nils-herrmann/clean_scirepeval huggingface dataset:
Public Perception of Solid Waste Management Practices in Nigeria: Ogun State Experience
Year: 2020

The effects of poor solid waste management practices in many developing countries have been identified in the literature. This study focuses on understanding the public perception and attitudes of people towards local waste management practices. Five Local Government Areas in Ogun State, Nigeria, were selected based on population, landmass, spatial location, and distribution. The study used a survey that looked into the socio demographics, household characteristics, and standard solid waste disposal practices at the household and municipal levels. Factors such as frequency of waste collection, presence of environmental task force/protection agency, and level of effectiveness of such task force/agency were all investigated. The study verified the impact of people's attitudes towards waste management, as well as the effects of monitoring and control on the management of waste. The results showed that significant factors such as age, income, and education levels affect the perceptions, practices, and attitudes of the people towards solid waste management. An average of 36.6% of the people in the selected local governments dispose of their solid wastes at open dumps, with the majority of the residents (54.4% still with the opinion that sanitation services are too costly and should be the prerogative of the local and state governments to carry out. These outcomes resonate that more efforts by the government and relevant stakeholders should be put into proper enforcement of environmental laws, as well as creating awareness on proper solid waste management practices in schools and public places.
Flexible wearable graphene/alginate composite non woven fabric temperature sensor with high sensitivity and anti interference
Venue: Cellulose
Year: 2019

The development of a sensitive flexible wearable temperature sensor has extraordinary significance in the field of human vital signs detection. Herein, we demonstrate a flexible temperature sensor (FTS) fitting on human skin based on non woven fabric, and it has been systematically characterized and tested for performance. The resistor type FTS integrated sodium alginate with graphene, behaved as negative temperature coefficient feature and exhibited excellent sensing performance of good sensitivity (TCR 1.5 degC 1 high accuracy of 0.1 degC, short response time (26.3 s) high stability and repeatability at the temperature range of 20.0 45.0 degC. Specially, the FTS eliminated strain and humidity interference, so that can be attached to the human body to detect skin temperature changes continuously and stably.
Surveying the Moral Landscape
Venue: Personality and social psychology review an official journal of the Society for Personality and Social Psychology, Inc
Year: 2013

We present a new six cell Model of Moral Motives that applies a fundamental motivational distinction in psychology to the moral domain. In addition to moral motives focused on the self or another, we propose two group based moralities, both communal in orientation, but reflecting distinct moral motives (Social Order/Communal Solidarity vs. Social Justice/Communal Responsibility) as well as differences in construals of group entitativity. The two group based moralities have implications for intragroup homogeneity as well as intergroup conflict. Our model challenges the conclusions of Haidt and colleagues that only conservatives (not liberals) are group oriented and embrace a binding morality. We explore the implications of this new model for politics in particular and for the self regulation versus social regulation of morality more generally.
A simple fluorescence aptasensor for gastric cancer exosome detection based on branched rolling circle amplification.
Venue: Nanoscale
Year: 2020

Exosomes are membrane nanovesicles carrying molecular information that may reflect the biological and genetic characteristics of their parent cells. Numerous studies have demonstrated the potential of exosomes as noninvasive cancer biomarkers. Hence, specific detection of cancer cell derived exosomes is of significant importance. Here, we developed a fluorescence assay for the determination of gastric cancer exosomes based on branched rolling circle amplification (BRCA) and an aptamer to target specific exosomes. The designed padlock probe was cyclized after incubation with an aptamer binding with the target exosome. BRCA was triggered by adding a second primer and the resulting long tandem double stranded DNA product was detected using SYBR Green I as the fluorescent dye. This method demonstrated a high specificity for target exosomes with a detection limit of 4.27 x 104 exosomes per mL. Moreover, plasma from gastric cancer patients was tested to verify the clinical applicability of this assay. Our results demonstrated that this aptamer based biosensor may show potential for the early diagnosis of gastric cancer.
SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline In Vitro
Venue: IEEE Geoscience and Remote Sensing Letters
Year: 2019

Lack of annotated samples greatly restrains the direct application of deep learning in remote sensing image scene classification. Although research studies have been done to tackle this issue by data augmentation with various image transformation operations, they are still limited in quantity and diversity. Recently, the advent of the unsupervised learning based generative adversarial networks (GANs) brings us a new way to generate augmented samples. However, such GAN generated samples are currently only served for training GANs model itself and for improving the performance of the discriminator in GANs internally (in vivo) It becomes a question of serious doubt whether the GAN generated samples can help better improve the scene classification performance of other deep learning networks (in vitro) compared with the widely used transformed samples. To answer this question, this letter proposes a SiftingGAN approach to generate more numerous, more diverse, and more authentic labeled samples for data augmentation. SiftingGAN extends traditional GAN framework with an Online Output method for sample generation, a Generative Model Sifting method for model sifting, and a Labeled Sample Discriminating method for sample sifting. Experiments on the well known aerial image data set demonstrate that the proposed SiftingGAN method can not only effectively improve the performance of the scene classification baseline that is achieved without data augmentation but also significantly excels the comparison methods based on traditional geometric/radiometric transformation operations.
Ficus insipida subsp. insipida (Moraceae) reveals the role of ecology in the phylogeography of widespread Neotropical rain forest tree species
Venue: Journal of biogeography
Year: 2014

