Miracle-dz/UniFAR-FTUs huggingface dataset:
Respiratory Animal Models in the Common Marmoset (Callithrix jacchus)

Common marmosets (Callithrix jacchus) are small non-human primates (NHPs) that are often used for respiratory research. Translational animal models of various pulmonary diseases in marmosets have been developed in favor of models in old world monkeys (OWM, e.g., rhesus or cynomolgus monkeys). The marmoset has the size of a rat (350–450 g), is easier to handle, and the husbandry, care, and management of colonies is much easier compared to OWMs. In contrast to rodents, marmosets provide a high homology to humans, which become especially visible in lung architecture and branching pattern. Features of inflammatory (e.g., COPD) pulmonary diseases can be modeled in marmosets as well the species is used to study bacterial and viral infection. Models for human melioidosis, tuberculosis, anthrax, as well as infections with SARS-associated coronavirus (SARS-CoV), influenza A virus and adenovirus are already established. Toxicological studies often use marmoset monkeys for the advantage of immunological identical twins that are produced by a Callitrichinae-specific placentation type, which ultimately causes blood chimerism. Relatively new approaches in gene therapy use marmosets for respiratory disease research. In this review we will give an overview of existing respiratory marmoset models and their impact on biomedical research.
Affective Friendship that Constructs Globally Spanning Transnationalism: The Onward Migration of Filipino Workers from South Korea to Canada

Abstract This article explores how affective friendship of migrant Filipino workers constructs transnationalism that overarches different host countries. Following a sequence of ‘mobility and sedentariness’ through ‘multi-sited ethnography’ methods, I discuss the affective friendship that emerges out of a specific sociocultural context in Korea, namely activities of the Catholic congregation. I also demonstrate that such friendship is accompanied by onward migration to Canada through the transfer of ties in a new social setting. Moving beyond the duality of home and abroad, this study reveals that migrants’ transnationalism exhibits cosmopolitanism through the reconfiguration of their compatriot friendship into globally spanning, multi-local ties.
Gender gap in current school enrolment: selection among ”irregular” student?

September 2009AbstractMany developing countries face a pro-male gender gap in schooling, as boys are more likelyto be enrolled at school than girls. This paper examines whether the current enrolment gapprevails at the same time among ”regular” and ”irregular” children. Regular children arechildren who complete primary education between the age of 12 and 15 years. Irregularchildren are the rest. We investigate the gender gap in schooling empirically using dataprovided by the 2001 Cameroon Household Survey. The empirical framework allows for adiﬀerent gender eﬀect among regular and irregular children. It also accounts for selectioninto the two groups. Results show no male-female diﬀerence among regular children. Amongirregular children however, females are more likely to stay out of schools. We thereforesuggest that, independently of the source of the gender gap, it seems to be at work mostlyamong irregular children.
Zeptomole detection sensitivity of prostate-specific antigen in a rapid microtitre plate assay using time-resolved fluorescence.

Prostate-specific antigen (PSA) was detected in microtitre wells coated with a PSA-specific antibody using biotinylated antibody and streptavidin-coated, highly fluorescent 107 nm nanoparticles, which contained more than 30000 europium ions entrapped by beta-diketones. PSA was monitored directly on the surface of a well without any additional enhancement step. The sensitivity of the assay was 1.6 ng/L, corresponding to 50 fmol/L or 250 zeptomoles (250 x 10(-21) mol/L) of PSA. The high specific activity and low non-specific binding of the streptavidin-coated nanoparticles improved the sensitivity of the PSA assay 100-fold compared to the conventional europium-labelled streptavidin tracer in the same assay format. Additionally, the streptavidin-coated nanoparticle label made very rapid assays possible, due to the high affinity of the streptavidin-biotin complex and a high number of binding sites available for tracing the biotinylated antibody on the surface. Due to the inherent problems of tracing analyte with a complex of biotinylated antibody and streptavidin-coated nanoparticles, the streptavidin-coated nanoparticles reacting with the surface-captured analyte and biotinylated antibody was favoured and factors influencing this are discussed. This universal labelling technology can be applied to detect any biotinylated molecule, either in solution or on a solid phase, in order to improve detection sensitivities in many areas of biochemical analysis, such as cyto- and histochemistry, multianalyte DNA-chip assays and single-particle assays.
Keyword search on external memory data graphs

