Miracle-dz/UniFAR-FTUs huggingface dataset:
OPERATIONALIZING “WHOLE-OF-GOVERNMENT” AS AN APPROACH TO STATE FRAGILITY AND INSTABILITY: CASE STUDIES FROM OTTAWA, CANADA AND LONDON, UNITED KINGDOM

viii List of Abbreviations Used . ix Acknowledgements . xiii Chapter 1: Introduction . 1 Research architecture . 4 Establishing scope and context . 7 Historical drivers of WoG . 13 Chapter 2: Research Design . 44 Interdisciplinary foundations . 44 Case study approach . 47 Research Design . 55 Theory development: interdisciplinary literature review and concept analysis . 57 Multiple-case study design . 60 Participant recruitment. 64 Case study interview questions . 67 Data analysis (interviews). 68 Chapter 3: Concept Analysis – “Whole-of-Government” . 70 Introduction . 70 Methods . 75 Analysis: Attributes of WoG . 85 WoG as a statement of purpose . 85 WoG as an adjective . 89 WoG as a form of interaction . 93 WoG as a complex system . 96 Analysis: Context . 102 Implications . 121 Chapter 4: Theoretical Framework – Operational Attributes of WoG . 127
Deriving Evidence Theoretical Functions in Multivariate Data Spaces: A Systematic Approach

The mathematical theory of evidence is a generalization of the Bayesian theory of probability. It is one of the primary tools for knowledge representation and uncertainty and probabilistic reasoning and has found many applications. Using this theory to solve a specific problem is critically dependent on the availability of a mass function (or basic belief assignment). In this paper, we consider the important problem of how to systematically derive mass functions from the common multivariate data spaces and also the ensuing problem of how to compute the various forms of belief function efficiently. We also consider how such a systematic approach can be used in practical pattern recognition problems. More specifically, we propose a novel method in which a mass function can be systematically derived from multivariate data and present new methods that exploit the algebraic structure of a multivariate data space to compute various belief functions including the belief, plausibility, and commonality functions in polynomial-time. We further consider the use of commonality as an equality check. We also develop a plausibility-based classifier. Experiments show that the equality checker and the classifier are comparable to state-of-the-art algorithms.
Using Analgesics for Emotional Modulation is Associated With Increased Distress, Depression, and Risk of Opioid and Alcohol Misuse: Initial Evaluation and Component Analysis of the Reasons for Analgesic Use Measure (RAUM)

Objectives: It is important to identify aspects of analgesic use that are associated with harm in chronic pain. Historically, the focus has been patterns of use (eg, overuse). This study evaluated another aspect of use—rather than evaluating how analgesics were being used, the primary interest was in why they were being used. Methods: In total, 334 analgesic using individuals with chronic pain responded to a pool of items assessing reasons for analgesic use. Measures of pain intensity, distress, depression, and opioid and alcohol misuse were also completed. Results: Exploratory factor analyses indicated 3 overarching reasons for use, including taking analgesics: (1) for pain reduction/functional improvement; (2) for emotional modulation/sedation; and (3) to be compliant with prescriber instructions. Correlation and regression analyses indicated that the second factor had the strongest relations with the other measures used, such that greater endorsement of analgesic use for emotional modulation was associated with greater distress, depression, and opioid and alcohol misuse. Using analgesics for pain reduction/functional improvement was associated with greater pain-related distress and depression. Using analgesics to be compliant was not associated with any measure. This pattern of results was generally replicated when a subsample of 131 individuals taking opioids was examined. Discussion: Results support the utility of examining reasons for analgesic use; use to achieve emotional modulation/sedation may be particularly associated with risk. The data also provide support for the questionnaire developed, the Reasons for Analgesic Use Measure.
Cervicovaginal anti-HIV antibodies in HIV-seronegative female sex workers in Abidjan, Côte d'Ivoire

