Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECT OF TRANSACTIONAL ANALYSIS TRAINING ON POSITIVE AND NEGATIVE AFFECT

The present research was performed with the purpose of surveying the effect of transactional analysis training on positive and negative affect of working women. This research has been an applied research in a quasi experimental research group (pre-test, post-test design with an unequal control group). 40 working women were selected to participate in the study applying convenient sampling method among which 20 were in control group and 20 were put in experimental group. The numbers of the experimental group were reduced to 16 persons after falling. First, these persons were tested to measure the positive and negative affect. Then, the control group was trained transactional analysis for 8 sections (once a week and for 90 minutes in each section). After the completion of the training course, post test were performed to measure the positive and negative affect rate in two groups. The results demonstrated that transactional analysis method of training could have a significant effect on negative affect
Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.
Forecasting Seasonal Influenza Fusing Digital Indicators and a Mechanistic Disease Model

The availability of novel digital data streams that can be used as proxy for monitoring infectious disease incidence is ushering in a new era for real-time forecast approaches to disease spreading. Here, we propose the first seasonal influenza forecast framework based on a stochastic, spatially structured mechanistic model (individual level microsimulation) initialized with geo-localized microblogging data. The framework provides for more than 600 census areas in the United States, Italy and Spain, the initial conditions for a stochastic epidemic computational model that generates an ensemble of forecasts for the main indicators of the epidemic season: peak time and intensity. We evaluate the forecasts accuracy and reliability by comparing the results with the data from the official influenza surveillance systems in the US, Italy and Spain in the seasons 2014/15 and 2015/16. In all countries studied, the proposed framework provides reliable results with leads of up to 6 weeks that became more stable and accurate with progression of the season. The results for the United States have been generated in real-time in the context of the Centers for Disease Control and Prevention ``Forecasting the Influenza Season Challenge''. A characteristic feature of the mechanistic modeling approach is in the explicit estimate of key epidemiological parameters relevant for public health decision-making that cannot be achieved with statistical models that do not consider the disease dynamic. Furthermore, the presented framework allows the fusion of multiple data streams in the initialization stage and can be enriched with census, weather and socioeconomic data.
On the Distribution of the Welfare Losses of Large Recessions

How big are the welfare losses from severe economic downturns, such as the U.S. Great Recession? How are those losses distributed across the population? In this paper we answer these questions using a canonical business cycle model featuring household income and wealth heterogeneity that matches micro data from the Panel Study of Income Dynamics (PSID). We document how these losses are distributed across households and how they are affected by social insurance policies. We find that the welfare cost of losing one's job in a severe recession ranges from 2% of lifetime consumption for the wealthiest households to 5% for low-wealth households. The cost increases to approximately 8% for low-wealth households if unemployment insurance benefits are cut from 50% to 10%. The fact that welfare losses fall with wealth, and that in our model (as in the data) a large fraction of households has very low wealth, implies that the impact of a severe recession, once aggregated across all households, is very significant (2.2% of lifetime consumption). We finally show that a more generous unemployment insurance system unequivocally helps low-wealth job losers, but hurts households that keep their job, even in a version of the model in which output is partly demand determined, and therefore unemployment insurance stabilizes aggregate demand and output.
Bacteremia Caused by Escherichia coli producing Extended-spectrum Beta-lactamase: a Case-control Study of Risk Factors and Outcomes

A case-control study was conducted in order to identify the risk factors associated with bloodstream infection caused by Escherichia coli producing extended-spectrum β-lactamase (ESBL) and to determine the outcomes of infected patients. Risk factors associated with ESBL production, according to univariate analysis, included a history of recent hospitalization [odds ratio (OR) 4.3, 95% confidence interval (CI) 2.1-8.9; p < 0.001], severe underlying diseases (OR 15, 95% CI 4.4-51.5; p < 0.001), prior exposure to urinary catheters (OR 8.3, 95% CI 3.2-21.7; p < 0.001) and nosocomial (OR 14.1, 95% CI 6.1-32.8; p < 0.001) or urinary (OR 3.6, 95% CI 1.7-7.4; p < 0.001) origin of the bacteria. Multivariate analysis revealed that severe underlying diseases (OR 31.2, 95% CI 6.7-144; p < 0.001) and nosocomial (OR 16.5, 95% CI 5.6-49; p < 0.001) and urinary origins (OR 7.8, 95% CI 2.6-23.8; p < 0.001) of the bacteria were independently associated with ESBL production in bacteremic E. coli. Crude mortality in case patients was more than twice as high as that in controls (p = 0.04). Production of ESBL increased the risk of inappropriate initial therapy (OR 95.6, 95% CI 27.4-334.2; p < 0.001). Treatment failed in 4/7 case patients treated with ceftazidime to which the isolate was susceptible in vitro. Our findings have implications for the choice of empirical therapy in nosocomial urinary tract infection.
A retrospective study of canine D-dimer concentrations measured using an immunometric "Point-of-Care" test.

