Miracle-dz/UniFAR-FTUs huggingface dataset:
The conditions of primary infection define the load of latent viral genome in organs and the risk of recurrent cytomegalovirus disease

Recurrence of cytomegalovirus (CMV) from latency is a frequent cause of disease in immunocompromised patients. To date, there is no explanation for the diversity in the clinical manifestations. Primary infection can occur perinatally or later in life, and inevitably results in latent infection. Seropositivity for antibodies against CMV is indicative of latent infection, but is insufficient as a predictor for the risk of recurrence. As a model for this important medical problem, we compared the risks of murine CMV recurrence from latency established after neonatal primary infection and after infection at adult age. The risk of CMV recurrence was high only after neonatal infection. The copy number of latent viral genome in tissues was identified as the key parameter that determines the overall and organ-specific risks of recurrence. Latent CMV burden and risk of recurrence were related to the extent of virus multiplication during primary infection. The presence of latent CMV in multiple organs provides the molecular basis for stochastic events of recurrence in single organs or in any combination thereof. These findings are discussed as a concept of multifocal CMV latency and recurrence. It provides a rationale for the diversity in the clinical outcome of CMV disease.
The Teaching Artist: a model for university dance teacher training

This paper describes a teaching model, The Teaching Artist, developed to address the pedagogical and cultural divide between the traditional dance teacher and the dance artist who teaches: traditionally, one teaching about dance and the other, teaching through dance. The Teaching Artist model was developed through the Q150 Project. The Q150 Project provided an opportunity to meld these cultural idioms. It involved pre-service secondary dance teachers in their second year of teacher training at the Queensland University of Technology. The Project’s design involved three components: artistic development, pedagogic development and implementation. The participants researched social and artistic dance histories and practices across Queensland towns. From their research, they created dance works specific to those local communities. The works created formed the basis for primary and secondary school workshops taught by the participants. By their participation in the Project, the pre-service teachers created tangible links with the schools in which they will practise and experienced the nexus between artist and teacher in an authentic teaching and learning environment.
Consumer-Retailer Relationships from a Multi-Level Perspective

Abstract Consumers get an image of stores after evaluating its brands, personnel and other general elements. However, literature on consumer-retailer relationships from a multi-level perspective is scarce. This paper proposes a model that comprises three interrelated levels of trust and satisfaction-with store brands, the personnel and the firm-and also shows the influence of trust and satisfaction on affective and temporal commitment to the store. Results confirm there is a transference process between trust levels and between satisfaction levels, support the relationship between trust and satisfaction in each level and stress the interpersonal level as the one that will more probably engender affective and temporal commitment.
Detection of 3-dimensional textured object without depth information

We propose a feature-based approach for detection of a 3-dimensional textured object in a single image. Each object has a training set which contains various poses in the template of small size. And then multiple objects are placed in the background, some of which are mixed with untrained objects. Background of some images is complicated and textured, which makes it difficult to find target object. In this experimental environment, the proposed algorithm finds the textured object comparing with the training template set we construct. It is based on Speeded Up Robust Features (SURF) descriptor and homography matching. First, it detects feature points of textured object using SURF descriptor. And second, it matches template to object in example with homography using RANdom SAmple Consensus (RANSAC). For texture-less object, the proposed algorithm did not show the good performance. For textured objects, however, it found the object in the complicated or simple background successfully for each.
Willing or able? The meanings of self-efficacy

Abstract One hundred and twenty college students (97 women) completed measures of anticipated performance for a fear-based snake behavioral avoidance task (BAT) and a skill-based basket-shooting task. Half of the participants were instructed to identify the task steps they believed themselves able to do (standard self-efficacy instructions). The remaining participants were instructed to identify the task steps they would be willing to try. Prior to completing the anticipatory performance measures, half of the participants in each of the “able to do” or “willing to try” conditions received information, called disambiguation instructions, about Kirsch's (1982) hypothesis that people frequently use these terms interchangeably for fear-based tasks but not skill-based tasks. Results revealed that, for participants who did not receive the disambiguation instructions, participants endorsed a similar number of BAT steps regardless of questionnaire instructions. On the basket-shooting task, participants asked to i.
Morgan revisited

