Miracle-dz/UniFAR-FTUs huggingface dataset:
CONTEXTUALIZING TECHNOLOGY USE

This paper presents a contextualized analysis of the ways that organizers did and did not use Internet-enabled communication technologies in an organizing context in which material inequality was a prominent focus: a local homeless movement. Few studies on ICTs and social movements have taken seriously the very real material inequalities that structure technology use. While all movements include participants that either do not have access to ICTs or choose not to use them based on organizing contexts, these participants have been systematically excluded from analysis in the rush to understand how a narrow technological elite think, feel, and act in relation to ICTs. This paper draws on a communication-oriented participant observation of three overlapping campaigns to examine the communication practices employed by both housed and unhoused organizers: a campaign to ‘Stop the Sweeps’ of urban homeless encampments, a direct action tent-city project aimed at providing emergency shelter for up to 1,000 people called ‘Nickelsville’, and a campaign to stop the construction of a new jail organized around the ‘No New Jail’ slogan. Four themes are presented that characterize the strategies organizers used in communicating within and between constituents: how organizers emphasized ‘relational’ face-to-face communication, used ICTs to connect with housed allies, encouraged participants to move from the computer screen to street, and relied upon existing organizationally sponsored communications infrastructure in facilitating communication tasks. This paper proposes that an analysis of communication practices broadly defined is important in understanding the role of technologies of communication more specifically.
Nursing Theorists and Their Work

Part 1 Analysis of nursing theories: introduction to analysis of nursing theorists terminology of theory development history and philosophy of science logical reasoning theory development process evolution of nursing theory development. Part 2 Philosophies: Florence Nightingale - modern nursing Ernestine Wiedenbach - the helping art of clinical nursing Virginia Henderson - definition of nursing Faye Glenn Abdellah - 21 nursing problems Lydia E. Hall - core, care and cure model Jean Watson - philosophy and science of caring Patricia Benner - from novice to expert - excellence and power in clinical nursing practice. Part 3 Conceptual models - grand theories: Dorothea E. Orem - self-care deficit theory of nursing Myra Estrin Levine - four conservation principles Martha E. Rogers - unitary human beings Dorothy E. Johnson - behavioural system model Sister Callista Roy - adaptation model Betty Neuman - systems model Imogene King - theory of goal attainment. Part 4 Middle range nursing theories: Hildegard E. Peplau - psychodynamic nursing Ida Jean Orlando (Pelletier) - nursing process theory Joyce Travelbee - human-to-human relationship model Joan Riehl Sisca - symbolic interactionism Helen C. Erickson, Evelyn M. Tomlin, Mary Ann P. Swain - modelling and role-modelling Ramona T. Mercer - maternal role attainment Kathryn E. Bernard - parent-child interaction model Madeleine Leininger - cultural care theory Rosemarie Rizzo Parse - man-living-health Joyce J. Fitzpatrick - life perspective rhythm model Margaret A. Newman - model of health Evelyn Adam - conceptual model for nursing Nola J. Pender - the health promotion model.
Unipolar depression with bipolar family history: Links with the bipolar spectrum

The aim of the present paper was to find if unipolar major depressive disorder (MDD) with bipolar family history could be included in the bipolar spectrum, by comparing it to unipolar MDD without bipolar family history, and to bipolar II disorder, on typical bipolar variables. A sample of 280 consecutive bipolar II outpatients, and a sample of 135 consecutive unipolar MDD outpatients, presenting for major depressive episode (MDE) treatment, were interviewed with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (4th edn). Hypomanic symptoms during the MDE were systematically assessed. Clinical variables used to validate the inclusion of unipolar MDD with bipolar family history in the bipolar spectrum were young age of onset, many MDE recurrences, atypical features, and depressive mixed state (DMX; an MDE plus >2 concurrent hypomanic symptoms), following many previous studies reporting that these variables were typical features of bipolar disorders. Means were compared by t‐test and frequencies by χ2 test (stata 7). Two‐tailed P < 0.05 was chosen. Unipolar MDD with bipolar family history was present in 20% of MDD patients. Comparisons among unipolar MDD with bipolar family history (UP+BPFH), unipolar MDD without bipolar family history (UP–BPFH), and bipolar II (BPII), found that UP+BPFH versus UP–BPFH had a significantly lower age, lower age of onset, fewer recurrences, and more DMX; that UP+BPFH versus BPII had no significant differences (apart from recurrences); and that UP–BPFH versus BPII had significantly different age, age of onset, recurrences, atypical features, and DMX. Findings suggest that UP+BPFH shows many bipolar signs, and that it could therefore be included in the bipolar spectrum. Unipolar MDD with bipolar family history had a clinically significant 20.0% frequency in the unipolar MDD sample, supporting the clinical usefulness of this depression subtype. The subtyping of MDD based on bipolar family history could have treatment implications.
Severe Schistosomiasis in the Absence of Interleukin-4 (IL-4) Is IL-12 Independent

