Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth and activity of black holes in galaxy mergers with varying mass ratios

We study supermassive black holes (BHs) in merging galaxies, using a suite of hydrodynamical simulations with very high spatial (~10 pc) and temporal (~1 Myr) resolution, where we vary the initial mass ratio, the orbital configuration, and the gas fraction. (i) We address the question of when and why, during a merger, increased BH accretion occurs, quantifying gas inflows and BH accretion rates. (ii) We also quantify the relative effectiveness in inducing AGN activity of merger-related versus secular-related causes, by studying different stages of the encounter: the stochastic (or early) stage, the (proper) merger stage, and the remnant (or late) stage. (iii) We assess which galaxy mergers preferentially enhance BH accretion, finding that the initial mass ratio is the most important factor. (iv) We study the evolution of the BH masses, finding that the BH mass contrast tends to decrease in minor mergers and to increase in major mergers. This effect hints at the existence of a preferential range of mass ratios for BHs in the final pairing stages. (v) In both merging and dynamically quiescent galaxies, the gas accreted by the BH is not necessarily the gas with $low$ angular momentum, but the gas that $loses$ angular momentum.
Well-Being and Perceived Health in Multiple Sclerosis (MS): The Role of Personality

Objectives: Personality is known to have a substantial impact on health and overall well-being. Neuroticism, extraversion, and conscientiousness in particular have been shown to be strongly correlated with subjective well-being (SWB), psychological well-being (PWB), and overall health. The present study aimed to examine the role of personality and its relationship to SWB, PWB, and health in a multiple sclerosis (MS) sample. Methods: One hundred and seventy-two individuals with MS completed measures of personality, SWB, PWB, and health. Pearson correlations were conducted to examine the relationship among these factors. Results: Consistent with what has been shown in the general, healthy population personality has a strong correlation with many aspects of well-being and health. This was particularly true for neuroticism and extraversion, and to a lesser extent, conscientiousness. Openness and agreeableness demonstrated the weakest associations. Conclusion: The role of personality on well-being and health has long been established. The present study is one of the first to examine these associations in a MS sample. Findings suggest that assessment of personality should be considered part of routine care for individuals with MS in hopes of tailoring interventions to assure maintenance and/ or improvement in well-being and health.
NiTi loss on the dentinal walls and instrument deformation during root canal preparation

The purpose of this study was to quantify the presence of nickel (Ni) and titanium (Ti) on dentin walls of prepared root canals using Endosequence (ES) and Wave One (WO) systems, the deformation, and fracture of these instruments. Thirty extracted human premolar teeth were selected and prepared with WO, ES, and manually (control group—CG). Each instrument was used in four root canals. The root canals were irrigated with 2.5% sodium hypochlorite solution. After preparation, roots were sectioned longitudinally and the apical third was analyzed by scanning electron microscopy with X‐ray microanalysis (SEM‐EDS). The percentage of Ni and Ti found on dentin walls was compared using Kruskal–Wallis test and post hoc Dunn. The instruments deformation and fracture was evaluate by SEM before and after use. Spiral distortion, fractures, and surface wear were compared using Mann–Whitney test. The level of significance was set at 5%. Ni and Ti were found on the dentin walls of the apical root canal for ES and WO systems (p > .05). No distortion in the spirals and no instrument fracture were observed. Regarding to surface wear, most of the instruments scored as moderate wear (p > .05). This study concluded the WO and ES presented Ni and Ti loss. In addition, the preparation of four root canals did not caused irreversible deformation in WO and ES instruments.
Prediction of heart disease using ensemble learning and Particle Swarm Optimization

Advancement and emergence of newer technologies such as analytics, artificial intelligence, machine learning have impacted many sectors such as health care, automotive etc. In the healthcare sector, these technologies resulted in various benefits such as clinical decision support, better care coordination, improving patient wellness etc. The World over, Coronary Heart Disease (CHD) is affecting millions of people. Various machine learning techniques include ensemble classifiers can be used in healthcare for improving prediction accuracy. This paper analyses various ensemble methods (Bagged Tree, Random Forest, and AdaBoost) along with Feature subset selection method — Particle Swarm Optimization (PSO), to accurately predict the occurrence of heart disease for a particular patient. Experimental results show that Bagged Tree and PSO achieved the highest accuracy.
Forecasters' Disagreement About How the Economy Operates, and the Role of Long-Run Relationships

Macro-variables such as consumption, investment and output are expected to move together in the long run. We consider whether survey forecasts of these quantities suggest beliefs about equilibrium relationships play a prominent role in expectations formation. Evidence is brought to bear from an analysis of multivariate measures of forecaster disagreement, as well as tests of forecast optimality. The analysis of disagreement provides little support for the proposition that equilibrium considerations play a key role. Moreover, we generally reject forecast optimality for a majority of forecasters, but there is no evidence that this is due to long-run mis-specifcation.
GSTT 1 and gastric cancer susceptibility in the Chinese population : an updated meta-analysis and review

