Miracle-dz/UniFAR-FTUs huggingface dataset:
The Afterlife of “Teachers’ Beliefs”

How do articles get written in ways that lead them to keep getting cited decades later—even when they are bad or mediocre articles that do not merit re-reading? The question may seem trivial, but answering it requires us to rethink research practice and methods: Instead of particular projects and studies, or the work of individual researchers (how one conducts interviews, writes, etc.), methodology becomes a problem of assembling textlines, hooking up with viable ones, connecting some, cutting others, enfolding or highlighting particular threads, redirecting others across disciplines, and eventually putting texts in the stream, sending them downline into an afterlife in other researchers’ textwork. The present article, based on archival research, uses a detailed case study of the production and subsequent transformation and citation of an article on “teachers’ beliefs” to develop these ideas and consider the methodological implications of attending to textlines and textual afterlives.
Examining Text Enhancement Methods to Improve Look-alike Drug Name Differentiation Accuracy

The current study examined the use of several text enhancement methods with the aim of improving the accuracy of differentiating between confusing look-alike drug names. It also evaluated the influence of orthographic similarity. Although Tall Man (uppercase) lettering is recommended as a means of improving such differentiation, studies have produced mixed results on its efficacy, with other typographic styles suggested as potential alternatives. In the present study, university students (n = 40) participated in a differentiation task in which they were asked to determine whether the two drug names in each of 336 potentially confusing name pairs were the same or different. Accuracy (the proportion of correct responses) was the study outcome. The experiment adopted a two-way, within-subjects factorial design, the factors being text enhancement (Tall Man, boldface, boldface+Tall Man, colored text (red), and contrast and a lowercase control) and orthographic similarity (low, medium, and high degrees of similarity). The results showed text enhancement, orthographic similarity, and the interaction term to have significant main effects. The accuracy of each of the five text enhancement conditions was significantly greater than that of the lowercase control, and, relative to Tall Man lettering, all of the other text enhancement methods produced significantly higher degrees of accuracy. With regard to orthographic similarity, a high degree of similarity yielded the least accuracy, followed by medium and low degrees. Highlighting the primary dissimilarities between confusing drug name pairs using text enhancement methods clearly makes the names easier to differentiate, although Tall man lettering may not be the most effective such method. The results of this study demonstrate that other typographic styles have greater potential to render confusing look-alike names more visually distinct and to reduce confusion errors.
Face Alignment Assisted by Head Pose Estimation

In this paper we propose a supervised initialization scheme for cascaded face alignment based on explicit head pose estimation. We first investigate the failure cases of most state of the art face alignment approaches and observe that these failures often share one common global property, i.e. the head pose variation is usually large. Inspired by this, we propose a deep convolutional network model for reliable and accurate head pose estimation. Instead of using a mean face shape, or randomly selected shapes for cascaded face alignment initialisation, we propose two schemes for generating initialisation: the first one relies on projecting a mean 3D face shape (represented by 3D facial landmarks) onto 2D image under the estimated head pose; the second one searches nearest neighbour shapes from the training set according to head pose distance. By doing so, the initialisation gets closer to the actual shape, which enhances the possibility of convergence and in turn improves the face alignment performance. We demonstrate the proposed method on the benchmark 300W dataset and show very competitive performance in both head pose estimation and face alignment.
Distinct Recognition of Non-Clade B Human Immunodeficiency Virus Type 1 Epitopes by Cytotoxic T Lymphocytes Generated from Donors Infected in Africa

ABSTRACT We present detailed studies of human immunodeficiency virus (HIV)-specific cytotoxic T-lymphocyte (CTL) responses to clade A or C HIV type 1 in three donors infected in East Africa. We define several novel non-clade B CTL epitopes, including some restricted by HLA alleles common in Africans. Although cross-clade CTL recognition of these epitopes does occur, recognition can also be highly clade specific.
Temporal Message Ordering in Wireless Sensor Networks

Wireless sensor networks (WSN) are envisioned to fulfill com plex monitoring tasks in the near future. A typical WSN applicati on like object tracking fuses sensor readings produced by nodes thr oug out the network to obtain a high-level sensing result such as the current speed of a tracked vehicle. In order to produce corre t esults, the application typically has to process sensor even ts in the order of their occurrence at the sensor nodes. Temporal mess ag ordering ensures that sensor events arrive at the applicati on in this order. Due to the requirements and characteristics of senso r networks, temporal message ordering is a non-trivial problem i n th s environment. We motivate the need for temporal message orde ring in WSN and present an energy efficient temporal message order ing scheme for sensor networks.
Hardware support for a wireless sensor network virtual machine

