Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite-size spherical particles in a square duct flow of an elastoviscoplastic fluid: an experimental study

The present experimental study addresses the flow of a yield stress fluid with some elasticity (Carbopol gel) in a square duct. The behaviour of two fluids with lower and higher yield stress is investigated in terms of the friction factor and flow velocities at multiple Reynolds numbers $Re^{\ast }\in$ (1, 200) and, hence, Bingham numbers $Bi\in$ (0.01, 0.35). Taking advantage of the symmetry planes in a square duct, we reconstruct the entire 3-component velocity field from two-dimensional particle image velocimetry (PIV). A secondary flow consisting of eight vortices is observed to recirculate the fluid from the core towards the wall centre and from the corners back to the core. The extent and intensity of these vortices grows with increasing $Re^{\ast }$ or, alternately, as the plug size decreases. The second objective of this study is to explore the change in flow in the presence of particles. To this end, almost neutrally buoyant finite-size spherical particles with a duct height, $2H$, to particle diameter, $d_{p}$, ratio of 12 are used at two volume fractions $\unicode[STIX]{x1D719}=5$ and 10 %. Particle tracking velocimetry is used to measure the velocity of these refractive-index-matched spheres in the clear Carbopol gel, and PIV to extract the fluid velocity. Additionally, simple shadowgraphy is also used to qualitatively visualise the development of the particle distribution along the streamwise direction. The particle distribution pattern changes from being concentrated at the four corners, at low flow rates, to being focussed along a diffused ring between the centre and the corners, at high flow rates. The presence of particles induces streamwise and wall-normal velocity fluctuations in the fluid phase; however, the primary Reynolds shear stress is still very small compared to turbulent flows. The size of the plug in the particle-laden cases appears to be smaller than the corresponding single-phase cases. Similar to Newtonian fluids, the friction factor increases due to the presence of particles, almost independently of the suspending fluid matrix. Interestingly, predictions based on an increased effective suspension viscosity agrees quite well with the experimental friction factor for the concentrations used in this study.
Tuning the mechanical and flow properties of colloidal gels with ultrasound

Colloidal gels, where nanoscale particles aggregate into an elastic yet fragile network, are at the heart of materials that combine specific optical, electrical and mechanical properties. Tailoring the viscoelastic features of colloidal gels in real-time thanks to an external stimulus currently appears as a major challenge in the design of "smart" soft materials. Here we show that ultrasound allows one to achieve this goal in well-controlled conditions. By using a combination of rheological and structural characterization, we evidence and quantify a strong softening in three widely different colloidal gels submitted to ultrasonic vibrations (with submicron amplitude and frequency 20-500 kHz). This softening is attributed to the fragmentation of the gel network into large clusters that may or may not fully re-aggregate once ultrasound is turned off depending on the acoustic intensity. Ultrasound is further shown to dramatically decrease the gel yield stress and accelerate shear-induced fluidization, thus opening the way to a full control of elastic and flow properties by ultrasonic vibrations.
Sphingolipids: regulators of crosstalk between apoptosis and autophagy

Apoptosis and autophagy are two evolutionarily conserved processes that maintain homeostasis during stress. Although the two pathways utilize fundamentally distinct machinery, apoptosis and autophagy are highly interconnected and share many key regulators. The crosstalk between apoptosis and autophagy is complex, as autophagy can function to promote cell survival or cell death under various cellular conditions. The molecular mechanisms of crosstalk are beginning to be elucidated and have critical implications for the treatment of various diseases, such as cancer. Sphingolipids are a class of bioactive lipids that mediate many key cellular processes, including apoptosis and autophagy. By targeting several of the shared regulators, sphingolipid metabolites differentially regulate the induction of apoptosis and autophagy. Importantly, individual sphingolipid species appear to “switch” autophagy toward cell survival (e.g., sphingosine-1-phosphate) or cell death (e.g., ceramide, gangliosides). This review assesses the current understanding of sphingolipid-induced apoptosis and autophagy to address how sphingolipids mediate the “switch” between the cell survival and cell death. As sphingolipid metabolism is frequently dysregulated in cancer, sphingolipid-modulating agents, or sphingomimetics, have emerged as a novel chemotherapeutic strategy. Ultimately, a greater understanding of sphingolipid-mediated crosstalk between apoptosis and autophagy may be critical for enhancing the chemotherapeutic efficacy of these agents.
Understanding of Object Manipulation Actions Using Human Multi-Modal Sensory Data