ABSTRACT An interleukin-4 (IL-4)-dependent Th2 response allows wild-type mice to survive infection with the parasite Schistosoma mansoni. In the absence of IL-4, infected mice mount a Th1-like proinflammatory response, develop severe disease, and succumb. Neither the Th1 response nor morbidity is IL-12 dependent in this system.
The green impact: bacterioplankton response toward a phytoplankton spring bloom in the southern North Sea assessed by comparative metagenomic and metatranscriptomic approaches

Phytoplankton blooms exhibit a severe impact on bacterioplankton communities as they change nutrient availabilities and other environmental factors. In the current study, the response of a bacterioplankton community to a Phaeocystis globosa spring bloom was investigated in the southern North Sea. For this purpose, water samples were taken inside and reference samples outside of an algal spring bloom. Structural changes of the bacterioplankton community were assessed by amplicon-based analysis of 16S rRNA genes and transcripts generated from environmental DNA and RNA, respectively. Several marine groups responded to bloom presence. The abundance of the Roseobacter RCA cluster and the SAR92 clade significantly increased in bloom presence in the total and active fraction of the bacterial community. Functional changes were investigated by direct sequencing of environmental DNA and mRNA. The corresponding datasets comprised more than 500 million sequences across all samples. Metatranscriptomic data sets were mapped on representative genomes of abundant marine groups present in the samples and on assembled metagenomic and metatranscriptomic datasets. Differences in gene expression profiles between non-bloom and bloom samples were recorded. The genome-wide gene expression level of Planktomarina temperata, an abundant member of the Roseobacter RCA cluster, was higher inside the bloom. Genes that were differently expressed included transposases, which showed increased expression levels inside the bloom. This might contribute to the adaptation of this organism toward environmental stresses through genome reorganization. In addition, several genes affiliated to the SAR92 clade were significantly upregulated inside the bloom including genes encoding for proteins involved in isoleucine and leucine incorporation. Obtained results provide novel insights into compositional and functional variations of marine bacterioplankton communities as response to a phytoplankton bloom.
Implementing a national strategy for patient safety: lessons from the National Health Service in England

Improving patient safety has become a core issue for many modern healthcare systems. However, knowledge of the best ways for government initiated efforts to improve patient safety is still evolving, although there is considerable commonality in the challenges faced by countries. Actions to improve patient safety must operate at multiple levels of the healthcare system simultaneously. Using the example of the NHS in England, this article highlights the importance of a strategic analysis of the policy process and the prevailing policy context in the design of the national patient safety strategy. The paper identifies a range of policy “levers” (forces for change) that can be used to support the implementation of the national safety initiative and, in particular, discusses the strengths and limitations of the “business case” approach that has attracted recent interest. The paper offers insights into the implementation of national patient safety goals that should provide learning for other countries.
Evaluating generalized association rules through objective measures

Generalized association rules are rules that contain some background knowledge, therefore, giving a more general view of the domain. This knowledge is codified by a taxonomy set over the data set items. Many researches use taxonomies in different data mining steps to obtain generalized rules. In general, those researches reduce the obtained set by pruning some specialized rules using a subjective measure, but rarely analyzing the quality of the rules. In this context, this paper presents a quality analysis of the generalized association rules, where a different objective measure has to be used depending on the side a generalization item occurs. Based on this fact, a grouping measure was generated according to the generalization side. These measure groups can help the specialists to choose an appropriate measure to evaluate their generalized rules.
Double resolution from a set of aliased images

In this paper, we present a super-resolution method to approximately double image resolution in both dimensions from a set of four low resolution, aliased images. The camera is shifted and rotated by small amounts between the different image captures. Only the low frequency, aliasing-free part of the images is used to find the shift and rotation parameters. When the images are registered, it is possible to reconstruct a higher resolution, aliasing-free image from the four low resolution images using cubic interpolation. We applied our algorithm in a simulation, where all parameters are known and controlled, as well as in a practical experiment using images taken with a real digital camera. The results obtained in both tests prove the validity of our method.
High-density mapping of electrically induced atrial fibrillation in humans.

