Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemistry in Protoplanetary Disks: the gas-phase CO/H2 ratio and the Carbon reservoir

The gas mass of protoplanetary disks, and the gas-to-dust ratio, are two key elements driving the evolution of these disks and the formation of planetary system. We explore here to what extent CO (or its isotopologues) can be used as a tracer of gas mass. We use a detailed gas-grain chemical model and study the evolution of the disk composition, starting from a dense pre-stellar core composition. We explore a range of disk temperature profiles, cosmic rays ionization rates, and disk ages for a disk model representative of T Tauri stars. At the high densities that prevail in disks, we find that, due to fast reactions on grain surfaces, CO can be converted to less volatile forms (principally s-CO$_2$, and to a lesser extent s-CH$_4$) instead of being evaporated over a wide range of temperature. The canonical gas-phase abundance of 10$^{-4}$ is only reached above about 30-35 K. The dominant Carbon bearing entity depends on the temperature structure and age of the disk. The chemical evolution of CO is also sensitive to the cosmic rays ionization rate. Larger gas phase CO abundances are found in younger disks. Initial conditions, such as parent cloud age and density, have a limited impact. This study reveals that CO gas-phase abundance is heavily dependent on grain surface processes, which remain very incompletely understood so far. The strong dependence on dust temperature profile makes CO a poor tracer of the gas-phase content of disks.
Anomaly detection on OpenStack logs based on an improved robust principal component analysis model and its projection onto column space

With the advent of technology and the development of more complex software systems, the size of logs generated by these systems has increasingly risen so that the anomaly detection for remediating common errors has been more difficult than ever. The cloud emergence in the information technology (IT) industry has led to the immigration of enterprises toward it, which has extended the application of cloud management stacks such as OpenStack. By using the OpenStack platform, users can access resource infrastructure and manage virtual machines (VMs). The anomaly detection in OpenStack logs is not realized conveniently due to the substantial size of logs, and it is required to automate this process. Since there is no appropriate open‐source dataset for OpenStack logs, we have generated 25,000 logs by injecting three types of anomalies to propose a more efficient technique in terms of performance and time in detecting anomalies in OpenStack logs relative to recent studies by proper OpenStack log parsing and analyzing these logs by data mining algorithms. To this end, compared to the previous research study, we could improve the anomaly detection performance in terms of F1 score, recall, and precision by 9%, 4%, and 14%, respectively, and decrease the running time relative to the log size by at least 30 s.
The Role of MicroRNAs in Dilated Cardiomyopathy: New Insights for an Old Entity

Dilated cardiomyopathy (DCM) is a clinical diagnosis characterized by left ventricular or biventricular dilation and systolic dysfunction. In most cases, DCM is progressive, leading to heart failure (HF) and death. This cardiomyopathy has been considered a common and final phenotype of several entities. DCM occurs when cellular pathways fail to maintain the pumping function. The etiology of this disease encompasses several factors, such as ischemia, infection, autoimmunity, drugs or genetic susceptibility. Although the prognosis has improved in the last few years due to red flag clinical follow-up, early familial diagnosis and ongoing optimization of treatment, due to its heterogeneity, there are no targeted therapies available for DCM based on each etiology. Therefore, a better understanding of the mechanisms underlying the pathophysiology of DCM will provide novel therapeutic strategies against this cardiac disease and their different triggers. MicroRNAs (miRNAs) are a group of small noncoding RNAs that play key roles in post-transcriptional gene silencing by targeting mRNAs for translational repression or, to a lesser extent, degradation. ﻿A growing number of studies have demonstrated critical functions of miRNAs in cardiovascular diseases (CVDs), including DCM, by regulating mechanisms that contribute to the progression of the disease. Herein, we summarize the role of miRNAs in inflammation, endoplasmic reticulum (ER) stress, oxidative stress, mitochondrial dysfunction, autophagy, cardiomyocyte apoptosis and fibrosis, exclusively in the context of DCM.
EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.
Vulnerable but stronger together: An interpretative phenomenological analysis of the experiences of mothers of young adults with profound intellectual and multiple disabilities during the COVID-19 pandemic