ObjectiveTo detect anti-HIV antibodies in cervicovaginal secretions of HIV-seronegative female sex workers and to evaluate whether the presence of these antibodies is associated with increased sexual exposure. MethodsA cross-sectional study was carried out at a confidential clinic for female sex workers in Abidjan, Côte d'Ivoire. The participants were 342 HIV-seronegative female sex workers in whom a cervicovaginal lavage was collected.The main outcome measures were the detection of antibodies to HIV-1 in cervicovaginal lavages using an in-house and a commercial (Seradyn Sentinel®; Calypte Biomedical Corporation, Berkeley, California, USA) enzyme immunoassay; the detection of semen in cervicovaginal lavages; and the assessment of epidemiological and biological markers of sexual exposure to HIV. ResultsCervicovaginal anti-HIV antibodies were detected in 7.3 and 29.8% of women using in-house enzyme-linked immunosorbent assay (ELISA) and Seradyn Sentinel respectively. All cervicovaginal secretions found to be positive by in-house ELISA were also positive by Seradyn Sentinel. In a minority of women, ranging from 2.9% by in-house ELISA to 12.3% by Seradyn Sentinel, the anti-HIV antibodies were present in vaginal fluids that did not contain semen. Sexual exposure to HIV was similar in women with anti-HIV antibodies in their semen-free cervicovaginal secretions compared with women without anti-HIV antibodies in their cervicovaginal secretions. ConclusionsCervicovaginal HIV-specific antibodies were detected in a minority of sexually exposed HIV-seronegative female sex workers in Abidjan. The lack of association between increased sexual exposure to HIV and presence of cervicovaginal HIV-specific antibodies suggests that the production of genital HIV-specific antibodies in exposed seronegative women depends on the ability of individual women to mount specific mucosal immunity to HIV antigens, the determinants of which are currently unknown.
An ethnobotanical study of medicinal plants used by the Lisu people in Nujiang, Northwest Yunnan, China

An ethnobotanical survey was carried out to collect information on the use of medicinal plants by the Lisu people who live in the mountainous areas of the Nujiang Canyon (Salween River Valley) in Nujiang Prefecture, northwestern Yunnan Province, China. A total of 52 medicinal plants, belonging to 32 families, were reported as being used locally for the treatment of human ailments. The scientific and Lisu names, parts used, and preparation of the plants are presented. Most of these species are wild (80%), while others are domesticated (8%) or semi-cultivated (12%). Among the 52 species, 11 species (21.2%) were reported as rare and 16 were widely commercialized in the region. Over-exploitation and deforestation are the main causes for the depletion of medicinal plants in this area. The Lisu people still mostly depend on medicinal plants for their health care. The loss and endangered status of these plants will, to a certain extent, impede their existing health care system; conservation and sustainable harvest of medicinal plants in the area are urgently needed.
High susceptibility to pemphigus vulgaris due to HLA‐DRB1*14:54 in the Slovak population

The current work describes an association between pemphigus vulgaris (PV) and class II HLA alleles in the Slovak population, the first such study in Slovakia on the ‘high‐resolution level’. This work takes into account the new HLA allele nomenclature, officially adopted in 2010. In particular, we have focused on the associations between PV and DRB1*14:54 and DRB1*14:01. This case–control study was performed in a cohort of 43 PV Caucasian patients and 113 Caucasian control subjects from Slovakia. HLA typing was performed using PCR‐SSP (polymerase chain reaction with sequence‐specific primers). We found significantly positive associations between PV and the HLA alleles DRB1*04:02, DRB1*04:04, DRB1*14:54, DRB1*14:04, DRB1*14:05, DQB1*03:02 and DQB1*05:03. In contrast, HLA‐DQB1*06, DRB1*07 and DRB1*13 were negatively associated with PV. Importantly, 93% of PV patients possessed at least one of two HLA haplotypes, DRB1*04–DQB1*03 or HLA‐DRB1*14–DQB1*05. We confirmed the previously reported associations between HLA class II alleles and PV and described a new association between PV and DRB1*14:54. This allele was first described in 2005, and there has been only one report of its association with PV to date.
Neural Networks Applied to Speed Cheating Detection in Online Computer Games

This work presents a new approach to deal with speed cheating in online computer games. With the great growth of the online computer games, some efforts have been made to avoid cheaters in this scenario, but the models to avoid cheaters are localized into the protocol level. Examining the state-of-art, it was observed that research exploring the Artificial Intelligence application to this goal becomes relevant. This work shows the usage of artificial neural networks (ANN) applied in a massive multiplayer online games (MMOG) called Hoverkill to avoid this kind of cheat. Through the results's comparison from two different architectures approaches, the multi layer perceptron network (MLP) and the focused time lagged network (FTLFN), it was possible to conclude that their utilization avoiding speed cheating in MMOG is possible, once good results were found in this work.
Energy Harvesters Driven by Broadband Random Vibrations

Simple analytical models have proved very useful in understanding vibration energy harvesters driven by a sinusoidal acceleration. Corresponding analyses for broadband excitations have been absent. In this paper, we present new closed-form results on the output power, proof mass displacement, and optimal load of linear resonant energy harvesters driven by broadband vibrations. Output power dependence on signal bandwidth is also considered. The results are compared with those that are already well established for a sinusoidal acceleration. We formulate a stochastic description of more general energy-harvester models and show that the influence of elastic mechanical stoppers on the output power is dependent on the electrical load for large amplitude vibrations.
Glottal mixture model (GLOMM) for speaker identification on telephone channels

