Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of Typical and Atypical Hangman's Fractures

Study Design Retrospective study of a prospectively maintained database. Objective Our aim was to retrospectively review management and outcomes of patients with low-grade hangman's fractures, specifically looking at differences in outcomes between collars and halo immobilization. We also studied fracture patterns and their treatment outcomes. Methods Forty-one patients with hangman's fractures were identified from 105 patients with axis fractures between 2007 and 2013. Typical hangman's fractures were defined as traumatic spondylolisthesis of the axis causing a bilateral pars interarticularis fracture. Fractures involving the posterior cortex of C2 on one or both sides or an asymmetrical pattern were defined as atypical. Results There were 41 patients with a mean age of 59 years, with 13 (31.7%) typical and 28 (68.2%) atypical fractures. There were 22 (53.6%) type 1 fractures, 7 (41.4%) type 2 fractures, and 2 (4.9%) type 2a fractures in this series. Cervical collars were used to manage 11 patients (27% of all patients with hangman's fractures) and halo orthosis was used in 27 (65.8%). Three (7.3%) patients underwent surgical fixation of the fracture. Bony union was achieved in all patients on radiologic follow-up. Permanent neurologic deficit occurred in one patient due to associated injuries. Neck pain and stiffness were reported more commonly in the atypical group, but this finding was not statistically significant. Conclusions The majority of hangman type fractures can be treated nonoperatively. We found no difference in outcomes between a rigid collar or halo immobilization for treatment of low-grade fractures. Radiologic follow-up is essential to identify cases of nonunion.
Bioinformatics Applications Note Multi-query Sequence Blast Output Examination with Museqbox

MuSeqBox is a program to parse BLAST output and store attributes of BLAST hits in tabular form. The user can apply a number of selection criteria to filter out hits with particular attributes. MuSeqBox provides a powerful annotation tool for large sets of query sequences that are simultaneously compared against a database with any of the standard stand-alone or network–client BLAST programs. We discuss such application to the problem of annotation and analysis of EST collections. Availability: The program was written in standard C++ and is freely available to noncommercial users by request from the authors. The program is also available over the web at The ready availability of complete genomes necessitates computational approaches to functional genome annotation (Brenner, 1999). A starting point for any such analysis is gene identification and annotation on the basis of inferred homology to previously established genes and gene products. The NCBI BLAST database search tool (Altschul et al., 1997) is probably the most popular program designed to solve single query problems. For genome-wide comparisons, the comparison challenge changes from the standard one-to-many to a many-to-many query problem, for example when comparing all proteins of one bacterial species to all proteins from another species (Koonin et al., 2000). In this case, a first step analysis might involve successive applications of BLAST with each protein of one species in turn serving as a query against the database of all protein sequences of the second species. Inspection and interpretation of what may be thousands of individual BLAST output files clearly must involve automated post-processing of the output (e.g. Sonnhammer and Durbin, 1994). We describe our MuSeqBox program that was developed for such applications. MuSeqBox serves as a filter that stores only essential features of BLAST hits in tabular form. Flexible 'slicing and dicing' capabilities allow post-processing of the hit table to select only hits with particular attributes. We first describe the general capabilities of the program and then discuss an exemplary application of annotation and interpretation of species-specific sets of Expressed Sequence Tags (ESTs).
H2/H∞ approach to the histogram method for density estimation

In this paper, we study nonparametric density estimation by the histogram method. Histogram is interpreted as quantization, which decreases the amount of information. Then interpolation (or estimation) of the missing information is needed. To achieve this, we introduce sampled-data H2/H∞ optimization. We design the reconstruction system which optimizes the worst case error between the original PDF and the estimation. The optimization is formulated by linear matrix inequalities and equalities. Numerical examples are illustrated to show effectiveness of our method.
Automating the development of quantum computational software

We introduce a novel programming framework that will fundamentally change the way highly complex ab initio molecular dynamics (aiMD) algorithms are implemented. Our approach combines a domain-specific mathematical language based on operator notation with mature compiler technology. This powerful combination enables the automatic generation of efficient implementations from high-level, concise, and readable aiMD algorithm representations, while leveraging the use of existing highly efficient numerical libraries, such as FFTW and ATLAS. We report on progress made on the development of this framework and preliminary results concerning the implementation of Car-Parrinello molecular dynamics.
Disparities in Spatial Prevalence of Feline Retroviruses due to Data Aggregation: A Case of the Modifiable Areal Unit Problem

