Miracle-dz/UniFAR-FTUs huggingface dataset:
Twitter as a Platform for an Israeli Community of Information Science Professionals

This paper examines an Israeli professional community on Twitter, which connects people working or studying the field of Information Science. The participants were 31 individual and organizational users and 175 structural connections established among them during March 2007- November 2011. The data was extracted using NodeXL application and analyzed in terms of user's investments (i.e., participation by tweeting and following others) and gratification mechanisms (i.e., influence on the audience: the degree of centrality into the community network, the number of followers and tweets marked as favorites). The results show that (1) The evolution of the community over time was in a bell curve, in concordance with the Diffusion of Innovations Theory (Rogers, 2003). (2) Concerning the rate of active participation, five of the most active individual community members (16.1%) shared 54% of the community tweets. Thus, the head of this "long tail" distribution is relatively small, indicating a moderate level of participation inequality in the community. (3) Regarding user investment and gratification mechanisms, participation by tweeting and following others is highly related to the visible form of influencing community audience the number of followers, moderately related to the hidden influence - location of the participant in the community network measured by PageRank, and unrelated to the content quality - the percentage of user's tweets marked as favorites by others.
Strain-Specific Contribution of Eukaryotic Elongation Factor 1 Gamma to the Translation of Influenza A Virus Proteins

Influenza A virus exploits multiple host proteins during infection. To define the virus–host interactome, our group conducted a proteomics-based screen and identified 299 genes that contributed to virus replication and 24 genes that were antiviral. Of these genes, we focused on the role during virus replication of eukaryotic elongation factor 1 gamma (eEF1G), which is a subunit of the eukaryotic elongation factor-1 complex and known to be a pro-viral host protein. Using the CRISPR/Cas9 system, we obtained two clones that were defective in eEF1G expression. In both of these clones, A/WSN/33 (H1N1) virus growth and protein expression were significantly suppressed, but viral mRNA, vRNA, and cRNA expression were not reduced. However, the replication and protein expression of A/California/04/2009 (H1N1pdm) virus in both clones were similar to those in parental cells. We found that the PB2 and PA proteins of WSN virus were responsible for the eEF1G-dependent replication. Our data show that eEF1G plays a role in the translation of virus proteins in a strain-specific manner. Additional analyses may be needed to further understand the role of strain-specific host proteins during virus replication.
Experimenting with a Generalized Rhythmic Density Function for Live Coding

A previously implemented realtime algorithmic composition system with live coding interface had rhythm functions which produced stylistically limited output and lacked flexibility. Through a cleaner separation between the generation of base rhythmic figures and the generation of variations at various rhythmic densities, flexibility was gained. These functions were generalized to make a greater variety of output possible. As examples, L-systems were implemented, as well as the use of ratios for generating variations at different rhythmic densities. This increased flexibility should enable the use of various standard algorithimic composition techniques and the development of new ones.
Antitumor polysaccharides from mushrooms : a review on their isolation process , structural characteristics and antitumor activity

Antitumor polysaccharides from mushrooms: a review on their isolation process, structural characteristics and antitumor activity M. Zhang, S.W. Cui*, P.C. K. Cheung and Q. Wang Food research program, Agriculture and Agri-Food Canada, 93 Stone Road West, Guelph, Ontario, Canada, NIG 5C9 (Tel.: D1 519 780 8028; fax: D1 519 829 2600; e-mail: cuis@agr.gc.ca) The Department of Biology, The Chinese University of Hong Kong, Shatin, NT, HK, China
Micro and nanoengineering advances for the development and commercialization of Organ-on-chips

Received: May 21, 2017; Accepted: June 06, 2017; Published: June 08, 2017 Advances in micro and nanoengineering have permitted to implement Organ-on-chips (OOC) that mimic accurately physiological functions. OOC are multichannel 3D microfluidic cell culture biodevices that mimic and model physiological mechanisms, activities, functions and responses of organs and tissues. These biomimetic microengineering approaches have gained significant relevance in biomedicine because they allow providing a better approximation of structure, behavior of cells and mechanisms of diseases to propose better diagnostic methods and personalized therapies [1].
Relationship between fertilization success and the number of milt donors in rainbow smelt Osmerus mordax (Mitchell): implications for population growth rates

A series of artificial fertilizations using rainbow smelt Osmerus mordax were conducted, each designed to assess the fertilization success of a female’s eggs with milt from one to five males. Mean egg fertilization success increased and variance in fertilization success decreased when more males contributed to a constant volume of milt. This may indicate the presence of an Allee effect. The results suggest that potential changes in egg fertilization success due to a decrease in the number of males, in addition to changes in egg production due to a decrease in the number of females, can affect estimates of maximum sustainable harvest rates, and recovery of depleted
Postpartum Depression: Prevalence and Predictors among Women at El Eman's Specialized Hospital

