26 research outputs found
The Time Course of Attentional Selection on the Basis of External Signals and Internal Representations
No full textOlivers, C.N.L. [Promotor]Theeuwes, J.L. [Promotor
Practicing the disseminary: technology lessons from Napster
No full textWhatever will happen in the way of the confluence of pedagogy and technology, it will not so much perpetuate past models in more efficient ways as it will reflect a stronger element of (for example) the unanticipated success of Napster. The author suggests a fivefold interpretation of Napster's implications as a guideline of what cybermedia do well, and how theological educators can use cybermedia to enrich their classroom teaching by distinguishing online from in-class education. Cybermedia serve best when they do not duplicate or usurp functions best accomplished in person, and personal interaction thrives when not burdened with information-transmission that might as well take place online
ツツジ科アルブトゥス亜科の花粉形態の大要とその体系学的意義
No full textSubfamily Arbutoideae (Ericaceae) comprises four genera (Arbutus, Arctostaphylos, Comarostaphylos and Ornithostaphylos) and 81 species. We have examined the pollen morphology of 17 species from three of these genera: Arbutus, Arctostaphylos, Comarostaphylos representing using light microscopy (LM) and scanning electron microscopy (SEM) and also, for selected species, transmission electron microscopy (TEM). The Arbutoideae are generally stenopalynous; the four 3-colpor(-oid)ate grains are united in compact rounded permanent tetrads. No pollen morphological characters or character combinations distinguish Arbutoideae within the Ericaceae. However, within the subfamily, Arctostaphylos and Comarostaphylos commonly have smaller pollen tetrads with a thin perforated septum, while Arbutus pollen tetrads are usually larger and characterized by thicker septum without distinct perforations. The rugulate apocolpial exine sculpture of Arctostaphylos is usually less distinct than the coarser rugulate ectexine often observed for the pollen of Arbutus and Comarostaphylos.広義のツツジ科全体の花粉形態を観察し,その体系学的意義をあきらかにする目的で,これまで科に含まれる８亜科のうちドウダンツツジ亜科,シャクジョウソウ亜科,スノキ亜科の３亜科について報告してきた,.本研究ではアルブトゥス亜科の花粉形態について報告した,.本亜科を構成する4属81種のうち3属17種の花粉サンプルを得て,その花粉形態を光学顕微鏡,走査型電子顕微鏡,透過型電子顕微鏡で観察し,先行研究の結果と併せて花粉形態の体系学的意義について検討した,.本亜科の花粉形態は均一で,３溝孔（類孔）の花粉粒４個が合着した緊密で球状の花粉四集粒を形成する,.ツツジ科の中でアルブトゥス亜科のみを特徴づけるような花粉形態形質やその組み合わせはなかった,.ウラシマツツジ属とコマロスタフィロス属の花粉サイズは小さく四集粒内隔壁は薄く穿孔があるのが普通であるが,アルブトゥス属の花粉サイズは通常大きく,四集粒内隔壁はより厚く明確な穿孔がなかった,.溝粒極域の花粉表面模様において,ウラシマツツジ属では通常は中程度の細かさのしわ模様だが,コマロスタフィロス属とアルブトゥス属ではしばしばより粗いしわ模様となる点でやや異なっていた,
オオバスノキ(ツツジ科)における四集粒花粉の個体発生
No full textThe ontogenetic development of pollen tetrads in Vaccinium smallii was investigated by light and transmission electron microscopy with special attention to the mode of exine deposition. The deposition of the primexine matrix represented by a fibrillar surface coat started during the cytokinesis of the microspore mother cell within a thick callose wall. The deposition of dark lipoidal globules of sporopollenin precursor substances was observed within the primexine matrix. After the disappearance of these globules, radially directed pro-columellae appeared within the primexine matrix, and the primexine gives rise to the tectum, columellae and foot layer after the callose dissolution. The position of future apertures was observed at a thick zone and/or a thin layer of the primexine matrix. In both regions, the pro-columellae, protectum and foot layer were not formed. Major binding mechanism of the permanent mature pollen tetrads in V. smallii is attributed to 1) the early deposition of the primexine matrix on the microspore mother cell undergoing cytokinesis, and 2) thin and tenuous callose depositions, 3) the common primexine matrix, and 4) the cytoplasmic channels between the adjoining microspores of the meiotic tetrad within a thick callose wall
Hyperglycaemia and the SOAR stroke score in predicting mortality
No full textAcknowledgements S.J.M. and T.A.A. are joint first authors. P.K.M. is the PI of both NNUSTR and ASCNES, and conceived the idea; S.D.M. and J.H.B-.S. performed data linkages; S.J.M. and T.A.A. did literature search, and cleaned and analysed the data under supervision of A.B.C.; J.F.P.D.M., M.O.B. and A.K.M. are co-I of ASCNES, and J.F.P.D.M., K.M.B. and A.K.M. are co-I of NNUSTR; and S.J.M. and P.K.M. drafted the manuscript. All authors contributed in writing the paper. P.K.M. is the guarantor. The authors gratefully acknowledge the data teams of the eight NHS Trusts which made up the ASCNES and the data team at the Norfolk and Norwich NHS Foundation Trust. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors would like to acknowledge the funders of the Anglia Stroke Clinical Network Evaluation Study (ASCNES) and the Norfolk and Norwich Stroke and TIA Register. ASCNES is funded by the National Institute for Health Research (NIHR) Research for Patient Benefit Programme (PB-PG-1208-18240). This work presents independent research funded by the NIHR under its Research for Patient Benefit (RfPB) programme (grant reference no. PB-PG-1208-18240). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The NNUH stroke and TIA register is maintained by the NNUH NHS Foundation Trust Stroke Services, and data management for this study is supported by the NNUH Research and Development Department through Research Capability Funds.Peer reviewe
Modeling and Analyzing Users\u27 Privacy Disclosure Behavior to Generate Personalized Privacy Policies
