Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of homogenizer pressure and temperature on physicochemical, oxidative stability, viscosity, droplet size, and sensory properties of Sesame vegetable cream

Abstract In this study, the effects of homogenization pressure (125, 145, and 165 bars) and temperature (45, 60, and 75°C) on the properties of Sesame vegetable cream are investigated. The physical stability of cream was characterized by droplet size and syneresis, and chemical stability of it was evaluated by determining peroxide value and p‐anisidine. The results showed that the cream in the presence of high pressure and temperature treatment exhibits lower stability. At 75°C temperature and 165 bar, the vegetable cream had highest peroxide value (3.61) and p‐anisidine (2.16). However, pressure could protect the droplets against aggregation in the high pressure (165 bar) and greatly increased the physical stability. During increase in process parameters, the syneresis of cream was decreased with a rise of pressure and extension of temperature. The process condition in 145 bar and 60°C led to the high acceptability of vegetable cream.
Man vs. Machine? The Impact of Algorithm Authorship on News Credibility

Abstract Facing budget constraints, many traditional news organizations are turning their eyes on automation to streamline manpower, cut down on costs, and improve efficiency. But how does automation fit into traditional values of journalism and how does it affect perceptions of credibility, an important currency valued by the journalistic field? This study explores this question using a 3 (declared author: human vs. machine vs. combined) × 2 (objectivity: objective vs. not objective) between-subjects experimental design involving 420 participants drawn from the national population of Singapore. The analysis found no main differences in perceived source credibility between algorithm, human, and mixed authors. Similarly, news articles attributed to an algorithm, a human journalist, and a combination of both showed no differences in message credibility. However, the study found an interaction effect between type of declared author and news objectivity. When the article is presented to be written by a human journalist, source and message credibility remain stable regardless of whether the article was objective or not objective. However, when the article is presented to be written by an algorithm, source and message credibility are higher when the article is objective than when the article is not objective. Findings for combined authorship are split: there were no differences between objective and non-objective articles when it comes to message credibility. However, combined authorship is rated higher in source credibility when the article is not objective than when the article is objective.
Liquid biopsy of HPV DNA in cervical cancer.

BACKGROUND A blood test to serve as a tumor marker for cervical cancer would be useful to clinicians to guide treatment and provide an early signal for recurrence. The development of droplet digital PCR has enabled the detection of HPV DNA in patient serum, providing a potential marker for cervical cancer. OBJECTIVES To report on a blood-based test for HPV-specific E7 and L1 genes, which may serve as a tumor marker to guide treatment and detect early recurrence in cervical cancer. STUDY DESIGN Pre-treatment plasma samples were investigated from 138 Hong Kong Chinese women with primary invasive squamous cell carcinoma and adenocarcinoma of the cervix with tumor samples expressing HPV16 or HPV18. Two genes specific to the human papillomavirus, E7 and L1, were measured in cell free DNA (cfDNA) extracted from plasma using droplet digital PCR. Analysis of detectable E7 and L1 levels was performed to investigate the potential of liquid biopsy of E7 and L1 as a clinically useful molecular biomarker. RESULTS The majority of patients had HPV16 (71.7%), squamous cell carcinoma (78.3%) and stage IB-II disease (82.6%). HPV E7 and L1 sequences were detected in plasma cfDNA from 61.6% (85/138) of patients. Patients with high viral load (defined as ≥20 E7 or L1 copies per 20 μL reaction volume) had increased risk of recurrence and death at 5 years on univariate analysis but not multivariate analysis. CONCLUSIONS HPV DNA can be quantitatively detected with the use of cfDNA. This has the potential to provide a clinically useful tumor marker for patients with cervical cancer that can aid in post-treatment surveillance and estimating the risk of disease relapse.
Does Clearance of Positive Margins Improve Local Control in Oral Cavity Cancer? A Meta-analysis

Objectives To compare local recurrence-free survival (LRFS) in early oral cavity cancer (OCC) patients with positive/close frozen section (FS) cleared with further resection (R1 to R0) or positive FS not cleared (R1) to those with negative margins on initial FS analysis (R0). Data Sources PubMed, EMBASE, and Cochrane. Review Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) for reporting in our study. Only English-language articles that included patients with OCC and local recurrence (LR) comparisons between R0 and initially R1 to final R0 or final R1 groups were included. We requested the raw data from the corresponding authors of eligible studies and performed an individual participant data (IPD) meta-analysis of LRFS outcomes across groups. Results Pooled LRFS data from 8 studies showed that patients in the R1 to R0 group had worse LRFS compared to the R0 group (hazard ratio [HR] = 2.897, P < .001). Patients in the R1 group were also found to have worse LRFS compared to the R0 group (HR = 3.795, P < .001). When compared to final R1 group, the initially R1 to final R0 only showed a trend toward better LRFS. Conclusion Margin revision of initially positive margins to “clear” based on FS guidance does not equate to an initially negative margin and does not significantly improve local control. These findings call into question the effectiveness of the current methodology of intraoperative FS in OCC resections and call for a prospective study to determine what system of resected specimen analysis best predicts completeness of resection.
Early Identification of Sensory Processing Difficulties in High-Risk Infants

