Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative effects of long-acting and short-acting loop diuretics on cardiac sympathetic nerve activity in patients with chronic heart failure

Objective Short-acting loop diuretics are known to enhance cardiac sympathetic nerve activity (CSNA) in patients with chronic heart failure (CHF). The effects of two loop diuretics—long-acting azosemide and short-acting furosemide—on CSNA were evaluated using 123I-metaiodobenzylguanidine (MIBG) scintigraphy in patients with CHF. Methods The present study was a subanalysis of our previously published study, which had reported that serial 123I-MIBG studies were the most useful prognostic indicator in patients with CHF. Patients with CHF (n=208, left ventricular ejection fraction <45%) but no history of cardiac events for at least 5 months prior to the study were identified according to their histories of acute decompensated heart failure requiring hospitalisation. Patients underwent 123I-MIBG scintigraphy immediately before hospital discharge and at a 6-month follow-up. The delayed % denervation, delayed heart/mediastinum count (H/M) ratio and washout rate (WR) were determined using 123I-MIBG scintigraphy. A total of 108 patients were selected, and propensity score matching was used to compare patients treated with either oral azosemide (n=54) or furosemide (n=54). Results After treatment, 123I-MIBG scintigraphic parameters improved in both groups. However, the degree of change in % denervation was −13.8±10.5 in the azosemide group and −5.7±12.7 in the furosemide group (p<0.01), the change in H/M ratio was 0.20±0.16 in the azosemide group and 0.06±0.19 in the furosemide group (p<0.01), and the change in WR was −11.3±9.2% in the azosemide group and −3.0±12.7% in the furosemide group (p<0.01). Moreover, multivariate analysis showed an independent and significant positive relationship between furosemide and δ-WR from hospital discharge to 6 months after treatment in patients with CHF (p=0.001). Conclusions These findings indicate that azosemide suppresses CSNA compared with furosemide in patients with CHF. Trial registration number UMIN000000626 (UMIN-CTR Clinical Trial).
Transportation Noise and Blood Pressure in a Population-Based Sample of Adults

Background: There is some evidence for an association between traffic noise and ischemic heart disease; however, associations with blood pressure have been inconsistent, and little is known about health effects of railway noise. Objectives: We aimed to investigate the effects of railway and traffic noise exposure on blood pressure; a secondary aim was to address potentially susceptible subpopulations. Methods: We performed adjusted linear regression analyses using data from 6,450 participants of the second survey of the Swiss Study on Air Pollution and Lung Disease in Adults (SAPALDIA 2) to estimate the associations of daytime and nighttime railway and traffic noise (A-weighted decibels) with systolic blood pressure (SBP) and diastolic blood pressure (DBP; millimeters of mercury). Noise data were provided by the Federal Office for the Environment. Stratified analyses by self-reported hypertension, cardiovascular disease (CVD), and diabetes were performed. Results: Mean noise exposure during the day and night was 51 dB(A) and 39 dB(A) for traffic noise, respectively, and 19 dB(A) and 17 dB(A) for railway noise. Adjusted regression models yielded significant effect estimates for a 10 dB(A) increase in railway noise during the night [SBP β = 0.84; 95% confidence interval (CI): 0.22, 1.46; DBP β = 0.44; 95% CI: 0.06, 0.81] and day (SBP β = 0.60; 95% CI: 0.07, 1.13). Additional adjustment for nitrogen dioxide left effect estimates almost unchanged. Stronger associations were estimated for participants with chronic disease. Significant associations with traffic noise were seen only among participants with diabetes. Conclusion: We found evidence of an adverse effect of railway noise on blood pressure in this cohort population. Traffic noise was associated with higher blood pressure only in diabetics, possibly due to low exposure levels. The study results imply more severe health effects by transportation noise in vulnerable populations, such as adults with hypertension, diabetes, or CVD.
Personality and Social Psychology Psychological effects of (non)employment: A cross-national comparison of the United States and Japan