Keyword search on graph structured data has attracted a lot of attention in recent years. Graphs are a natural "lowest common denominator" representation which can combine relational, XML and HTML data. Responses to keyword queries are usually modeled as trees that connect nodes matching the keywords. In this paper we address the problem of keyword search on graphs that may be significantly larger than memory. We propose a graph representation technique that combines a condensed version of the graph (the "supernode graph") which is always memory resident, along with whatever parts of the detailed graph are in a cache, to form a multi-granular graph representation. We propose two alternative approaches which extend existing search algorithms to exploit multigranular graphs; both approaches attempt to minimize IO by directing search towards areas of the graph that are likely to give good results. We compare our algorithms with a virtual memory approach on several real data sets. Our experimental results show significant benefits in terms of reduction in IO due to our algorithms.
Social support from fellow group members triggers additional effort in groups

This research demonstrates social support from fellow group members as unique trigger of additional effort and performance in groups. Support-induced effort gains are shown both compared with groups without social support and individual work. Study 1 examined existing beliefs about motivating group work among employees with professional group work experience (n = 130). The results revealed social support as one of the most frequently reported sources of group-induced effort gains. Study 2 explored self-reported effort intentions in group training scenarios among athletes (n = 94). Finally, Study 3 examined performance as a manifest indicator of effort in an experimental persistence task among students (n = 88). The results of Study 2 and Study 3 showed significant gains due to social support in both self-reported effort and manifest performance, respectively. Together, the results demonstrate that receiving social support from fellow group members leads to higher effort in groups at the level of existing beliefs about motivating group work, at the level of effort intentions, and at the level of manifest performance behavior. The observed findings cannot be explained by established sources of motivation gains in groups such as social comparison or social indispensability. Copyright © 2014 John Wiley & Sons, Ltd.
An effective approach for classification of advanced malware with high accuracy

Combating malware is very important for software/systems security, but to prevent the software/systems from the advanced malware, viz. metamorphic malware is a challenging task, as it changes the structure/code after each infection. Therefore in this paper, we present a novel approach to detect the advanced malware with high accuracy by analyzing the occurrence of opcodes (features) by grouping the executables. These groups are made on the basis of our earlier studies [1] that the difference between the sizes of any two malware generated by popular advanced malware kits viz. PS-MPC, G2 and NGVCK are within 5 KB. On the basis of obtained promising features, we studied the performance of thirteen classifiers using N-fold cross-validation available in machine learning tool WEKA. Among these thirteen classifiers we studied in-depth top five classifiers (Random forest, LMT, NBT, J48 and FT) and obtain more than 96.28% accuracy for the detection of unknown malware, which is better than the maximum detection accuracy (95.9%) reported by Santos et al (2013). In these top five classifiers, our approach obtained a detection accuracy of 97.95% by the Random forest.
WhiB7, an Fe-S-dependent Transcription Factor That Activates Species-specific Repertoires of Drug Resistance Determinants in Actinobacteria*