ABSTRACT Background Mothers of young adults with profound intellectual and multiple disabilities that live at home are less likely to be on the radar of formal services. We explored the experience of these mothers over the course of the COVID-19 pandemic. Methods A qualitative study using three case studies. Transcripts were analysed using Interpretative Phenomenological Analysis. Results Two overarching themes with various subthemes emerged. The first theme focuses on the impact of being a mother of a young adult with profound intellectual and multiple disabilities who lives at home during the COVID-19 pandemic. The second theme describes both the vulnerability and resilience of the broader system, as well as its need to experience togetherness. Conclusions Families of a young adult with profound intellectual and multiple disabilities exhibit both resilience and vulnerability during the COVID-19 pandemic, underscoring the importance to support and promote the visibility of these families.
On the Comparability of Chemical Structure and Roughness of Nanochannels in Altering Fluid Slippage

Interfacial hydrodynamic slippage of water depends on both on surface chemistry and roughness. This study tries to connect the effect of chemical property and the physical structure of the surface on the interfacial slippage of water. By performing molecular dynamics simulations (MDS) of Couette flow of water molecules over a reduced Lennard-Jones (LJ) surface, the velocity profile is obtained and extrapolated to get the slip lengths. The slip lengths are measured for various surface-fluid interactions. These interactions are varied by changing the wettability of the surface (characterized by the static contact angle) and its roughness. The slip length variation with the static contact angle as $(1+cos\theta)^{-2}$ is observed. However, it is also observed that the presence of surface roughness always reduces the slip length and it is proposed that the slip length varies with non-dimensionalized average surface roughness as $(1+\alpha^*)^{-2}$ . Thus a relation between the chemical wettability and the physical roughness is established and their coupled interactions modifying slip length is probed.
Synthesis and Optimization of Nisin-Silver Nanoparticles at Different Conditions

Silver nitrate and commercial sigma Nisin were used to synthesize Nisin-Silver nanoparticles; different concentrations of Nisin at different pH conditions were used to optimize the characterization.10 μ g/ml at pH 6.0 had the greatest observation and the deferent conditions characterization of Nisin-Silver nanoparticles agreed with that different methods were used to prepare the Nisin-Silver nanoparticles and the results showed that the best method to prepare the nanoparticles (Nisin-Silver) was sunlight method.
Exploring the connection between radio and GeV-TeV γ-ray emission in the 1FHL and 2FHL AGN samples

Context. With the advent of the Fermi Large Area Telescope (LAT) it was revealed that blazars, representing the most extreme radio-loud active galactic nuclei (AGN) population, dominate the census of the γ -ray sky, and a significant correlation was found between radio and γ -ray emission in the 0.1−100 GeV energy range. However, the possible connection between radio and very high energy (VHE, E > 0.1 TeV) emission still remains elusive, owing to the lack of a homogeneous coverage of the VHE sky. Aims. The main goal of this work is to quantify and assess the significance of a possible connection between the radio emission on parsec scale measured by the very long baseline interferometry (VLBI) and GeV-TeV γ -ray emission in blazars, which is a central issue for understanding blazar physics and the emission processes in these objects. Methods. We investigate the radio VLBI and high energy γ -ray emission by using two large and unbiased AGN samples extracted from the first and second Fermi -LAT catalogs of hard γ -ray sources detected above 10 GeV (1FHL) and 50 GeV (2FHL). For comparison, we perform the same correlation analysis by using the 0.1−300 GeV γ -ray energy flux provided by the third Fermi -LAT source catalog (3FGL). We assess the correlation’s statistical significance by means of a method based on permutations of the luminosities, by taking into account the various observational biases, which may apparently enhance or spoil any intrinsic correlation. Results. We find that the correlation strength and significance depend on the γ -ray energy range, with a different behavior among the blazar sub-classes. Overall, the radio and γ -ray emission above 10 GeV turns out to be uncorrelated for the full samples and for all of the blazar sub-classes with the exception of high synchrotron peaked (HSP) objects, which show a strong and significant correlation. On the contrary, when 0.1−300 GeV γ -ray energies are considered, a strong and significant correlation is found for the full blazar sample as well as for all of the blazar sub-classes. Conclusions. We interpret and explain this correlation behavior within the framework of the blazar spectral energy distribution properties. In the most powerful blazars, which are in general of low synchrotron peaked type, the high energy emission component peaks at energies lower than those sampled by the LAT. On the contrary, in HSP blazars the part of the high energy spectrum affected by cooling effects is well beyond the energy range sampled by the LAT, showing a rising spectrum both in the 3FGL and 1FHL/2FHL energy ranges.
Proposal for a scalable universal bosonic simulator using individually trapped ions