No full textPrivacy and its importance to society have been studied for centuries. While our understanding and continued theory building to hypothesize how users make privacy disclosure decisions has increased over time, the struggle to find a one-size solution that satisfies the requirements of each individual remains unsolved. Depending on culture, gender, age, and other situational factors, the concept of privacy and users\u27 expectations of how their privacy should be protected varies from person to person. The goal of this dissertation is to design and develop tools and algorithms to support personal privacy management for end-users. The foundation of this research is based on ensuring the appropriate flow of information based on a user\u27s unique set of personalized rules, policies, and principles. This goal is achieved by building a context-aware and user-centric privacy framework that applies insights from the users\u27 privacy decision-making process, natural language processing (NLP), and formal specification and verification techniques. We conducted a survey (N=401) based on the theory of planned behavior (TPB) to measure the way users\u27 perceptions of privacy factors and intent to disclose information are affected by three situational factors embodied by hypothetical scenarios: information type, recipients\u27 role, and trust source. To help build usable privacy tools, we developed multiple NLP models based on novel architectures and ground truth datasets, that can precisely recognize privacy disclosures through text by utilizing state-of-the-art semantic and syntactic analysis, the hidden pattern of sentence structure, tone of the author, and metadata from the content. We also designed a methodology to formally model, validate, and verify personalized privacy disclosure behavior based on the analysis of the users\u27 situational decision-making process. A robust model checking tool (UPPAAL) is used to represent users\u27 self-reported privacy disclosure behavior by an extended form of finite state automata (FSA). Further, reachability analysis is performed for the verification of privacy properties through computation tree logic (CTL) formulas. Most importantly, we study the correctness, explainability, usability, and acceptance of the proposed methodologies. This dissertation, through extensive amounts of experimental results, contributes several insights to the area of user-tailored privacy modeling and personalized privacy systems
Understanding the impact of information sources on COVID-19 related preventive measures in Finland
No full textThe COVID-19 pandemic amplified the influence of information reporting on human behavior, as people were forced to quickly adapt to a new health threatening situation by relying on new information. Drawing from protection-motivation and cognitive load theories, we formulated a structural model eliciting the impact of the three online information sources: (1) social media, (2) official websites, and (3) other online news sources; on motivation to adopt recommended COVID-19 preventive measures. The model was tested with the data collected from university employees and students (n = 225) in March 2020 through an online survey and analyzed using partial least square structural equation modeling (PLS-SEM). We observed that social media and other online news sources increased information overload amongst the online information sources. This, in turn, negatively affected individuals' self-isolation intention by increasing perceived response costs and decreasing response efficacy. The study highlights the role of online information sources on preventive behaviors during pandemics
The application of data mining techniques for the regionalisation of hydrological variables
No full textFlood quantile estimation for ungauged catchment areas continues to be a routine problem faced by the practising Engineering Hydrologist, yet the hydrometric networks in many countries are reducing rather than expanding. The result is an increasing reliance on methods for regionalising hydrological variables. Among the most widely applied techniques is the Method of Residuals, an iterative method of classifying catchment areas by their geographical proximity based upon the application of Multiple Linear Regression Analysis (MLRA). Alternative classification techniques, such as cluster analysis, have also been applied but not on a routine basis. However, hydrological regionalisation can also be regarded as a problem in data mining — a search for useful knowledge and models embedded within large data sets. In particular, Artificial Neural Networks (ANNs) can be applied both to classify catchments according to their geomorphological and climatic characteristics and to relate flow quantiles to those characteristics. This approach has been applied to three data sets from the south-west of England and Wales; to England, Wales and Scotland (EWS); and to the islands of Java and Sumatra in Indonesia. The results demonstrated that hydrologically plausible clusters can be obtained under contrasting conditions of climate. The four classes of catchment found in the EWS data set were found to be compatible with the three classes identified in the earlier study of a smaller data set from south-west England and Wales. Relationships for the parameters of the at-site distribution of annual floods can be developed that are superior to those based upon MLRA in terms of root mean square errors of validation data sets. Indeed, the results from Java and Sumatra demonstrate a clear advantage in reduced root mean square error of the dependent flow variable through recognising the presence of three classes of catchment. Wider evaluation of this methodology is recommended.Hydraulic EngineeringCivil Engineering and Geoscience