Background: WhiB7 is essential for antibiotic resistance in M. tuberculosis. Results: WhiB7 requires conserved residues, including a redox-sensitive center and DNA-binding motif, to coordinate transcription of species-specific drug resistance genes in diverse Actinobacteria. Conclusion: WhiB7 activates species-specific drug resistance genes in Actinobacteria. Significance: Understanding WhiB7 activity may allow the development of drugs that sensitize bacteria to antibiotics. WhiB-like (Wbl) proteins are well known for their diverse roles in actinobacterial morphogenesis, cell division, virulence, primary and secondary metabolism, and intrinsic antibiotic resistance. Gene disruption experiments showed that three different Actinobacteria (Mycobacterium smegmatis, Streptomyces lividans, and Rhodococcus jostii) each exhibited a different whiB7-dependent resistance profile. Heterologous expression of whiB7 genes showed these resistance profiles reflected the host's repertoire of endogenous whiB7-dependent genes. Transcriptional activation of two resistance genes in the whiB7 regulon, tap (a multidrug transporter) and erm(37) (a ribosomal methyltransferase), required interaction of WhiB7 with their promoters. Furthermore, heterologous expression of tap genes isolated from Mycobacterium species demonstrated that divergencies in drug specificity of homologous structural proteins contribute to the variation of WhiB7-dependent drug resistance. WhiB7 has a specific tryptophan/glycine-rich region and four conserved cysteine residues; it also has a peptide sequence (AT-hook) at its C terminus that binds AT-rich DNA sequence motifs upstream of the promoters it activates. Targeted mutagenesis showed that these motifs were required to provide antibiotic resistance in vivo. Anaerobically purified WhiB7 from S. lividans was dimeric and contained 2.1 ± 0.3 and 2.2 ± 0.3 mol of iron and sulfur, respectively, per protomer (consistent with the presence of a 2Fe-2S cluster). However, the properties of the dimer's absorption spectrum were most consistent with the presence of an oxygen-labile 4Fe-4S cluster, suggesting 50% occupancy. These data provide the first insights into WhiB7 iron-sulfur clusters as they exist in vivo, a major unresolved issue in studies of Wbl proteins.
Is Winning Everything? The Relative Contributions of Motivational Climate and Won-Lost Percentage in Youth Sports

The purpose of this study was to examine the main and interactive effects of motivational climate and won-lost percentage upon young athletes’ evaluations of their coaches, enjoyment of their team experience, and perceived parental liking for the coach. A total of 268 male and female youth basketball players, aged 10 to 15 years, completed the Motivational Climate Scale for Youth Sports (Smith, Cumming, & Smoll, in press) and selected attitudinal scales relating to their sport enjoyment and their evaluations of their coach. Regular season won-lost percentages were calculated for each of the 50 teams. Hierarchical linear modeling was used to predict player evaluations of the coach. Attitudes toward the coach were positively associated with perceptions of a mastery-involved climate and negatively associated with perceptions of an ego-involved climate. Won-lost percentages positively predicted players’ evaluations of their coach's knowledge and teaching ability, but accounted for far less attitudinal variance than did the motivational climate measures. Consistent with earlier findings, young athletes’ sport enjoyment, and evaluations of their coach were more strongly related to coaching behaviors than to their team's won-lost record. No significant interactions involving winning and motivational climate were found.
The central role of fallacious thinking in science education

This manuscript presents a model of conceptual change from a social constructivism perspective by examining the fallacious argumentation and discourse patterns revealed by students as they form scientific and social judgments. A central premise is advanced that likens how individuals react when anomalous data is presented in conflict with their own scientific beliefs to how they react when the social, moral, and ethical beliefs held by others are in conflict with their own convictions. A framework is provided that will allow science educators to examine “samples of thought” related to “social thinking. ” A special case of fallacious reasoning—the effects of core beliefs on argumentation—seems to suggest the need for a view of science that moves beyond traditional (positivistic and postpositivistic) notions of “scientific” thinking and allows for the social construction of knowledge. © 1997 John Wiley & Sons, Inc. Sci Ed81:483-496, 1997.
Attributions for Success: Exploring the Potential Impact on Music Learning in High School

