Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordination in language: Temporality and time-ranging

Temporality underpins how living systems coordinate and function. Unlike measures that use mathematical conventions, lived temporalities grant functional cohesion to organisms-in-the-world. In foxtail grasses, for example, self-maintenance meshes endogenous processes with exogenous rhythms. In embrained animals, temporalities can contribute to learning. And cowbirds coordinate in a soundscape that includes conspecifics: social learning allows them to connect copulating with past events such that females exert ‘long-distance’ control over male singing. Using Howard Pattee’s work, we compare the foxtail’s self-maintenance, gender-based cowbird learning and how humans manage multi-scalar activity. We argue that, while all living things coordinate, temporal ranging is typical of vertebrates. As primates, humans too use temporal ranging – they can draw on social learning, anticipate winter and manage coordinated action. However language behaviour (or languaging) grants new control over the scales of time. People connect the impersonal to lived experience in narratives, as they draw on autobiography and enact cultural practices. Humans become singular individuals who use temporal experience to manage affect, relationships, beliefs, fictions, and knowledge. Individual subjectivity permits collaborative and competitive activity based on linking events with quite different histories. As a result, alone of the vertebrates, we claim that humans become time-rangers.
Implementation of the Digital Assessment Tool Kahoot in Elementary School

The purpose of this study was to investigate the usability of the Kahoot! , the digital assessment tool, in elementary schools. With this respect, the participants were selected by using the simple random sampling method. 23 students and 1 teacher in state elementary school in Mugla in Turkey participated in the study in the spring term of the 2017-2018 academic year. The Kahoot! was implemented in the social studies class for 4 weeks. It was a qualitative and quantitative study. The survey technique was used to collect data and the data were analyzed by using the descriptive analysis technique. The results of the study indicated that the students thought the Kahoot! was enjoyable, informative, useful, perfect and fine. The students also rated the difficulty level in using the Kahoot! application as ‘Not difficult’, ‘A Little Difficult’ and ‘Difficult’. These challenges were the difficulties in reaching the Kahoot! website, the problems about the internet connection, the difficulties in reading the board, the difficulties in selecting the answers and the application’s disconnections because of the connection timeouts. The teacher, however, displayed positive opinions about the Kahoot! application.
Clindamycin Resistance among Staphylococcus Aureus Isolated at Mbarara Regional Referral Hospital, in South Western Uganda

Aims The study was conducted to determine the prevalence of Clindamycin (CL) resistance and antimicrobial susceptibility among clinical isolates of Staphylococcus aureus (S. aureus) from Mbarara Regional Referral Hospital (MRRH) in Southwestern Uganda. Study Design Laboratory based cross sectional study. Place and Duration of the Study The study was conducted at the Microbiology department of Mbarara Regional referral hospital between November 2012 and December 2013. Methodology In our study, we recruited 300 S. aureus isolates that were stored in the laboratory and were obtained from different clinical samples. The isolates were tested for antimicrobial susceptibility by phenotypic methods and for the genotypic expression of Macrolide Lincosamide StreptograminB (MLSB) resistance genes (ermA, ermB, ermC, and msrA). The D-test was also performed. Results Phenotypically, a total of 109 (36%) S. aureus isolates were resistant to CL, of which 9 (3%) were constitutively resistant while 100 (33.3%) were inducibly resistant. Genotypicaly, 134/300 (44.7%) isolates possessed at least one of the MLSB resistance genes. 23/300 (7.7%) tested positive for ermB, 98/300 (32.7%) tested positive for the ermC and 43/300 (14.3%) tested positive for the msrA genes with none possessing the ermA gene. Isolates were highly resistant to Sulfamethoxazole/trimethoprim, Erythromycin and Oxacillin with moderate resistance to Vancomycin and Imipenem and least resistance to Linezolid Conclusion S. aureus resistance to CL was high in this set up. There was also high resistance to Sulfamethoxazole/trimethoprim, Erythromycin and Oxacillin but low resistance to Linezolid.
Genesis and Classification of Soils on a Toposequence Underlain by Mica Schist in Ife Area, Southwestern Nigeria.

