Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing a categorization system for rapists’ speech

Abstract Case linkage, the linking of crimes into series, is used in policing in the UK and other countries. Previous researchers have proposed using rapists’ speech in this practice; however, researching this application requires the development of a reliable coding system for rapists’ speech. A system was developed based on linguistic theories of pragmatics which allowed for the categorization of an utterance into a speech act type (e.g. directive). Following this classification, the qualitative properties of the utterances (e.g. the degree of threat it carried) could be captured through the use of rating scales. This system was tested against a previously developed system using 188 rapists’ utterances taken from victims’ descriptions of rape. The pragmatics-based system demonstrated higher inter-rater reliability whilst enabling the classification of a greater number of rapists’ utterances. Inter-rater reliability for the subscales was also tested using a sub-sample of 50 rapists’ utterances and inter-item correlations were calculated. Seventy-six per cent of the subscales had satisfactory to high inter-rater reliability. Based on these findings and the inter-item correlations, the classification system was revised. The potential use of this system for the practices of case linkage and offender profiling is discussed.
Higher-Order-Statistics-Based Radial Basis Function Networks for Signal Enhancement

In this paper, a higher-order-statistics (HOS)-based radial basis function (RBF) network for signal enhancement is introduced. In the proposed scheme, higher order cumulants of the reference signal were used as the input of HOS-based RBF. An HOS-based supervised learning algorithm, with mean square error obtained from higher order cumulants of the desired input and the system output as the learning criterion, was used to adapt weights. The motivation is that the HOS can effectively suppress Gaussian and symmetrically distributed non-Gaussian noise. The influence of a Gaussian noise on the input of HOS-based RBF and the HOS-based learning algorithm can be mitigated. Simulated results indicate that HOS-based RBF can provide better performance for signal enhancement under different noise levels, and its performance is insensitive to the selection of learning rates. Moreover, the efficiency of HOS-based RBF under the nonstationary Gaussian noise is stable
Plan 9 From Cyberspace: The Implications of the Internet for Personality and Social Psychology

Just as with most other communication breakthroughs before it, the initial media and popular reaction to the Internet has been largely negative, if not apocalyptic. For example, it has been described as “awash in pornography”, and more recently as making people “sad and lonely. ” Yet, counter to the initial and widely publi cized claim that Internet use causes depression and social isolation, the body of ev idence (even in the initial study on which the claim was based) is mainly to the con trary. More than this, however, it is argued that like the telephone and television before it, the Internet by itself is not a main effect cause of anything, and that psy chology must move beyond this notion to an informed analysis of how social iden tity, social interaction, and relationship formation may be different on the Internet than in real life. Four major differences and their implications for self and identity, social interaction, and relationships are identified: one's greater anonymity, the greatly reduced importance of physical appearance and physical distance as “gating features” to relationship development, and one's greater control over the time and pace of interactions. Existing research is reviewed along these lines and some promising directions for future research are described.
Shared decision making: developing the OPTION scale for measuring patient involvement

Background: A systematic review has shown that no measures of the extent to which healthcare professionals involve patients in decisions within clinical consultations exist, despite the increasing interest in the benefits or otherwise of patient participation in these decisions. Aims: To describe the development of a new instrument designed to assess the extent to which practitioners involve patients in decision making processes. Design: The OPTION (observing patient involvement) scale was developed and used by two independent raters to assess primary care consultations in order to evaluate its psychometric qualities, validity, and reliability. Study sample: 186 audiotaped consultations collected from the routine clinics of 21 general practitioners in the UK. Method: Item response rates, Cronbach’s alpha, and summed and scaled OPTION scores were calculated. Inter-item and item-total correlations were calculated and inter-rater agreements were calculated using Cohen’s kappa. Classical inter-rater intraclass correlation coefficients and generalisability theory statistics were used to calculate inter-rater reliability coefficients. Basing the tool development on literature reviews, qualitative studies and consultations with practitioner and patients ensured content validity. Construct validity hypothesis testing was conducted by assessing score variation with respect to patient age, clinical topic “equipoise”, sex of practitioner, and success of practitioners at a professional examination. Results: The OPTION scale provided reliable scores for detecting differences between groups of consultations in the extent to which patients are involved in decision making processes in consultations. The results justify the use of the scale in further empirical studies. The inter-rater intraclass correlation coefficient (0.62), kappa scores for inter-rater agreement (0.71), and Cronbach’s alpha (0.79) were all above acceptable thresholds. Based on a balanced design of five consultations per clinician, the inter-rater reliability generalisability coefficient was 0.68 (two raters) and the intra-rater reliability generalisability coefficient was 0.66. On average, mean practitioner scores were very similar (and low on the overall scale of possible involvement); some practitioner scores had more variation around the mean, indicating that they varied their communication styles to a greater extent than others. Conclusions: Involvement in decision making is a key facet of patient participation in health care and the OPTION scale provides a validated outcome measure for future empirical studies.
Abusive supervision, distributive justice, and work-life balance: perspectives from salespeople and managers

