certain. Some customers enjoying the benefits of competition in certain retail choice states are, ironically, those who do not choose a third party supplier. As can be seen in case studies from Illinois and Maryland, these 'default' utility customers benefit from use of best practices in competitive procurement
Democratic Education for Hope: Contesting the Neoliberal Common Sense
Venue: Studies in Philosophy and Education
Year: 2019

This paper provides a reinterpretation of Paulo Freire's philosophy of hope and suggests that this interpretation may function as a fruitful ground for democratic education that aims to contest the prevailing neoliberal 'common sense' The paper defines hope as a democratic virtue required for resisting the discursive practises and affective mechanisms associated with the contemporary neoliberal ethos those, which Carlos Alberto Torres characterizes as the "neoliberal common sense" and Lauren Berlant as "cruel optimism" Conclusively, the paper constructs three principles for democratic education 'history as possibility' 'the ethics of intervention' and 'democratization' which are intended to function as a foundation for democratic education through which the virtue of hope can be fostered. These principles are argued to form a basis for reviving the political dimensions of education and thus allowing collective transformative action.
Cross View Semantic Segmentation for Sensing Surroundings
Venue: IEEE Robotics and Automation Letters
Year: 2020

Sensing surroundings plays a crucial role in human spatial perception, as it extracts the spatial configuration of objects as well as the free space from the observations. To facilitate the robot perception with such a surrounding sensing capability, we introduce a novel visual task called Cross view Semantic Segmentation as well as a framework named View Parsing Network (VPN) to address it. In the cross view semantic segmentation task, the agent is trained to parse the first view observations into a top down view semantic map indicating the spatial location of all the objects at pixel level. The main issue of this task is that we lack the real world annotations of top down view data. To mitigate this, we train the VPN in 3D graphics environment and utilize the domain adaptation technique to transfer it to handle real world data. We evaluate our VPN on both synthetic and real world agents. The experimental results show that our model can effectively make use of the information from different views and multi modalities to understanding spatial information. Our further experiment on a LoCoBot robot shows that our model enables the surrounding sensing capability from 2D image input. Code and demo videos can be found at https:/view parsing network.github.io.
Trust Management: 4th International Conference, iTrust 2006, Pisa, Italy, May 16 19, 2006, Proceedings (Lecture Notes in Computer Science)
Year: 2006

Invited Talks. Why We Need a Non reductionist Approach to Trust.  Trust as Relational Capital. A Requirements Driven Trust Framework for Secure Interoperation in Open Environments. Normative Structures in Trust Management. Gathering Experience in Trust Based Interactions. Multilateral Decisions for Collaborative Defense Against Unsolicited Bulk E mail. Generating Predictive Movie Recommendations from Trust in Social Networks. Temporal Logic Based Specification and Verification of Trust Models. Modelling Trade and Trust Across Cultures. Estimating the Relative Trustworthiness of Information Sources in Security Solution Evaluation. Trust Based Route Selection in Dynamic Source Routing. Implementing Credential Networks. Exploring Different Types of Trust Propagation.  A Trust Based Reputation Service for Virtual Organization Formation. A Versatile Approach to Combining Trust Values for Making Binary Decisions.  A Scalable Incentive Based Architecture for Improving Rating Quality. Virtual Fingerprinting as a Foundation for Reputation in Open Systems. Towards Automated Evaluation of Trust Constraints. Provision of Trusted Identity Management Using Trust Credentials. Acceptance of Voting Technology: Between Confidence and Trust. B Trust: Bayesian Trust Framework for Pervasive  Towards Anonymous Trusted Authentication. The Design, Generation, and Utilisation of a Semantically Rich Personalised Model of Trust. A Trust Assignment Model Based on Alternate Actions Payoff. Privacy, Reputation, and Trust: Some Implications for Data Protection. A Reputation Based System for Confidentiality Modeling in Peer to Peer Networks. Robust Reputations for Peer to Peer Marketplaces. From Theory to Practice: Forgiveness as a Mechanism to Repair Conflicts in CMC. A Novel Protocol for Communicating Reputation in P2P Networks. A Scalable Probabilistic Approach to Trust Evaluation. Demonstration Overviews. The Agent Reputation and Trust (ART) Testbed. Trust Establishment in Emergency Case. Evaluating Trust and Authenticity with Caution. Using Jiminy for Run Time User Classification Based on Rating Behaviour.  A Trust Negotiation Based Authorization Service. The Interactive Cooperation Tournament. eTVRA, a Threat, Vulnerability and Risk Assessment Tool for eEurope.
The Effectiveness of Scrabble and Wordsearch Games to Teach Vocabulary to Students with Different Interests
Year: 2017