The study was conducted to establish the morphological, physical and chemical properties of soils on a toposequence underlain by mica schist in Ife Area, identify the pedogenic processes that produced the soils and establish the taxonomic and fertility capability classes of the soils. The toposequence was delineated into five physiographic units and soil profile pits were established, described and sampled at each unit. The soil samples collected from each of the genetic horizon were subjected to routine analyses following the procedures in methods of soil analysis. Taxonomic and fertility capability classification of the soils were carried out.
Robust Voronoi-based curvature and feature estimation

Many algorithms for shape analysis and shape processing rely on accurate estimates of differential information such as normals and curvature. In most settings, however, care must be taken around non-smooth areas of the shape where these quantities are not easily defined. This problem is particularly prominent with point-cloud data, which are discontinuous everywhere. In this paper we present an efficient and robust method for extracting principal curvatures, sharp features and normal directions of a piecewise smooth surface from its point cloud sampling, with theoretical guarantees. Our method is integral in nature and uses convolved covariance matrices of Voronoi cells of the point cloud which makes it provably robust in the presence of noise. We show analytically that our method recovers correct principal curvatures and principal curvature directions in smooth parts of the shape, and correct feature directions and feature angles at the sharp edges of a piecewise smooth surface, with the error bounded by the Hausdorff distance between the point cloud and the underlying surface. Using the same analysis we provide theoretical guarantees for a modification of a previously proposed normal estimation technique. We illustrate the correctness of both principal curvature information and feature extraction in the presence of varying levels of noise and sampling density on a variety of models.
Predicting responses of nonlinear neurons in monkey striate cortex to complex patterns

The overwhelming majority of neurons in primate visual cortex are nonlinear. For those cells, the techniques of linear system analysis, used with some success to model retinal ganglion cells and striate simple cells, are of limited applicability. As a start toward understanding the properties of nonlinear visual neurons, we have recorded responses of striate complex cells to hundreds of images, including both simple stimuli (bars and sinusoids) as well as complex stimuli (random textures and 3-D shaded surfaces). The latter set tended to give the strongest response. We created a neural network model for each neuron using an iterative optimization algorithm. The recorded responses to some stimulus patterns (the training set) were used to create the model, while responses to other patterns were reserved for testing the networks. The networks predicted recorded responses to training set patterns with a median correlation of 0.95. They were able to predict responses to test stimuli not in the training set with a correlation of 0.78 overall, and a correlation of 0.65 for complex stimuli considered alone. Thus, they were able to capture much of the input/output transfer function of the neurons, even for complex patterns. Examining connection strengths within each network, different parts of the network appeared to handle information at different spatial scales. To gain further insights, the network models were inverted to construct “optimal” stimuli for each cell, and their receptive fields were mapped with high-resolution spots. The receptive field properties of complex cells could not be reduced to any simpler mathematical formulation than the network models themselves.
Indocyanine green fluorescence angiography during laparoscopic and robotic colorectal surgery – a video vignette

Anastomotic leaks are a dreaded complication of all colorectal surgery with the main factors contributing to it being tension on the anastomosis, intra-abdominal or systemic sepsis, distal obstruction, inadequate blood supply and improper surgical techniques. The leak rate of left-sided high colorectal resections can have a clinically significant leak rate from as low as 1-5% in high anterior resections to 7.9% in low anastomoses. This article is protected by copyright. All rights reserved.
Hydrocarbons in diffuse and translucent clouds

We investigate the consequences on hydrocarbon chemistry in diffuse and translucent clouds of including an interaction between gaseous C + ions and dust grains. In general, we find that models in which much of the carbon is deposited and retained on grain surfaces within the cloud lifetime represent a poor match to observations. Conversely, models in which carbon is efficiently converted to methane generally provide satisfactory agreement with the observed chemistry of translucent clouds. Such models also predict that the hydrocarbons C 2H, C3H2 and H2CO may be detectable in diffuse clouds.
A Dissociated Glucocorticoid Receptor Modulator Reduces Airway Hyperresponsiveness and Inflammation in a Mouse Model of Asthma

The glucocorticoid receptor (GR) is a transcription factor able to support either target gene activation via direct binding to DNA or gene repression via interfering with the activity of various proinflammatory transcription factors. An improved therapeutic profile for combating chronic inflammatory diseases has been reported through selectively modulating the GR by only triggering its transrepression function. We have studied in this paper the activity of Compound A (CpdA), a dissociated GR modulator favoring GR monomer formation, in a predominantly Th2-driven asthma model. CpdA acted similarly to the glucocorticoid dexamethasone (DEX) in counteracting OVA-induced airway hyperresponsiveness, recruitment of eosinophils, dendritic cells, neutrophils, B and T cells, and macrophages in bronchoalveolar lavage fluid, lung Th2, Tc2, Th17, Tc17, and mast cell infiltration, collagen deposition, and goblet cell metaplasia. Both CpdA and DEX inhibited Th2 cytokine production in bronchoalveolar lavage as well as nuclear translocation of NF-κB and its subsequent recruitment onto the IκBα promoter in the lung. By contrast, DEX but not CpdA induces expression of the GR-dependent model gene MAPK phosphatase 1 in the lung, confirming the dissociative action of CpdA. Mechanistically, we demonstrate that CpdA inhibited IL-4–induced STAT6 translocation and that GR is essential for CpdA to mediate chemokine repression. In conclusion, we clearly show in this study the anti-inflammatory effect of CpdA in a Th2-driven asthma model in the absence of transactivation, suggesting a potential therapeutic benefit of this strategy.
Research on Community Detection Algorithm Based on the UIR-Q