Aim: To assess the effects of GSTT1 null genotype on the risk of gastric cancer (GC), an updated metaanalysis was performed in the Chinese population. Methods: Related studies were identified from PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure (CNKI), and Chinese Biology Medicine (CBM) to up 5th March 2015. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the strength of the associations. Results: A total of 19 case-control studies including 2861 GC cases and 5064 controls were involved in this meta-analysis. Overall, significantly increased GC risk was associated with the null GSTT1 with OR of 1.20 (95% CI: 1.04-1.38) in the Chinese population. In subgroup analyses stratified by geographic area and source of controls, the significant results were found in South China and population-based studies. We also undertook gene-gene interaction analysis between GSTT1 and GSTM1 genes for GC risk, and the results indicated that the dual null genotypes of GSTT1 and GSTM1 might elevate the risk of GC (OR = 2.02, 95% CI: 1.63-12.51). Conclusion: This meta-analysis suggests that GSTT1 null genotype is associated with elevated GC risk in Chinese, but these associations vary in different geographic location.
Moral Hazard in Active Asset Management

We consider a model of active asset management in which mutual fund managers exert unobservable effort to earn excess returns. Investors allocate capital to actively managed funds and passively managed products. In equilibrium, investors are indifferent between investing an additional dollar with an active manager or with a passively managed product. As passively managed products become more attractive to investors, active managers’ revenues from portfolio-management services fall, reducing their effort incentives. More-severe decreasing-returns-to-scale are also associated with reduced incentives and increased moral hazard. Performance-based fees and holdings-based data are all unlikely to mitigate moral hazard.
Species distribution, virulence factors and antimicrobial resistance of Acinetobacter spp. isolates from dogs and cats: a preliminary study

In this study, the prevalence of virulence factors and antimicrobial resistance among 67 Acinetobacter spp. isolates, consisting of 21 Acinetobacter baumannii and 46 non‐baumannii Acinetobacter obtained from companion animals, was investigated. PCR analysis showed that the most prevalent virulence gene was afa/draBC (29.9%), followed by papC (22.4%) and cvaC (20.9%). Antimicrobial susceptibility testing revealed that resistance to gentamicin (14.9%) and ciprofloxacin (11.9%) was relatively prevalent. Five gentamicin‐ and/or ciprofloxacin‐resistant A. baumannii strains were assigned to ST25, ST149, ST164, ST203 and ST1198. All ciprofloxacin‐resistant isolates harbored point mutations in gyrA and/or parC. To the best of our knowledge, this is the first report of preliminary monitoring of animal‐origin Acinetobacter spp. in Japan.
Accountability Mechanisms in Public Services: Activating New Dynamics in a Prison System

ABSTRACT This qualitative study analyzes the activation of accountability mechanisms in public services and the changing dynamics between relevant actors. It remains unclear how accountability relationships emerge, when they are introduced, and under which circumstances administrative values are challenged over the course of administrative reforms. Our analysis of a Brazilian state prison system elucidates some of these elements by investigating a case in which an institutional crisis resulted in administrative reforms and new accountability dynamics. Our findings suggest that initiating accountability reforms before some services reach the level of severe crisis may be particularly difficult. We demonstrate that the development of accountability relationships is largely influenced by prominent actors capable of strategizing their actions in a collaborative fashion with other stakeholders. Additional layers of external regulation are also crucial to reduce the risks of political and regulatory capture, engage previously absent stakeholders, activate accountability mechanisms, and make reforms possible.
An Arithmetic Modeling Framework for the Term Structure of Electricity Prices

We propose a tractable class of arbitrage-free models for the term structure of electricity prices, where spot and forward prices are a linear function of latent factors. The modeling approach offers much flexibility in the specification of the factor dynamics by only restricting their risk-neutral drift. We derive a canonical form where the parameters determining the factor loadings for the forward prices can be separated from the parameters describing the factor dynamics. The factor loading parameters can be consistently estimated by directly fitting the cross-section of forward prices. The modeling framework is applied to a panel of daily prices on forward contracts from the Nordpool electricity market, using affine factor dynamics. We find that forward prices (i) are mainly driven by changes in the level, slope and curvature of the forward curve; (ii) exhibit time-varying volatilities; and (iii) incorporate time-varying forward premia.
Identification and Validation of Radiographic Enhancement for Reliable Differentiation of CD117(+) Benign Renal Oncocytoma and Chromophobe Renal Cell Carcinoma