To examine the phylogeography of Ficus insipida subsp. insipida in order to investigate patterns of spatial genetic structure across the Neotropics and within Amazonia. Location Neotropics.  Plastid DNA (trnH psbA; 410 individuals from 54 populations) and nuclear ribosomal internal transcribed spacer (ITS; 85 individuals from 27 populations) sequences were sampled from Mexico to Bolivia, representing the full extent of the taxon's distribution. Divergence of plastid lineages was dated using a Bayesian coalescent approach. Genetic diversity was assessed with indices of haplotype and nucleotide diversities, and genetic structure was examined using spatial analysis of molecular variance (SAMOVA) and haplotype networks. Population expansion within Amazonia was tested using neutrality and mismatch distribution tests. Results trnH psbA sequences yielded 19 haplotypes restricted to either Mesoamerica or Amazonia; six haplotypes were found among ITS sequences. Diversification of the plastid DNA haplotypes began c. 14.6 Ma. Haplotype diversity for trnH psbA was higher in Amazonia. Seven genetically differentiated SAMOVA groups were described for trnH psbA, of which two were also supported by the presence of unique ITS sequences. Population expansion was suggested for both markers for the SAMOVA group that contains most Amazonian populations.  Our results show marked population genetic structure in F. insipida between Mesoamerica and Amazonia, implying that the Andes and seasonally dry areas of northern South America are eco climatic barriers to its migration. This pattern is shared with other widespread pioneer species affiliated to wet habitats, indicating that the ecological characteristics of species may impact upon large scale phylogeography. Ficus insipida also shows genetic structure in north western Amazonia potentially related to pre Pleistocene historical events. In contrast, evident population expansion elsewhere in Amazonia, in particular the presence of genetically uniform populations across the south west, indicate recent colonization. Our findings are consistent with palaeoecological data that suggest recent post glacial expansion of Amazonian forests in the south.
Scale Free Convolutional Neural Network for Remote Sensing Scene Classification
Venue: IEEE Transactions on Geoscience and Remote Sensing
Year: 2019

Fine tuning of pretrained convolutional neural networks (CNNs) has been proven to be an effective strategy for remote sensing image scene classification, particularly when a limited number of labeled data sets are available for training purposes. However, such a fine tuning process often needs that the input images are resized into a fixed size to generate input vectors of the size required by fully connected layers (FCLs) in the pretrained CNN model. Such a resizing process often discards key information in the scenes and thus deteriorates the classification performance. To address this issue, in this paper, we introduce a scale free CNN (SF CNN) for remote sensing scene classification. Specifically, the FCLs in the CNN model are first converted into convolutional layers, which not only allow the input images to be of arbitrary sizes but also retain the ability to extract discriminative features using a traditional sliding window based strategy. Then, a global average pooling (GAP) layer is added after the final convolutional layer so that input images of arbitrary size can be mapped to feature maps of uniform size. Finally, we utilize the resulting feature maps to create a new FCL that is fed to a softmax layer for final classification. Our experimental results conducted using several real data sets demonstrate the superiority of the proposed SF CNN method over several well known classification methods, including pretrained CNN based ones.
Tableau Big Data Visualization Tool in the Higher Education Institutions for Sustainable Development Goals
Year: 2019

The purpose of this paper is to use of Tableau in HEIs to achieve the Sustainable Development Goals (SDGs) Tableau can use large data sets to analyse, visualize and share knowledge, such as: whole Egypt, HEIs, governorate, university, college, program, course, faculty members, and students to determine the demography and performance. It provides a variety of graphs, chart forms and dashboards that can assist to have a better tool in HEIs for sustainability. An analysis based on a literature review of visualization tools such as Tableau and sustainable development goals. This paper suggests that most 17 SDGs and ESDGs can be analysed, visualized and shared knowledge using Tableau. Tableau tool can be used to study the extent to which higher education institutions can be used to contribute to the achievement of sustainable development both internal and external EHEIs geographical boundaries. This paper emphasizes the application of a relevant practical underpinning to support Sustainable Development Goals (SDGs) Keywords Big Data, Visualization Tools, Tableau; HEIs, SDGs.
From Automatic Keyword Detection to Ontology Based Topic Modeling
Venue: DAS
Year: 2020