OBJECTIVE. Our objective was to determine the extent to which young children at high risk for sensory processing difficulties differed from those who were at low risk. METHOD. We compared high- versus low-risk young children using standardized measures. High-risk participants had older siblings identified as having sensory processing difficulties after a comprehensive occupational therapy evaluation (n = 13); low-risk participants (n = 16) had typically developing siblings and no family history of sensory or other neurological disorders. RESULTS. High-risk infants scored significantly lower on the Language and Cognitive scales of the Bayley Scales of Infant and Toddler Development–Third Edition. The high-risk group presented with more atypical positions on the Toddler and Infant Motor Evaluation and fewer sensation-seeking behaviors on the Toddler Sensory Profile–2. CONCLUSION. Results suggest that sensory, motor, cognitive, and language dimensions may be associated with sensory processing difficulties. Implications exist for the design of future studies and for early intervention.
Factor-driven two-regime regression

We propose a novel two-regime regression model where the switching between the regimes is driven by a vector of possibly unobservable factors. When the factors are latent, we estimate them by the principal component analysis of a much larger panel data set. Our approach enriches conventional threshold models in that a vector of factors may represent economy-wide shocks more realistically than a scalar observed random variable. Estimating our model brings new challenges as well as opportunities in terms of both computation and asymptotic theory. We show that the optimization problem can be reformulated as mixed integer optimization and present two alternative computational algorithms. We derive the asymptotic distributions of the resulting estimators under the scheme that the threshold effect shrinks to zero. In particular, with latent factors, not only do we establish the conditions on factor estimation for a strong oracle property, which are different from those for smooth factor augmented models, but we also identify semi-strong and weak oracle cases and establish a phase transition that describes the effect of first stage factor estimation as the cross-sectional dimension of panel data increases relative to the time-series dimension. Moreover, we develop a consistent factor selection procedure with a penalty term on the number of factors and present a complementary bootstrap testing procedure for linearity with the aid of efficient computational algorithms. Finally, we illustrate our methods via Monte Carlo experiments and by applying them to factor-driven threshold autoregressive models of US macro data.
Dynamics of Dirac observables in canonical cosmological perturbation theory

The relational formalism based on geometrical clocks and Dirac observables in linearized canonical cosmological perturbation theory is used to introduce an efficient method to find evolution equations for gauge invariant variables. Our method generalizes an existing technique by Pons et al (2010 J. Phys.: Conf. Ser. 222 012018); (2009 Phys. Rev. D 80 084015) to relate the evolution of gauge invariant observables with the one of gauge variant quantities, and is applied as a demonstration for the longitudinal and spatially flat gauges. Gauge invariant evolution equations for the Bardeen potential and the Mukhanov–Sasaki variable are derived in the extended ADM phase space. Our method establishes a full agreement at the dynamical level between the canonical and conventional cosmological perturbation theory at the linear order using Dirac observables.
Robust Tests for Convergence Clubs

In many applications common in testing for convergence the number of cross-sectional units is large and the number of time periods are few. In these situations asymptotic tests based on an omnibus null hypothesis are characterised by a number of problems. In this paper we propose a multiple pairwise comparisons method based on an a recursive bootstrap to test for convergence with no prior information on the composition of convergence clubs. Monte Carlo simulations suggest that our bootstrap-based test performs well to correctly identify convergence clubs when compared with other similar tests that rely on asymptotic arguments. Across a potentially large number of regions, using both cross-country and regional data for the European Union we find that the size distortion which afflicts standard tests and results in a bias towards finnding less convergence, is ameliorated when we utilise our bootstrap test.
Social Behavioral Phenotyping of Drosophila With a 2D–3D Hybrid CNN Framework

Behavioural phenotyping of drosophila is an important means in biological and medical research to identify the genetic, pathologic, or psychological impact on animal behavior. Automated behavioral phenotyping from videos has been a desired capability that can waive long-time boring manual work in behavioral analysis. In this paper, we introduced deep learning into this challenging topic and proposed a new 2D+3D hybrid CNN framework for drosophila’s social behavioral phenotyping. In the proposed multi-task learning framework, action detection and localization of drosophila jointly are carried out with action classification, and a given video is divided into clips with fixed length. Each clip is fed into the system, and a 2-D CNN is applied to extract features at the frame level. Features extracted from adjacent frames are then connected and fed into a 3-D CNN with a spatial region proposal layer for classification. In such a 2D+3D hybrid framework, drosophila detection at the frame level enables the action analysis at different durations instead of a fixed period. We tested our framework with different base layers and classification architectures and validated the proposed 3D CNN-based social behavioral phenotyping framework under various models, detectors, and classifiers.
Heart Failure Patients’ Knowledge and Barriers of Low Sodium Diet Adherence in Erbil City