Purpose: The diagnostic differential for CD117/KIT(+) oncocytic renal tumor biopsies is limited to benign renal oncocytoma versus chromophobe renal cell carcinoma (ChRCC); however, further differentiation is often challenging and requires surgical resection. We investigated clinical variables that might improve preoperative differentiation of CD117(+) renal oncocytoma versus ChRCC to avoid the need for benign tumor resection. Experimental Design: A total of 124 nephrectomy patients from a single institute with 133 renal oncocytoma or ChRCC tumors were studied. Patients from 2003 to 2012 comprised a retrospective cohort to identify clinical/radiographic variables associated with renal oncocytoma versus ChRCC. Prospective validation was performed among consecutive renal oncocytoma/ChRCC tumors resected from 2013 to 2017. Results: Tumor size and younger age were associated with ChRCC, and multifocality with renal oncocytoma; however, the most reliable variable for ChRCC versus renal oncocytoma differentiation was the tumor:cortex peak early-phase enhancement ratio (PEER) using multiphase CT. Among 54 PEER-evaluable tumors in the retrospective cohort [19 CD117(+), 13 CD117(−), 22 CD117-untested], PEER classified each correctly as renal oncocytoma (PEER >0.50) or ChRCC (PEER ≤0.50), except for four misclassified CD117(−) ChRCC variants. Prospective study of PEER confirmed 100% accuracy of renal oncocytoma/ChRCC classification among 22/22 additional CD117(+) tumors. Prospective interobserver reproducibility was excellent for PEER scoring (intraclass correlation coefficient, ICC = 0.97) and perfect for renal oncocytoma/ChRCC assignment (ICC = 1.0). Conclusions: In the largest clinical comparison of renal oncocytoma versus ChRCC to our knowledge, we identified and prospectively validated a reproducible radiographic measure that differentiates CD117(+) renal oncocytoma from ChRCC with potentially 100% accuracy. PEER may allow reliable biopsy-based diagnosis of CD117(+) renal oncocytoma, avoiding the need for diagnostic nephrectomy. Clin Cancer Res; 24(16); 3898–907. ©2018 AACR.
Shifts in nursing and medical students’ attitudes, beliefs and behaviours about interprofessional work: An interprofessional placement in ambulatory care

AIM AND OBJECTIVES To examine students' beliefs, behaviours and attitudes in relation to interprofessional socialisation, and their expectations and experience, before and after a 2-week clinical placement in ambulatory care. BACKGROUND Interprofessional clinical placements for students are important for developing an understanding of interprofessional collaboration and identity, for the benefit of patient care. Ambulatory care environment involves collaborative management of complex chronic problems. This educator supported placement that enabled final-year nursing and medical students to work together. DESIGN A descriptive matched before-after study was conducted. METHODS Students' completed an online questionnaire before and after their clinical placement. The questionnaire comprised of three sections: demographic information, the Interprofessional Socialisation and Valuing Scale and open-ended questions. Descriptive analysis and paired t-tests were conducted for the three subscales, and thematic analysis of qualitative responses was conducted. RESULTS Sixty-two of the 151 students between 2011-2014 completed both surveys. There was a significant increase after placement in the overall Interprofessional Socialisation and Valuing Scale scores. The change was greater for nursing students compared with medical students, although for both groups the change was small. The majority had a good-to-very good experience learning each other's and their own professions and identified the nurse educator and teaching registrar as key to success. CONCLUSION A clinical placement in an ambulatory setting for nursing and medical students resulted in an increase in self-perceived ability to work with others and in valuing working with others. RELEVANCE TO CLINICAL PRACTICE Interprofessional clinical placements are essential for students to understand interprofessional practice for better patient outcomes and developing their own perspective of future work within an interprofessional team. Ambulatory care is an ideal environment for nursing and other health professional students to engage in interprofessional clinical placements.
Random Walk and Indian Equity Futures Market

The present study investigates weak form of efficiency in Indian equity futures market. For this purpose, informational efficiency of the Nifty futures and 24 stock futures is examined. The Nifty and stock futures returns are found to be deviating from normal distribution. The futures prices are found to be nonstationary at levels whereas, first difference futures returns are stationary. Empirical analysis finds evidence of statistical dependence in the returns generating process. Further analysis through Autoregressive Integrated Moving Average (ARIMA) process reveals that the Nifty and stock futures returns are not independent and shows strong dependencies.
The influence of utterance chunking on machine translation performance

Speech translation systems commonly couple automatic speech recognition (ASR) and machine translation (MT) components. Hereby the automatic segmentation of the ASR output for the subsequent MT is critical for the overall performance. In simultaneous translation systems, which require a continuous output with a low latency, chunking of the ASR output into translatable segments is even more critical. This paper addresses the question how utterance chunking influences machine translation performance in an empirical study. In addition, the machine translation performance is also set in relation to the segment length produced by the chunking strategy, which is important for simultaneous translation. Therefore, we compare different relatively simple chunking/ segmentation strategies on speech recognition hypotheses as well as on reference transcripts.
Human activity recognition method based on inertial sensor and barometer