Many students feel difficult to memorize the vocabularies given by the teacher. Students in my school like to act like learning while playing. In fact, the teacher almost never used media in teaching and learning process.The objective of the study is to find out the effectiveness of scrabble and word search games on teaching vocabulary.The researcher applied quantitative and qualitative methods to collect the data. Quantitatively, the data were gathered through vocabulary test and questionnaire sheet. Vocabulary test was used to examine students' vocabulary achievement in the form of multiple choice and cloze test items. Questionnaire was given to the students in order to know the students' interest. Qualitatively, the observation checklist used to know level of vocabulary competence before using games.Then, I analysed the data from questionnaire and vocabulary test using t test and ANOVA.The resultsshowed that Scrabble and wordsearch games were more effective to students. Mean score of wordsearch strategy was higher than scrabble in vocabulary to high and low interest students. The last results indicated that there was no significant interaction among the teaching techniques (scrabble and word search games) interest, and students' vocabulary achievement.It can be concluded that taught by using scrabble or wordsearch was effective to high and low students. Mean score of the experimental and control class increased. There were significant both of games
Tesseract medical imaging: open source browser based platform for artificial intelligence deployment in medical imaging
Venue: Medical Imaging
Year: 2019

Artificial Intelligence (AI) is increasingly becoming a tool to enhance various medical image analysis tasks with accuracies comparable to expert clinicians. Computer assisted detection and diagnosis, and image segmentation and registration have significantly benefited from AI. However, integration of AI into the clinical workflow has been slow due to requirements for libraries that are specific to each model, and also environments that are specific to clinical centers. These challenges demonstrate the need for an AI based solution that can be integrated into any environment with minimum hardware and software overhead. Tesseract Medical Imaging (Tesseract MI) is an open source, web based platform which enables deployment of AI models while simultaneously providing standard image viewing and reporting schemes. The goal of Tesseract MI is to augment 3D medical imaging and provide a 4th dimension (AI) when requested by a user. As a case study, we demonstrate the utility of our platform and present ProstateCancer.ai, a web application for identification of clinically significant prostate cancer in MRI.
Active learning based information structure analysis of full scientific articles and two applications for biomedical literature review
Venue: Bioinform.
Year: 2013

Techniques that are capable of automatically analyzing the information structure of scientific articles could be highly useful for improving information access to biomedical literature. However, most existing approaches rely on supervised machine learning (ML) and substantial labeled data that are expensive to develop and apply to different sub fields of biomedicine. Recent research shows that minimal supervision is sufficient for fairly accurate information structure analysis of biomedical abstracts. However, is it realistic for full articles given their high linguistic and informational complexity? We introduce and release a novel corpus of 50 biomedical articles annotated according to the Argumentative Zoning (AZ) scheme, and investigate active learning with one of the most widely used ML models Support Vector Machines (SVM) on this corpus. Additionally, we introduce two novel applications that use AZ to support real life literature review in biomedicine via question answering and summarization.  We show that active learning with SVM trained on 500 labeled sentences (6% of the corpus) performs surprisingly well with the accuracy of 82% just 2% lower than fully supervised learning. In our question answering task, biomedical researchers find relevant information significantly faster from AZ annotated than unannotated articles. In the summarization task, sentences extracted from particular zones are significantly more similar to gold standard summaries than those extracted from particular sections of full articles. These results demonstrate that active learning of full articles' information structure is indeed realistic and the accuracy is high enough to support real life literature review in biomedicine. AVAILABILITY The annotated corpus, our AZ classifier and the two novel applications are available at http:/www.cl.cam.ac.uk/yg244/12bioinfo.html
Pathophysiology of hypoxic ischemic encephalopathy: a review of the past and a view on the future
Venue: Acta Neurologica Belgica
Year: 2020

Hypoxic ischemic encephalopathy, also referred as HIE, is a type of brain injury or damage that is caused by a lack of oxygen to the brain during neonatal period. The incidence is approximately 1.5 cases per 1000 live births in developed countries. In low and middle income countries, the incidence is much higher (10 20 per 1000 live births) The treatment for neonatal HIE is hypothermia that is only partially effective (not more than 50% of the neonates treated achieve an improved outcome) HIE pathophysiology involves oxidative stress, mitochondrial energy production failure, glutaminergic excitotoxicity, and apoptosis. So, in the last years, many studies have focused on peptides that act somewhere in the pathway activated by severe anoxic injury leading to HIE. This review describes the pathophysiology of perinatal HIE and the mechanisms that could be the target of innovative HIE treatments.
Describing Self Care Self Efficacy: Definition, Measurement, Outcomes, and Implications
Venue: International journal of nursing knowledge
Year: 2018