Object manipulation actions represent an important share of the Activities of Daily Living (ADLs). In this work, we study how to enable service robots to use human multi-modal data to understand object manipulation actions, and how they can recognize such actions when humans perform them during human-robot collaboration tasks. The multi-modal data in this study consists of videos, hand motion data, applied forces as represented by the pressure patterns on the hand, and measurements of the bending of the fingers, collected as human subjects performed manipulation actions. We investigate two different approaches. In the first one, we show that multi-modal signal (motion, finger bending and hand pressure) generated by the action can be decomposed into a set of primitives that can be seen as its building blocks. These primitives are used to define 24 multi-modal primitive features. The primitive features can in turn be used as an abstract representation of the multi-modal signal and employed for action recognition. In the latter approach, the visual features are extracted from the data using a pre-trained image classification deep convolutional neural network. The visual features are subsequently used to train the classifier. We also investigate whether adding data from other modalities produces a statistically significant improvement in the classifier performance. We show that both approaches produce a comparable performance. This implies that image-based methods can successfully recognize human actions during human-robot collaboration. On the other hand, in order to provide training data for the robot so it can learn how to perform object manipulation actions, multi-modal data provides a better alternative.
When the tale comes true: multiple populations and wide binaries in the Orion Nebula Cluster

Context. Recently published high-quality OmegaCAM photometry of the 3 × 3 deg around the Orion Nebula Cluster (ONC) in r, and i filters revealed three well-separated pre-main sequences in the color-magnitude diagram (CMD). The objects belonging to the individual sequences are concentrated toward the center of the ONC. The authors concluded that there are two competitive scenarios: a population of unresolved binaries and triples with an exotic mass ratio distribution, or three stellar populations with different ages (≈1 Myr age differences). Aims. We use Gaia DR2 in combination with the photometric OmegaCAM catalog to test and confirm the presence of the putative three stellar populations. We also study multiple stellar systems in the ONC for the first time using Gaia DR2. Methods. We selected ONC members based on parallaxes and proper motions and take advantage from OmegaCAM photometry that performs better than Gaia DR2 photometry in crowded regions. We identify two clearly separated sequences with a third suggested by the data. We used Pisa stellar isochrones to estimate ages of the stellar populations with absolute magnitudes computed using Gaia parallaxes on a star by star basis. Results. (1) We confirm that the second and third sequence members are more centrally concentrated toward the center of the ONC. In addition we find an indication that the parallax and proper motion distributions are different among the members of the stellar sequences. The age difference among stellar populations is estimated to be 1−2 Myr. (2) We use Gaia proper motions and other measures to identify and remove as many unresolved multiple system candidates as possible. Nevertheless we are still able to recover two well-separated sequences with evidence for the third one, supporting the existence of the three stellar populations. (3) Due to having ONC members with negligible fore- or background contamination we were able to identify a substantial number of wide binary objects (separation between 1000 and 3000 au) and with relative proper motions of the binary components consistent with zero. This challenges previously inferred values that suggested no wide binary stars exist in the ONC. Our inferred wide-binary fraction is ≈5%. Conclusions. We confirm the three populations correspond to three separated episodes of star formation. Based on this result, we conclude that star formation is not happening in a single burst in this region. In addition we identify 5% of wide-binary stars in the ONC that were thought not to be present.
A pilot study on short term heart rate variability & its correlation with disease activity in Indian patients with rheumatoid arthritis

