Miracle-dz/UniFAR-FTUs huggingface dataset:
The complexity of phosphorylated H2AX foci formation and DNA repair assembly at DNA double-strand breaks

The maintenance of genome stability requires efficient DNA double-stranded break (DSB) repair mediated by the phosphorylation of multiple histone H2AX molecules near the break sites. The phosphorylated H2AX (γ-H2AX) molecules form foci covering many megabases of chromatin. The formation of g-H2AX foci is critical for efficient DNA damage response (DDR) and for the maintenance of genome stability, however, the mechanisms of protein organization in foci is largely unknown. To investigate the nature of γ-H2AX foci formation, we analyzed the distribution of γ-H2AX and other DDR proteins at DSB sites using a variety of techniques to visualize, expand and partially disrupt chromatin. We report here that γ-H2AX foci change composition during the cell cycle, with proteins 53BP1, NBS1 and MRE11 dissociating from foci in G2 and mitosis to return at the beginning of the following G1. In contrast, MDC1 remained colocalized with g-H2AX during mitosis. In addition, while γ-H2AX was found to span large domains flanking DSB sites, 53BP1 and NBS1 were more localized and MDC1 colocalized in doublets in foci. H2AX and MDC1 were found to be involved in chromatin relaxation after DSB formation. Our data demonstrates that the DSB repair focus is a heterogeneous and dynamic structure containing internal complexity.
Application of Ontology-Based Knowledge Representation to Design Reuse

Ontolingua, a language for ontology-based knowledge representation, provides the capability to construct comprehensive characterizations of knowledge bases. While the ability to characterize the content of a knowledge base is not new, Ontolingua includes a number of features that greatly enhance conventional data representation and modeling technologies through the incorporation of semantic context. In addition to supporting object-oriented modeling techniques, Ontolingua enables representation of constraints, definitions, and relationships among terms within ontologies. This facility provides a framework that supports automated translation among knowledge bases with differing data models and physical implementations. The ability to formally describe and unambiguously distinguish between diverse data sources is essential to enabling reuse of intellectual property. This paper presents a high-level view of ontology-based knowledge representation and an approach to solving the intellectual property reuse problem through the application of this technology.
The Well-Being of Australian Service Mothers

In recent years servicewomen with dependent children have for the first time in history been deployed into conflict zones in support of Australian Defence Force operations. This represents a significant social change, and the implications of deployment on the health of these service mothers are not fully understood. Data from women who participated in the Middle East Area of Operations Census study were analyzed to compare the psychological and physical symptoms reported by service mothers with service women who had no dependent children at the time of deploying to Afghanistan and/or Iraq. Of the 921 women who were included in this analysis, 235 had dependent children and 686 had no dependent children (comparison group). Service mothers were significantly older and were more likely to have served in the Air Force than women in the comparison group. Findings demonstrate that serving mothers were not at any significantly higher risk of psychological distress, post-traumatic stress symptoms, alcohol misuse, or reporting of somatic symptoms, than women who had no dependent children. A number of possible explanations for these findings are discussed, including the healthy soldier/mother effect, support from partners and extended family members, and collegial networks.
Successful and safe use of Q‐switched lasers in the treatment of nevus of Ota in children with phototypes IV–VI

Nevus of Ota represents congenital dermal melanocytosis in a trigeminal distribution, most commonly occurring in Asian individuals and other individuals with skin of color. Evidence suggests early treatment is beneficial. Multiple reports have shown efficacy and safety of Q‐switched laser treatment in adults. There is little data on children and in non‐Asian skin types. This series was done to demonstrate safe and effective use of Q‐switched laser therapy in children of multiple skin types.
Post-traumatic Stress Reaction Symptoms among Turkish Students: Assessments One and Six Months after a Terrorist Attack in Istanbul

Objective: This study investigated high school students’ symptoms of post-traumatic stress disorder one and six months after a terrorist attack in Istanbul, Turkey on November 2003, and the relationship between the severity of the post-traumatic stress disorder symptoms and the level of depression and anxiety. Patients and Methods: 113 students filled in questionnaires and were assessed by use of Child Post-traumatic Stress Reaction Index, Children’s Depression Inventory, and State-Trait Anxiety Inventory for Children. Results: We found high rates of post-traumatic stress reactions at the end of the first month (51.3%). The assessment of the students at the end of six months revealed that the symptoms of posttraumatic stress disorder tended to persist, although the total scores of Child Pos t-traumatic Stress Reaction Index were decreased. Post-traumatic st ress disorder scores were significantly correlated with the scores of depression and anxiety at both assessments (p < 0.05). Conclusion: These results indicate that post-traumatic stress disorder symptoms can be seen after a stressful event that was perceived as life-threatening by at least some of the children, even though the children did not experience major losses, injury, or ongoing disruption in the community.
Combining text categorization and dialog modeling for speaker role identification on call center conversations