The pragmatic utility method of concept analysis was used to explore the usefulness of the concept self care self efficacy.  Empirical studies across disciplines published between 1996 and 2015 were used as data.  A data matrix was developed. Analytical questions and responses were derived from the data to understand patterns, develop new knowledge and achieve synthesis.  Usefulness of the concept is contingent on how it is defined and measured. Self care self efficacy is associated with performance of self care activities and positive health outcomes in diverse populations.  Research can guide development of targeted interventions to increase patients' self care self efficacy, thus reducing costs, and assisting people to achieve optimal health.
Modified hard carbon negative electrode material for lithium ion battery and preparation method for modified hard carbon negative electrode material
Year: 2012

The invention discloses a modified hard carbon negative electrode material for a lithium ion battery and a preparation method for the modified hard carbon negative electrode material. The preparation method is simple and feasible, the modified hard carbon negative electrode material can be prepared through uniform mixing, pyrolysis, coating and the like, the production cost is low and the preparation method can be applied to industrial production. The modified hard carbon negative electrode material has high electrochemical properties and high lithium intercalating and separating capacity, has the first discharge specific capacity of more than 926 mAh/g, and has the first discharge specific capacity of 982 mAh/g and the first charge discharge efficiency of 93 percent in the optimal mode of execution, and is suitable for power and energy storage lithium ion batteries.
CONFINEMENT CAPACITY OF SQUARE AND CIRCULAR CONCRETE COLUMNS REINFORCED WITH PREFABRICATED CAGE REINFORCEMENT SYSTEM
Year: 2018

Prefabricated Cage System (PCS) is introduced as a new steel reinforcement system that can be used in reinforced concrete members. PCS is expected to perform as an integral system performing the functions of both longitudinal and lateral reinforcement. The proposed system is anticipated to be a superior alternative to the existing reinforcement systems in reinforced concrete members, most notably in beams and columns. PCS is fabricated by perforating hollow steel tubes or steel plates. Various methods could be used to fabricate PCS reinforcement such as; punching, cutting methods, and casting. PCS reinforcement is prefabricated off site and then placed inside the formwork eliminating the time consuming and costly labor associated with cutting, bending, and tying steel bars in traditional rebar construction. PCS can be used to reinforce almost any kind of concrete member which involves reinforcement and concrete. In this paper, six concrete columns reinforced by rebar, steel tube, and PCS of square and circular geometry are compared. It was observed that, PCS provided higher confinement to concrete than rebar reinforcement and Concrete Filled Steel Tubes (CFST)
The rhetoric of celebration in seventeenth century Venetian funerary monuments
Year: 2016

This thesis investigates seventeenth century Venetian funerary monuments as representing the Republic's celebrative imagery. Going beyond the traditional interpretation of these monuments as a display of funerary memory, a series of case studies provided in six chapters examines them as rhetorical devices which celebrated Venice and instilled subtle forms of its republican propaganda. Chapter One focuses on early seventeenth century ducal monuments and the republican ethos, scrutinising their function as ideological instruments which asserted the grandeur of Venice through their celebration of the doges. Chapter Two analyses the architectural and visual sources of the monument to Doge Giovanni Pesaro, a crucial model for later funerary monuments, focusing on the interaction between sculpture, architecture and the viewer. The comparative reading of contemporary panegyric poems of the Pesaro monument demonstrates how it was perceived as a living presence which was capable of eliciting the involvement of the viewer and gaining his or her persuasion. Monuments to the Venetian captains Caterino Cornaro and Antonio Barbaro are investigated in Chapter Three as significant examples which embody the notion of sacrifice as an act of both civic and religious piety. This forms the basis of the fabrication of the Venetian identity of the newly ennobled families and merchants through the memorials on the facades of San Moise and Santa Maria dei Derelitti which are analysed in Chapter Four. Chapters Five and Six explore Antonio Gaspari's project proposals for Doge Francesco Morosini and the Valier family, which remained unexecuted. Inspired by Roman Baroque architecture, Gaspari enhanced the aggrandisement of the ducal families to a quasi imperialist state. Nevertheless, the actual Valier monument devised by Andrea Tirali remained an indirect celebration of Venice through the celebration of the doge's achievements. The six chapters thus demonstrate how funerary monuments create a public imagery which complements the so called "myth of Venice"