nils-herrmann/clean_scirepeval huggingface dataset:
Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime
Venue: 2018 21st International Conference on Intelligent Transportation Systems (ITSC)
Year: 2018

This work addresses the problem of semantic image segmentation of nighttime scenes. Although considerable progress has been made in semantic image segmentation, it is mainly related to daytime scenarios. This paper proposes a novel method to progressive adapt the semantic models trained on daytime scenes, along with large scale annotations therein, to nighttime scenes via the bridge of twilight time the time between dawn and sunrise, or between sunset and dusk. The goal of the method is to alleviate the cost of human annotation for nighttime images by transferring knowledge from standard daytime conditions. In addition to the method, a new dataset of road scenes is compiled; it consists of 35,000 images ranging from daytime to twilight time and to nighttime. Also, a subset of the nighttime images are densely annotated for method evaluation. Our experiments show that our method is effective for knowledge transfer from daytime scenes to nighttime scenes, without human annotation.
The Dynamics of Youth Radicalisation in Africa Reviewing the Current Evidence
Year: 2016

Youth radicalisation towards violent extremism is a global phenomenon that threatens peace, security and stability. This paper reviews the evidence on the factors that may contribute to the dynamics of youth radicalisation. Available findings from East Africa and the Horn of Africa, West Africa and the Sahel, and North Africa are used to understand the dynamics that may contribute to radicalisation and, potentially, to violent extremism. Many factors emerge including political, economic, social and individual factors. Religion, identity and gender also arise as topics for further analysis. Youth radicalisation is a complex phenomenon that cannot be attributed to any one explanation or set of factors. This paper recognises these complexities, offers recommendations and identifies additional issues that should be explored further.
A randomized construction of high girth regular graphs
Venue: Random Struct. Algorithms
Year: 2021

We describe a new random greedy algorithm for generating regular graphs of high girth: Let $k\geq 3$ and $c \in (0,1) be fixed. Let $n \in \mathbb{N} be even and set $g c \log_{k 1} (n) Begin with a Hamilton cycle $G$ on $n$ vertices. As long as the smallest degree \delta (G)<k$ choose, uniformly at random, two vertices $u,v \in V(G) of degree \delta(G) whose distance is at least $g 1$ If there are no such vertex pairs, abort. Otherwise, add the edge $uv$ to $E(G) We show that with high probability this algorithm yields a $k$ regular graph with girth at least $g$ Our analysis also implies that there are \left( \Omega (n) \right){kn/2} labeled $k$ regular $n$ vertex graphs with girth at least $g$
Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
Venue: ACL
Year: 2019

Many state of the art neural models for NLP are heavily parameterized and thus memory inefficient. This paper proposes a series of lightweight and memory efficient neural architectures for a potpourri of natural language processing (NLP) tasks. To this end, our models exploit computation using Quaternion algebra and hypercomplex spaces, enabling not only expressive inter component interactions but also significantly (75% reduced parameter size due to lesser degrees of freedom in the Hamilton product. We propose Quaternion variants of models, giving rise to new architectures such as the Quaternion attention Model and Quaternion Transformer. Extensive experiments on a battery of NLP tasks demonstrates the utility of proposed Quaternion inspired models, enabling up to 75% reduction in parameter size without significant loss in performance.
Tomographic reconstruction of shock layer flows
Year: 2007

The tomographic reconstruction of supersonic flows faces two challenges. Firstly, techniques used in the past, such as the direct Fourier method (DFM) (Gottlieb and Gustafsson in On the direct Fourier method for computer tomography, 1998; Morton in Tomographic imaging of supersonic flows, 1995) or various backprojection (Kak and Slaney in Principles of computerized tomographic imaging, vol. 33 in Classics in Applied Mathematics, 2001) techniques, have only been able to reconstruct areas of the flow which are upstream of any opaque objects, such as a model. Secondly, shock waves create sharp discontinuities in flow properties, which can be difficult to reconstruct both in position and in magnitude with limited data. This paper will present a reconstruction method, matrix inversion using ray tracing and least squares conjugate gradient (MI RLS) which uses geometric ray tracing and a sparse matrix iterative solver (Paige and Saunders  1982) to overcome both of these challenges. It will be shown, through testing with a phantom object described in tomographic literature, that the results compare favourably to those produced by the DFM technique. Finally, the method will be used to reconstruct three dimensional density fields from interferometric shock layer images, with good resolution (Faletic in Tomographic reconstruction of shock layer flows, 2005)
O36: DEVELOPING A TRAUMA REGISTRY IN A MIDDLE INCOME COUNTRY BOTSWANA
Year: 2021