Background & objectives: Cardiovascular complications may lead to mortality in patients with rheumatoid arthritis (RA). We assessed heart rate variability (HRV), an important autonomic function, to quantify the risk for cardiovascular complications in Indian patients with RA. Methods: The study was carried out in RA patients (n=45) diagnosed as per American College of Rheumatology criteria and healthy controls. HRV recording and analysis was done using Nevrokard software using time and frequency domain analyses. The overall autonomic tone, parasympathetic drive, sympathetic drive and sympatho-vagal ratio were quantified by using various parameters. It included standard deviation of all R-R intervals (SDNN), standard deviation of successive differences between adjoining normal cycles (SDSD), root-mean square of successive differences (RMSSD), and number of R-R intervals differing by >50 ms from adjacent intervals (NN50) in the time domain analysis. In frequency domain analysis, low frequency (LF) and high frequency (HF), LF/HF and total power were assessed. Results: Demographic profile was comparable between groups; however, systolic BP was higher in patients with RA. SDNN, SDSD, RMSSD, NN50, LF and HF power and total power (ms × ms) were significantly lower in patients with RA versus healthy controls (P<0.001). Disease activity score at 28 joints indicating severity of the disease was significantly and positively correlated with SDSD (r=0.375, R2=14.06; P=0.045) while LF and HF power (ms × ms) were significantly and inversely correlated with rheumatoid factor (r=-0.438 and -0.445; R2=19.1 and 19.8; P=0.017 and 0.016, respectively). Interpretation & conclusions: HRV was significantly altered in patients with RA and independently associated with disease activity. Hence autonomic function testing, using HRV, may be useful as part of cardiovascular risk assessment in these patients.
Justification of the Point Vortex Approximation for Modified Surface Quasi-Geostrophic Equations

In this paper, we give a rigorous justification of the point vortex approximation to the family of modified surface quasi-geostrophic (mSQG) equations globally in time in both the inviscid and vanishing dissipative cases. This result completes the justification for the remaining range of the mSQG family unaddressed by Geldhauser and Romito in the article arXiv:1812.05166, in the case of identically signed vortices.
Non-linear relationships between nurse staffing and patients' length of stay in acute care units: Bayesian dependence modelling.

AIMS This study sought to analyse relationships between nurse staffing and patients' length of stay in acute care units and to determine whether non-linear relationships exist between variables. BACKGROUND Healthcare systems are complex and it could be assumed that they comprise non-linear associations. However, current planning and evaluation of nurse staffing are based primary on linear reasoning. DESIGN This quantitative study adopted a retrospective longitudinal design. METHOD Retrospective register data, consisting of information relating to 35,306 patient episodes and administrative information concerning 381 nurses, were used. Data were collected in 2009 from 20 somatic inpatient units at a university hospital in Finland as a monthly time series of 2008 data and analysed using Bayesian dependency modelling. RESULTS Patients' acuity was the most important agent that connected all eleven variables in the dependency network of nurse staffing and short length of stay. Non-linear associations were found between short length of stay and the proportion of Registered Nurses. Skill mix consisting of an average proportion of Registered Nurses (65-80%) was conducive to a short length of stay and predicted a 66% likelihood of short length of stay. Higher and lower percentages of Registered Nurses predicted lower likelihood of short length of stay. CONCLUSION Flexible nurse staffing is preferable to fixed staffing to provide patients with shorter length of stay in acute care units. In the present research, the Bayesian method revealed non-linear relationships between nurse staffing and patient and care outcomes.
Active Galactic Nuclei in Dusty Starbursts at z = 2: Feedback Still to Kick in