BACKGROUND Mapping studies in animals have suggested that atrial fibrillation (AF) is based on multiple reentering wavelets. Little information is available about the patterns of activation during AF in humans. The objective of the present study was to reconstruct and classify the patterns of human right atrial (RA) activation during electrically induced AF. METHODS AND RESULTS AF was induced by rapid atrial pacing in 25 patients with Wolff-Parkinson-White syndrome undergoing surgery for interruption of their accessory pathway(s). The free wall of the RA was mapped using a spoon-shaped electrode containing 244 unipolar electrodes. The activation of the RA during AF showed large interindividual differences. Based on the complexity of atrial activation, three types of AF were defined. In type I (40% of patients), single broad wave fronts propagated uniformly across the RA. Type II (32%) was characterized by one or two nonuniformly conducting wavelets, whereas in type III (28%), activation of the RA was highly fragmented and showed three or more different wavelets that frequently changed their direction of propagation as a result of numerous arcs of functional conduction block. There were significant differences (P < .05) among the three types of AF in median intervals (174 +/- 28, 150 +/- 14, and 136 +/- 16 milliseconds), variation in AF intervals (P5-95) (54 +/- 25, 94 +/- 21, and 104 +/- 22 milliseconds), incidence of electrical inactivity (42 +/- 11%, 21 +/- 4%, and 8 +/- 4%) and reentry (3 +/- 7%, 36 +/- 28%, and 99 +/- 36%), and average conduction velocity during AF (61 +/- 6, 54 +/- 4, and 38 +/- 10 cm/s). CONCLUSIONS During pacing-induced AF in humans, the RA is activated by one or multiple wavelets propagating in different directions. Three types of RA activation during AF were identified. From type I to type III, the frequency and irregularity of AF increased, and the incidence of continuous electrical activity and reentry became higher. These various types of AF in humans appear to be characterized by different numbers and dimensions of the intra-atrial reentrant circuits.
Change the Space, Change the Practice?

This paper explores the results of the introduction of the Pop-Up Newsroom, a virtual, temporary citizen journalism-style mobile news operation, to university student journalists. The results revealed two categories of response: those who embraced change and began to develop networked journalism identities; and those who advocated for the traditional brick-and-mortar newsroom and accompanying practices as preserving professional journalism identities.
Multi-label Classification with ART Neural Network s

Multi-label Classification (MC) is a classification task with instances labelled by multiple classes rather than just one. This task becomes increasingly important in such fields as gene function prediction or web-mining. Early approaches to MC were based on learning independent binary classifiers for each class and combining their outputs in order to obtain multi-label predictions. Alternatively, a classifier can be directly trained to predict a label set of an unknown size for each unseen instance. Recently, several direct multi-label learning algorithms have been proposed. This paper investigates a novel method to solve a MC task by using an Adaptive Resonance Theory (ART) neural network. A modified Fuzzy ARTMAP algorithm Multi-Label-FAM (MLFAM) was applied to classification of multi-label data. The obtained preliminary results on the Yeast data set and their comparison with the results of existing algorithms demonstrate the effectiveness of the proposed approach. Keywords-Multi-label Classification, Neural Networks, Fuzzy ARTMAP
Optimal Rectilinear Steiner Minimal Trees in O (n22.62n) Time

This paper presents an algorithm that computes an optimal rectilinear Steiner minimal tree of n points in at most O(n 2 2:62 n) time. For instances small enough to solve in practice, this time bound is provably faster than any previous algorithm, and improves the previous best bound for practically solvable instances, which is O(n3 n). Experimental evidence is also presented that demonstrates that the algorithm is fast in practice as well|much faster, in fact, than its worst-case time complexity suggests. As part of the analysis, it is proven that the number of full sets on a set of n terminals is at most O(n1:62 n).
Novos caminhos: pensando materiais didáticos de língua portuguesa como segunda língua para alunos surdos

O projeto de extensao Recursos e materiais para o ensino de Portugues para alunos surdos visa ao desenvolvimento de atividades voltadas para a comunidade surda e oferece tambem um espaco de discussao para os graduandos e professores de Lingua Portuguesa, considerando, em uma perspectiva de educacao bilingue, a Lingua Brasileira de Sinais – LIBRAS – como a primeira lingua do aluno surdo e a Lingua Portuguesa como sua segunda lingua. O objetivo do projeto e a elaboracao materiais didaticos que atendam as necessidades linguisticas dos surdos. Nota-se que a oferta de tais materiais dirigidos a comunidade surda, quando existente, nao atende ao desenvolvimento das interfaces de leitura e escrita da Lingua Portuguesa, visto que os materiais voltados para esse alunado pressupoem categorias e aspectos distintos daqueles enderecados a alunos ouvintes. Para refletir sobre as especificidades desse alunado, faz-se necessario o contato com pesquisas sobre educacao bilingue para surdos e o desenvolvimento de metodologias visuais a fim de aplica-las no cotidiano escolar. Assim, pretende-se que o projeto suscite a discussao e a construcao de conhecimento sobre novas metodologias e estrategias didaticas.
Old World fruitbat phylogeny: evidence for convergent evolution and an endemic African clade.