Background and objective: A low sodium diet is a cornerstone of non-pharmacologic therapy for heart failure patients. The objective of the study was to assess knowledge and perceived barriers of low sodium diet adherence of heart failure patients in Erbil City.Methods: A descriptive, cross-sectional study design was conducted among a sample of 50 patients diagnosed heart failure in Medical Wards and Cardiac Care Units at both Rizgary and Hawler Teaching Hospitals in Erbil City from Feb 2018 to Oct 2019. Patients who met the inclusion criteria were selected for participation of the study, interviews based on a questionnaire patient’s sociodemographic, clinical characteristics and the Dietary Sodium Restriction Questionnaire (DSRQ). Frequency, percentage, and the chi-square test were used for analyzing data.Results: The results show that majority of heart failure patients were low knowledge (80%) and high perceived barriers (66%) to low sodium diet adherence. There were significant associations between knowledge and barrier with age group (p-value=0.01; p-value=0.04), gender, (p-value=0.00; p=0.05), level of education (p-value=0.00; p-value=0.02) and economic status (p-value= < 0.001; p-value= <0.001). Conclusion: Results of the study show that heart failure patients had low knowledge and perceived more barriers to adherence of low sodium diet.
A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems

In this paper, we consider high-dimensional nonconvex square-root-loss regression problems and introduce a proximal majorization-minimization (PMM) algorithm for these problems. Our key idea for making the proposed PMM to be efficient is to develop a sparse semismooth Newton method to solve the corresponding subproblems. By using the Kurdyka-Łojasiewicz property exhibited in the underlining problems, we prove that the PMM algorithm converges to a d-stationary point. We also analyze the oracle property of the initial subproblem used in our algorithm. Extensive numerical experiments are presented to demonstrate the high efficiency of the proposed PMM algorithm.
Multipulse Fermi Gamma-Ray Bursts. I. Evidence of the Transition from Fireball to Poynting-flux-dominated Outflow

The composition of a jet is still an unsolved problem in gamma-ray bursts (GRBs). Several previous studies have suggested that the prompt emission spectrum of GRBs is likely to consist of a few components that may arise from different jet compositions. Here we present a systematic analysis to search for the GRBs that seem to show the transition from a fireball to the Poynting-flux-dominated outflow between well-separated pulses within a single burst, like GRB 160626B, using the Gamma-ray Burst Monitor data of the Fermi satellite. We obtain 43 GRBs with clear multiple pulses and find that 9/43 (21%) bursts may exhibit such a transition based on the time-integrated spectral analysis. We then select a further four bursts with data of adequate quality to perform a detailed time-resolved spectral analysis, and we find that in three bursts the thermal-like pulse is a precursor. Furthermore, based on the time-resolved spectra, we constrain the outflow properties for those thermal pulses and find them consistent with the typical properties of the photosphere emission. Also, the later pulses with the softer low-energy spectral index are compatible with the optically thin synchrotron emission model. Our analysis indicates that a good fraction of the multipulse Fermi bursts may obtain the transition from fireball to the Poynting-flux-dominated outflow.
An Integrated Panel Data Approach to Modelling Economic Growth

Accurate estimation for extent of cross-sectional dependence in large panel data analysis is paramount to further statistical analysis on the data under study. Grouping more data with weak relations (cross-sectional dependence) together often results in less efficient dimension reduction and worse forecasting. This paper describes cross-sectional dependence among a large number of objects (time series) via a factor model and parametrizes its extent in terms of strength of factor loadings. A new joint estimation method, benefiting from unique feature of dimension reduction for high dimensional time series, is proposed for the parameter representing the extent and some other parameters involved in the estimation procedure. Moreover, a joint asymptotic distribution for a pair of estimators is established. Simulations illustrate the effectiveness of the proposed estimation method in the finite sample performance. Applications in cross-country macro-variables and stock returns from S&P 500 are studied.
Transiting exocomets detected in broadband light by TESS in the β Pictoris system