Virtual Machines (VMs) have been proposed as an efficient programming model for Wireless Sensor Network (WSN) devices. However, the processing overhead required for VM execution has a significant impact on the power consumption and battery lifetime of these devices. This paper describes the design of a hardware accelerator for Mate, a VM running on TinyOS. While faster execution speed is not important in the WSN applications, reduction in the number of clock cycles for performing the same task results in the lower duty cycle, which in turn saves the power consumption. With the dedicated data path, it is expected that the numbers of clock cycles can be reduced by one to two orders of magnitude compared to the software implementation of Mate.
The Perceptions and Experiences of School Management Teams and Teachers of the Management of Physical Resources in Public Schools

The effective management of physical resources significantly impacts on the quality of teaching and learning in schools. The procurement, utilization and maintenance of physical resources through organized structures, well-designed policies and rigid processes are critical for quality education. According to the South African Schools Act 1996, a governing body is responsible for managing the school’s finances and physical assets. However, most school governing bodies seriously lack essential knowledge and skills to manage both, the finances as well as physical resources effectively, resulting in poor learner performance and low educational outcomes. We administered a structured questionnaire to investigate the management teams and teachers’ perceptions and experiences of the management of physical resources in schools. Findings revealed that many governing bodies lack the necessary financial skills to develop practical budgets and procure physical resources economically for their schools. They are unable to set-up systematic structures and stringent processes, and this has caused wasteful expenditure for schools, and the failure of teachers to maintain and productively use physical resources. Their function to constantly monitor and evaluate the procurement and maintenance of physical resources is seriously lacking. Governors who are proficient will experience very little difficulty in managing the school’s physical resources effectively.
Comment Generator-Project Report

In this work I describe the implementation of a recurrent neural network language model (RNN-LM) to solve the problem of automatic generation of logical comments for a specific context. The RNN makes use of LSTM cells to help keep long term data dependencies, improving the performance of the model. For completeness I compared the training evaluation of the LSTM cell vs the GRU cell under the same conditions. Then I discuss the reactions that the generated comments got from the Reddit community and how to improve the model in order to give it more context and understanding of sentences.
Migration and the dialogue of multiple identifications: Kurdish migrants in the tourist industry of Istanbul

This article examines the cultural dilemmas proceeding from the multiple identifications of Kurdish migrants working in the multicultural environment of Istanbul’s tourist industry. Since identifications invariably multiply when migrants enter multicultural environments, the question emerges how migrants cope with increasing identifications? How are multiple identifications related within the self? In this article, these questions are addressed, first, by analysing how Kurds explain ethnic stereotypes of themselves with reference to migration from the region of origin. Furthermore, conflicts and ambiguities between identifications as individual migrant and identifications as family member are investigated. Third, identifications of the ‘villager’ versus the ‘urbanite’ are reviewed, while, finally, the role of ‘learning’ in the migration process for Kurdish identifications will be highlighted. Dialogical self theory is used to situate the analysis of cultural dilemmas and contradictions of Kurdish migrants in Istanbul within the broader study of multiple identifications of migrants in multicultural societies.
Mapping multiple South Asian 8-bit character sets to the Unicode Standard

In this paper we discuss issues surrounding the representation of Indic writing systems in electronic documents. Having reviewed methods currently employed in the presentation of South Asian textual data on the web, we explore issues in the conversion of South Asian scripts from 8-bit to Unicode format. A range of issues are presented to outline the difficulties inherent in this task. We conclude by reporting briefly on work being undertaken to generate a tool for producing 8-bit to Unicode mappings. Issues Addressed: User Requirements cell 6, Creator Requirements cell 4, Archivist Requirements cells 1, 3 and 8.
Frail older adults and patterns of exercise engagement: understanding exercise behaviours as a means of maintaining continuity of self

In this article, we draw on data from in‐depth interviews with five men and five women, aged 71–87, who had between four and 17 chronic conditions, to explore patterns of engagement in exercise amongst frail older adults. Having experienced marked declines in their health statuses over the previous two‐year period, our participants scored low on tests of functional abilities and reported profound physical changes and concomitant social losses. Despite their grave health statuses, seven were engaged in formal exercise programmes. We use Atchley’s continuity theory of ageing to discuss the three patterns of participation in exercise across the life course that emerged in our analysis, namely, lifelong participation, lifelong non‐engagement and later‐life adoption. In all three patterns, participants’ decisions to engage or not engage in exercise reflected efforts to maintain continuities of self and valued social or physical activities. We argue that rather than simply focusing on barriers and facilitators, we need to situate older adults’ decisions regarding exercise in the context of continuities of self.
Indigenous Peoples and Radical Futures in Global Politics