Perhaps in no other field is the employee–manager relationship as important as in sales. Given the performance-driven nature of the profession, firms seek managers who can optimize individual performance while providing a work environment that leads to satisfied employees. Using data collected from salespeople and sales managers, this study suggests that abusive supervision is one factor which negatively impacts both of these goals. Integrating justice theory within a sales management framework, we advance that abusive sales managers alter perceptions of workplace fairness. In turn, this perceived justice negatively impacts life satisfaction of not only salespeople experiencing the abuse but of managers administering it. Further, an unjust workplace established by an abusive manager can actually have detrimental effects on selling performance. Finally, we uncover normative and continuance commitment as factors that can suppress this negative relationship. If salespeople believe that job is a necessity or either party feels some sense of moral or ethical obligation to their firm, they are able to overlook the abuse, and possibly avoid the ‘double whammy' of negative outcomes associated with it.
Identification of CD4+ T Cell Epitopes from NY-ESO-1 Presented by HLA-DR Molecules

In previous studies, the shared cancer-testis Ag, NY-ESO-1, was demonstrated to be recognized by both Abs and CD8+ T cells. Gene expression of NY-ESO-1 was detected in many tumor types, including melanoma, breast, and lung cancers, but was not found in normal tissues, with the exception of testis. In this study, we describe the identification of MHC class II-restricted T cell epitopes from NY-ESO-1. Candidate CD4+ T cell peptides were first identified using HLA-DR4 transgenic mice immunized with the NY-ESO-1 protein. NY-ESO-1-specific CD4+ T cells were then generated from PBMC of a patient with melanoma stimulated with the candidate peptides in vitro. These CD4+ T cells recognized NY-ESO-1 peptides or protein pulsed on HLA-DR4+ EBV B cells, and also recognized tumor cells expressing HLA-DR4 and NY-ESO-1. A 10-mer peptide (VLLKEFTVSG) was recognized by CD4+ T cells. These studies provide new opportunities for developing more effective vaccine strategies by using tumor-specific CD4+ T cells. This approach may be applicable to the identification of CD4+ T cell epitopes from many known tumor Ags recognized by CD8+ T cells.
Optimizing the location of ECC protection in Network-on-Chip

The communication in Network-on-Chips (NoCs) may be subject to errors. Error Correcting Codes (ECCs) can be used to tolerate the transient faults in flits caused by Single Event Upsets (SEU). ECC can improve the reliability of a NoC significantly at the cost of extra area and power consumption. However, ECC units (encoders and decoders) may also suffer from SEU faults and thus may lead to over-protection, meaning that providing more ECC units does not further improve reliability. This work analyzes reliability in NoCs, i.e. fractions of correctly received flits, considering the SEU errors introduced by both protected circuits and ECC units. The results show the potential for over-protection. Based on this analysis, we maximize the protection by optimizing the location of the ECC units. We study the reliability of an 8 × 8 Mesh NoC with six ECC protection strategies, and we conclude that one protection strategy called SLOPE achieves the best trade-off among the six examined strategies by considering reliability, latency, area, energy consumption and design space comprehensively.
Pachymic Acid Inhibits Growth and Induces Apoptosis of Pancreatic Cancer In Vitro and In Vivo by Targeting ER Stress

Pachymic acid (PA) is a purified triterpene extracted from medicinal fungus Poria cocos. In this paper, we investigated the anticancer effect of PA on human chemotherapy resistant pancreatic cancer. PA triggered apoptosis in gemcitabine-resistant pancreatic cancer cells PANC-1 and MIA PaCa-2. Comparative gene expression array analysis demonstrated that endoplasmic reticulum (ER) stress was induced by PA through activation of heat shock response and unfolded protein response related genes. Induced ER stress was confirmed by increasing expression of XBP-1s, ATF4, Hsp70, CHOP and phospho-eIF2α. Moreover, ER stress inhibitor tauroursodeoxycholic acid (TUDCA) blocked PA induced apoptosis. In addition, 25 mg kg-1 of PA significantly suppressed MIA PaCa-2 tumor growth in vivo without toxicity, which correlated with induction of apoptosis and expression of ER stress related proteins in tumor tissues. Taken together, growth inhibition and induction of apoptosis by PA in gemcitabine-resistant pancreatic cancer cells were associated with ER stress activation both in vitro and in vivo. PA may be potentially exploited for the use in treatment of chemotherapy resistant pancreatic cancer.
Gene Co-Expression Network Analysis Provides Novel Insights into Myostatin Regulation at Three Different Mouse Developmental Timepoints