OBJECTIVES To measure the D-dimer concentrations in both healthy dogs and dogs with and without evidence of thromboembolic disease/disseminated intravascular coagulation using a "Point-of-Care" test. METHODS Sixty-seven clinical cases and 26 healthy dogs were included in this retrospective study. D-dimer was measured using the NycoCard D-dimer test. Clinical conditions were categorised based on clinical findings, laboratory results, imaging, cytology, histopathology, necropsy or a combination of these tests. RESULTS There were no dogs for which the NycoCard D-dimer test did not produce a result. The D-dimer range in clinically healthy dogs was 0.1 to 0.5 mg/l (median 0.2 mg/l). In eight of nine cases with thromboembolic disease/disseminated intravascular coagulation and 43 of 58 of the cases without thromboembolic disease/disseminated intravascular coagulation , the D-dimer concentrations were greater than those of healthy dogs. CLINICAL SIGNIFICANCE The NycoCard D-dimer test card required no specialised equipment and could therefore facilitate rapid screening for thromboembolic disease/disseminated intravascular coagulation in first opinion practice. Elevations in D-dimer concentration can be found in a number of clinical conditions apart from thromboembolic disease/disseminated intravascular coagulation and should not therefore be used as the sole basis of diagnosis. D-dimer may be considered a good screening test for thromboembolic disease/disseminated intravascular coagulation as only one case with histopathological evidence of thromboembolic disease/disseminated intravascular coagulation had a D-dimer concentration in the range seen in healthy dogs.
Estimating trends in data from the Weibull and a generalized extreme value distribution

Where changes in hydrologic regime occur, whether as a result of change in land use or climate, statistical procedures are needed to test for the existence of trend in hydrological data, particularly those expected to follow extreme value distributions such as annual peak discharges, annual minimum flows, and annual maximum rainfall intensities. Furthermore, where trend is detected, its magnitude must also be estimated. A later paper [ Clarke, 2002 ] will consider the estimation of trends in Gumbel data; the present paper gives results on tests for the significance of trends in annual and minimum discharges, where these can be assumed to follow a Weibull distribution. The statistical procedures, already fully established in the statistical analysis of survival data, convert the problem into one in which a generalized linear model is fitted to a power‐transformed variable having Poisson distribution and calculates the trend coefficients (as well as the parameter in the power transform) by maximum likelihood. The methods are used to test for trend in annual minimum flows over a 19‐year period in the River Paraguay at Cáceres, Brazil, and in monthly flows at the same site. Extension of the procedure to testing for trend in data following a generalized extreme value distribution is also discussed. Although a test for time trend in Weibull‐distributed hydrologic data is the motivation for this paper, the same approach can be applied in the analysis of data sequences that can be regarded as stationary in time, for which the objective is to explore relationships between a Weibull variate and other variables (covariates) that explain its behavior.
“We The Parents Were Actually More Nervous About The Change” – How Parents Experience Their Child's Schooling in Upper Primary School

The study set out to explore parents' experiences of their child's upper primary schooling. Academically and vocationally educated mothers and fathers (N = 326) were prompted to give positive and negative comments on their child's school years at the end of his/her 7th and 9th grade. It was found that a great majority of the comments were positive and that the mothers and the academically educated parents reported significantly more of both positive and negative events from their child's school years than the vocationally educated parents and the fathers did. Furthermore, the parents of boys expressed more concerns than those of girls did. It was concluded that parents' social position, such as education and gender, seem to be good measures of their social-psychological distance from the school.
Yoga for the prevention of depression, anxiety, and aggression and the promotion of socio-emotional competencies in school-aged children

Children and youth coming from disadvantaged socioeconomic backgrounds are at risk of developing behavioural problems. This study examined the efficacy of a Yoga programme implemented in a low-socioeconomic status school, for the prevention of depression, anxiety, and aggression. After-school workshops were delivered twice a week during 12 weeks to 125 students in 5th, 8th, and 9th grades, enrolled in a school in Bogotá, Colombia. Participants were randomly assigned to an intervention and to a control group. Children's anxiety, depression, aggression, and some socioemotional competencies (specifically empathy, anger management, and prosociality) were quantitatively assessed before and after the intervention, by means of self- and peer-reported questionnaires. Qualitative data were also collected to assess children's perceived benefits from the workshops. Results suggested a potential of the programme to reduce children's anxiety problems, in particular. Results are discussed in terms of recommended improvements to the programme and its future evaluation.
Meta-Analysis of the Efficacy and Safety of Mirabegron Add-On Therapy to Solifenacin for Overactive Bladder