In this paper, we address the problem of speaker role identification on a corpus of manually transcribed call center conversations. We first tackle it as a text categorization task. Then, we combine these categorization results with a dialog modeling approach. We achieve 93% of correct role assignment with the least method. Our method also offers the possibility to extract text spans specific to each role. These strings slightly improve the role identification results and are an interesting element for conversation analysis.
Radar ATR of maritime targets

For commercial ship traffic the automatic identification system (AIS) is obligatory for all vessels above a certain size and thus warrants their cooperative classification and even identification. However, for smaller craft and especially for non-cooperative objects with hostile intent, the classification has to rely on classical approaches of automatic target recognition (ATR), which mostly are based on radar due to its day/night and all-weather capabilities. This leads to applications such as coastal surveillance for border control, the protection of harbour installations, ship self-defence or the suppression of drug trafficking, where the classification of ships by means of ATR schemes becomes more and more important. This is especially true in times of asymmetric (terrorist) threat and piracy. With a modern high resolution radar one has the choice of two different ways of target imaging. The first is 2D imaging, either from an airborne (SAR) or from a ground-based platform (ISAR). The latter depends on the relative motion of the target itself and therefore may be difficult in the case of non-cooperative targets. The desired axis of rotation should be vertical, which may not be the case when high sea states cause strong roll and pitch motion for smaller ships. Moreover, when the hostile ship is approaching or receding on a straight course, there is no relative rotation that lends itself to ISAR exploitation.
Prevalence of otitis externa in stray cats in northern Italy

Feline otitis externa is a dermatological disorder that has not been evaluated much in stray cats. One hundred and eighty-seven stray cats were randomly selected during a trap–neuter–release programme to investigate the prevalence of otitis externa in stray cat colonies in northern Italy. Swabs for cytological examination were obtained from the external ear canal of each cat. A direct otoscopic assessment of the external ear canal was made in 86/187 cats. Cytological evidence of otitis externa was present in 55.1% of cats. The influence on otitis of age, gender, habitat and season of sampling was tested, but no risk factors were found. Otodectes cynotis (as a sole agent or in combination) was the primary cause of otitis in 53.3% of cats. Cocci and rods, either alone or in combination with other agents, were perpetuating factors in 71.8% and 29.1% of cats, respectively. Pregnancy status was a risk factor for otitis caused by coccal infections. Malassezia species, alone or in combination, was the perpetuating factor in 50.5% of cats with otitis. Urban habitat and winter season were risk factors for otitis associated with Malassezia species. Demodex cati was identified as an incidental finding in two cats. There was good agreement between otoscopy and cytology with regard to the diagnosis of otitis externa. The results of this study show a high prevalence of otitis externa in stray colony cats and provide information on causal factors for feline otitis externa.
Region Of Interest Based Image Classification: A Study in MRI Brain Scan Categorization

The principle challenge ofMRI brain scan classification is the capture of the features of interest in such a way that relative spatial information is retained while at the same time ensuring tractability. Some popular feature representations are directed at colour, texture and/or shape. Little work has been done on techniques that maintain the relative structure of the features of interest. This chapter describes a number of mechanisms whereby this may be achieved. More specifically, the work is directed at medical image classification according to a particular feature of interest that may appears across a given image set. There are many medical studies [1, 8, 10, 12, 15, 24, 26, 32, 38, 40, 49] that demonstrate that the shape and size of specific regions of interest plays an important role in medical image classification. One example (and the application focus of the work described) is that the shape and size of the corpus callosum, a prominent feature located in brain MRI scans, is influenced by neurological diseases such as epilepsy and autism, and by special abilities (such as mathematical or musical ability) [35, 43, 47].
Design and analysis of a lean interface for Sanskrit corpus annotation

We describe an innovative computer interface designed to assist annotators in the efficient selection of segmentation solutions for proper tagging of Sanskrit corpora. The proposed solution uses a compact representation of the shared forest of all segmentations. The main idea is to represent the union of all segmentations, abstracting from the sandhi rules used, and aligning with the input sentence. We show that this representation provides an exponential saving, in both space and time. The segmentation methodology is lexicon-directed. When the lexicon does not have full coverage of the corpus vocabulary, some chunks of the input may fail to be recognized. We designed a lexicon-acquisition facility, which remedies this incompleteness and makes the interface more robust. This interface has been implemented, and is currently being applied to the annotation of the Sanskrit Library corpus. Evaluation over 1,500 sentences from the Pancatantra text shows the effectiveness of the proposed interface on real corpus data.
Neurobehavioral evidence for working‐memory deficits in school‐aged children with histories of prematurity