Gnambs, T. , Stiglbauer, B. & Selenko, E. (2015). Psychological effects of (non)employment: A cross-national comparison of the United States and Japan. Scandinavian Journal of Psychology, 56 ,6 59–669. The involuntary loss of employment has been shown to deteriorate subjective well-being. Adopting a cross-cultural perspective on Jahoda’s (1982) deprivation model this study examines several latent and manifest benefits of work that were expected to mediate the effects of employment status on wellbeing. It was hypothesized that in more collectivistic societies the decline in subjective well-being would be a consequence of a diminished sense of collective purpose for the non-employed, whereas in individualistic societies the crucial factors would be a loss of social status and financial benefits. The findings from two representative national surveys conducted in the United States (N = 1,093) and Japan (N = 647) provided partial support for these hypotheses. Cultural differences moderated the effects of employment status on the benefits of work. As a consequence, different processes mediated the decline in well-being for the non-employed in the two countries. These results are embedded within the wider discourse on culture and its effect on unemployment.
NETWORKS , LEADERS , AND TIME IN TEAMS : CONNECTIONS TO VIABILITY AND PERFORMANCE

How do social network structures of teams, leaders and members help or hinder effectiveness? We answer that question via a meta-analysis of 31 studies with 67 effect sizes spanning six decades and involving 2618 teams working in natural contexts. Teams with dense rather than sparse configurations of interpersonal ties better attain their goals (team task performance), and are more committed to staying together (team viability). In addition, teams with leaders who are central in the intrateam network, and teams that are central in the intergroup network, tend to be more productive. Temporal features and the content of ties moderate social network-team task performance connections. Results augur for stronger incorporation of network concepts into theories about team effectiveness. 1 Teams have become the basic unit through which work is carried out in organizations (Gerard, 1995). The prevalence of team structures in contemporary organizations has been paralleled by a vigorous stream of theory and applied research (Ilgen, 1999). In hundreds of studies, researchers have attempted to understand the factors contributing to team effectiveness To take stock of these studies, various meta-analyses of the antecedents of team effectiveness have been conducted. The meta-analyses affirm definitive answers regarding the effects of some of those antecedents, such as collective efficacy Despite this impressive and growing body of findings about determinants of team outcomes, our understanding of a potentially critical set of determinants is limited. Namely, social network structures, or the patterns of informal connections ("ties") among individuals, can have important implications for teams because they have the potential to facilitate and constrain the flow of resources between and within teams (Brass, 1984). Despite a recent resurgence of consensus nor awareness surrounding what is known about social network effects in work groups or teams-perhaps because most such studies were conducted before current researchers and their mentors were trained (e.g., Fiedler, 1954) or because of academic amnesia (Hunt & Dodge, 2000). Indeed, unresolved questions and debates persist about whether or not some social network features yield longer survival or improved task completion in teams. For example, some investigators have found that the density of a team's network of informal social ties is associated with team performance (Reagans & Zuckerman, 2001); whereas others have not 2 (Sparrowe, Liden, Wayne, & Kraimer, 2001). Similarly, some have proposed that a leader who is central in the team network of friendship ties has a burden of maintaining too many close relationships …
Monday mornings are my fave :) #not Exploring the Automatic Recognition of Irony in English tweets

Recognising and understanding irony is crucial for the improvement natural language processing tasks including sentiment analysis. In this study, we describe the construction of an English Twitter corpus and its annotation for irony based on a newly developed fine-grained annotation scheme. We also explore the feasibility of automatic irony recognition by exploiting a varied set of features including lexical, syntactic, sentiment and semantic (Word2Vec) information. Experiments on a held-out test set show that our irony classifier benefits from this combined information, yielding an F1-score of 67.66%. When explicit hashtag information like #irony is included in the data, the system even obtains an F1-score of 92.77%. A qualitative analysis of the output reveals that recognising irony that results from a polarity clash appears to be (much) more feasible than recognising other forms of ironic utterances (e.g., descriptions of situational irony).
From the Milk River: Spatial and temporal processes in Northwest Amazonia: Works cited