Myostatin (Mstn) knockout mice exhibit large increases in skeletal muscle mass. However, relatively few of the genes that mediate or modify MSTN effects are known. In this study, we performed co-expression network analysis using whole transcriptome microarray data from MSTN-null and wild-type mice to identify genes involved in important biological processes and pathways related to skeletal muscle and adipose development. Genes differentially expressed between wild-type and MSTN-null mice were further analyzed for shared DNA motifs using DREME. Differentially expressed genes were identified at 13.5 d.p.c. during primary myogenesis and at d35 during postnatal muscle development, but not at 17.5 d.p.c. during secondary myogenesis. In total, 283 and 2034 genes were differentially expressed at 13.5 d.p.c. and d35, respectively. Over-represented transcription factor binding sites in differentially expressed genes included SMAD3, SP1, ZFP187, and PLAGL1. The use of regulatory (RIF) and phenotypic (PIF) impact factor and differential hubbing co-expression analyses identified both known and potentially novel regulators of skeletal muscle growth, including Apobec2, Atp2a2, and Mmp13 at d35 and Sox2, Tmsb4x, and Vdac1 at 13.5 d.p.c. Among the genes with the highest PIF scores were many fiber type specifying genes. The use of RIF, PIF, and differential hubbing analyses identified both known and potentially novel regulators of muscle development. These results provide new details of how MSTN may mediate transcriptional regulation as well as insight into novel regulators of MSTN signal transduction that merit further study regarding their physiological roles in muscle and adipose development.
Two forms of cerebellar glial cells interact differently with neurons in vitro

Specific interactions between neurons and glia dissociated from early postnatal mouse cerebellar tissue were studied in vitro by indirect immunocytochemical staining with antisera raised against purified glial filament protein, galactocerebroside, and the NILE glycoprotein. Two forms of cells were stained with antisera raised against purified glial filament protein. The first, characterized by a cell body 9 microns diam and processes 130-150 microns long, usually had two to three neurons associated with them and resembled Bergmann glia. The second had a slightly larger cell body with markedly shorter arms among which were nestled several dozen neuronal cells, and resembled astrocytes of the granular layer. Staining with monoclonal antisera raised against purified galactocerebroside revealed the presence of immature oligodendroglia in the cultures. These glial cells constituted approximately 2% of the total cell population in the cultures and, in contrast to astroglia, did not form specific contacts with neurons. Staining with two neuronal markers, antisera raised against purified NILE glycoprotein and tetanus toxin, revealed that most cells associated with presumed astroglia were small neurons (5-8 microns). After 1-2 d in culture, some stained neurons had very fine, short processes. Nearly all of the processes greater than 10-20 micron long were glial in origin. Electron microscopy also demonstrated the presence of two forms of astroglia in the cultures, each with a different organizing influence on cerebellar neurons. Most neurons associated with astroglia were granule neurons, although a few larger neurons sometimes associated with them. Time-lapse video microscopy revealed extensive cell migration (approximately 10 microns/h) along the arms of Bergmann-like astroglia. In contrast, cells did not migrate along the arms of astrocyte-like astroglia, but remained stationary at or near branch points. Growth cone activity, pulsating movements of cell perikarya, and ruffling of the membranes of glial and neuronal processes were also seen.
Interpretation of Hidden Node Methodology with Network Accuracy

Bayesian networks are constructed under a conditional independency assumption. This assumption however does not necessarily hold in practice and may lead to loss of accuracy. We previously proposed a hidden node methodology whereby Bayesian networks are adapted by the addition of hidden nodes to model the data dependencies more accurately. Empirical results in a computer vision application to classify and count the neural cell automatically showed that a modified network with two hidden nodes achieved significantly better performance with an average prediction accuracy of 83.9% compared to 59.31% achieved by the original network. In this paper we justify the improvement of performance by examining the changes in network accuracy using four network accuracy measurements; the Euclidean accuracy, the Cosine accuracy, the Jensen-Shannon accuracy and the MDL score. Our results consistently show that the network accuracy improves by introducing hidden nodes. Consequently, we were able to verify that the hidden node methodology helps to improve network accuracy and contribute to the improvement of prediction accuracy.
Cross-Lingual Lexical Triggers in Statistical Language Modeling

We propose new methods to take advantage of text in resource-rich languages to sharpen statistical language models in resource-deficient languages. We achieve this through an extension of the method of lexical triggers to the cross-language problem, and by developing a likelihood-based adaptation scheme for combining a trigger model with an N-gram model. We describe the application of such language models for automatic speech recognition. By exploiting a side-corpus of contemporaneous English news articles for adapting a static Chinese language model to transcribe Mandarin news stories, we demonstrate significant reductions in both perplexity and recognition errors. We also compare our cross-lingual adaptation scheme to monolingual language model adaptation, and to an alternate method for exploiting cross-lingual cues, via cross-lingual information retrieval and machine translation, proposed elsewhere.
Current Worldwide Side Impact Activities - Divergence versus Harmonisation and the Possible Effect on Future Car Design