Purpose We performed a meta-analysis to evaluate the efficacy and safety of mirabegron add-on therapy to solifenacin for patients with overactive bladder (OAB). Methods We conducted a systematic literature review to identify all randomized, double-blind, controlled trials (RCTs) of this combination (mirabegron and solifenacin) for OAB. Embase, MEDLINE, and the Cochrane Central Register of Controlled Trials were searched. A manual search was also performed to investigate relevant references from the retrieved studies. Results Four publications describing 5 RCTs that compared combination therapy with solifenacin, including a total of 3,309 patients, were analyzed. The mean number of micturitions per 24 hours (mean difference [MD], -0.45; 95% confidence interval [CI], -0.65 to -0.26; P<0.00001), number of episodes of incontinence per 24 hours (MD, -0.71; 95% CI, -0.14 to -0.02; P=0.04), volume voided per micturition, and number of urgency episodes per 24 hours demonstrated that combination therapy was more effective than solifenacin therapy alone. Safety assessments, including common treatment-emergent adverse events (odds ratio, 1.09; 95% CI, 0.95–1.27; P=0.23) and discontinuations due to adverse events (P=0.30), demonstrated that the combination therapy was well tolerated. Conclusions This meta-analysis suggests that mirabegron therapy as an add-on to solifenacin provides a satisfactory therapeutic effect for OAB symptoms with a low occurrence of side effects.
On the design and performance of prefix-preserving IP traffic trace anonymization

Even though real-world Internet traffic traces are crucial for network research, only a tiny percentage of traffic traces collected are made public. One major reason why traffic trace owners hesitate to make the traces publicly available is the concern that the confidential and private information may be inferred from the trace. In this paper we focus on the problem of anonymizing IP addresses in a trace. More specifically, we are interested in prefixpreserving anonymization in which the prefix relationship among IP addresses is preserved in the anonymized trace, making such a trace usable in situations where such prefix relationships are important. The goal of our work is two fold. First, we are interested in analyzing the security properties inherent in prefix-preserving IP address anonymization. Through the analysis of IP traffic traces, we investigate the effect of some types of attacks on the security of the prefix-preserving anonymization process. We also derive results for the optimum manner in which an attack should proceed which provides a bound on the performance of attacks in general. Second, we observe that an existing scheme used for prefix-preserving anonymization, TCPdpriv, has some drawbacks that limit its use in a large-scale, distributed setting. We develop an alternative cryptography-based, prefixpreserving anonymization technique to address these drawbacks while maintaining the same level of anonymity as TCPdpriv.
Here to Stay? The Rising Threat of Violent Dissident Republicanism in Northern Ireland

Since the advent of the Good Friday peace agreement, violence associated with dissident Irish Republican groups continues to present major security challenges. While there has not been a tragedy on the scale of the 1998 Omagh bombing, the level of violent dissident Republican (VDR) activity has risen steadily in frequency since then, and in 2010 reached unprecedented levels. This article presents findings from the VDR Project at the International Center for the Study of Terrorism at Pennsylvania State University. The research is based on the extensive identification, collection, and analysis of open source material examining the nature and extent of VDR activity from 1997 to 2010. The project analyses data on VDR activity across this period as well as the individuals taking part in these violent events. The data suggests that while originally recruitment was predominantly southern based it is now more focused on Northern Ireland. Analysis of the data also indicates that the VDR leadership continues to recruit individuals with skill-sets to serve the movement's aims.
Smooth estimation of mean residual life under random censoring

We propose here a smooth estimator of the mean residual life function based on randomly censored data. This is derived by smoothing the product-limit estimator using the Chaubey-Sen technique (Chaubey and Sen (1998)). The resulting estimator does not suffer from boundary bias as is the case with standard kernel smoothing. The asymptotic properties of the estimator are investigated. We establish strong uniform consistency and asymptotic normality. This complements the work of Chaubey and Sen (1999) which considered a similar estimation procedure in the case of complete data. It is seen that the properties are similar, though technically more difficult to prove, to those in the complete data case with appropriate modifications due to censoring.
Negotiating ‘ethically important moments’ in research with young people: reflections of a novice researcher