Cognitive performance in 7‐ to 9‐year‐old preterm neonatal intensive‐care survivors was compared with that in age‐matched control children. Non‐verbal memory span, spatial working‐memory abilities, planning, set‐shifting, and recognition memory for both spatial and patterned stimuli were assessed using the Cambridge Neuropsychological Testing Automated Battery. Relative to children in the control group, neonatal intensive‐care unit (NICU) survivors demonstrated 25% more memory errors on the spatial working‐memory task. Their use of strategy on this task was similar to a control group of 5‐year‐olds. Planning times on‘Tower of London’problems were long relative to those of term controls. NICU survivors demonstrated poorer pattern recognition as well as a shorter spatial memory span. The groups did not differ in visual‐discrimination learning or in spatial‐recognition memory. No specific neonatal risk factor accounted for the observed differences, although scores on the Neurobiological Risk Score (NBRS), a composite measure of neonatal risk, did predict several aspects of later task performance. Whether these data reflect a developmental delay in brain maturation in NICU survivors or the presence of a permanent information‐processing deficit due to adverse neonatal events must be assessed through continued follow‐up.
Spoken language understanding with kernels for syntactic/semantic structures

Automatic concept segmentation and labeling are the fundamental problems of spoken language understanding in dialog systems. Such tasks are usually approached by using generative or discriminative models based on n-grams. As the uncertainty or ambiguity of the spoken input to dialog system increase, we expect to need dependencies beyond n-gram statistics. In this paper, a general purpose statistical syntactic parser is used to detect syntactic/semantic dependencies between concepts in order to increase the accuracy of sentence segmentation and concept labeling. The main novelty of the approach is the use of new tree kernel functions which encode syntactic/semantic structures in discriminative learning models. We experimented with support vector machines and the above kernels on the standard ATIS dataset. The proposed algorithm automatically parses natural language text with off-the-shelf statistical parser and labels the syntactic (sub)trees with concept labels. The results show that the proposed model is very accurate and competitive with respect to state-of-the-art models when combined with n-gram based models.
Fast Key-Word Searching via Embedding and Active-DTW

In this paper we present a novel approach for fast search of handwritten Arabic word-parts within large lexicons. The algorithm runs through three steps to achieve the required results. First it warps multiple appearances of each word-part in the lexicon for embedding into the same euclidean space. The embedding is done based on the warping path produced by the Dynamic Time Warping (DTW) process while calculating the similarity distance. In the next step, all samples of different word-parts are resampled uniformly to the same size. The $kd$-tree structure is used to store all shapes representing word-parts in the lexicon. Fast approximation of $k$-nearest neighbors generates a short list of candidates to be presented to the next step. In the third step, the Active-DTW~\cite{sridha99} algorithm is used to examine each sample in the short list and give final accurate results. We demonstrate our method on a database of $23,500$ images of word-parts extracted from the IFN/ENIT and 22,000 images collected from 93 writers. Our method achieves a speedup of 5 orders of magnitude over the exact method, at the cost of only a 3.8\% reduction in accuracy.
Feature selection for urban impervious surfaces estimation using optical and SAR images

Urban impervious surfaces, such as transport related land (e.g., roads, streets, and parking lots) and building roof tops (commercial, residential, and industrial areas), have been widely recognized as important indicator for urban environments. Numerous methods have been proposed to estimate impervious surfaces from remotely sensed images. However, most of these approaches were proposed with optical remote sensing images, and accurate estimation of impervious surfaces remains challenging due to the diversity of urban land covers. This study presents the effort to synergistically combine optical and SAR data to improve the mapping of impervious surfaces using the Random Forest (RF). The Multilayer Perceptron, Support Vector Machine, and RF are compared for impervious surfaces mapping with the single use of optical image and with the combined optical and SAR images. Experiment shows some interesting results: 1) synergistic use of SPOT-5 and TerraSAR-X images produced more accurate classification of impervious surface mapping, no matter what combinations of features are used; 2) The SAN-based features appeared to provide effective complementary information to the conventional GLCM-based features for the classification, increasing the accuracy by about 0.6% by using supervised classifiers; 3) SVM and RF tended to be superior to MLP for the fusion of SPOT-5 and TerraSAR-X images for LULC classification and ISE. RF is better for the LULC classification as it better handled the spectral confusion among sub types of impervious and non-impervious land covers, while SVM appeared more stable before and after the combination of sub land cover types, and thus is more suitable for the ISE with the classification strategies of mapping impervious surface.
Analyzing Social Support on the Experience Project CS 224 W Project