Botswana has a large burden of disease from injury, but no trauma registry. This study sought to design and pilot test a trauma registry at two hospitals. A cross sectional study was piloted at a tertiary hospital and a secondary level hospital in Botswana. The study consisted of two stages: stage 1 mainly involved stakeholder consultations on existing data collection tools. Stage 2 consisted of two phases: Phase I involved retrospective collection of existing data from existing data collection tools and Phase II collected data prospectively using the proposed trauma registry prototype. The pre hospital road traffic accident data is collected using hard copy forms and some of this data is transferred to a stand alone electronic registry. The hospital phase of road traffic accident data all goes into hard copy files then stored in institutional registry departments. The post hospital data is also partially stored as hard copies and some data is stored in a stand alone electronic registry. The demographics, pre hospital, triage, diagnosis, management and disposition had a high percent variable completion rate with no significant difference between phases I and II. However, the primary survey variables in Phase I had a low percent variable completion rate which was significantly different from the high completion rates in phase II at both hospitals. A similar picture was observed for the secondary survey at both hospitals. Electronic trauma registries are feasible and data completion rate is high when using the electronic data registry as opposed to data collected using the existing paper based data collection tools. Trauma registry, Injury registry, Road Traffic Accident Trauma Registry,
Lo sviluppo della motivazione attraverso un percorso di scrittura
Year: 2018

Lo scopo del mio lavoro di diploma consiste in una ricerca azione volta a studiare la componente motivazionale nell'ambito di un percorso di apprendimento dedicato alla produzione di testi descrittivi, in una classe di seconda media. Piu precisamente, l'oggetto di studio intende comprendere come alimentare la motivazione e portare gli allievi a percepire la scrittura come un'attivita positiva e stimolante e, nel contempo, come promuovere l'autoefficacia e l'autostima, attraverso lo sviluppo della consapevolezza nelle proprie competenze. Modificando la modalita di insegnamento e l'organizzazione delle attivita didattiche si vuole cosi promuovere un apprendimento motivato e autoregolato nell'acquisizione delle competenze di scrittura di testi descrittivi. Misurare il livello di motivazione comporta inevitabilmente la mancanza di una verifica empirica, non essendo possibile confrontare i risultati ottenuti. Per questo motivo questa ricercaazione si limita a determinare quali fattori il docente puo controllare e gestire nelle sue pratiche d'insegnamento, evitando un agire didattico che spesso induce alla demotivazione. Sul piano metodologico, ho scelto di raccogliere, attraverso un questionario in entrata, alcuni dati sulla motivazione personale, sulla propria autoefficacia e prassi scrittoria, per poi confrontarli con un secondo questionario in uscita. I prodotti scritti mi hanno permesso di verificare eventuali cambiamenti nelle competenze e abitudini scrittorie, volti allo sviluppo di un'autoregolazione piu consapevole e attiva. L'analisi delle prove di scrittura e dei questionari e stata focalizzata su tre allievi emblematici: in due casi e stato possibile verificare un notevole miglioramento nella pratica scrittoria e nel controllo delle proprie capacita; nel terzo ho riscontrato invece un leggero peggioramento della competenza di scrittura, ma un aumento della propria capacita di autoregolazione e della sua consapevolezza.
Christfried Jakob (1866 1956)
Venue: Journal of Neurology
Year: 2006