The Glottal Mixture Model (GLOMM) extracts speaker-dependent voice source information from speech data. It has previously been shown to provide speaker identification performance on clean speech comparable to universal background model (UBM), a state of the art method based on MFCC. And, when combined with UBM, the error rate was reduced by a factor of three, showing that the voice source information is largely independent of the information contained in the MFCC, yet holds as much speaker-related information. We now describe how GLOMM can be adapted for telephone quality audio and provide significant error reduction when combined with UBM and I-vector approaches. We demonstrate a factor of two error reduction on the NTIMIT data set with respect to the best published results.
Depictions of auditory verbal hallucinations in news media

Background: The characterization of auditory verbal hallucinations (AVH) in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V), diverges from recent research literature, which demonstrates the occurrence of AVH in individuals who are psychologically healthy. This discrepancy raises the question of how the public perceives AVH. Public perceptions are important because they could potentially affect how individuals with AVH interpret these experiences and how people view voice hearers. Aims: Because media portrayals can provide a window into how phenomena are viewed by the public, an archival study of newspaper articles was carried out to examine depictions of AVH. Methods: A sample of 181 newspaper articles originating in the United States was analyzed using a content analysis approach. Results: The majority of articles examined contained no suggestion that AVH are possible in psychologically healthy individuals. Most articles suggested that AVH were a symptom of mental illness, and many suggested that AVH were associated with criminal behavior, violence and suicidality. Conclusion: The news media examined tended to present a misleading and largely pathologizing view of AVH. More research is needed to shed light on how, and to what extent, public perceptions may influence those who experience AVH.
Using focused ethnography to explore and describe the process of nurses’ shift reports in a psychiatric intensive care unit

AIMS AND OBJECTIVES To explore and describe the cultural routine of shift reports among nursing staff in a psychiatric intensive care unit and further to develop a taxonomic, thematic and theoretical understanding of the process. BACKGROUND Lack of communication among healthcare staff is associated with risks for medical errors. Thus, handovers and shift reports are an essential and integral routine among nurses to pass on information about the patients' health status. Previous studies within the field have highlighted the benefits of structured reporting tools. However, shift reports as a cultural activity within the nursing tradition have been given less attention, not the least in psychiatric care. METHODS Focused ethnography was used. The data comprised 20 observational sessions. The observations ranged over a time span of 5 months and were conducted in a psychiatric intensive care unit in Sweden. RESULTS The process of shift reports encompassed the following three phases: (a) getting settled, (b) giving the report and (c) engaging in the aftermath. The results demonstrate that the phases entail different cultural activities, which take place in different areas of the ward and that the level of formality varied. CONCLUSIONS Shift reports are not an isolated event with clear boundaries. The study enriches the understanding of shift reports as a "fuzzy process". The individual phases were found to be tied to cultural connotations, such as activities, places and roles with certain meanings for staff members. RELEVANCE TO CLINICAL PRACTICE The new insights are useful for nurses in overcoming an uncritical adoption of the biomedical tradition regarding pace and tone during shift reports. The reporting nurse has the potential to transform shift reports from a monologue with a foreclosed style to a more dialogical interaction with colleagues that focuses on the patients' needs rather than the needs of staff.
Joint Bootstrapping Machines for High Confidence Relation Extraction

Semi-supervised bootstrapping techniques for relationship extraction from text iteratively expand a set of initial seed instances. Due to the lack of labeled data, a key challenge in bootstrapping is semantic drift: if a false positive instance is added during an iteration, then all following iterations are contaminated. We introduce BREX, a new bootstrapping method that protects against such contamination by highly effective confidence assessment. This is achieved by using entity and template seeds jointly (as opposed to just one as in previous work), by expanding entities and templates in parallel and in a mutually constraining fashion in each iteration and by introducing higherquality similarity measures for templates. Experimental results show that BREX achieves an F1 that is 0.13 (0.87 vs. 0.74) better than the state of the art for four relationships.
The cytotoxic effects of synthetic 6‐hydroxylated and 6‐methoxylated polybrominated diphenyl ether 47 (BDE47)