Aiming at the current problems of community detection algorithm in which user’s property is not used; the community structure is not stable and the efficiency of the algorithm is low, this paper proposes a community detection algorithm based on the user influence and its parallelization method. In terms of the concept of user influence in the subject communication and the PageRank algorithm, this paper uses the properties of nodes of users in social networks to form the user influence factors. Then, the user with the biggest influence is set as the initial node of new community and and the local modularity is introduced into detecting the community structure. in order to make the result of community detection quick and efficient. Many experiments show that the improved algorithm can efficiently detect the community structure with large scale users and the results are stable. Therefore, this algorithm will have a wide applied prospect.
Gastrointestinal stromal tumors and shock

Gastrointestinal stromal tumors (GIST) are the most common mesenchymal tumor of the gastrointestinal tract. Clinically, they are associated with nonspecific symptoms, but some patients can present gastrointestinal bleeding with shock. We report two cases of GIST of the small bowel, revelated by hemorrhagic shock secondary to acute bleeding, succesfully treated by emergency surgery.
GAIN RATIO BASED FEATURE SELECTION METHOD FOR PRIVACY PRESERVATION

: Privacy-preservation is a step in data mining that tries to safeguard sensitive information from unsanctioned disclosure and hence protecting individual data records and their privacy. There are various privacy preservation techniques like k-anonymity, l-diversity and t-closeness and data perturbation. In this paper k-anonymity privacy protection technique is applied to high dimensional datasets like adult and census. since, both the data sets are high dimensional, feature subset selection method like Gain Ratio is applied and the attributes of the datasets are ranked and low ranking attributes are filtered to form new reduced data subsets. K-anonymization privacy preservation technique is then applied on reduced datasets. The accuracy of the privacy preserved reduced datasets and the original datasets are compared for their accuracy on the two functionalities of data mining namely classification and clustering using naïve Bayesian and k-means algorithm respectively. Experimental results show that classification and clustering accuracy are comparatively the same for reduced k-anonym zed datasets and the original data sets.
Wideband subharmonic mixer in bilateral finline at U-band

A wideband subharmonically pumped mixer is presented and demonstrated at U-band. A wide bandwidth from 40 to 60 GHz is achieved by asymmetric bilateral finline and a pair of anti-parallel diodes. The local oscillator signal passes through a novel microstrip-to-finline transition to the bilateral finline, which is helpful to impedance match. The transition structure enables the mixer to conveniently integrate with monolithic microwave integrated circuits (MMIC). The compact subharmonic mixer is fabricated on 0.254 mm thick Rogers Duroid 5880 substrate, which is suspended in the E-plane of a standard rectangular waveguide WR-19. Measurement result shows its conversion loss is less than 15 dB from 40 to 60 GHz. The isolations between each port are higher than 40 dB.
The Dissection of Expression Quantitative Trait Locus Hotspots

Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effects on gene expression: expression quantitative trait locus hotspots. We describe a set of exploratory graphical methods as well as a formal likelihood-based test for assessing whether a given hotspot is due to one or multiple polymorphisms. We first look at the pattern of effects of the locus on the expression traits that map to the locus: the direction of the effects and the degree of dominance. A second technique is to focus on the individuals that exhibit no recombination event in the region, apply dimensionality reduction (e.g., with linear discriminant analysis), and compare the phenotype distribution in the nonrecombinant individuals to that in the recombinant individuals: if the recombinant individuals display a different expression pattern than the nonrecombinant individuals, this indicates the presence of multiple causal polymorphisms. In the formal likelihood-based test, we compare a two-locus model, with each expression trait affected by one or the other locus, to a single-locus model. We apply our methods to a large mouse intercross with gene expression microarray data on six tissues.
University of Groningen Lower Plasma Magnesium, Measured by Nuclear Magnetic Resonance Spectroscopy, is Associated with Increased Risk of Developing Type 2 Diabetes Mellitus in Women