Bavarian born Alfons Maria Jakob (1884 1931) Professor of Neurology and Psychiatry at the University of Hamburg, after whom Jakob Creutzfeldt disease is named. Another Jakob, altogether unheeded in the English biomedical literature, is the neuropathologist Christfried (Christofredo) Jakob, 18 years senior to Alfons, also Bavarian born, and considered to be the father of Neurology in Argentina, his adopted homeland. Commanding an impressive background knowledge in philosophy, literary studies and classical music, Jakob dedicated his life to the study of unknown areas of comparative neurobiology with special emphasis on the natural history of the cerebral cortex, descriptive and pathological anatomy and neuropathology [6] psychiatry, neuropsychology [7] neurophilosophy, embryology, zoology, botany, hydrobiology, palaeontology and geography. Christfried Jakob was born on 25 December 1866 in Wornitzostheim. He studied medicine at the University of Erlangen from 1886 1890. For his thesis he studied aortitis syphilitica, under Friedrich Albert von Zenker (1825 1898) In the early 1890s he was assistant to Adolf von Strumpell (1853 1925) at Erlangen Medical Clinic and privately practised medicine in Bamberg [9, 10] Jakob published his first book in 1895, an atlas of the normal and pathological anatomy of the nervous system  with lithographs and woodcuts made from original drawings and photographs, and cross sections of the brain showing different layers with the aid of superimposed flaps. The book was duly translated into English, Russian, French and Italian and went through a second edition in 1899. In 1897 Jakob published an atlas of methods of clinical investigation  an epitome of internal medicine, which was also translated into French and English. In 1899, through the mediation of Domingo Cabred (1859 1929) the Argentinian Professor of Psychiatry, Jakob went to Argentina to direct the Laboratory of the Psychiatric and Neurological Clinic of Hospicio de las Mercedes at the University of Buenos Aires [9, 10] He was attracted by the prospect of collecting 300 brains per year for pathoanatomical study, as opposed to 2 3 brains he had access to in Germany. His three year contract was later extended until 1910. For a dozen years, Jakob produced works in anatomy [4, 5, 8] neurology, psychopathology and anthropology  Lazaros C. Triarhou Manuel del Cerro Christfried Jakob (1866 1956)
Z scheme Bi2WO6/CuBi2O4 heterojunction mediated by interfacial electric field for efficient visible light photocatalytic degradation of tetracycline
Venue: Chemical Engineering Journal
Year: 2019

In order for the removal of Tetracycline (TC) in wastewaters, an efficient binary Bi2WO6/CuBi2O4 Z scheme heterojunction photocatalyst was synthesized by loading Bi2WO6 (BWO) nanoparticles on CuBi2O4 (CBO) nanorods via a solvothermal route. The obtained Bi2WO6/CuBi2O4 composite displays photocatalytic activity for TC degradation more than five times higher than that for pure CBO nanorods. The recycling experiment shows that over 91% of TC can be photo degraded by the optimal Bi2WO6/CuBi2O4 photocatalyst within 60 min even after four cycles. Results of SEM, transient photocurrent response, EIS measurement prove that solvothermal process for BWO loading can introduce rough surface with high density negative charge on CBO, contributing to effective photo induced carrier transfer. XPS, Mott Schottky plots and PL spectra reveal that the loading of BWO as well as interfacial charge redistribution can induce the formation of interfacial electric field for Z scheme heterojunction, contributing to the high oxidation and reduction capabilities ability of Bi2WO6/CuBi2O4 composite. The study on photocatalytic mechanism discloses that hole (h+ and superoxide radical O2 are dominating reactive oxidation species (ROS) in the photodegradation process. This study has provided a novel route to fabricate Z scheme photocatalysts for effective photocatalytic degradation processes.
The importance of context sensitivity of Basic Interpersonal Communication Skills (BICS) in Content and Language Integrated Learning (CLIL) in Bilingual Education
Year: 2015