The knowledge of the spatial distribution feline immunodeficiency virus and feline leukemia virus infections, which are untreatable, can inform on their risk factors and high-risk areas to enhance control. However, when spatial analysis involves aggregated spatial data, results may be influenced by the spatial scale of aggregation, an effect known as the modifiable areal unit problem (MAUP). In this study, area level risk factors for both infections in 28,914 cats tested with ELISA were investigated by multivariable spatial Poisson regression models along with MAUP effect on spatial clustering and cluster detection (for postal codes, counties, and states) by Moran's I test and spatial scan test, respectively. The study results indicate that the significance and magnitude of the association of risk factors with both infections varied with aggregation scale. Further more, Moran's I test only identified spatial clustering at postal code and county levels of aggregation. Similarly, the spatial scan test indicated that the number, size, and location of clusters varied over aggregation scales. In conclusion, the association between infection and area was influenced by the choice of spatial scale and indicates the importance of study design and data analysis with respect to specific research questions.
OVERCOMING OBSTACLES OF CAR CULTURE: PROMOTING AN ALTERNATIVE TO CAR DEPENDENCE INSTEAD OF ANOTHER TRAVEL MODE

Car advertising is about fashion and lifestyle rather than the convenience of a particular car for a specific market segment’s travel needs. Yet public transport markets its convenience for some trip components. Has this strategy proven effective? Public transport is not an adequate alternative for car dependence as it cannot meet the majority of the diverse travel needs of most of the population. However, when combined with walking and cycling, the three Environment Friendly Modes (EFMs) together can offer a viable alternative to the car for most travel needs. This paper explores the effectiveness of promoting EFMs as a group rather than the promotion of public transport alone, drawing from travel behaviour and social marketing theory. It then examines the process and results from the Individualised Marketing (IndiMark) travel behaviour change technique within the context of promoting an alternative to car dependence. Future actions are recommended to explore the complementary nature of walking, cycling and public transport and how best to market these to convince car dependents to take the risk.
Memory and Cognition in Its Social Context

Contents: Preface. Introduction. A General Model of Social Information Processing. The Structure and Function of the Work Space. The Organization of Information in Permanent Memory. Retrieval Processes. Encoding and Organization: I. The Effects of Concept Accessibility on the Interpretation of Information. Encoding and Organization: II. The Cognitive Representation of Persons. Encoding and Organization: III. The Cognitive Representation of Social Events. Inference Making: I. General Processes. Inference Making: II. Judgments of Persons. Response Generation. The Role of Affect and Emotion in Information Processing. The Self. Appendix: Summary of Postulates.
Bayesian Classification (AutoClass): Theory and Results

We describe AutoClass, an approach to unsupervised classi(cid:12)cation based upon the classical mixture model, supplemented by a Bayesian method for determining the optimal classes. We include a moderately detailed exposition of the mathematics behind the AutoClass system. We emphasize that no current unsupervised classi(cid:12)cation system can produce maximally useful results when operated alone. It is the interaction between domain experts and the machine searching over the model space, that generates new knowledge. Both bring unique information and abilities to the database analysis task, and each enhances the others' e(cid:11)ectiveness. We illustrate this point with several applications of AutoClass to complex real world databases, and describe the resulting successes and failures
Expression of bile acid synthesis and detoxification enzymes and the alternative bile acid efflux pump MRP4 in patients with primary biliary cirrhosis

Background: Bile acid synthesis, transport and metabolism are markedly altered in experimental cholestasis. Whether such coordinated regulation exists in human cholestatic diseases is unclear. We therefore investigated expression of genes for bile acid synthesis, detoxification and alternative basolateral export and regulatory nuclear factors in primary biliary cirrhosis (PBC).
Robust H ∞ control for T–S fuzzy systems with time-varying delay

This article focuses on the problem of robust H ∞ control for uncertain T–S fuzzy systems with time-varying delay. By employing a novel technique, new delay-dependent stabilisation conditions for the existence of a robust H ∞ controller are obtained based on the parallel distributed compensation method. The result obtained is an important contribution as it establishes a new way that can reduce the conservatism without imposing any restrictions and computational efforts at the same time. In this article, all the conditions are shown in terms of linear matrix inequalities (LMIs), which can be solved efficiently by using LMI optimisation techniques. Two numerical examples are given to demonstrate the merits of the approach proposed in this article. Finally, application to control a truck-trailer is also given to demonstrate the effectiveness of the proposed design method.
Detection of vinculin-binding proteins with an 125I-vinculin gel overlay technique