Car manufacturers design vehicles and side impact restraint systems to protect passengers from the risk of serious injury in the event of a side impact. In each of the major markets of the world, the side-impact testing requirements as set by the regulatory and the consumer interests are generally different. This paper documents and compares the international side impact regulatory and consumer test requirements of now and the future. Using a sample of results from vehicles tested in accordance with the discussed future regulations and consumer tests, it is shown that vehicles currently “best rated” for side-impact protection in consumer tests need to be redesigned in order to meet the prospective regulatory requirements. This paper discusses the vehicle structural, interior and restraint design changes, which could be required. The global side-impact tests and requirements are diverging, and not converging towards a harmonized Side-impact Testing Protocol as presented by the International Harmonized Research Activities committee (IHRA) at the 2003 ESV Conference. It is the goal of car manufacturers that side-impact requirements and procedures should become less diversified and more harmonized as they continue to improve side-impact protection for all customers worldwide.
Shigui Ruan epidemiological model of influenza A drift Sustained oscillations in an evolutionary

(158 articles) applied mathematics (44 articles) differential equations (54 articles) mathematical modelling Articles on similar topics can be found in the following collections Email alerting service here the box at the top right-hand corner of the article or click Receive free email alerts when new articles cite this article-sign up in Understanding the seasonal/periodic reoccurrence of influenza will be very helpful in designing successful vaccine programmes and introducing public-health interventions. However, the reasons for seasonal/periodic influenza epidemics are still not clear, even though various explanations have been proposed. In this paper, we study an age-structured type evolutionary epidemiological model of influenza A drift, in which the susceptible class is continually replenished because the pathogen changes genetically and immunologically from one epidemic to the next, causing previously immune hosts to become susceptible. Applying our recently established centre manifold theory for semi-linear equations with non-dense domain, we show that Hopf bifurcation occurs in the model. This demonstrates that the age-structured type evolutionary epidemiological model of influenza A drift has an intrinsic tendency to oscillate owing to the evolutionary and/or immunological changes of the influenza viruses.
Inflammatory and genotoxic effects of nanoparticles designed for inclusion in paints and lacquers

Abstract Manufactured nanomaterials are projected to be used on a large scale in paints and lacquers. We selected seven commercially interesting materials: Three titanium dioxide-based (two coated rutile; one uncoated anatase), one carbon black (Flamrüss 101), one kaolinite clay, and two silica products, whereas carbon black, Printex 90, was used as reference material. DNA damaging activity and inflammogenicity (pulmonary cell composition and mRNAs) were determined 24 h after intratracheal instillation of a single dose of 54 μg in mice. Greatest inflammation was induced by Printex 90 and uncoated titanium dioxide. The inflammatory potency correlated with instilled surface area (R2 = 0.94) but not with material volume (R2 = 0.17). The coated titanium dioxides induced DNA damage in lung lining fluid cells. The uncoated titanium dioxide was not DNA damaging by the comet assay 24 h after exposure despite being highly inflammogenic. This suggests that inflammation is not a prerequisite to DNA damage in titanium dioxide-based products.
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization

The Schatten-p quasi-norm (0<p<1) is usually used to replace the standard nuclear norm in order to approximate the rank function more accurately. However, existing Schatten-p quasi-norm minimization algorithms involve singular value decomposition (SVD) or eigenvalue decomposition (EVD) in each iteration, and thus may become very slow and impractical for large-scale problems. In this paper, we first define two tractable Schatten quasi-norms, i.e., Frobenius/nuclear hybrid and bi-nuclear quasi-norms, and then prove that they are in essence the Schatten-2/3 and 1/2 quasi-norms, respectively, which lead to the design of very efficient algorithms that only need to update two much smaller factor matrices. We also design two efficient proximal alternating linearzied minimization algorithms for solving representative matrix completion problems. Finally, we provide the global convergence and performance guarantees for our algorithms, which have better convergence properties than existing algorithms. Experimental results on synthetic and real-world data show that our algorithms are more accurate than the state-of-the-art methods, and are orders of magnitude faster.
Organizational Change and the Provision of a Secure Base: Lessons from the Field

In this article I lay groundwork for a theory of practice related to organization members' dependency on change agents. A promising place to begin such a theory of practice is attachment theory, a framework developed in child developmental psychology that focuses on how relationships between children and attachment figures (typically parents) facilitate or undermine children feeling secure. Using material from an organizational diagnosis and change project I conducted from multiple theoretical perspectives, I show how I as a change agent created and undermined a secure attachment with organization members. I then offer implications about how change agents-as temporary attachment figures-may undermine or facilitate fundamental change in organization members' patterns of relating.