National Education Commission proposed Bilingual Education to the national curriculum in 2003. One of the main objectives of this introduction is to improve the second Language proficiency of learners. The Ministry of Education in collaboration with the National Institute of Education is designing a model based on CLIL; a widely used learning teaching approach in bilingual education, to suit the Sri Lankan context. Cummins (1981) claims two language proficiencies that are necessary in improving the bilingual learner's second language proficiency; BICS (Basic Interpersonal Communication Skills) and Cognitive Academic Language Proficiency (CALP) BICS is an informal day today language that learners acquire when exposed to an acquisition rich environment while CALP refers to the use of academic language in formal learning teaching contexts. Cummins claim that BICS lays the foundation for CALP. The objective of this paper is to examine Cummins' BICS in relation to Bilingual Education in Sri Lankan context. This analysis is based on interviews held with a purposive sample of bilingual teachers and teachers of English and observation of classrooms and content analysis of pupils textbooks. Literature relating to CLIL too was studied. Cummins' interpretation of BICS has to be modified if it is to be applied to Sri Lanka. Opportunities for the pupils to acquire BICS are not adequately available in Sri Lanka as the teachers are not well equipped with learning teaching strategies facilitating BICS .Therefore BICS should be facilitated in the formal classroom context. Text books prescribed to teach bilingually are the direct translation of monolingual textbooks designed for monolingual learners .It is recommended that teachers be trained in CLIL pedagogy and textbooks be revised. Teachers should be equipped with knowledge and skills to adapt available textbooks to facilitate BICS.
FABP4 and MMP9 levels identified as predictive factors for poor prognosis in patients with nonalcoholic fatty liver using data mining approaches and gene expression analysis
Venue: Scientific Reports
Year: 2019

Nonalcoholic fatty liver (NAFLD) may progress to nonalcoholic steatohepatitis (NASH) and ultimately to cirrhosis and hepatocellular carcinoma (HCC) Prognostic markers for these conditions are poorly defined. The aim of this study was to identify predictive gene markers for the transition from NAFL to NASH and then to poorer conditions. Gene expression omnibus datasets associated with a prediction analysis algorithm were used to create a matrix composed of control subject (n 52) healthy obese (n 51) obese with NAFL (n 42) and NASH patients (n 37) and 19,085 genes in order to identify specific genes predictive of the transition from steatosis to NASH and from NASH to cirrhosis and HCC and thus patients at high risk of complications. A validation cohort was used to validate these results. We identified two genes, fatty acid binding protein 4 (FABP4) and matrix metalloproteinase 9 (MMP9) which respectively allowed distinguishing patients at risk of progression from NAFL to NASH and from NASH to cirrhosis and HCC. Thus, NAFL patients expressing high hepatic levels of FABP4 and NASH patients expressing high hepatic levels of MMP9 are likely to experience disease progression. Therefore, using FABP4 and MMP9 as blood markers could help to predict poor outcomes and/or progression of NAFL during clinical trial follow up.
KEPLER: A Unified Model for Knowledge Embedding and Pre trained Language Representation
Venue: Transactions of the Association for Computational Linguistics
Year: 2021

Pre trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relational facts in knowledge graphs (KGs) with informative entity embeddings, but conventional KE models cannot take full advantage of the abundant textual information. In this paper, we propose a unified model for Knowledge Embedding and Pre trained LanguagERepresentation (KEPLER) which can not only better integrate factual knowledge into PLMs but also produce effective text enhanced KE with the strong PLMs. In KEPLER, we encode textual entity descriptions with a PLM as their embeddings, and then jointly optimize the KE and language modeling objectives. Experimental results show that KEPLER achieves state of the art performances on various NLP tasks, and also works remarkably well as an inductive KE model on KG link prediction. Furthermore, for pre training and evaluating KEPLER, we construct Wikidata5M1 a large scale KG dataset with aligned entity descriptions, and benchmark state of the art KE methods on it. It shall serve as a new KE benchmark and facilitate the research on large KG, inductive KE, and KG with text. The source code can be obtained from https:/github.com/THU KEG/KEPLER.
Self Regression Learning for Blind Hyperspectral Image Fusion Without Label
Venue: ArXiv
Year: 2021