List of figures, tables and maps List of myths Preface Acknowledgements Orthography 1. Introduction 2. Social structure 3. The set of specialist roles 4. Kinship and marriage 5. The life-cycle 6. Production and consumption 7. Concepts of space-time 8. Conclusion Appendices Works cited Index.
Evaluating Content Selection in Human- or Machine-Generated Summaries: The Pyramid Scoring Method

From the outset of automated generation of summaries, the diÆculty of evaluation has been widely discussed (e.g., [10] [25]). Despite many promising attempts, we believe it remains an unsolved problem. Here we present a method for scoring the content of summaries of any length against a weighted inventory of content units, which we refer to as a pyramid. Our method is derived from empirical analysis of human-generated summaries, and provides an informative metric for human or machine-generated summaries. It is particularly suited for naturalistic summaries of multiple documents. By naturalistic summaries, we mean humanor machine-generated summaries that select information from source texts and re-present the information in concise, uent text. What di erentiates the pyramid method from other approaches is that we take the frequently made observation that there is no best model summary as a foundation, rather than an obstacle. As we discuss later, we think the use of multiple models, while preferable to a single gold standard, can only be an indirect way of approximatingwhat a pyramid addresses directly. Previous work has shown that despite the observed variations in content across human summaries, certain information will be consistently selected from a source text ([3]). Our inventory-based approach assigns di erential weights to content units, depending on their cognitive importance as re ected by their frequency within a pool of summaries. Given a pyramid inventory, there can exist multiple con gurations of content units that would be assigned the same score. As a consequence, our method predicts multiple, equally good summaries. Our score is calibrated to observed distributions of content units in human summaries, rather than to highly variable human scores (in contrast to the approach taken in [7]), because it is diÆcult to elicit robust ratings from humans. To construct the pyramid, we abstract from a repository of human-written summaries, although we believe this is only one method for constructing a pyramid. We believe alternative methods, such as eliciting human judgments about the content in the source texts ([22]), might lead to equally useful weighted inventories.
Anxiety Increases the Feeling of Presence in Virtual Reality

Given previous studies indicating a significant correlation between anxiety and presence, the purpose of this investigation was to explore the direction of the causal relationship between them. The sample consisted of 31 adults suffering from snake phobia. The study featured a randomized within-between design with two conditions and three counterbalanced immersions: (a) a baseline control immersion (BASELINE), (b) an immersion in a threatening and anxiety-inducing environment (ANX), and (c) an immersion in a nonthreatening environment that should not induce anxiety (NOANX). In the NOANX environment, participants were immersed for 5 min in a virtual Egyptian desert. They were told that the environment was safe and contained no snakes. The ANX immersion was identical, except that participants were led to believe that a multitude of hidden and dangerous snakes were lurking in the environment. A period of distraction (reading a text on relaxation) separated the ANX and NOANX immersions. Experimenters recorded presence and anxiety in the middle of and after each VR immersion. These brief measures of presence supported our hypothesis and were significantly higher in the anxious immersion than in the baseline or the nonanxious immersion. This finding was not corroborated by the presence questionnaire, where scores varied significantly in the opposite direction. The results from the brief one-item measures of presence support the significant contribution of emotions felt during the immersion on the subjective feeling of presence. The mixed results with the presence questionnaire are discussed, along with psychological factors potentially involved in presence.
Unsupervised learning of affordance relations on a humanoid robot