Postpartum depression is a serious public health concern because of its demonstrated adverse consequences on the development of maternal confidence and the cognitive, emotional and social development of their infant. This study aimed to estimate the prevalence and severity of postpartum depression among women at El Eman's Specialized Hospital and examine the main predictors for postpartum depression among these women during the first three months postpartum. The study was carried out in the Family Planning out patient's Clinic, El Eman Specialized Hospital at Assiut City, Egypt. The study sample comprised 110 pregnant women. Three tools were used for data collection, namely: Sociodemographic Data Structured Interview schedules, postpartum depression predictors inventory (PDPI), and Edinburgh Postnatal depression scale. The main results yielded by the study proved that, 42.73% of the studied sample were in the age group from 25 to 30 years, the majority of sample were house wives (84.5 %) , 29.1 % of sample feeling of depression during pregnancy , 50% of them suffering from anxiety during pregnancy , 44.5% of them feeling of maternity blues and 80.7% of women had postpartum depression . the study recommended to help women to improve the outcome of families suffering with post-partum depression by engaging in routine screening and providing education and referral sources to women. [Naglaa A. Mohamed; Ghadah A. Mahmoud; Nadia A. Sayed; Hamida A. Abdelhafez and Ahmed M. A. Maklof Postpartum Depression: Prevalence and Predictors among Women at El Eman's Specialized Hospital]. Journal of American Science 2011; 7(12):122-128]. (ISSN: 1545-1003). http://www.americanscience. org
Processes After Cold Exposure Leading to the Onset of Stroke

Background: The mortality from stroke is known to increase to a greater extent with the fall of temperature. Environmental factors may play a major role in triggering of the onset of stroke. There is a delay between cold exposure and the onset of stroke. This fact may reflect the complex mechanism after cold exposure. However, a precise process after cold exposure is not well documented. The purpose of this paper is to study the processes after cold exposure that affect human health, exploring the changes in both weather and gene expression. Methods and findings: We used ambulance data of patients provided by the city of Nagoya in Japan during a period from 2002 to 2005. The data included the daily number of patients of all ages, who were first transported by ambulance to a hospital and then diagnosed at the hospital with stroke or cerebral infarction. We used also gene expression data extracted from the database GEO (gene expression omnibus) maintained by The National Center for Biotechnology Information (NCBI). The method is based on random walks in the plane of two variables, mean temperature and relative humidity. We extracted random walks that correspond to paths after cold exposure leading to the onset of stroke and classified the characteristic feature of cooling and rewarming random walks. The increase of relative humidity was observed during these random walks, and suggested the importance of inflammatory system. To discuss a possible mechanism after cold exposure, we examined the gene expression data among the database GEO, and found the increase of cytokine-related genes, especially interleukin 6 signal transducer IL6st and interleukin receptors of IL17. These interleukins play an important role in inflammatory responses. Conclusion: The correspondence between the gene expressions of cytokines and "cooling and rewarming random walks" in the meteorological factors will provide a scheme that connects weather and disease, and will provide novel avenues for research in the prevention of stroke.
Liver function of Streptozotocin-Induced Diabetic Rats Orally Administered Aqueous Root-Bark Extracts of Tetrapleura tetraptera ( Taub )

The aqueous root-bark extract of Tetrapleura tetraptera Taub. has been shown to ameliorate streptozotocin (STZ)-induced hyperglycaemia and dyslipidaemia. This study evaluated the liver status of STZinduced diabetic rats treated with aqueous root-bark extract of T. tetraptera for 35 days. Twenty-four (24) rats in four groups (normal control, diabetic control, T. tetraptera treated STZ induced diabetic rats at 150 mg/kg b. w. and T. tetraptera treated STZ-diabetic rats at 300 mg/kg b. w.) were used. Serum and liver alanine and aspartate transaminases (ALT and AST), alkaline phosphatase (ALP), gamma glutamyl transferase (γGT) activities and protein concentration were assessed. Also, serum albumins, globulins, total and direct bilirubin concentrations were measured. STZ induced diabetes significantly (P<0.05) increased serum ALT, AST and ALP activities, while treatment of diabetic rats with T. tetraptera reduced the activities of these enzymes. T. tetraptera caused significant (P<0.05) increases in serum γGT, total and direct bilirubin levels, especially at the higher dose (300mg/kg body weight). While the treatment of STZ induced diabetic rats with the extract of T. tetraptera ameliorated hepatocellular damage, at the higher dose of 300mg/kg body weight, T. tetraptera treatment may cause bile duct obstruction. The use of this plant in the treatment of diabetes or other diseases should therefore be monitored with respect to hepato-biliary toxicity.
Synthesis of an Isotopically Labelled Analog of the Antimicrobial Peptide LL-37