In this paper, we propose a novel, two staged system, for keyword detection and ontology driven topic modeling. The first stage specializes in keyword detection in which we introduce a novel graph based unsupervised approach called Collective Connectivity Aware Node Weight (CoCoNoW) for detecting keywords from the scientific literature. CoCoNoW builds a connectivity aware graph from a given publication text and eventually assigns weight to the extracted keywords to sort them in order of relevance. The second stage specializes in topic modeling, where a domain ontology serves as an attention map/context for topic modeling based on the detected keywords. The use of an ontology makes this approach independent of domain and language. CoCoNoW is extensively evaluated on three publicly available datasets Hulth2003, NLM500 and SemEval2010. Analysis of results reveals that CoCoNoW consistently outperforms the state of the art approaches on the respective datasets.
La Literatura Filipina en Espanol Durante la era Barroca (Philippine Literature in Spanish during the Baroque Age)
Year: 2016

This paper presents a comprehensive description of the Literature written in Spanish in the Philippine Archipelago from the 16th century to mid 18th century. Philippine literature has been divided in the 20th century by a political historiography that distinguishes between what is considered national from non national literature. Literary Criticism has not been able to build a holistic picture of Philippine Literature, as it has tended till now to create independent islands and fragmented traditions. The literature written in the Philippines during the Baroque period, together with its aesthetics, constitutes one of the most neglected of these traditions. This paper aims to enrich Philippine corpora recovering a huge heritage, composed of relaciones, poemas, loas, pasiones, sermones, doctrinas, and the first novels and narratives in the country. Being the product of an international society, the Baroque period exposes the genesis of the Philippines as exceptional culture within the global world. This is the first general study undertaken about this topic.  Historiography, Criticism, Baroque, Cronicas, Loas, Blancas de San Jose, Gaspar de San Agustin, Vicente Alemany
Respiratory syncytial virus promoted the differentiation of Th17 cells in airway microenvironment through activation of Notch 1/Delta3.
Venue: Journal of medical microbiology
Year: 2019

Respiratory syncytial virus (RSV) infection is associated with serious lung disease in infants and immunocompromised individuals and is linked to development of asthma. Infection of RSV has been shown to induce Th lymphocyte differentiation. The present study was designed to determine the effects of RSV on the expression of Notch 1 and the related mechanisms on subsequent differentiation of Th lymphocytes.  A RSV infected animal model was established and investigated at 7, 28 and 60 days post infection. Real time qPCR and Western blot were used to observe the expression levels of Notch 1 in CD4+ T cells and its five ligands in lung tissues. The methylation levels of CpG islands in autoimmune regulator (AIRE) and Notch 1 promoters were analysed by time of flight mass spectrometry. The differentiation of Th lymphocytes was assayed by real time qPCR. The distribution of JAG1 and DLL3 in the lung tissues were assayed by immunohistochemistry. The correlation between Th17 and DLL3 was analysed by simple correlation.  The results showed that RSV promoted the expression and de methylation of Notch 1 promoters in CD4+ T cells. Moreover, RSV infection promoted Th1 differentiation at day 7 and day 28; Th17 differentiation at day 7, day 28 and day 60; Th2 differentiation at day 28 and day 60. At the same time, RSV infection promoted the expression of JAG1 and DLL3. Activation of Notch 1/ DLL 3 in lungs may be associated with the differentiation of Th17 lymphocytes.  Our data showed that activation of RSV stimulated the differentiation of Th17 in airway microenvironment through activation Notch 1/DLL3, which may be associated with the occurrence and development of RSV induced asthma.
L'avenir de la chirurgie pediatrique en France la demographie des chirurgiens pediatres en formation
Year: 2011

Objectifs Faire le recensement des internes et chefs de clinique des universites assistants des hopitaux (CCA) en formation en chirurgie pediatrique et analyser les resultats en fonction des besoins de la specialite. Materiel et methodes Les donnees concernant la demographie des chirurgiens pediatres en formation ont ete recueillies par un questionnaire adresse aux internes, CCA et coordonnateurs interregionaux de la specialite, de septembre 2009 a mars 2010. Les informations suivantes ont ete recueillies nom et prenom, sexe, annee de validation du concours de l'internat ou des epreuves classantes nationales, orientation choisie en chirurgie pediatrique, le centre hospitalier universitaire (CHU) de formation durant l'internat, lieu d'exercice. Resultats Cinquante trois internes sont inscrits en diplome d'etudes specialisees complementaires (DESC) de chirurgie infantile avec une orientation urologique, viscerale, thoracique ou plastique et vingt et un en orthopedie pediatrique. Par ailleurs treize internes en DESC d'orthopedie adulte vont s'orienter vers l'orthopedie pediatrique. La repartition des internes sur le territoire montre des differences importantes entre les inter regions. Il existe 55 postes de CCA en chirurgie pediatrique.  Cette etude devra servir de socle aux reflexions engagees par la Commission nationale de l'internat et du post internat. Le nombre important d'internes formes chaque annee montre l'attractivite de la chirurgie pediatrique pour les chirurgiens en formation. Il nous alerte sur la necessite d'adapter la formation des chirurgiens pediatres aux capacites de formation de notre systeme de sante et aux besoins de sante de la population francaise.
A survey on routing protocols in Wireless Sensor Networks
Venue: 2012 18th IEEE International Conference on Networks (ICON)
Year: 2012