Vinculin is an adhesion plaque component localized on the cytoplasmic side of the cell membrane where stress fibers end. To detect vinculin- binding proteins, we have developed an 125I-vinculin gel overlay method. SDS PAGE was used to separate different protein preparations. After fixing the proteins in the gel with methanol-acetic acid, the SDS was removed with ethanol and the proteins renatured in buffer. The gel was then incubated with 125I-vinculin. After extensive washing to remove nonspecifically associated label, the gel was dried and autoradiographed. Chick embryo fibroblasts, their Rous sarcoma virus transformants, and HeLa cells were found to contain two proteins (Mr 220,000 and 130,000) that bound 125I-vinculin strongly and another (Mr 42,000) that bound it moderately. The 130,000-mol-wt protein was identified as vinculin itself, which suggests that it may self- associate. The 42,000-mol-wt protein was identified as actin with which vinculin is known to interact. The identity of the 220,000-mol-wt protein is not known. It is not cellular fibronectin, myosin, or filamin. When fibroblast proteins were separated into Triton X-100 soluble and insoluble fractions, most of the vinculin and the 220,000- mol-wt protein was found to be in the soluble fraction. Chicken gizzard also contained these vinculin-binding proteins along with three others of Mr 190,000, 170,000, and 100,000.
Semi-parametric Models Using False Positive Patterns for Face Detection

A good performance of a semi-parametric model has been demonstrated in many applications. That it can make flexible and compact model by controlling the number of clusters is the main advantage of it. However, it has many parameters to fit, and this feature makes learning more difficult. In this paper, we propose a new semi-parametric model. A proposed algorithm previously not defines the number of clusters but dynamically adjusts it by using false positive patterns(FPP) that are classified a face among non-face images. A proposed model starts with just one Gaussian cluster, and examines whether a cluster that contains a non-face pattern in its boundary exists or not. Those clusters are decomposed into two Gaussian clusters by a proposed simple clustering algorithm. This procedure is repeated until there are no FPPs. By using FPPs, a proposed model dynamically determines the number of clusters from a clustering phase rather than an experiment.
Interventions to Support Integrated Psychological Care and Holistic Health Outcomes in Paediatrics

There are strong calls from many national and international bodies for there to be a ‘holistic’ and integrated approach to the understanding and management of psychological and physical health needs. Such holistic approaches are characterized by the treatment of the whole person, taking into account mental and social factors, rather than just the symptoms of a disease. Holistic approaches can impact on mental and physical health and are cost-effective. Several psychological interventions have demonstrated efficacy in improving holistic health outcomes, for example Cognitive Behaviour Therapy, Behavioural Therapies and Problem Solving Therapies. They have shown to impact upon a wide range of outcomes, including psychological distress, pain, physical health, medication adherence, and family outcomes. There is increasing recognition that the holistic goals of the child and family should be prioritised, and that interventions and outcomes should reflect these goals. A focus on holistic goals in therapy can be achieved through a combination of personalised goal-based outcomes in addition to symptom-based measures.
Decomposing Image Computation for Symbolic Reachability Analysis Using Control Flow Information

The main challenge in BDD-based symbolic reachability analysis is represented by the sizes of the intermediate decision diagrams obtained during image computations. Methods proposed to mitigate this problem fall broadly into two categories: Search strategies that depart from breadth-first search, and efficient techniques for image computation. In this paper we present an algorithm that belongs to the latter category. It exploits define-use information along executable paths extracted from the control-flow graph of the model being analyzed; this information enables an effective constraining of the transition relation and a decomposition of the image computation process that often leads to much smaller intermediate BDDs. Our experiments confirm that this reduction in the size of the representation of state sets translates in significant decreases in CPU and memory requirements
Key Perspectives on Dyslexia: An essential text for educators

This indispensable book critically sets out the skills and knowledge required by a specialist educator for students who present with dyslexia. The British Dyslexia Association Professional Criteria (BDA, 2012) provides an anchor throughout for this book? s content. Chapters are explicitly mapped to specific professional criteria, offering the reader confidence that guidance in Key Perspectives on Dyslexia is underpinned by this internationally recognised professional framework. Key issues in the education and care of those affected by dyslexia are critically explained and explored in this publication, using both author? s years of specialist experience in this field. As established scholars both authors also suggest how research can inform and enrich how an educator responds to these issues.
Supporting the shared care of diabetic patients

This paper reports on a study of clinicians who care for diabetic patients, and on the design of an application to support their work. The clinicians' long-term activity is rooted in a series of private sessions with the patient. Clinicians exchange information but the timeliness, specificity and other salient features of the communication are often unsatisfactory. Problems consequently arise such as the omission or duplication of tests. We describe a conceptual framework to account for the effectiveness of knowledge-sharing in groups such as these, and use it to motivate an application aimed at improving the clinicians' levels of communication and coordination.
Practical identification with encrypted biometric data using oblivious RAM