LL-37 is a cationic cathelin-associated broad spectrum antibiotic peptide of human neutrophils. Its mechanism of action is by disruption of the bacterial cell membrane structure. LL-21 is a simplified form of the peptide that contains only the core portion of LL-37, which retains antimicrobial activity and is easier to synthesize. We synthesized an N –Val-labeled LL-21 peptide which allows us to perform antimicrobial assays to know the antimicrobial activity of the new peptide LL-21 on various gram positive and gram negative bacteria. We found that our new peptide LL-21 shows good minimum inhibitory concentrations on various gram positive and gram negative bacteria except in the case of Bacillus subtilis and when compared with the parent analog, the new peptide requires slightly higher concentrations to kill the bacteria. Solid state NMR studies on LL-21 help to measure helix tilt in the bacterial cell membranes. This will provide information on its precise mode of action, either detergentlike activity or pore formation. In the future, the replacement of some of the amino acids in LL-21 with F and deuterium labels in specified positions will give more information on the orientation, dynamics, and rotation of the peptide in bacterial cell bilayers.
Towards a Computational Reading of Emergence in Experimental Game Design

In any prolonged creative act, there may be moments when an interesting and/or surprising aspect of the artefact being created, or a related idea, emerges without prior knowledge of the creator. Such emergent properties can be capitalised on to drive the creative process. With the Gamika iOS app, we have made it possible to create novel casual game levels in minutes and hours rather than the usual days and weeks. This has enabled us to undertake and analyse game design sessions with a think aloud methodology, focusing on moments of emergence and how they influenced the level design. This has in turn led us to an initial computational reading of emergence in game design, where we imagine how an automated game designer could recognise and take advantage of unexpected changes in aspects such as aesthetics, gameplay and playing strategies which arise during the creative process.
KIIDSOnto : An OWL DL Ontology for Narrative Reasoning

The most important problem in Interactive Narrative Environments like computer games or interactive fictions is called “the interaction dilemma” [2], an inevitable conflict between the designer's determinism and the user's freedom. An interactive storytelling systems needs to structure an intensive and meaningful experience at the same time as enabling the right development of a pre-authored plot. KIIDS (Knowledge-Intensive Interactive Digital Storytelling) system represents a computational solution for addressing this problem by the application in real time of artificial intelligence algorithms on the supervision and management of the interactive storytelling process. The proposal is based on a Knowledge-Intensive Case-Based Reasoning approach that deals with narrative knowledge [3], an overview of the system architecture is presented in figure 1.
Resilience and Cognitive Function in Patients With Schizophrenia and Bipolar Disorder, and Healthy Controls

Background: This study compared adaptive resilience among patients with schizophrenia, bipolar disorder, and healthy controls, and examined the relationship of resilience to cognitive function. Methods: A sample of 81 patients diagnosed with schizophrenia, 34 with bipolar disorder, and 52 healthy controls completed the Connor-Davidson Resilience Scale (CD-RISC) and cognitive tests of verbal comprehension, executive functioning, and working memory. Paired comparison of diagnostic groups on CD-RISC and cognitive tests was conducted. Linear regression was used to identify the independent association of clinical diagnoses and neurocognition with resilience deficits. Results: Both patient groups showed significantly lower CD-RISC scores and poorer cognitive function than healthy controls and the schizophrenia group scored lower than bipolar group on these measures as well. CD-RISC scores were positively correlated with all three cognitive measures in the entire sample but not within the diagnostic subgroups. Multiple regression analysis showed differences in CD-RISC between diagnostic groups were not mediated by differences in these three measures of neurocognition. Discussion: Schizophrenia and bipolar disorder are associated with impairments in both resilience and cognitive function but the impairment in resilience appears to be independent of deficits in cognitive function measured here and may reflect unmeasured dimensions of cognitive function, other impairments or environmental factors.
Where Can I Go From Here ? Drawing Contextual Navigation Maps of the London Underground

Network administrators often wish to ascertain where network attackers are located; therefore it would be useful to display the network map from the context of either the attacker’s potential location or the attacked host. As part of a bigger project we are investigating how to best visualize contextual network data. We use a dataset of station adjacencies with journey times as edge weights, to explore which visualization design is most suitable, and also ascertain the best network shortest-path metric. This short paper presents our initial findings, and a visualization for Contextual Navigation using circular, centered-phylogram projections of the network. Our visualizations are interactive allowing users to explore different scenarios and observe relative distances in the data.
Dynamic layering graphical elements for graphical password schemes: creating the difference