This paper presents a survey of state of the art routing techniques in Wireless Sensor Networks (WSNs) Compared with traditional wireless networks, WSNs are characterized with denser levels of node deployment, higher unreliability of sensor nodes and severe power, computation and memory constraints. Various design challenges such as energy efficiency, data delivery models, quality of service, overheads etc. for routing protocols in WSNs are highlighted. We addressed most of the proposed routing methods along with scheme designs, benefits and result analysis wherever possible. The routing protocols discussed are classified into seven categories such as Data centric routing, Hierarchical routing, Location based routing, Negotiation based routing, Multipath based routing, Quality of Service (QoS) routing and Mobility based routing. This paper also compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation. The paper concludes with possible open research issues in WSNs.
Travel Time Dependent Maximum Entropy Inverse Reinforcement Learning for Seabird Trajectory Prediction
Venue: 2017 4th IAPR Asian Conference on Pattern Recognition (ACPR)
Year: 2017

Trajectory prediction is a challenging problem in the fields of computer vision, robotics, and machine learning, and a number of methods for trajectory prediction have been proposed. Most methods generate trajectories that move toward a goal in a straight line (goal directed) while avoiding obstacles. However, there are not only such goal directed trajectories but also trajectories that taking detours to reach the goal (non goal directed) In this paper, we propose a method of predicting such non goal directed trajectories based on the maximum entropy inverse reinforcement learning framework. Our method introduces travel time as a state of the Markov decision process. As a practical example, we apply the proposed method to seabird trajectories measured using global positioning system loggers. Experimental results show that the proposed method can effectively predict non goal directed trajectories.
Reconceptualising feedback as interactional contingent scaffolding: Improving argumentation in second language undergraduate writing: A praxiology
Year: 2018

Current conceptual models of feedback in L1 writing pedagogy advocate a dialogic approach which can encourage independence and scaffold learning effectively. This represents a departure from the monologic 'error correction' approach which is still favoured in EAP classrooms. In this thesis, a 'praxiology' (Elliott, 1991) is outlined, which draws on theoretical models from both L1 and L2 writing pedagogy and comprises theoretical principles and practical strategies for a dialogic feedback practice to support L2 writers in realising the task of argumentation in their academic writing. A dialogic feedback framework (DFF) was developed through a comprehensive practitioner inquiry with the guiding research question: how can written commentary feedback be used more effectively to improve argumentation in second language writing? This inquiry was conducted over three stages. The first stage of the inquiry comprised an examination of conceptual models and challenges of feedback, and the learning and teaching of argumentation through a review of existing literature and in two published studies I conducted. The first of these published studies evaluated the effectiveness of an interactive self evaluation essay cover sheet that I had developed. In the second published study, I explored the problems with argumentation that I identified in L2 undergraduate writing at the paragraph level, specifically in relation to the role of metadiscourse in developing an argument. In the second stage of the inquiry, I developed a proposed set of theoretical principles and strategies for a dialogic feedback practice to support L2 writers in the high task of argumentation. Feedback was re conceptualised as 'interactional contingent scaffolding' (Hammond Gibbons, 2005) through inter related elements in a supporting chain, based on Beaumont, O' Doherty and Shannon's (2011) dialogic feedback cycle, rather than as monological and corrective comment solely on current text. In an approach grounded in socio constructivism, practical strategies were framed using Ajjawi and Boud's (2017) concept of 'episodes of dialogue' These practical strategies were operationalised in two tutorial classes of a first year first semester course at one campus of an Australian university in Queensland Griffith University. Teacher and student generated data were collected through classroom observations and questionnaires, and from four case studies using a variety of instruments and methods. In the final stage of the inquiry, I used these findings to articulate the theoretical principles and practical strategies of an enhanced DFF. Qualitative and quantitative findings from this practitioner inquiry suggest that, although a dialogic and collaborative approach to feedback is unfamiliar, and therefore challenging for learners, this principled framework has pedagogic value for L2 novice writers.