Knud Andersen (1912, Catalogue of the Chiroptera in the Collections of the British Museum: I. Megachiroptera, British Museum of Natural History, London) divided Old World fruitbats (family Pteropodidae) into the rousettine, cynopterine, epomophorine, eonycterine, and notopterine sections. The latter two sections comprise the subfamily Macroglossinae; members of this subfamily exhibit specializations for nectarivory (e.g., elongated, protrusible, brushy tongues) and cluster together in cladistic analyses based on anatomical characters. Other evidence, including single-copy DNA hybridization, suggests that macroglossines are either paraphyletic or polyphyletic; this implies that adaptations for pollen and nectar feeding evolved independently in different macroglossine lineages or were lost in nonmacroglossines after evolving in a more basal common ancestor. Hybridization data also contradict Andersen's phylogeny in providing support for an endemic African clade that includes representatives of three of Andersen's sections. Here, we present complete mitochondrial 12S rRNA and valine tRNA gene sequences for 20 pteropodids, including representatives of all of Andersen's sections, and examine the aforementioned controversies. Maximum likelihood, minimum evolution, and maximum parsimony analyses all contradict macroglossine monophyly and provide support for an African clade that associates Megaloglossus and Lissonycteris and those two with Epomophorus. In conjunction with the DNA hybridization results, there are now independent lines of molecular evidence suggesting: (i) convergent evolution of specializations for nectarivory, at least in Megaloglossus versus other macroglossines, and (ii) a previously unrecognized clade of endemic Africa taxa. Estimates of divergence time based on 12S rRNA and DNA hybridization data are also in good agreement and suggest that extant fruitbats trace back to a common ancestor 25 million to 36 million years ago.
Deciding knowledge properties of security protocols

Logics for specifying properties of security protocols and reasoning about them have received increasing attention over the past few years. In this paper, we propose a propositional logic of knowledge, augmented with tense modalities, in which many important properties of security protocols can be naturally expressed. We also describe in some detail the protocol model, which helps provide a precise and general semantics for the logic. The main technical result is the decidability of the verification problem for the logic.
A 32nm High-k metal gate SRAM with adaptive dynamic stability enhancement for low-voltage operation

SRAM scaling faces increasing challenges in meeting power, performance, and density requirements as Moore's law continues to drive CMOS technology scaling. Due to process variation, SRAM bitcell design margin continues to shrink in scaled technologies and conventional SRAM is no longer able to fully realize the benefits of scaling. Smart and adaptive assist circuits can improve design margins while satisfying SRAM power and performance requirements in scaled technologies. VCC scaling is especially important to meet increasingly stringent power constraints [1]. Circuit techniques proposed in recent years enable SRAM VCC scaling by expanding read and write margins [2–6]. However, the improved design margins for SRAM VCC scaling are often achieved with significant design overhead, e.g., additional power supply [4], increased circuit complexity [5], and testing overheads required for die-by-die programming [6].
Malware Analysis Using Visualized Image Matrices

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.
Turning On Lights to Stop Neurodegeneration: The Potential of Near Infrared Light Therapy in Alzheimer's and Parkinson's Disease

Alzheimer's and Parkinson's disease are the two most common neurodegenerative disorders. They develop after a progressive death of many neurons in the brain. Although therapies are available to treat the signs and symptoms of both diseases, the progression of neuronal death remains relentless, and it has proved difficult to slow or stop. Hence, there is a need to develop neuroprotective or disease-modifying treatments that stabilize this degeneration. Red to infrared light therapy (λ = 600–1070 nm), and in particular light in the near infrared (NIr) range, is emerging as a safe and effective therapy that is capable of arresting neuronal death. Previous studies have used NIr to treat tissue stressed by hypoxia, toxic insult, genetic mutation and mitochondrial dysfunction with much success. Here we propose NIr therapy as a neuroprotective or disease-modifying treatment for Alzheimer's and Parkinson's patients.
Automatically assessing acoustic manifestations of personality in speech

In this paper, we present first results on applying a personality assessment paradigm to speech input, and comparing human and automatic performance on this task. We cue a professional speaker to produce speech using different personality profiles and encode the resulting vocal personality impressions in terms of the Big Five NEO-FFI personality traits. We then have human raters, who do not know the speaker, estimate the five factors. We analyze the recordings using signal-based acoustic and prosodic methods and observe high consistency between the acted personalities, the raters' assessments, and initial automatic classification results. This presents a first step towards being able to handle personality traits in speech, which we envision will be used in future voice-based communication between humans and machines.