Abstract The latter half of the twentieth century witnessed a surge in interest around ethics in research. Originally focused on the compilation of ethics guidelines and the importance of having all research approved by institutional review boards before commencement, discussions of research ethics have more recently centred on how such guidelines translate into ethical practice during the research process. Leisure research has been no exception to this trend. Using as an example, a research project in Ireland centred on focus groups with young people (aged 15–19) regarding their physical activity behaviours and preferences, this paper explores the situated judgement of the interviewer, a novice researcher, as she attempted to navigate four ethically important moments. Discussions centre on moments where the interviewer’s situated judgement resulted in research ethics being compromised and moments where the interviewer experienced difficulty reconciling personal and research ethics. Our intention in sharing the situations and resulting questions from this research is to shine a light on the decision-making which takes place during the research process and consider how researchers might prepare adequately to make decisions in an ethically sound way.
A Hierarchical Multi-Label Classification Algorithm for Gene Function Prediction

Gene function prediction is a complicated and challenging hierarchical multi-label classification (HMC) task, in which genes may have many functions at the same time and these functions are organized in a hierarchy. This paper proposed a novel HMC algorithm for solving this problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph (DAG) and is more difficult to tackle. In the proposed algorithm, the HMC task is firstly changed into a set of binary classification tasks. Then, two measures are implemented in the algorithm to enhance the HMC performance by considering the hierarchy structure during the learning procedures. Firstly, negative instances selecting policy associated with the SMOTE approach are proposed to alleviate the imbalanced data set problem. Secondly, a nodes interaction method is introduced to combine the results of binary classifiers. It can guarantee that the predictions are consistent with the hierarchy constraint. The experiments on eight benchmark yeast data sets annotated by the Gene Ontology show the promising performance of the proposed algorithm compared with other state-of-the-art algorithms.
Strategy of Surgical Management of Peripheral Neuropathy Form of Diabetic Foot Syndrome in Ghana

Introduction. Foot disorders such as ulceration, infection, and gangrene which are often due to diabetes mellitus are some major causes of morbidity and high amputation. Aim. This study aims to use a group of methods for the management of diabetic foot ulcers (DFU) in order to salvage the lower limb so as to reduce the rate of high amputations of the lower extremity. Materials and Methods. A group of different advanced methods for the management of DFU such as sharp debridement of ulcers, application of vacuum therapy, and other forms of reconstructive plastic surgical procedures were used. Data collection was done at 3 different hospitals where the treatments were given. Results. Fifty-four patients with type 2 diabetes mellitus were enrolled in the current study: females n = 37 (68.51%) and males n = 17 (31.49%) with different stages of PEDIS classification. They underwent different methods of surgical management: debridement, vacuum therapy (some constructed from locally used materials), and skin grafting giving good and fast results. Only 4 had below knee amputations. Conclusion. Using advanced surgical wound management including reconstructive plastic surgical procedures, it was possible to reduce the rate of high amputations of the lower limb.
Behavioral Finance: Contributions of Cognitive Psychology and Neuroscience to Decision Making

This paper employs a five-paradigm model to assess various contributions of cognitive psychology and neuroscience to understanding financial decision making. Whereas conventional academic finance emphasizes financial theory, the emerging field of behavioral finance encompasses investigations of cognitive and emotional factors affecting the financial decision making processes of individuals, groups, and organizations. It looks at how people really make financial decisions, not at how theory predicts they should make such decisions. Behavioral finance expands our understanding of financial decision making in terms of personal financial decisions and how markets work but also comprises a new instrument in the decision maker’s toolbox.
Prevalence, characteristics and prognostic significance of anemia in daily practice.

BACKGROUND The prevalence of anemia has been studied in well-defined populations, but no large study is available for less restricted populations with various disorders. DESIGN Two-phase nationwide study: (i) a cross-sectional study including 1351 patients aimed to define the prevalence and characteristics of anemic patients seen in France, and (ii) a prospective longitudinal study of 398 anemic patients aimed to define factors associated with survival. RESULTS Anemia was present in 874 (65%) patients according to WHO criteria, and 573 (42%) patients had hemoglobin levels <110 g/l. Characteristics independently associated with anemia were the presence of cancer, hematological disorder, renal failure and inflammatory syndrome. Baseline factors negatively associated with the 3-month survival were cancer, older age and a lower target hemoglobin level defined at baseline. Negative predictive factors at Month 3 of the 6-month survival were older age and the absence of correction of anemia according to the target hemoglobin level defined at baseline. CONCLUSION Anemia is frequent and is associated with cancer, hematological disorders, renal failure and inflammatory syndrome. At baseline, prognostic factors of 3-month survival include cancer, older age and lower target hemoglobin level, whereas reaching the target hemoglobin level at Month 3 has a favorable prognostic impact on 6-month survival.