Aims. We search for signs of falling evaporating bodies (FEBs, also known as exocomets) in photometric time series obtained for β Pictoris after fitting and removing its δ Scuti-type pulsation frequencies. Methods. Using photometric data obtained by the TESS satellite we determined the pulsational properties of the exoplanet host star β Pictoris through frequency analysis. We then pre-whitened the 54 identified δ Scuti p-modes and investigated the residual photometric time series for the presence of FEBs. Results. We identify three distinct dipping events in the light curve of β Pictoris over a 105-day period. These dips have depths from 0.5 to 2 millimagnitudes and durations of up to 2 days for the largest dip. These dips are asymmetric in nature and are consistent with a model of an evaporating comet with an extended tail crossing the disc of the star Conclusions. We present the first broadband detections of exocomets crossing the disc of β Pictoris, complementing the predictions made 20 years earlier by Lecavelier Des Etangs et al. (1999, A&A, 343, 916). No periodic transits are seen in this time series. These observations confirm the spectroscopic detection of exocomets in calcium H and K lines that have been seen in high resolution spectroscopy.
Identifying Bid Leakage in Procurement Auctions: Machine Learning Approach

We propose a novel machine-learning-based approach to detect bid leakage in first-price sealed-bid auctions. We extract and analyze the data on more than 1.4 million Russian procurement auctions between 2014 and 2018. As bid leakage in each particular auction is tacit, the direct classification is impossible. Instead, we reduce the problem of bid leakage detection to Positive-Unlabeled Classification. The key idea is to regard the losing participants as fair and the winners as possibly corrupted. This allows us to estimate the prior probability of bid leakage in the sample, as well as the posterior probability of bid leakage for each specific auction. We find that at least 16% of auctions are exposed to bid leakage. Bid leakage is more likely in auctions with a higher reserve price, lower number of bidders and lower price fall, and where the winning bid is received in the last hour before the deadline.
Renal Vein Thrombosis After Open Repair of Abdominal Aortic Aneurysm Successfully Treated by Direct Oral Anticoagulants

Introduction: Venous thromboembolism (VTE) of the lower extremities frequently occurs after surgery. It is unknown whether the complication of renal vein thrombosis (RVT) develops after an open repair (OR) for abdominal aortic aneurysm (AAA). Furthermore, anticoagulation therapy with apixaban, a direct oral anticoagulant (DOAC), has not been described as treatment for RVT in such cases. Case: A 64-year-old man underwent OR for AAA. Postoperative computed tomography revealed RVT in the left renal vein. Apixaban (5 mg twice a day) therapy was initiated. Six months later, we discontinued anticoagulation therapy and observed no recurrence. Following OR, our patient developed RVT for which DOACs were very useful. Conclusion: Thus, RVT can manifest as VTE after OR and direct anticoagulants can be considered as a therapeutic option.
THE BROAD CONSEQUENCES OF NARROW BANKING

We investigate the macroeconomic consequences of narrow banking in the context of stock-flow consistent models. We begin with an extension of the Goodwin–Keen model incorporating time deposits, government bills, cash, and central bank reserves to the base model with loans and demand deposits, and use it to describe a fractional reserve banking system. We then characterize narrow banking by a full reserve requirement on demand deposits and describe the resulting separation between the payment system and lending functions of the resulting banking sector. By way of numerical examples, we explore the properties of fractional and full reserve versions of the model and compare their asymptotic properties. We find that narrow banking does not lead to any loss in economic growth when both versions of the model converge to a finite equilibrium, while allowing for more direct monitoring and prevention of financial breakdowns in the case of explosive asymptotic behavior.
Exchange Dynamics of Typical Emerging and Legacy Persistent Organic Pollutants at the Air‐Water Interface Over a Strongly Human‐Influenced Large River Estuary

To explore the riverine or atmospheric influence on the source‐sink fates of typical persistent organic pollutants (POPs): polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) in the large river estuary, atmospheric and seawater samples were collected simultaneously over a whole year at a remote small island in the Yangtze River Estuary (YRE), the East China Sea. A comparable net input of BDE‐209 from the atmosphere to the sea for both air‐water gas exchange and dry/wet deposition was observed. The gas deposition of BDE‐209 had a strong dependence on the gaseous concentration, which was in turn governed by atmospheric transport. For Br<10‐BDEs, which have been prohibited in recent years, the gas exchange almost reached equilibrium at the air‐water interface during the whole observation period. However, a strong net gas volatilization was observed for legacy ΣICESPCBs especially in the flood season, and the volatilization was significantly associated with ambient parameter‐wind speed. These remarkably different exchange dynamics of PBDEs and PCBs at the air‐water interface over the YRE could be attributed to their primary emission intensity and inconsistent environmental transport pathways. The reversal of the source‐sink fates of BDE‐209 and legacy PCBs suggest that the strongly human‐influenced large river estuary water could act as a source‐sink buffer for POPs during the switch from approved to prohibited usage.