Bringer et al. introduced a new primitive that enables identification over encrypted biometric data stored on a remote database and that preserves the privacy of the database users toward the database holder. The tools used in their scheme however rely on heavy cryptographic protocols that prevent it from being used in practice for large databases. We modify their technique using Oblivious RAM and prove its usability by an implementation adapted to iris recognition. For a database of 250,000 IrisCodes, only 3.6 MB of data need to be locally stored and an identification request using our new protocol requires less than 350 ms of computation time.
Baseline performance and learning rate of conceptual and perceptual skill-learning tasks: The effect of moderate to severe traumatic brain injury

Existing literature presents a complex and inconsistent picture of the specific deficiencies involved in skill learning following traumatic brain injury (TBI). In an attempt to address this difficulty, individuals with moderate to severe TBI (n = 29) and a control group (n = 29) were tested with two different skill-learning tasks: conceptual (i.e., Tower of Hanoi Puzzle, TOHP) and perceptual (i.e., mirror reading, MR). Based on previous studies of the effect of divided attention on these tasks and findings regarding the effect of TBI on conceptual and perceptual priming tasks, it was predicted that the group with TBI would show impaired baseline performance compared to controls in the TOHP task though their learning rate would be maintained, while both baseline performance and learning rate on the MR task would be maintained. Consistent with our predictions, overall baseline performance of the group with TBI was impaired in the TOHP test, while the learning rate was not. The learning rate on the MR task was preserved but, contrary to our prediction, response time of the group with TBI was slower than that of controls. The pattern of results observed in the present study was interpreted to possibly reflect an impairment of both the frontal lobes as well as that of diffuse axonal injury, which is well documented as being affected by TBI. The former impairment affects baseline performance of the conceptual learning skill, while the latter affects the overall slower performance of the perceptual learning skill.
An ε-Relaxation Method for Separable Convex Cost Network Flow Problems

We propose a new method for the solution of the single commodity, separable convex cost network flow problem. The method generalizes the $\epsilon$-relaxation method developed for linear cost problems and reduces to that method when applied to linear cost problems. We show that the method terminates with a near optimal solution, and we provide an associated complexity analysis. We also present computational results showing that the method is much faster than earlier relaxation methods, particularly for ill-conditioned problems.
‘What Does Donor Mean to a Four‐Year‐Old?’: Initial Insights into Young Children's Perspectives in Solo Mother Families

This study reports on the questions, thoughts and feelings of children aged 4–9 conceived by donor insemination to single mothers. Fifty‐one mothers and 47 children from the same families were each administered a semi‐structured interview. Mothers generally reported that while children either lack understanding, or have not yet been told, about their donor conception, they may be thinking and talking about the absence of a father. Most children did not mention either donor conception or father absence and reported positive feelings about their families and friendships. Possible explanations for the discrepancy between mothers’ and children's reports are discussed.
A Plea for Utilising Synthetic Data when Performing Machine Learning Based Cyber-Security Experiments

Cyber-security research is a challenging venture where researchers especially face the problem of not having broad access to labelled real-world data sets. This unavailability of data challenges performing scientific sound experiments. Especially, for machine learning based systems this unavailability effectively hinders us to assess performance, attributes and limitations of such systems. One approach to address this lack of publicly available data is to perform experiments using synthetic data. However, we experience that synthetic data is seldom used in our community. This position paper gives a plea for utilising synthetic data when performing machine learning based cyber-security experiments. For this, we collect major challenges our community faces today and discuss how synthetic data can help solving them. Furthermore, we discuss open questions in the area of data synthesis and propose directions for future work.
Three Central Dimensions of Sexual Recidivism Risk: Understanding the Latent Constructs of Static-99R and Static-2002R

The most commonly used risk assessment tools for predicting sexual violence focus almost exclusively on static, historical factors. Consequently, they are assumed to be unable to directly inform the selection of treatment targets, or evaluate change. However, researchers using latent variable models have identified three dimensions in static actuarial scales for sexual offenders: Sexual Criminality, General Criminality, and a third dimension centered on young age and aggression to strangers. In the current study, we examined the convergent and predictive validity of these dimensions, using psychological features of the offender (e.g., antisocial traits, hypersexuality) and recidivism outcomes. Results indicated that (a) Sexual Criminality was related to dysregulation of sexuality toward atypical objects, without intent to harm; (b) General Criminality was related to antisocial traits; and (c) Youthful Stranger Aggression was related to a clear intent to harm the victim. All three dimensions predicted sexual recidivism, although only General Criminality and Youthful Stranger Aggression predicted nonsexual recidivism. These results indicate that risk tools for sexual violence are multidimensional, and support a shift from an exclusive focus on total scores to consideration of subscales measuring psychologically meaningful constructs.