In this paper, we propose a human activity recognition (HAR) method based on inertial sensors and barometer. The proposed method recognizes eight human activities following a multi-layer strategy. Activities are classified into two categories: dynamic and static activities; then explicit activity recognition is taken individually in the two categories. Three classifiers are adopted for different classification, including random forest (RF) and support vector machine (SVM). Different feature sets have been selected for different classifiers which are more targeted and effective. In addition, the classifier result is further verified by additional parameters and previous recognition results to decide the final recognition result. Experiments have shown the effectiveness and good performance of the proposed HAR method.
An Investigation into the Status of Water Quality Health Indicators of the Swimming Pools in Tehran in 2015

Background: Poor quality of water in swimming pools may cause health problems and transmission of infectious diseases to swimmers. The aim of this study was to study the status of Water Quality Health Indicators of the swimming Pools in Tehran in 2015. Materials and Methods: This cross - sectional study was conducted in the 24 pools (n=288) in west of Tehran. Residual chlorine, temperature and pH were measured in field and microbial tests according to standard protocols. The SPSS software was used for data analysis. Results: Average residual chlorine, pH, pool and Jacuzzi temperature, were calculated as 1.7 ± 1.05, 7.70 ± 0.24, 26.92 ± 0.97, 39.39 ± 1.48, respectively. Heterotrophic plate count (HPC) in 5.21%, total coliforms in 9.4% and fecal coliforms 17% of the samples were above the standard level. A significant but inverse correlation between residual chlorine and HPC, total coliform and fecal coliform were found. Conclusion: Results showed that the Water Quality Health Indicators of the Swimming Pools in more than 80% of pools as compared to standards is at desirable and expected levels. To improve the sanitary conditions of other pools, standards compliance and sanitary requirements and regular and periodic monitoring of above indicators is necessary.
Simplifying Sentences with Sequence to Sequence Models

We simplify sentences with an attentive neural network sequence to sequence model, dubbed S4. The model includes a novel word-copy mechanism and loss function to exploit linguistic similarities between the original and simplified sentences. It also jointly uses pre-trained and fine-tuned word embeddings to capture the semantics of complex sentences and to mitigate the effects of limited data. When trained and evaluated on pairs of sentences from thousands of news articles, we observe a 8.8 point improvement in BLEU score over a sequence to sequence baseline; however, learning word substitutions remains difficult. Such sequence to sequence models are promising for other text generation tasks such as style transfer.
Extracting structured dynamical systems using sparse optimization with very few samples

Learning governing equations allows for deeper understanding of the structure and dynamics of data. We present a random sampling method for learning structured dynamical systems from under-sampled and possibly noisy state-space measurements. The learning problem takes the form of a sparse least-squares fitting over a large set of candidate functions. Based on a Bernstein-like inequality for partly dependent random variables, we provide theoretical guarantees on the recovery rate of the sparse coefficients and the identification of the candidate functions for the corresponding problem. Computational results are demonstrated on datasets generated by the Lorenz 96 equation, the viscous Burgers' equation, and the two-component reaction-diffusion equations (which is challenging due to parameter sensitives in the model). This formulation has several advantages including ease of use, theoretical guarantees of success, and computational efficiency with respect to ambient dimension and number of candidate functions.
The microbiologic profile of dacryocystitis

ABSTRACT Purpose: Recent studies suggest an increasing incidence of gram-negative bacteria and methicillin-resistant Staphylococcus aureus in dacryocystitis. Since patients are often treated empirically without culture data, a changing microbiologic profile will markedly affect the success of oral treatment. To provide current guidelines for the treatment of this common condition, we investigated the microbiology and antibiogram of dacryocystitis seen at our institution. Methods: The charts of all patients presenting with acute and/or chronic dacryocystitis in University Hospital, Newark, from 2007 to 2015 were reviewed. Patient demographics, culture isolates, and in vitro antimicrobial susceptibility data were collected. Additional sensitivity data were obtained from the Sanford Guide to Antimicrobial Therapy. Results: A total of 137 patients were included in the study. Of 205 samples collected, S. aureus was the most commonly isolated organism (46 of 156, 30%) followed by Pseudomonas species (19 of 156, 12%) and Propionibacterium acnes (15 of 156, 10%). Based on sensitivity data, the two oral antibiotics that would have been most effective in this population were levofloxacin and amoxicillin/clavulanate; however, even these antibiotics would have encountered at least one resistant organism in 16% and 32% of patients, and potentially in another 15% and 8% of patients, respectively. Conclusions: Given the broad range of causative organisms, routine treatment of dacryocystitis with any specific antibiotic may fail in up to one-third of patients. Obtaining a culture at the time empiric antibiotic treatment is initiated can prove extremely valuable when treating patients with dacryocystitis.