Background: Low circulating magnesium (Mg) is associated with an increased risk of developing type 2 diabetes mellitus (T2DM). We aimed to study the performance of a nuclear magnetic resonance (NMR)-based assay that quantifies ionized Mg in EDTA plasma samples and prospectively investigate the association of Mg with the risk of T2DM. Methods: The analytic performance of an NMR-based assay for measuring plasma Mg was evaluated. We studied 5747 subjects free of T2DM at baseline in the Prevention of Renal and Vascular End-stage Disease (PREVEND) study. Results: Passing–Bablok regression analysis, comparing NMR-measured ionized Mg with total Mg measured by the Roche colorimetric assay, produced a correlation of r = 0.90, with a slope of 1.08 (95% CI: 1.00–1.13) and an intercept of 0.02 (95% CI: −0.02–0.08). During a median follow-up period of 11.2 (IQR: 7.7–12.0) years, 289 (5.0%) participants developed T2DM. The association of NMR-measured ionized Mg with T2DM risk was modified by sex (Pinteraction = 0.007). In women, we found an inverse association between Mg and the risk of developing T2DM, independent of adjustment for potential confounders (HR: 1.80; 95% CI: 1.20–2.70). In men, we found no association between Mg and the risk of developing T2DM (HR: 0.90; 95%: 0.67–1.21). Conclusion: Lower NMR-measured plasma ionized Mg was independently associated with a higher risk of developing T2DM in women, but not in men.
On the effect of stemming algorithms on extractive summarization: a case study

In this paper, we discuss the efficiency of stemming algorithms and their contribution to the improvement of shallow summarization methods. We describe a benchmarking experiment on the use of two stemming algorithms and two different sets of stopwords in combination with two approaches to extractive summarization in Greek texts. The results of our experimentation show the limits of extractive summarization and stemming algorithms.
‘Home’ or away? The higher education choices of expatriate children in the United Arab Emirates

The purpose of the research upon which this article is based was to identify the factors that influence the higher education choices of expatriate children. The study involved a self-completed written questionnaire and structured face-to-face interviews with nineteen students at four international schools in the United Arab Emirates (UAE). The study found that the higher education choices of these expatriate children were most influenced by their need or desire to return to the place regarded as home; to study in the country where they intend to settle permanently; to live with, or be close to, siblings or extended members of their family; to minimize tuition, accommodation and general living costs; and to study in the location where they would feel most comfortable. For students leaving the UAE, rankings and institutional reputation were key determinants of choice of higher education institution. Students remaining in the UAE were far more likely to rely on word of mouth from family or friends. It is concluded that living an internationally mobile lifestyle has significant impacts on the choices made by expatriate children.
Improved POLSAR Image Classification by the Use of Multi-Feature Combination

Polarimetric SAR (POLSAR) provides a rich set of information about objects on land surfaces. However, not all information works on land surface classification. This study proposes a new, integrated algorithm for optimal urban classification using POLSAR data. Both polarimetric decomposition and time-frequency (TF) decomposition were used to mine the hidden information of objects in POLSAR data, which was then applied in the C5.0 decision tree algorithm for optimal feature selection and classification. Using a NASA/JPL AIRSAR POLSAR scene as an example, the overall accuracy and kappa coefficient of the proposed method reached 91.17% and 0.90 in the L-band, much higher than those achieved by the commonly applied Wishart supervised classification that were 45.65% and 0.41. Meantime, the overall accuracy of the proposed method performed well in both C- and P-bands. Polarimetric decomposition and TF decomposition all proved useful in the process. TF information played a great role in delineation between urban/built-up areas and vegetation. Three polarimetric features (entropy, Shannon entropy, T11 Coherency Matrix element) and one TF feature (HH intensity of coherence) were found most helpful in urban areas classification. This study indicates that the integrated use of polarimetric decomposition and TF decomposition of POLSAR data may provide improved feature extraction in heterogeneous urban areas.
Circular Economies and Canada ’ s Forest Sector

The concept of circular economies suggests that optimal flow of goods and services can be represented as a loop. This can be manifest in a process when products are recovered after a period of use and transformed into new goods, and when the last product may be used as the basis for a new iteration of products. The concept is also present in regional geographies, where resources may flow from point to point for processing and use, and where the final leg of the process brings materials back to the starting point. A popular example of the circular economy is the carbon cycle, which sees old products serve as the basis for new growth and eventually new commercial activity. The forest economy has the potential to take the circular approach. This paper describes the current state of Canada's forest sector and identifies barriers to achieving a true circular approach. For example, Ontario is a region where massive disruptions to the existing economy have left the industry in crisis. Opportunities for reinventing the forest sector are discussed, as are the potential impacts on employment and economic returns from this approach. Presented at the Work in a Warming World (W3) Researchers’ Workshop: “Greening Work in a Chilly Climate”, Toronto, Canada, November, 2011 Warren Mabee
Finding Ways to Bring Education to Everyone in Panama Through Mobile Learning

This paper presents the main features developed for a mobile learning application to expand the possibilities of learning for students from rural areas or those constrained by schedule and location to attend school. The work presented is focused on methodologies and tool selections to develop the system. Still remains one of the main concerns about the system, which consists on making sure the system is light in terms of power consumption and bandwidth needs.