Students' beliefs about why they may or may not be successful in various pursuits can influence the extent to which they are likely to invest effort in these pursuits and which in turn affects the level of achievement likely to be experienced. Attributional beliefs assign causes for success and failure to a range of factors, including ability, effort, task difficulty and luck (Weiner, 1986). This paper reports on high school students' beliefs about the reasons for their success or otherwise in school subjects and other activities, using data collected as part of a larger study using a researcher-designed Survey of Musical Experiences and Self-Concept. The participants (N=282) were a mixture of Year 9 and 10 students from three high schools in metropolitan Adelaide. The data collected reveals that the facet of 'enjoyment' was perceived as being an important element among the reasons given for achieving success. There are implications for teaching in general, as well as specific applications to high school music education practices.
An Upstream Oct-1- and Oct-2-Binding Silencer Governs B29 (Igβ) Gene Expression1

The B cell-specific B29 (Igβ) gene is activated in the earliest B cell precursors and is expressed throughout B cell development. Tissue-specific expression of the murine B29 gene is controlled by a B cell-specific promoter whose activity is governed by a cassette of upstream transcriptional silencers. This study describes a potent new silencer that is located 5′ of the previously identified B29 silencer elements, FROG and TOAD. Like these known elements, the new B29 silencer is not restricted to the B29 promoter. Nuclear proteins from all cell lines tested interacted with this A+T-rich sequence, which closely resembled a noncanonical octamer binding motif and also conformed to the consensus sequence for nuclear matrix attachment regions. Interaction of Oct-1 and Oct-2 with the B29 A+T-rich sequence was confirmed using octamer-specific Abs. Oct-1/Oct-2 binding was required for the inhibitory activity of this sequence because mutations that blocked Oct-1/Oct-2 binding also eliminated inhibition of the B29 promoter. This B29 A+T-rich sequence specifically interacted with isolated nuclear matrix proteins in vitro, suggesting that it may also function as a matrix attachment region element. Maintenance of the level of B29 gene expression through the interaction of the minimal promoter and the upstream silencer elements FROG, TOAD, and the A+T-rich Oct-1/Oct-2 binding motif may be essential for normal B cell development and/or function.
Chabot: Retrieval from a Relational Database of Images

Selecting from a large, expanding collection of images requires carefully chosen search criteria. We present an approach that integrates a relational database retrieval system with a color analysis technique. The Chabot project was initiated at our university to study storage and retrieval of a vast collection of digitized images. These images are from the State of California Department of Water Resources. The goal was to integrate a relational database retrieval system with content analysis techniques that would give our querying system a better method for handling images. Our simple color analysis method, if used in conjunction with other search criteria, improves our ability to retrieve images efficiently. The best result is obtained when text-based search criteria are combined with content-based criteria and when a coarse granularity is used for content analysis. >
A Review on Automatic Analysis of Human Embryo Microscope Images

Over the last 30 years the process of in vitro fertilisation (IVF) has evolved considerably, yet the efficiency of this treatment remains relatively poor. The principal challenge faced by doctors and embryologists is the identification of the embryo with the greatest potential for producing a child. Current methods of embryo viability assessment provide only a rough guide to potential. In order to improve the odds of a successful pregnancy it is typical to transfer more than one embryo to the uterus. However, this often results in multiple pregnancies (twins, triplets, etc), which are associated with significantly elevated risks of serious complications. If embryo viability could be assessed more accurately, it would be possible to transfer fewer embryos without negatively impacting IVF pregnancy rates. In order to assist with the identification of viable embryos, several scoring systems based on morphological criteria have been developed. However, these mostly rely on a subjective visual analysis. Automated assessment of morphological features offers the possibility of more accurate quantification of key embryo characteristics and elimination of inter- and intra-observer variation. In this paper, we describe the main embryo scoring systems currently in use and review related works on embryo image analysis that could lead to an automatic and precise grading of embryo quality. We summarise achievements, discuss challenges ahead, and point to some possible future directions in this research field.
Assessment of cartilage disorder in knee with VAG signals using wavelet transform and neural network