We investigate a sample of 152 dusty sources at 1.5 < z < 2.5 to understand the connection of enhanced star formation rate (SFR) and black hole accretion rate. The sources are Herschel-selected, having stellar masses M* > 1010 M⊙ and SFR (∼100–1000 M⊙ yr−1) elevated (>4×) above the star-forming “main sequence,” classifying them as starbursts (SBs). Through a multiwavelength fitting approach (including a dusty torus component), we divided the sample into active SBs (dominated by an active galactic nucleus (AGN) emission, SBs-AGN, ∼23% of the sample) and purely star-forming SBs (SBs-SFR). We visually inspected their Hubble Space Telescope/ultraviolet (UV) rest frame maps: SBs-SFR are generally irregular and composite systems; ∼50% of SBs-AGN are instead dominated by regular compact morphologies. We then found archival Atacama Large Millimeter/submillimeter Array continuum counterparts for 33 galaxies (12 SBs-AGN and 21 SBs-SFR). For these sources we computed dust masses, and, with standard assumptions, we also guessed total molecular gas masses. SBs turn into gas-rich systems (fgas = Mgas/(Mgas + M*) ≃ 20%–70%), and the gas fractions of the two SB classes are very similar (fgas = 43% ± 4% and fgas = 42% ± 2%). Our results show that SBs are consistent with a mixture of: (1) highly star-forming merging systems (dominating the SBs-SFR) and (2) primordial galaxies, rapidly growing their M* together with their black hole (mainly the more compact SBs-AGN). Feedback effects have not yet reduced their fgas. Indeed, SBs at z = 2, with relatively low bolometric AGN luminosities in the range 1044 < Lbol(AGN) < 1046 erg s−1 (compared to bright optical and X-ray quasars), are still relatively far from the epoch when the AGN feedback will quench the SFR in the host and will substantially depress the gas fractions.
Revealing the Stellar Mass and Dust Distributions of Submillimeter Galaxies at Redshift 2

We combine high-resolution ALMA and HST/CANDELS observations of 20 submillimeter galaxies (SMGs), predominantly from the AS2UDS survey at z ≃ 2, with bright rest-frame optical counterparts ( ) to investigate the resolved structural properties of their dust and stellar components. We derive two-dimensional stellar-mass distributions that are inferred from spatial mass-to-light ratio ( ) corrections based on rest-frame optical colors. Due to the high central column densities of dust in our SMGs, our mass distributions likely represent a lower limit to the true central mass density. The centroid positions between the inferred stellar-mass and the dust distributions agree within 1.1 kpc, indicating an overall good spatial agreement between the two components. The majority of our sources exhibit compact dust configurations relative to the stellar component (with a median ratio of effective radii = 0.6). This ratio does not change with specific star formation rate over the factor of 30 spanned by our targets, sampling the locus of “normal” main-sequence galaxies up to the starburst regime, . Unlike typical spiral galaxies in the local universe, our results imply that massive SMGs are experiencing centrally enhanced star formation. The sizes and stellar densities of our SMGs are in agreement with those of the passive population at z = 1.5, which is consistent with these systems being the descendants of z ≃ 2 SMGs.
The INSTI HIV-1/HIV-2 antibody test: a review.

INTRODUCTION Rapid HIV tests have been widely adopted globally as an important component of HIV prevention and control programs. The INSTI™ HIV-1/HIV-2 antibody test is a second-generation HIV antibody test, available in most countries for use from whole blood, serum, and plasma. AREAS COVERED Available data on kit characteristics and current performance data on the INSTI™ HIV-1/HIV-2 antibody test are presented together with six other rapid point-of-care tests (RPOCTs) for HIV antibody. Few published data are available providing direct comparisons of INSTI™ with other RPOCTs for HIV antibody and standard laboratory-based HIV-1/HIV-2 antibody assays. Existing data showed that INSTI™ has comparable performance to other RPOCTs but detected seroconversion later than standard laboratory-based assays. EXPERT OPINION The good performance of INSTI HIV-1/HIV-2 antibody test, its ease of use, the rapid availability of results (< 5 min), and the lack of specialized equipment required to use the kit make this kit a useful addition to the global market. The unique antigen and flow through technology contained in the kit make it a strong addition to HIV RPOCTs and to rapid/rapid algorithms used in many resource-limited settings.
Cleaned Similarity for Better Memory-Based Recommenders