More and more people are turning online for social support, and large social networking/online support sites such as the Experience Project have seen incredible growth in the past few years. Using network analysis, we analyze the structure and dynamics of social support in the Experience Project, where users anonymously write posts about emotional events and comment on each others posts. We define two types of social support: active suggestions or solutions to their problem, and passive sympathy and commiseration, and analyze the differences in propagation behavior in the network, finding some support for the hypothesis that active support results in longer cascades. We find that social support improves network modularity, and that influence on cascades is not strongly correlated with number of friends.
Radon levels in abandoned metalliferous mines, Devon, southwest England.

Radon levels underground in two abandoned mines in Devon, United Kingdom, are reported and analyzed. Extremely high levels have been noted, 7,100,000 Bq m(-3) being the highest level recorded. This is approximately 89 times higher than the highest published radon level for caves and mines in Devon and Cornwall, England, which is 80,000 Bq m(-3). These levels have significant health implications for both casual and occupational mine explorers.
Significant Shift in Median Guinea Pig Infectious Dose Shown by an Outbreak-Associated Listeria monocytogenes Epidemic Clone Strain and a Strain Carrying a Premature Stop Codon Mutation in inlA

ABSTRACT Listeria monocytogenes contains (i) epidemic clone (EC) strains, which have been linked to the majority of listeriosis outbreaks worldwide and are overrepresented among sporadic cases in the United States, and (ii) strains commonly isolated from ready-to-eat foods that carry a mutation leading to a premature stop codon (PMSC) in inlA, which encodes the key virulence factor internalin A (InlA). Internalin A binds certain isoforms of the cellular receptor E-cadherin to facilitate crossing the intestinal barrier during the initial stages of an L. monocytogenes infection. Juvenile guinea pigs, which express the human isoform of E-cadherin that binds InlA, were intragastrically challenged with a range of doses of (i) an EC strain associated with a listeriosis outbreak or (ii) a strain carrying a PMSC mutation in inlA. Recovery of L. monocytogenes from tissues (i.e., liver, spleen, mesenteric lymph nodes, and ileum) was used to develop strain-specific dose-response curves on the basis of individual and combined organ data. Modeling of individual and combined organ data revealed an approximate 1.2 to 1.3 log10 increase in the median infectious dose for the strain carrying a PMSC in inlA relative to that for the EC strain. Inclusion of the strain parameter significantly improved the goodness of fit for individual and combined organ models, indicating a significant shift in median infectious dose for guinea pigs challenged with an inlA PMSC strain compared to that for guinea pigs challenged with an EC strain. Results from this work provide evidence that the L. monocytogenes dose-response relationship is strain specific and will provide critical data for enhancement of current risk assessments and development of future risk assessments.
Forest School for All

Introduction: Setting the Scene - Sara Knight PART ONE: NURSERY AND PRIMARY SCHOOL-BASED FOREST SCHOOL Breaking through Concrete: The Emergence of Forest School in London - Katherine Milchem Forest School: A Whole-School Approach - Clare Lamb Developing Practice and Delivering a Forest School Programme for Children Identified as Gifted and Talented - Tracey Maciver Using Forest School to Make the Transition to High School - Alisdair Horning PART TWO: FOREST SCHOOL, SOCIAL AND EMOTIONAL NEEDS Supporting Emotional and Social Development in Forest School with Adolescents - Clare Neenan with Sara Knight Forest School: An Alternative Curriculum - Ross Evans Learning from Working with Disaffected Year 10 Pupils - Rich Sylvester Maintaining the Forest School Ethos while Working with 14 to 19-Year-Old Boys - Jon Cree PART THREE: FOREST SCHOOL AND YOUNG PEOPLE WITH PARTICULAR NEEDS Removing Barriers: Getting Children with Physical Challenges into the Woods - Fiona Hopkins SEALs in the Woods! - Xavier Elonquin and Tina Hutchinson Forest School and Looked-after Children - Rebecca Wicks Autism, Art and Nature as Relational Aspects of Forest School - Kevin Burrows PART FOUR: USING FOREST SCHOOL STRATEGICALLY Addicts and Forest School - Mike Brady Forest School for Families - Lucy Partridge and Wendy Taylor Forest School Countywide: A Norfolk Perspective - Louise Ambrose Edinburgh's Forest School Partnership Project 'Building Local Capacity' - Jenny Watters Conclusion - Sara Knight