We describe a possible architecture to implement a universal bosonic simulator (UBS) using trapped ions. Single ions are confined in individual traps, and their motional states represent the bosonic modes. Single-mode linear operators, nonlinear phase-shifts, and linear beam splitters can be realized by precisely controlling the trapping potentials. All the processes in a bosonic simulation, except the initialization and the readout, can be conducted beyond the Lamb-Dicke regime. Aspects of our proposal can also be applied to split adiabatically a pair of ions in a single trap.
Comparative effect of upper thoracic spine mobilization with mobility exercises and upper cervical spine mobilization with stabilization exercises in mechanical neck pain: a randomized clinical trial

Background & Objective: Neck pain is a very prevalent health condition. Physiotherapists use multiple treatment options for treating mechanical neck pain. We evaluated the effects of upper thoracic spine mobilization and mobility exercise and upper cervical spine mobilization and stabilization exercises in treating patients with mechanical neck pain. Methodology: A randomized clinical trial was conducted comprising of 36 patients recruited from different clinics of Faisalabad, both genders, ages from 20-40 y, and randomly divided into two groups. Group A underwent upper thoracic mobilization and mobility exercise while Group B underwent upper cervical mobilization with stabilization exercises for 2 times a week for 4 weeks. Pain scores on Numerical Pain Rating Scale (NPRS) and cervical range of movements (ROM) scores were measured before treatment and then weekly for 4 weeks, while Neck Disability Index (NDI) was assessed at baseline and at the end of 4th week. SPSS version. 22 was used to analyze the data. Independent sample t-test was used for between group compression and P ≤ 0.05 (95%) was considered as significant. Results: There was significant improvement in mean NPRS scores at 1st week, 2nd week, 3rd week and 4th week post-treatment (P < 0.05). There was significant improvement in mean cervical ROM at 2nd week, 3rd week and 4th week post-treatment readings (P < 0.05) and mean NDI score at 4th week (P < 0.05). Conclusion: Both groups were found effective in improving pain, range of motion and neck function, but significant improvement in outcomes was observed in upper cervical mobilization and stabilization exercises group. Abbreviations: NPRS - Numerical Pain Rating Scale; ROM - Range of movements; NDI - Neck Disability Index; MNP - Mechanical neck pain; Key words: Adult; Cervical Vertebrae / physiopathology; Disability Evaluation; Exercise Therapy / methods; Female; Humans; Male; Manipulation, Spinal / methods; Neck / physiopathology; Neck Pain / physiopathology; Neck Pain / rehabilitation; Pain Measurement; Range of Motion, Articular; Thoracic Vertebrae / physiopathology; Treatment Outcome; Young Adult Citation: Tahir R, Sohail MAA, Ain NU, Aine QU, Mannan H, Maqbool A. Comparative effect of upper thoracic spine mobilization with mobility exercises and upper cervical spine mobilization with stabilization exercises in mechanical neck pain: a randomized clinical trial. Anaesth. pain intensive care 2022;26(4):488-495. DOI: 10.35975/apic.v26i4. 1952 Received: April 11, 2022; Reviewed: June 23, 2022; Accepted: July 14, 2022
Path integral representation of spin foam models of 4D gravity