Contemporary indigenous movements in global politics are energized by indigenous histories as paradoxical sites of both domination and resistance. Indigenous knowledges work as sites of indigenous epistemologies that take centuries-long subordination by a myriad of forces and turn it into a process productive of transformative politics. For indigenous peoples, this is a question of strategy of effective politics. This article examines how this strategy is made possible and how it challenges modern politics anchoring the hierarchical relations and institutions of local and global orders. It argues that historically indigenous experiences in modernity point to relations of domination and marginalization of indigenous ontologies as well as highlight the centuries-long insurrectional indigenous engagements with the modern world. The article draws on various historical and contemporary indigenous experiences—in the Americas, in Hawaii and at the United Nations—to contend that indigenous activisms in national and transnational settings offer new insights into how local and global political-economic relations and structures can be radically and constructively re-envisioned.
The Role of “Attention” in the Psychological Refractory Period

A set of experiments is described in which two consecutive signals, separated by a variable time interval, were presented to the subjects. Manual reaction times to these signals were recorded and the delays in the reactions to the second of the two signals were compared in situations where the subject was required to respond to both signals and where he was not required to respond to the first signal. The magnitude of the delays found at any particular interval were the same in both situations, and there was not much difference between cases where the two signals were in the same sense modality (visual) or in different modalities (visual, followed by auditory). These results confirm the suggestion of the writer in a previous paper that there may be a common analysing and classifying system for auditory and visual information and also illustrate a new point. It is paying attention to a signal rather than performing any overt response to it which gives rise to delays in subsequent responses.
A 2-D 8 Reasoning over networks with BioRevise and PowerGraphs

The analysis of protein interactions is a fundamental application of bioinformatics. Previous deliverables discussed the BioCham pathway analysis engine developed in the Paris group, this deliverable introduces the BioRevise systems, which integrates a non-monotonic reasoning engine orginially developed in Lisbon with the application of reasoning over metabolic pathways. We discuss examples, modelling of the networks, reasoning, and the demonstrator. Complex networks such as the metabolic networks in BioRevise require sophisticated visualisation. We develop power graph analysis, which identifies modules in networks and visualises them in a compact fashion. The theoretical basis for power graphs are the identification of bicliques and cliques in graphs. Power graphs can be applied to any network including class dependencies and UML diagrams as discussed in groups I1 and I3. The deliverable introduces an algorithm and discusses a number of bioinformatics applications for power graphs. Keyword List Reasoning, revision, conflic resolution, metabolic network, protein interaction, visualisation Project co-funded by the European Commission and the Swiss Federal Office for Education and Science within the Sixth Framework Programme.
TCR Signal Transduction in Antigen-Specific Memory CD8 T Cells1

Memory T cells are more responsive to Ag than naive cells. To determine whether memory T cells also have more efficient TCR signaling, we compared naive, effector, and memory CD8 T cells of the same antigenic specificity. Surprisingly, initial CD3 signaling events are indistinguishable. However, memory T cells have more extensive lipid rafts with higher phosphoprotein content before TCR engagement. Upon activation in vivo, they more efficiently induce phosphorylation of-LAT (linker for activation of T cells), ERK (extracellular signal-regulated kinase), JNK (c-Jun N-terminal kinase), and p38. Thus, memory CD8 T cells do not increase their TCR sensitivity, but are better poised to augment downstream signals. We propose that this regulatory mechanism might increase signal transduction in memory T cells, while limiting TCR cross-reactivity and autoimmunity.
Relevance to the Rescue: Can “Smart Ads” Reduce Negative Response to Online Ad Clutter?

Search-engine marketing, sponsored-links services, and smart advertisements provide information relevant to content being consumed at any moment by an Internet user. Can they alleviate negative reactions to ad clutter on Web sites? We investigated whether or not relevance of such ads moderates negative effects of ad clutter on consumers' attitudes toward ads and Web sites. All subjects (N = 13) were exposed to all conditions of a 2 (cluttered; uncluttered) X 2 (relevant; irrelevant) factorial within-subjects experiment. Results showed significant main effects for ad clutter and ad relevance as well as interactions of the two on consumers' attitudes.
Quantifying the Changeable Self: The Role of Self-Tracking in Coming to Terms With and Managing Bipolar Disorder

There has been a recent increase in the development of digital self-tracking tools for managing mental illness. Most of these tools originate from clinical practice and are, as a result, largely clinician oriented. As a consequence, little is known about the self-tracking practices and needs of individuals living with mental illness. This understanding is important to guide the design of future tools to enable people to play a greater role in managing their health. In this article, we present a qualitative study focusing on the self-tracking practices of 10 people with bipolar disorder. We seek to understand the role self-tracking has played as they have come to grips with their diagnosis and attempted to self-manage their health. A central motivation for these participants is to identify risky patterns that may be harbingers of mood episodes, as well as positive trends that support recovery. What emerges is a fragmented picture of self-tracking, with no clear delineation between clinician-initiated and self-initiated practices, as well as considerable challenges participants face in making observations of themselves when their sense of self and emotional state is in flux, uncertain, and unreliable. Informed by these observations, we discuss the merits of a new form of self-tracking that combines manual and automated methods, addresses both clinician and individual needs, helps engage people with bipolar disorder in treatment, and seeks to overcome the significant challenges they face in self-monitoring.
The Extra Connectivity and Conditional Diagnosability of Alternating Group Networks