In this paper, we study how the concepts learned by a robot can be linked to verbal concepts that humans use in language. Specifically, we develop a simple tapping behaviour on the iCub humanoid robot simulator and allow the robot to interact with a set of objects of different types and sizes to learn affordance relations in its environment. The robot records its perception, obtained from a range camera, as a feature vector, before and after applying tapping on an object. We compute effect features by subtracting initial features from final features. We cluster the effect features using Kohonen self-organizing maps to generate a set of effect categories in an unsupervised fashion. We analyze the clusters using the types and sizes of objects that fall into the effect clusters, as well as the success/fail labels manually attached to the interactions. The hand labellings and the clusters formed by robot are found to match. We conjecture that this leads to the interpretation that the robot and humans share the same “effect concepts” which could be used in human-robot communication, for example as verbs. Furthermore, we use ReliefF feature extraction method to determine the initial features that are related to clustered effects and train a multi-class support vector machine (SVM) classifier to learn the mapping between the relevant initial features and the effect categories. The results show that, 1) despite the lack of supervision, the effect clusters tend to be homogeneous in terms of success/fail, 2) the relevant features consist mainly of shape, but not size, 3) the number of relevant features remains approximately constant with respect to the number of effect clusters formed, and 4) the SVM classifier can successfully learn the effect categories using the relevant
Impact of Surgical Approach on Clinical Outcomes in the Treatment of Lumbar Pseudarthrosis

Study Design Retrospective comparative cohort. Objective Pseudarthrosis following fusion for degenerative lumbar spine pathologies remains a substantial problem. Current data shows that patients who develop a pseudarthrosis have suboptimal outcomes. This study evaluates if treatment of pseudarthrosis can be affected by surgical approach. Methods Medical records of 63 female and 65 male patients (mean age 50.37) who were treated for nonunion following lumbar fusion were reviewed. Sixty patients underwent posterolateral fusion (PSF), 18 underwent PSF with transforaminal interbody fusion (TLIF), 32 underwent anterior and posterior spinal fusion (AP), and 24 underwent anterior lumbar interbody fusion (ALIF). Results Significant differences between the treatment groups were observed in length of stay (p = 0.000), blood loss (p = 0.000), and operative time (p = 0.000). In the AP fusion group, minimal clinically important difference (MCID) was reached in 47% of patients for back pain, 28% for leg pain, and 28% for Oswestry Disability Index (ODI). PSF had the highest percentage of patients reaching MCID for Short Form-36 (SF-36) physical composite score at 25%. ALIF and TLIF subgroups reached MCID for ODI in 17% of patients. Linear regression analysis showed that type of surgical approach did not impact change in ODI scores. Conclusion Although not statistically significant, the AP fusion group reached MCID more frequently in all outcomes except SF-36 Physical Component Summary. All surgical approaches examined for treatment of lumbar pseudarthrosis resulted in only poor to modest improvement in ODI. This result further emphasizes the importance of achieving a solid fusion with the index surgery.
A Manifesto for Higher Order Mutation Testing

We argue that higher order mutants are potentially better able to simulate real faults and to reveal insights into bugs than the restricted class of first order mutants. The Mutation Testing community has previously shied away from Higher Order Mutation Testing believing it to be too expensive and therefore impractical. However, this paper argues that Search Based Software Engineering can provide a solution to this apparent problem, citing results from recent work on search based optimization techniques for constructing higher order mutants. We also present a research agenda for the development of Higher Order Mutation Testing.
Exact BER analysis of distributed alamouti's code for cooperative diversity networks

We analyze the bit-error rate (BER) performance of the distributed Alamouti's code for cooperative diversity networks consisting of a source, two relays and a destination node over Rayleigh fading channels. It is assumed that the relays adopt the amplify-and-forward protocol. Firstly, assuming the existence of the direct path component from the source to the destination, we derive the exact BER expression in a one-integral form for M-pulse amplitude modulation (PAM) and M-quadrature amplitude modulation (QAM) constellations. We also present a series expansion of a very accurate BER approximation, which does not require any numerical calculation, and we prove this series is convergent. Secondly, considering the system where the direct path component does not exist, we obtain the exact BER expression in a one-integral form and a series expansion of the exact BER expression. Numerical results confirm that the two exact BER expressions in a one-integral form perfectly match the simulation results and the two series expressions of BER are very accurate, even with a small truncation window.
Non-Linear Dynamic Analysis of Inter-Word Time Intervals in Psychotic Speech