Polybrominated diphenyl ethers (PBDE) have been widely applied as flame retardants in plastics, polyurethane foam, paints, and synthetic fabrics. The rising PBDE level in human tissues and environment has led to concern about the health impact of exposure to PBDE. The 2,2′,4,4′‐tetrabromodiphenyl ether (BDE47), the dominant PBDE congener found in the environment and human tissues, has been shown to be an endocrine disruptor. It has also been reported to cause liver and neurodevelopmental toxicity. BDE47 can be metabolized to 6‐OH‐BDE47 and 6‐MeO‐BDE47. So far little has been reported on the cytotoxicity of the metabolites. In the present study, the cytotoxicity of the two metabolites was investigated by exposing human hepatoma cell line HepG2 to different doses of 6‐OH‐BDE47 and 6‐MeO‐BDE47. The cell viability, cell cycle, apoptosis, DNA damage, micronucleus levels, and oxidative stress response were studied. The results indicated that both metabolites could markedly inhibit the proliferation of HepG2 cells with 6‐OH‐BDE47 showing a stronger effect, and significantly increase the micronucleus level and apoptosis rate in a dose‐dependant manner. Moreover, treatment with 6‐OH‐BDE47 (≥0.5 μM) resulted in a marked cell cycle block. The SCGE experiments revealed that both metabolites could cause DNA damage in a dose‐dependant manner. Analysis of the oxidative stress response showed that 6‐OH‐BDE47 treatment (≥2.0 μM) significantly increased intracellular ROS levels as indicated by GSH depletion and elevation of SOD level, whereas 6‐MeO‐BDE47 showed a weaker effect, suggesting that oxidative stress might play a role in the cytotoxic effects. We concluded that 6‐OH‐BDE47 or 6‐MeO‐BDE47 exposure was able to induce inhibition of cell viability, increase of apoptosis rate, cell cycle block, and DNA damages, which might involve the alterated oxidative stress response due to the elevated free radicals and impaired antioxidative system. © 2010 Wiley Periodicals, Inc. Environ Toxicol, 2011.
Improvement of MFCC feature extraction accuracy using PCA in Indonesian speech recognition

In the pattern recognition system, there are many methods used. For speech recognition system, Mel Frequency Cepstral Coefficients (MFCC) becomes a popular feature extraction method but it has various weaknesses especially about the accuracy level and the high of result feature dimension of the extraction method. This paper presents the combination of MFCC feature extraction method with Principal Component Analysis (PCA) to improve the accuracy in Indonesian speech recognition system. By combining MFCC and PCA, it was expected to increase the accuracy system and reduce the feature data dimension. The result of MFCC data features extraction added with delta coefficients formed matrix data that later would be reduced using PCA. PCA method in the process of data reduction was designed to be two versions. Then the result of PCA reduction data was processed to the classification process using K-Nearest Neighbour (KNN) method. Composing the data was formed from 140 speech data that were recorded from 28 speakers. The research findings showed that adding PCA method version 1 could reduce the feature dimension from 26 to 12 by the same accuracy of speech recognition with the conventional MFCC method without PCA, that is 86.43%. Whereas PCA method version 2 could increase the accuracy of speech recognition from the conventional MFCC method without PCA in increasing from 86.43% to 89.29% and decreasing of the data dimension from 26 to 10 feature dimensions.
Characterizing the Usage and Impact of Java Annotations Over 1000+ Projects

As a kind of meta-data feature, annotations have been formally introduced into Java since Java 5. Since the introduction, annotations have been widely used by the Java community for different purposes, such as compiler guidance and runtime processing. Despite the ever-growing use, there is still limited empirical evidence about how developers use annotations in practice and the impact of annotation use on software quality. To fill this gap, we perform the first large-scale empirical study about Java annotation uses on 1,094 open-source projects hosted on GitHub. Our study answers some fundamental questions about Java annotation use. First, we answer the question "annotate what? " and find that annotations are typically used to annotate 4 aspects of program elements. Second, we answer the question "how annotations evolve? " and identify 6 different annotation change types, their frequencies, and their characteristics. Third, we answer the question "who uses annotations? " and establish the relationships between annotation uses and code ownership and developer experience. In addition, we also use regression models to explore the correlation between annotation uses and code quality, and we find that annotations do have an impact on making code less error-prone.
Ring Compute-and-Forward Over Block-Fading Channels

The compute-and-forward (C&F) protocol in quasi-static channels normally employs lattice codes based on the rational integers <inline-formula> <tex-math notation="LaTeX">$\mathbb {Z}$ </tex-math></inline-formula>, the Gaussian integers <inline-formula> <tex-math notation="LaTeX">$\mathbb {Z} [i]$ </tex-math></inline-formula>, or the Eisenstein integers <inline-formula> <tex-math notation="LaTeX">$\mathbb {Z} [\omega ]$ </tex-math></inline-formula>, while its extension to more general channels often assumes channel state information at transmitters (CSIT). In this paper, we propose a novel scheme for C&F in block-fading channels without CSIT, which is referred to as ring C&F because the fading coefficients are quantized to the canonical embedding of a ring of algebraic integers. Owing to the multiplicative closure of the algebraic lattices employed, a relay is able to decode an algebraic–integer linear combination of lattice codewords. We analyze its achievable computation rates and show it outperforms conventional C&F based on the <inline-formula> <tex-math notation="LaTeX">$\mathbb {Z}$ </tex-math></inline-formula>-lattices. By investigating the effect of the Diophantine approximation by algebraic conjugates, we prove that the degrees of freedom (DoFs) of the optimized computation rate are <inline-formula> <tex-math notation="LaTeX">${n}/{L}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> is the number of blocks and <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> is the number of users.