Ever since its description in 1965, the Morgan algorithm’ has been important in computer applications that handle chemical structure. It was originally proposed as a key step in the unique coding of chemical structures and was subsequently extended in slightly modified form by Wipke and Dyott2 as part of their chemical synthesis program, SECS. Corneil and Read3 mention it as a possible but incomplete method for partitioning vertices for isomorphism determinations. Shelley and Munk4 and Figueras5 used it in conjunction with other graph invariants for topological symmetry perception, and the algorithm played an important role in Shelley’s structure display program.6 In place of paraphrase, let me quote Morgan’s original description of his algorithm:’ “The ‘connectivity values’ are computed by first assigning to each node an initial ‘connectivity value’ equal to the number of nonhydrogen atoms attached to that node . The computer then calculates the number (k) of different ‘connectivity values’ which had been assigned. An iterative process is then established which calculates a new ‘connectivity value’ for each node. This new value is the sum of the assigned values for the nodes connected to the one under consideration. Having computed a value for each node based on the previous values, the computer calculates the number (k’) of different values in the set of new values. If k’> k, the new values are assigned to the corresponding nodes, k is set equal to k’, and the summation process is repeated. If, however, k’5 k, the process is terminated and the last set of values assigned to the nodes is used to induce a partial ordering among the nodes . ” It is apparent that, for each atom in the structure, each cycle of this computation brings in the next shell of atoms for computing the new connectivity values. A relationship between Morgan’s connectivity values and matrix powers of the adjacency matrix was noted by Razinger,7 who gave an empirical example but offered no proof. More recently, Riicker and Rucker* derived the relationship by proving that total walk counts, which can be computed as row sums of a power of the adjacency matrix, are identical to Morgan’s connectivity values. In this paper, the relationship is derived by direct representation of the Morgan algorithm as a recursive matrix multiplication.
The Alpha-Method Direct Transcription in Path Constrained Dynamic Optimization

Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to useful control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerate perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the original problem. The regularization is quantifiable in terms of time step size in the mesh and the regularization parameter. For fully regularized systems the scheme converges linearly in time step size. The method is illustrated with examples.
The influence of suggestions on children's reports of a unique experience versus an instance of a repeated experience

In Experiment 1 we compared the influence of misleading suggestions on 4-, 6-, and 8-year-olds' reports of details of an instance of a repeated experience versus a unique experience. For children who experienced the event repeatedly, some components remained constant across instances (fixed) whereas others varied (variable). Relative to children who had experienced the event only once, those who had experienced it repeatedly were less affected by suggestions regarding fixed details and more affected by suggestions regarding variable details. In Experiment 2 a misinformation effect was observed in responses to questions about variable details but not in responses to questions about fixed details. Copyright © 2001 John Wiley & Sons, Ltd. Language: en
Forward Stagewise Additive Model for Collaborative Multiview Boosting

Multiview assisted learning has gained significant attention in recent years in supervised learning genre. Availability of high-performance computing devices enables learning algorithms to search simultaneously over multiple views or feature spaces to obtain an optimum classification performance. This paper is a pioneering attempt of formulating a mathematical foundation for realizing a multiview aided collaborative boosting architecture for multiclass classification. Most of the present algorithms apply multiview learning heuristically without exploring the fundamental mathematical changes imposed on traditional boosting. Also, most of the algorithms are restricted to two class or view setting. Our proposed mathematical framework enables collaborative boosting across any finite-dimensional view spaces for multiclass learning. The boosting framework is based on a forward stagewise additive model, which minimizes a novel exponential loss function. We show that the exponential loss function essentially captures the difficulty of a training sample space instead of the traditional “1/0” loss. The new algorithm restricts a weak view from overlearning and thereby preventing overfitting. The model is inspired by our earlier attempt on collaborative boosting, which was devoid of mathematical justification. The proposed algorithm is shown to converge much nearer to global minimum in the exponential loss space and thus supersedes our previous algorithm. This paper also presents analytical and numerical analyses of convergence and margin bounds for multiview boosting algorithms and we show that our proposed ensemble learning manifests lower error bound and higher margin compared with our previous model. Also, the proposed model is compared with traditional boosting and recent multiview boosting algorithms. In the majority of instances, the new algorithm manifests a faster rate of convergence on training set error and also simultaneously offers better generalization performance. The kappa-error diagram analysis reveals the robustness of the proposed boosting framework to labeling noise.
Adverse drug reactions: managing the risk.