We give a unified description of all recent spin foam models introduced by Engle, Livine, Pereira and Rovelli (ELPR) and by Freidel and Krasnov (FK). We show that the FK models are, for all values of the Immirzi parameter γ, equivalent to path integrals of a discrete theory and we provide an explicit formula for the associated actions. We discuss the relation between the FK and ELPR models and also study the corresponding boundary states. For general Immirzi parameter, these are given by Alexandrov's and Livine's SO(4) projected states. For 0 ⩽ γ < 1, the states can be restricted to SU(2) spin networks.
Statistical errors and systematic biases in the calibration of the convective core overshooting with eclipsing binaries - A case study: TZ Fornacis

We attempt to constrain the initial helium abundance, the age and the efficiency of the convective core overshooting of the binary system TZ Fornacis. Our main aim is in pointing out the biases in the results due to not accounting for some sources of uncertainty. We adopt the SCEPtER pipeline, relying on stellar models computed with two stellar evolutionary codes (FRANEC and MESA). We found multiple independent groups of solutions. The best one suggests a system of age 1.10 $\pm$ 0.07 Gyr (primary star in the central helium burning stage, secondary in the sub-giant branch), with a helium-to-metal enrichment ratio of $\Delta Y/\Delta Z = 1$ and core overshooting parameter $\beta = 0.15 \pm 0.01$ (FRANEC) and $f_{\rm ov}= 0.013 \pm 0.001 $ (MESA). The second class of solutions, characterised by a worse goodness-of-fit, still suggest a primary star in the central helium-burning stage but a secondary in the overall contraction phase, at the end of the main sequence. The FRANEC grid provides an age of $1. 16_{-0.02}^{+0.03}$ Gyr and $\beta = 0. 25_{-0.01}^{+0.005}$, while the MESA grid gives $1.23 \pm 0.03$ Gyr and $f_{\rm ov} = 0.025 \pm 0.003$. We also show that very precise mass determinations with uncertainty of a few thousandths of solar mass are required to obtain reliable determinations of stellar parameters, as mass errors larger than approximately 1% lead to estimates that are not only less precise but also biased. Moreover, we show that a fit obtained with a grid of models computed at a fixed $\Delta Y/\Delta Z$ can provide biased age and overshooting estimates. The possibility of independent overshooting efficiencies for the two stars of the system is also explored. This work confirms that to constrain the core overshooting parameter by means of binary systems is a very difficult task that requires an observational precision still rarely achieved and robust statistical methods.
A Cellulose Nanofiber Capacitive Humidity Sensor with High Sensitivity and Fast Recovery Characteristics

Humidity sensors with high sensitivity and fast response characteristics are of great interest for researchers. In this work, capacitive humidity sensors were fabricated using ionic liquid/cellulose nanofibers (CNFs) as the composited sensing film. The porous CNFs are beneficial for preparing sensing films via a solution process, and the ionic liquid could be uniformly dispersed in the films. The humidity-sensing performance of the as-prepared sensors was investigated. The optimized sensor showed a high response (27.95 pF/% RH) in a wide humidity range (11–95% RH) and a fast response speed in the adsorption process (the recovery time was only ~1 s). The high response of the sensors was attributed to the polarization at the interface between the electrolyte and the metal electrode, while the fast recovery was due to the rapid desorption of water molecules on the sensing films. Finally, the application of the obtained sensors in human breath monitoring was explored.
Neutrinos and dark energy after Planck and BICEP2: data consistency tests and cosmological parameter constraints