Hyperspectral image fusion (HIF) is critical to a wide range of applications in remote sensing and many computer vision applications. Most traditional HIF methods assume that the observation model is predefined or known. However, in real applications, the observation model involved are often complicated and unknown, which leads to the serious performance drop of many advanced HIF methods. Also, deep learning methods can achieve outstanding performance, but they generally require a large number of image pairs for model training, which are difficult to obtain in realistic scenarios. Towards these issues, we proposed a self regression learning method that alternatively reconstructs hyperspectral image (HSI) and estimate the observation model. In particular, we adopt an invertible neural network (INN) for restoring the HSI, and two fully connected network (FCN) for estimating the observation model. Moreover, SoftMax nonlinearity is applied to the FCN for satisfying the non negative, sparsity and equality constraints. Besides, we proposed a local consistency loss function to constrain the observation model by exploring domain specific knowledge. Finally, we proposed an angular loss function to improve spectral reconstruction accuracy. Extensive experiments on both synthetic and real world dataset show that our model can outperform the state of the art methods.
Dilemas eticos en la investigacion cientifica desde la mirada de investigadores nacionales de una universidad privada en Mexico
Year: 2017

espanolEste trabajo se sustenta en lo afirmado por muchos filosofos contemporaneos (Morin, 2006; Lonergan, 1999) acerca del error de la modernidad al separar conocimiento y etica. De manera que toda investigacion deberia implicar un compromiso etico para que las universidades respondan a las necesidades y desafios del mundo globalizado, desde sus principales funciones sustantivas. Una forma de regular el trabajo de investigacion desde la etica son los codigos deontologicos, sin embargo algunos investigadores a pesar de estos codigos se enfrentan a dilemas eticos en el ejercicio de su profesion como investigadores. Este estudio se realizo con el objetivo de conocer la percepcion de los investigadores acerca de la relacion entre etica profesional, codigos deontologicos y dilemas eticos que surgen en el proceso de investigacion, asi como las conductas eticamente inaceptables en las distintas disciplinas del conocimiento. Para ello se aplicaron entrevistas semiestructuradas a un grupo de academicos miembros del Sistema Nacional de Investigadores (SNI) en Mexico, quienes trabajan en una universidad privada del Estado de Puebla. EnglishThis work is based on the assertions of many contemporary philosophers (Morin, 2006; Lonergan, 1999) about the mistake of modernity in separating knowledge and ethics. Any investigation should involve an ethical commitment in order for universities to meet the needs and challenges of the globalized world based on their main substantive functions. One way to regulate the research from the ethical perspective are codes of conduct, however some researchers despite these codes are faced with ethical dilemmas in the exercise of their profession as researchers. This study was conducted with the aim of knowing the perception of researchers about the relationship between professional ethics, codes of conduct and ethical dilemmas that arise in the research process, as well as ethically unacceptable conducts in different disciplines of research. In order to do so semi structured interviews were applied to a group of academic members of the National Research System (SNI) in Mexico, who work at a private university in the State of Puebla.
Rainfall integrated traffic speed prediction using deep learning method
Year: 2017

Traffic information prediction is one of the most essential studies for traffic research, operation and management. The successful prediction of traffic speed is increasingly significant for the benefits of both road users and traffic authorities. However, accurate prediction is challenging, due to the stochastic feature of traffic flow and shallow model structure. Furthermore, environmental factors, such as rainfall influence, should also be incorporated to improve accuracy. Inspired by deep learning, this paper investigates the performance of deep belief network (DBN) and long short term memory (LSTM) to conduct short term traffic speed prediction with the consideration of rainfall impact as a non traffic input. The deep learning models have the ability to learn complex features of traffic flow pattern under various rainfall conditions. To validate the performance of rainfall integrated DBN and LSTM, the traffic detector data from an arterial in Beijing are utilised for model training and testing. The experiment results indicate that with the combination input of speed and additional rainfall data, deep learning models have better prediction accuracy over other existing models, and also yields improvements over the models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic speed data.