Detection of knee joint pathology at an early stage is vital for the joint affected by degenerative disorders, since appropriate treatment can facilitate the extended functionality at the knee joint. Vibroarthrographic (VAG) signals could be used to develop a non-invasive methodology for monitoring articular cartilage pathology. This paper deals with the development of such a tool for the detection of abnormalities in knee joint using wavelet transform. Since VAG signals are non — stationary, wavelet transform are best suited to extract the statistical feature. The classification is performed using feed forward back propagation neural network.
CNC machine based on embedded wireless and Internet of Things for workshop development

This paper focus on the integration of wireless technology and CAD/CAM system for CNC workshop development. A specific case study is described a system based on embedded wireless device and Internet of Things (IoT) concept with Bezier techniques for the proposed model. The focus of the case study is to show a complete stage of manufacturing process starting from modeling in CAD system passing through CAM system, transferring NC code, gathering machine data, monitoring whole process and finally manufacturing product. Using MATLAB and UG-NX software for modeling, Monitoring machining process using temperature, accelerometers and gyroscope sensors based on IoT concept. Transferring NC codes to CNC machines using FTP protocol and DNC software, real-time report demonstrate information about machine name, parts progress, time, operation condition and Machine Cycle Time depending on DNC network.
Knowing the Tweeters: Deriving Sociologically Relevant Demographics from Twitter

A perennial criticism regarding the use of social media in social science research is the lack of demographic information associated with naturally occurring mediated data such as that produced by Twitter. However the fact that demographics information is not explicit does not mean that it is not implicitly present. Utilising the Cardiff Online Social Media ObServatory (COSMOS) this paper suggests various techniques for establishing or estimating demographic data from a sample of more than 113 million Twitter users collected during July 2012. We discuss in detail the methods that can be used for identifying gender and language and illustrate that the proportion of males and females using Twitter in the UK reflects the gender balance observed in the 2011 Census. We also expand on the three types of geographical information that can be derived from Tweets either directly or by proxy and how spatial information can be used to link social media with official curated data. Whilst we make no grand claims about the representative nature of Twitter users in relation to the wider UK population, the derivation of demographic data demonstrates the potential of new social media (NSM) for the social sciences. We consider this paper a clarion call and hope that other researchers test the methods we suggest and develop them further.
ExpertDiscovery and UGENE integrated system for intelligent analysis of regulatory regions of genes

The task of automatic extraction of the hierarchical structure of eukaryotic gene regulatory regions is in the junction of the fields of biology, mathematics and information technologies. A solution of the problem involves understanding of sophisticated mechanisms of eukaryotic gene regulation and applying advanced data mining technologies. In the paper the integrated system, implementing a powerful relation mining of biological data method, is discussed. The system allows taking into account prior information about the gene regulatory regions that is known by the biologist, performing the analysis on each hierarchical level, searching for a solution from a simple hypothesis to a complex one. The integration of ExpertDiscovery system into UGENE toolkit provides a convenient environment for conducting complex research and automating the work of a biologist. For demonstration, the system has been applied for recognition of SF1, SREBP, HNF4 vertebrate binding sites and for the analysis the human gene regulatory regions that promote liver-specific transcription.
LSSVM model of oil holdup of oil-water two phase flow using thermal method based on HHT

A new model based on least square support vector machines (LSSVM) and Hilbert-Huang transform (HHT) has been proposed for the first time, which is capable of forecasting oil holdup of oil-water two phase flow. Owing to the temperature signal of oil-water two phase flow is greatly disturbed by noises, which results in a limited measurement range of oil holdup. In order to solve the problem, a new signal processing method based on the improved HHT is used. With its ideal performance on local adaptability and time-frequency analysis, noises are removed. Experimental studies were carried out to compare the HHT with the wavelet transform. The instantaneous fluctuated amplitude and the standard deviation are obtained form the last residue component of HHT, together with total flux were employed as inputs of LSSVM model. In order to improve the predictive accuracy of the LSSVM model, a Genetic Arithmetic (GA) has been adopted to determine the optimal parameters of LSSVM automatically. The experiment results show that the average measurement error of LSSVM model was 0.542% in the range of 8% to 90% oil holdup.