The detection of the B-mode polarization of the cosmic microwave background (CMB) by the BICEP2 experiment implies that the tensor-to-scalar ratio r should be involved in the base standard cosmology. In this paper, we extend the ΛCDM r+neutrino/dark radiation models by replacing the cosmological constant with the dynamical dark energy with constant w. Four neutrino plus dark energy models are considered, i.e., the wCDM r ∑ mν, wCDM r Neff, wCDM r ∑ mν Neff, and wCDM r Neff mν,sterileeff models. The current observational data considered in this paper include the Planck temperature data, the WMAP 9-year polarization data, the baryon acoustic oscillation data, the Hubble constant direct measurement data, the Planck Sunyaev-Zeldovich cluster counts data, the Planck CMB lensing data, the cosmic shear data, and the BICEP2 polarization data. We test the data consistency in the four cosmological models, and then combine the consistent data sets to perform joint constraints on the models. We focus on the constraints on the parameters w, ∑ mν, Neff, and mν,sterileeff.
Quantum bus building-block for a scalable quantum computer architecture

In superconducting quantum computers, qubits are usually only coupled to their nearest-neighbors. To overcome this limitation, we propose a scalable architecture to simultaneously connect several pairs of distant logical qubits via a dispersively coupled quantum bus. The building-block of the bus is composed of orthogonal coplanar waveguide resonators connected through ancillary flux qubits working in the ultrastrong coupling regime. This regime activates virtual processes that boost the effective qubit-qubit interaction, which results in quantum gates on the nanosecond timescale. The architecture we are proposing has also the benefit of allowing the logical qubits to remain at their optimal bias point, preserving their coherence time.
Prognostic Potential of the Body Composition Indices in Predicting Positive Changes in Resting Blood Pressure after High-Intensity Interval Training in Adolescents

This study aimed to investigate the prognostic potential of body composition indices in predicting the improvement in resting blood pressure after 10 weeks of high-intensity interval training (HIIT) implemented in physical education lessons. The participants were 141 adolescents aged 16 years. Independent variables were body mass index (BMI), fat mass index (FMI), muscle mass index (SMI), and mass to fat ratio (MFR); dependent variables were systolic and diastolic blood pressure (SBP, DBP) and its indices: pulse pressure (PP), mid-blood pressure (MBP), and mean arterial pressure (MAP). The receiver operating curve (ROC) method was employed. SMI and MFR are body composition indices with prognostic potential to predict positive changes in SBP in males (SMI: AUC = 0.82; p < 0.001, MFR = 0.70; p = 0.039) and MFR in females (AUC = 0.72; p = 0.035). The respective cut-off point values used to classify participants as a beneficiary of HIIT intervention concerning SBP were SMI = 7.84 and MFR = 2.43 in males, and for SMI = 10.12 and MFR = 1.94 in females. Body composition indices based on skeletal muscle (SMI, MFR) were more likely to predict positive changes in SBP after HIIT intervention in adolescents. PP, MBP, and MAP did not reflect the detecting power of SMI and MFR. However, these thresholds’ utility is limited to adolescents of 16 years of age.
Eu-Chelate Polystyrene Microsphere-Based Lateral Flow Immunoassay Platform for hs-CRP Detection

Inflammation caused by viral or bacterial infection is a major threat to human health globally. Blood C-reactive protein (CRP) has been proven to be a sensitive indicator for the occurrence and development of inflammation. Furthermore, a tiny change of blood CRP concentration may portend chronic diseases; therefore, high-sensitivity CRP (hs-CRP) detection in a quantitative, rapid, user-friendly, and low-cost manner is highly demanded. In this paper, we developed a europium-chelate polystyrene microsphere (EuPSM)-based lateral flow immunoassay (LFIA) integrating with a benchtop fluorescence analyzer for hs-CRP detection. The optimization of the EuPSM-based LFIA was implemented through adjusting the antibody density on EuPSM from 100% to 60% of the saturated density. Finally, the limit of detection of 0.76 pg/mL and detection range of 0.025–250 ng/mL were obtained. Moreover, the clinical application capability of the proposed platform was validated through detecting CRP in clinical serum samples, showing high consistency with the results obtained from the clinical standard method. Hence, the proposed EuPSM-based LFIA has been verified to be well suitable for hs-CRP detection, while also showing great applicability for sensitively and rapidly detecting other biomarkers.