Extra connectivity, diagnosability, and conditional diagnosability are all important measures for a multiprocessor system's ability to diagnose and tolerate faults. In this paper, we analyze the fault tolerance ability for the alternating group graph, a well-known interconnection network proposed for multiprocessor systems, establish the h-extra connectivity, where 1 ≤ h ≤ 3, and prove that the conditional diagnosability of an n-dimensional alternating group graph, denoted by AGn, is 8n - 27 (n ≥ 4) under the PMC model. This is about four times of the AGn's traditional diagnosability. As a byproduct, the strong diagnosability of AGn is also obtained.
A benchmark for interactive augmented reality instructions for assembly tasks

With the opportunity to customize ordered products, assembly tasks are becoming more and more complex. To meet these increased demands, a variety of interactive instruction systems have been introduced. Although these systems may have a big impact on overall efficiency and cost of the manufacturing process, it has been difficult to optimize them in a scientific way. The challenge is to introduce performance metrics that apply across different tasks and find a uniform experiment design. In this paper, we address this challenge by proposing a standardized experiment design for evaluating interactive instructions and making them comparable with each other. Further, we introduce a General Assembly Task Model, which differentiates between task-dependent and task-independent measures. Through a user study with 12 participants, we evaluate the experiment design and the proposed task model using an abstract pick-and-place task and an artificial industrial task. Finally, we provide paper-based instructions for the proposed task as a baseline for evaluating Augmented Reality instructions.
Inhibitory potential of methanolic extracts of Aristolochia tagala and Curcuma caesia on hepatocellular carcinoma induced by diethylnitrosamine in BALB/c mice

Context: Aristolochia tagala (AT) and Curcuma caesia (CC) have been used traditionally by local herbal practitioners for cancer treatment and as chief ingredients of many polyherbal formulations for various types of ailments. However, there is void in scientific study to evaluate their anti-cancer property. Aims: The aim of this study was to evaluate the anti-carcinogenic properties of the crude methanolic extracts of roots of AT and rhizomes of CC in BALB/c mice exposed to a hepatocarcinogen, diethylnitrosamine (DEN). Settings and Design: (I) Toxicity of herbal plant extracts (HPE); (II) Anticancer studies; (III) Histological studies; and (IV) Biochemical studies. Materials and Methods: To evaluate the effects of these two HPE either alone or following DEN exposure, serum transaminases (aspartate aminotransferase [AST], alanine aminotransferase [ALT]), alkaline phosphatase (ALP), and cancer marker enzyme acetylcholine esterase (AChE) were assayed in mice. In addition, histological study was also carried out under similar conditions. The antioxidant potentials of the HPE were evaluated by monitoring the activity of antioxidant enzymes and metabolites, such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and glutathione (GSH). Statistical Analysis Used: Statistical analysis was performed by GraphPad Prism 6 Software using one-way analysis of variance followed by the Tukey's multiple comparisons test. Significance was set at P < 0.05. Results: Our findings show that DEN administration elevated AST, ALT, ALP, and AChE activities. CC or AT extracts attenuated the increased activities of these marker enzymes. The activities of antioxidant enzymes, which were decreased following DEN administration, were significantly increased in mice treated with CC or AT. Conclusions: The present study clearly documents anticarcinogenic and antioxidant properties of AT and CC in DEN-induced mouse liver cancer in vivo.
Significant of features selection for detecting network intrusions

Intrusion Detection System (IDS) is used to identify unknown or new type of attacks especially in dynamic environments as business and mobile networks. For that importance, IDS has become one of targeted research area that focuses on information security. Among different techniques, Steady State Genetic-Based Machine Learning Algorithm (SSGBML) offers the ability to detect intrusions especially in changing environments. The objective of this paper is to incorporate several feature selection. Selection network features has a great importance to increase detection rate, which is itself a problem in Intrusion Detection System (IDS). Since elimination of the insignificant and/or useless features leads to a simplified problem and enhance detection rate. By combining different selected features that will be evaluated, where this will lead us to determine suitable combination features to attain best results. In SSGBML, Zeroth Level Classifier System (ZCS) plays the role of detector by matching incoming environment message with classifiers to determine whether it is normal or intrusion. The experiments and evaluations for compound methods were performed on KDD 99 dataset to detect network intrusions.