Memory-based collaborative filtering methods like user or item k-nearest neighbors (kNN) are a simple yet effective solution to the recommendation problem. The backbone of these methods is the estimation of the empirical similarity between users/items. In this paper, we analyze the spectral properties of the Pearson and the cosine similarity estimators, and we use tools from random matrix theory to argue that they suffer from noise and eigenvalues spreading. We argue that, unlike the Pearson correlation, the cosine similarity naturally possesses the desirable property of eigenvalue shrinkage for large eigenvalues. However, due to its zero-mean assumption, it overestimates the largest eigenvalues. We quantify this overestimation and present a simple re-scaling and noise cleaning scheme. This results in better performance of the memory-based methods compared to their vanilla counterparts.
Towards robustness guarantees for feedback-based optimization

Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.
Combined inhibition of neutral endopeptidase with angiotensin converting enzyme or endothelin converting enzyme in experimental diabetes

Objective The effects of combined inhibition of neutral endopeptidase (NEP) with either angiotensin-converting enzyme (ACE), or endothelin-converting enzyme (ECE) on blood pressure, urinary albumin excretion and heart weight were explored in experimental diabetes. Design Streptozotocin-induced diabetic Sprague–Dawley rats were treated with vehicle, the NEP/ACE inhibitor S 21402, the NEP/ECE inhibitor CGS 26303, the NEP inhibitor SCH 42495, the ACE inhibitor captopril or the endothelin receptor antagonist bosentan for 4 weeks. Methods Blood pressure was measured by tail-cuff method and radiotelemetry. Albuminuria, plasma renin activity and plasma atrial natriuretic peptide (ANP) were determined by radioimmunoassay. NEP binding was assessed by in vitro quantitative autoradiography. Metabolic and biochemistry parameters including food intake, 24-h urine volume, plasma glucose, glycated hemoglobin, glomerular filtration rate (GFR) and urinary sodium excretion were also determined. Results Mean blood pressure over the 4-week study period after commencement of treatment was reduced to a similar extent by a range of treatments including the ACE inhibitor, NEP/ACE inhibitor, endothelin receptor antagonist, NEP/ECE inhibitor, but not the NEP inhibitor, compared with vehicle-treated diabetic rats. Heart to body weight ratio in diabetic rats was only reduced by the NEP/ACE and the NEP/ECE inhibitor. Increased albuminuria in diabetic rats (1.1 ×/÷ 1.2 mg/day) was reduced by the NEP/ACE (0.6 ×/÷ 1.2 mg/day) and the NEP/ECE inhibitors (0.4 ×/÷ 1.2 mg/day). Renal NEP was reduced by the NEP/ACE inhibitor (35 ± 4%) or NEP/ECE inhibitor (38 ± 4%) as well as by the pure NEP inhibitor (27 ± 4%) compared with the untreated diabetic group. Other abnormal metabolic and biochemical parameters in diabetic rats were not influenced by any drug treatment. Conclusions Combined inhibition of NEP/ACE or NEP/ECE confers beneficial effects on blood pressure, albuminuria and heart to body weight ratio in experimental diabetes.
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models

With an eye toward understanding complexity control in deep learning, we study how infinitesimal regularization or gradient descent optimization lead to margin maximizing solutions in both homogeneous and non-homogeneous models, extending previous work that focused on infinitesimal regularization only in homogeneous models. To this end we study the limit of loss minimization with a diverging norm constraint (the "constrained path"), relate it to the limit of a "margin path" and characterize the resulting solution. For non-homogeneous ensemble models, which output is a sum of homogeneous sub-models, we show that this solution discards the shallowest sub-models if they are unnecessary. For homogeneous models, we show convergence to a "lexicographic max-margin solution", and provide conditions under which max-margin solutions are also attained as the limit of unconstrained gradient descent.