Based on a systematic review of 35 graphical password schemes, in this article a new classification and evaluation framework is proposed. When positioning existing schemes in this framework a novelty is discovered that wasn’t previously described: a dynamic layered combination of graphical elements. Given this insight, a new graphical password scheme is created (PicassoPass). Positioned against other password systems, it has the potential to perform better on the combination of low memory burden and resistance to shoulder surfing attacks. A security analysis confirms its shoulder surfing resistance.
Characterization and flexural strength of iceberg and glacier ice

Abstract Flexural strength of iceberg and glacier ice was determined from Four-point beam-bending experiments. A large quantity of glacial ice was collected from four icebergs and one glacier, and a detailed ice-characterization program was performed on samples from the five sources. Beam-bending experiments were conducted at four temperatures in the range −1 ° to-16 °C and at strain rates of 10 −3 and 10−5 s−1. The flexural strength was found to increase with increasing strain rate (based on extreme fibre strain and decreasing temperature. The data suggest than air-bubble inclusions play an important role in determining the flexural strength of glacial ice and this can explain the significant differences in mean strength of the ice from the five sources. At a strain rate of 10−3 s−1 and temperature of —11 °C, the flexural strength was found to increase as the number of bubbles per unit volume increased. Reduction of crack-initiating stresses at grain boundaries by “softening” of grains due to intragranular air-bubble inclusions is thought to be the mechanism.
Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types

Annotated corpora enable supervised machine learning and data analysis. To reduce the cost of manual annotation, tasks are often assigned to internet workers whose judgments are reconciled by crowdsourcing models. We approach the problem of crowdsourcing using a framework for learning from rich prior knowledge, and we identify a family of crowdsourcing models with the novel ability to combine annotations with differing structures: e.g., document labels and word labels. Annotator judgments are given in the form of the predicted expected value of measurement functions computed over annotations and the data, unifying annotation models. Our model, a specific instance of this framework, compares favorably with previous work. Furthermore, it enables active sample selection, jointly selecting annotator, data item, and annotation structure to reduce annotation effort.
Selecting a Fatigue Rating Scale

There remains no “gold standard” of fatigue severity available to validate fatigue scales, nor can these measures distinguish fatigue related to physical exertion, emotional stress, pain, sleep disturbance, depression or the poorly understood causal mechanisms of CFS. Fortunately, recently developed measures of subjectively experienced fatigue, modeled after the measurement of other subjective states (e.g., pain, anxiety), have multiple applications in clinical and research settings. Based on a previous review of fatigue instruments 1 as well as more recent data, this article describes selected fatigue measures for two categories of fatigue scales (fatigue intensity and fatigue/function), and concludes with recommendations about the use of fatigue scales by clinicians and researchers.
Maturity model for collaborative innovation: Higher education challenge

Higher Education Institutions (HEI) have changed both the way of developing their substantive functions, and of managing the institution. In this permanent change, a diversity of technologies has been incorporated, which also affects the development of the institution. In this sense, education and knowledge are no longer unique to educational institutions. Therefore, it must incorporate open innovation strategies in its academic and administrative models, as part of its management model, where different internal and external actors are integrated. This article presents the Maturity Model for collaborative innovation (MMIC), focused on open innovation processes and strategic alignment. We conclude that innovation must be articulated with the mission processes of the HEI and with the models of corporate and technological governance to establish collaborative innovation communities (CIC).
A Multimodal Approach to Predict Social Media Popularity

Multiple modalities represent different aspects by which information is conveyed by a data source. Modern day social media platforms are one of the primary sources of multimodal data, where users use different modes of expression by posting textual as well as multimedia content such as images and videos for sharing information. Multimodal information embedded in such posts could be useful in predicting their popularity. To the best of our knowledge, no such multimodal dataset exists for the prediction of social media photos. In this work, we propose a multimodal dataset consisiting of content, context, and social information for popularity prediction. Speci? cally, we augment the SMPT1 dataset for social media prediction in ACM Multimedia grand challenge 2017 with image content, titles, descriptions, and tags. Next, in this paper, we propose a multimodal approach which exploits visual features (i.e., content information), textual features (i.e., contextual information), and social features (e.g., average views and group counts) to predict popularity of social media photos in terms of view counts. Experimental results con? rm that despite our multimodal approach uses the half of the training dataset from SMP-T1, it achieves comparable performance with that of state-of-the-art.