AIM This study aims to assess the need to formalize medication monitoring strategies in electronic records in two crisis resolution home treatment (CRHT) teams in one UK NHS Trust. BACKGROUND The management and monitoring of prescribed medications has long been a cause for concern. As a result of the potential adverse drug reactions associated with commonly prescribed medication, clients of mental health teams are vulnerable to iatrogenic risk linked to physical health problems. METHOD Electronic records for all clients receiving care in two CHRT teams in one UK mental health Trust in November 2007 were examined for evidence of monitoring for potential adverse drug reactions. Findings were compared with the sample of paper records submitted to a national audit. RESULTS Electronic records omitted important aspects of medication monitoring, for example: 14 out of 57 clients had blood pressure recorded; 15 out of 57 had heart rate recorded; 13 out of 57 had weight recorded. However, the teams' paper records were significantly better than both the electronic records and a national audit sample at recording blood pressure and obesity. We found few differences between our two teams. CONCLUSIONS The format of our electronic records requires modification to ensure that systems are in place to document adverse drug reactions and the physical health of those with mental illness. IMPLICATIONS FOR NURSING MANAGEMENT The transition to electronic records needs to be carefully managed to ensure that information on adverse drug reactions is included. The West Wales Adverse Drug Reaction profile, version II, is one strategy to achieve this in mental health.
Comparison Between Euro NCAP Test Results and Real-World Crash Data

Objective: The objective of this study was 2-fold: first, to compare Euro NCAP safety ratings of cars with those published by the Folksam real-world injury ratings; and second, to compare injury risk measures between Euro NCAP 2 and 5 Star cars with real-world injury and disability outcomes using police and insurance injury data. Methods: Car models were grouped according to the Euro NCAP star rating scores. Folksam risk of injury ratings come from statistical analysis of real-world crashes using police and insurance databases. The paired comparison method using 2-car crashes was used to control for crash speed and the mass differences between cars of different weights were normalized. Results: For all comparisons, 5-star rated Euro NCAP cars were found to have a lower risk of injury compared to 2-star rated cars (5-star cars were 10% ± 2.5% lower risk than 2-star cars). For fatal and serious injuries, the difference was 23 ± 8 percent, and for fatal injuries alone the difference was 68 ± 32 percent. By comparison, the Folksam 5-star rated cars had a relative risk of 0.020 ± 0.0024, whereas 2-star rated car risk was 0.028 ± 0.0016, corresponding to a 27 percent difference in risk between 5- and 2-star cars. Conclusions: Good correlation was found between Euro NCAP test results and real-world injury outcomes. The largest difference in injury risk between 2- and 5-star rated cars in Euro NCAP was found for risk of fatality, confirming that car manufacturers have focused their safety performance on serious crash outcomes. In addition, Euro NCAP crash tests were shown to be highly correlated with serious crash performance, confirming their relevance for evaluating real-world crash performance. Good concordance was found between Euro NCAP and Folksam real-world crash and injury ratings.
A “Motion Portrait” of a Psychodynamic Treatment of an 11-Year-Old Girl: Exploring Interrelations of Psychotherapy Process and Outcome Using the Child Psychotherapy Q-Set

In the sciences, new conjectures and theories generally do lead to innovations of method, since new means are necessary to “see” or investigate hitherto unknown entities or structures. Galison and Stump (1996), as cited by Rustin (2001, p. 81) Research into psychotherapy necessarily and inevitably changes the nature of the therapy it investigates. Fonagy (2005), as cited by Pruetzel-Thomas (2006, p. 8) Clinicians engaged in thinking about the nature of the therapeutic process in work with children frequently state concern that traditional research measures fail to do justice to the complex interactions that take place between therapist and child. The Child Psychotherapy Q-Set (CPQ; Schneider and Jones, 2004) is an instrument designed to describe psychotherapy process with children ages 3–13 in clinically meaningful ways and in a form suitable for quantitative comparison and analysis. The CPQ offers a common language to describe process and therapeutic action that could allow a mutual engagement with questions of therapeutic process and its relation to outcome for clinicians and researchers. Here we briefly describe this method and its application to study therapy process and outcome with an 11-year-old girl in psychodynamic psychotherapy.
Prioritising Infectious Disease Mapping