“Language is a form and not a substance” - Ferdinand de Saussure Objective: Analyses of speech processes in schizophrenia are invariably focused on words as vocal signals. The results of such analyses are, however, strongly related to content, and may be language- and culture-dependent. Little attention has been paid to a pure measure of the form of speech, unrelated to its content: inter-words time intervals. Method: 15 patients with schizophrenia and 15 healthy volunteers are recorded spontaneously speaking for 10-15 min. Recordings are analyzed for inter-words time intervals using the following nonlinear dynamical methods: unstable periodic orbits, correlation dimension, bi-spectral analysis, and symbolic dynamics. Results: The series of inter-word time intervals in normal speech have the characteristics of a low-dimensional chaotic attractor with a correlation dimension of 3.2 ± 1.1. Deconstruction of the attractor appears in psychosis with re-establishment after anti-psychotic treatment. Shannon entropy, a measure of the complexity in the time series, calculated from symbolic dynamics, is higher for psychotic speech, which is also characterized by higher levels of phase coupling: higher bicoherence, obtained using bi-spectral analysis. Conclusion: Non-linear dynamical methods applied to ITIs thus enable a content-independent, pure measure of the form of normal thought, its distortion in psychosis, and its restoration under treatment.
Association of inflammation and protein-energy wasting with endothelial dysfunction in peritoneal dialysis patients.

BACKGROUND Cardiovascular disease is the main cause of mortality in end-stage renal disease (ESRD) patients. Recent studies have indicated that non-traditional risk factors such as endothelial dysfunction (ED), chronic inflammation and protein-energy wasting (PEW) may contribute significantly to the increased cardiovascular mortality among dialysis patients. To further ascertain this association, we carried out a cross-sectional assessment of nutritional status, inflammatory markers and endothelial dysfunction in peritoneal dialysis (PD) patients. METHODS We measured ED functionally by flow-mediated vasodilatation (FMD) using doppler ultrasonography and biochemically by soluble intercellular adhesion molecule-1 (sICAM-1) in 105 stable PD patients and 32 age- and sex-matched healthy controls. We also simultaneously measured inflammatory markers and performed a subjective global assessment (SGA) of their nutritional status using a seven-point scoring scale. Subjects were subgrouped according to their nutritional and inflammatory status. RESULTS In PD patients, FMD was markedly lower (9.9 +/- 4.8% vs. 16.4 +/- 4.8%, P < 0.05), and sICAM-1 was significantly higher than those in controls. The malnourished patients had significantly lower FMD (8.4+/-4.6% vs. 10.8+/-4.7%, P <0.05) and higher sICAM-1 than the nourished patients. The inflamed group had significantly lower FMD (7.1 +/- 3.8 vs.11.1 +/- 4.6%, P < 0.05) and higher sICAM-1 than the non-inflamed group. In all PD patients, lean body mass/body weight %, albumin and SGA correlated positively with FMD (r = +0.207, r = +0.224, r = +0.285, P < 0.05). However, age, log high sensitivity C-reactive protein (hsCRP), log IL-6 and sICAM-1 were negatively correlated with FMD (r = -0.275, r = -0.361, r = -0.360, r = -0.271, P < 0.05). A multiple regression analysis showed that log hsCRP was an independent factor affecting FMD. Endothelial function, demonstrated as FMD and sICAM-1 in the nourished PD patients without inflammation, was well preserved compared to other subgroups. CONCLUSION Our data suggest that chronic inflammation and PEW are closely linked to ED in PD patients.
Sentence Simplification Aids Protein-Protein Interaction Extraction

Accurate systems for extracting ProteinProtein Inter actions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of sentences has on the performance of a state-of-art PPI extraction system, showing a substantial improvement in recall (8%) when the sentence simplification method is applied, without significant impact to precision.