Background Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. Methodology/Principal Findings Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. Conclusions/Significance A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited.
Evaluation of the VLSI adaptation of the CHEMFET, a biosensor for fluid analysis

A biosensor system is presented for identification of properties of a fluid. The class of biosensors studied in this work, are capable of operating as a dielectric constant measurement device. This paper focuses on studying the effectiveness of the VLSI adaptation on the CHEMFET in determining fluidic properties. The objective of this research is to determine metrology infrastructure issues needed for developing multisensor system-on-a-chip (SoC) devices.
Do Helper T Cell Subtypes in Lymphocytic Thyroiditis Play a Role in the Antitumor Effect?

Background Papillary thyroid carcinoma (PTC) is frequently accompanied by lymphocytic thyroiditis (LT). Some reports claim that Hashimoto’s thyroiditis (the clinical form of LT) enhances the likelihood of PTC; however, others suggest that LT has antitumor activity. This study was aimed to find out the relationship between the patterns of helper T cell (Th) cytokines in thyroid tissue of PTC with or without LT and the clinicopathological manifestation of PTC. Methods Fresh surgical samples of PTC with (13 cases) or without (10 cases) LT were used. The prognostic parameters (tumor size, extra-thyroidal extension of PTC, and lymph node metastasis) were analyzed. The mRNA levels of two subtypes of Th cytokines, Th1 (tumor necrosis factor α [TNF-α], interferon γ [IFN-γ ], and interleukin [IL] 2) and Th2 (IL-4 and IL-10), were analyzed. Because most PTC cases were microcarcinomas and recent cases without clinical follow-up, negative or faint p27 immunoreactivity was used as a surrogate marker for lymph node metastasis. Results PTC with LT cases showed significantly higher expression of TNF-α (p = .043), IFN-γ (p < .010), IL-4 (p = .015) than those without LT cases. Although the data were not statistically significant, all analyzed cytokines (except for IL-4) were highly expressed in the cases with higher expression of p27 surrogate marker. Conclusions These results indicate that mixed Th1 (TNF-α, IFN-γ , and IL-2) and Th2 (IL-10) immunity might play a role in the antitumor effect in terms of lymph node metastasis.
3D automatic anatomy segmentation based on graph cut-oriented active appearance models

In this paper, we propose a novel 3D automatic anatomy segmentation method based on the synergistic combination of active appearance models (AAM), live wire (LW) and graph cut (GC). The proposed method consists of three main parts: model building, initialization and segmentation. For the model building part, an AAM model is constructed and the LW cost function is trained. For the initialization part, an improved iterative model refinement algorithm is proposed for the AAM optimization, which synergistically combines the AAM and LW method (OAAM). And a multi-object strategy is applied to help the object initialization. A pseudo 3D initialization strategy is employed to segment the organs slice by slice via multi-object OAAM method. The model constraints are applied to the initialization result. For the segmentation part, the object shape information generated from the initialization step is integrated into the GC cost computation. And an iterative GCOAAM method is proposed for object delineation. This method is a general method and can be applied to any organ segmentation. The proposed method was tested on the clinical liver and kidney CT data sets. The results showed the following: (a) an overall segmentation accuracy of true positive fraction>93.5%, and false positive fraction<0.2% can be achieved. (b) The initialization performance is improved by combining the AAM and LW. (c) The multi-object strategy greatly helps the initialization due to inter-object constraints.
Peer Educators and Close Friends as Predictors of Male College Students' Willingness to Prevent Rape

Astin's (1977, 1991, 1993) input-environment-outcome (I-E-O) model provided a conceptual framework for this study which measured 156 male college students' willingness to prevent rape (outcome variable). Predictor variables included personal attitudes (input variable), perceptions of close friends' attitudes toward rape and rape prevention (environment variable), as well as exposure to sexual assault peer educators (environment variable). A hierarchical multiple regression analysis revealed that both input and environment variables significantly influenced male college students' willingness to prevent rape. Results from this study may help campus leaders develop programs and practices that engage men in rape prevention, which may subsequently reduce incidents of sexual violence on their campuses.