Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Approaches for the Treatment of Drug-Resistant Tuberculosis

Tuberculosis (TB) is a leading infectious disease that caused the deaths of a total of 1.5 million people in 2020 and is one of the top causes of death globally. India is a country with the highest TB burden, and it may affect all age groups. It is caused by the Mycobacterium tuberculosis bacteria, an intracellular pathogen, and its multidrug and extensively drug-resistant strains, which continue to emerge and spread, resulting in the deadliest infectious disease. After a gap of more than 40 years, the FDA approvals over the past decade of three second-line anti-TB drugs, bedaquiline, delamanid, and pretomanid, have been major forward steps in the management of drug-resistant-TB (DR-TB). Many medicinal plants such as Zanthoxylum leprieurii, Lantana camara , and Cryptolepis sanguinolenta have extensive therapeutic potential and represent a prospective option to fight against DR-TB. Some novel compounds are in the early clinical trial phases such as DprE1 inhibitors TBA-7371 and BTZ-043, and many others that are showing promising futures. This review describes DR-TB and its current chemotherapy guidelines including novel and repurposed drugs that are included in the anti-TB regimens, medicinal plants that have therapeutic potential for the development of drug-hit candidates, drugs that are currently in clinical development, host-directed therapy, and new drug delivery systems to better understand the novel therapeutic approaches that are currently being studied for the efficacious and safe management of DR-TB, a worldwide health problem.
Effect of Mn doping on the structural and optical properties of sol-gel derived ZnO nanoparticles

Un-doped and Mn-doped ZnO nanoparticles were successfully synthesized in an ethanolic solution by using a sol-gel method. Material properties of the samples dependence on preparation conditions and Mn concentrations were investigated while other parameters were controlled to ensure reproducibility. It was observed that the structural properties, particle size, band gap, photoluminescence intensity and wavelength of maximum intensity were influenced by the amount of Mn ions present in the precursor. The XRD spectra for ZnO nanoparticles show the entire peaks corresponding to the various planes of wurtzite ZnO, indicating a single phase. The diffraction peaks of doped samples are slightly shifted to lower angles with an increase in the Mn ion concentration, signifying the expansion of the lattice constants and increase in the band gap of ZnO. All the samples show the absorption in the visible region. The absorbance spectra show that the excitonic absorption peak shifts towards the lower wavelength side with the Mn-doped ZnO nanoparticles. The PL spectra of undoped ZnO consist of UV emission at 388 nm and broad visible emission at 560 nm with varying relative peak intensities. The doping of ZnO with Mn quenches significantly the green emission while UV luminescence is slightly affected.
The λ=6 cm VLBI polarization structure of nine BL Lacertae objects

VLBI total intensity (I) and linear polarization (P) images at λ=6 cm have been obtained for nine radio-bright BL Lacertae objects. These are the first VLBI P images for these sources, and, in a number of cases, the first I images as well. They confirm the previously noted tendency for the jet magnetic fields of BL Lacertae objects to be transverse to the local jet direction, but also provide new evidence that a sizeable minority of BL Lacertae objects have VLBI jet components with longitudinal magnetic fields. In addition, two sources have VLBI jet components in which the direction of the electric vector χ bears no obvious relation to the apparent local jet direction; the origin of these arbitrary χ offsets is unclear. A new tentative superluminal speed of β=6.3 h−1 has been determined for 0828+493; tentative speeds for two knots in 1418+546 are β=4.3 and 2.5 h−1. This work is part of an ongoing programme to determine the VLBI I and P structure of all 34 sources in the 1-Jy sample of northern BL Lacertae objects defined by Kuhr & Schmidt.
Regulatory Role of microRNA of Milk Exosomes in Mastitis of Dairy Cows

Simple Summary The microRNA (miRNA) cargos of exosomes isolated from milk were investigated in relation to the healthy conditions of the mammary gland. Samples were collected from a group of cows without mastitis (H), a group at risk of mastitis (ARM), and a group with subclinical mastitis (SCM). The differential expression analysis identified 38, 18, and 12 miRNAs (p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only bta-mir-221 was shared between the three groups. The miRNA cargos of milk exosomes can be considered to study the complex molecular machinery set in motion in response to mastitis in dairy cows and the quality of milk. Abstract The aim of this study was to compare the cargos of miRNA in exosomes isolated from the milk of healthy (H) cows, cows at risk of mastitis (ARM), and cows with subclinical mastitis (SCM). Based on the number of somatic cells and the percentage of polymorphonuclear cells, 10 cows were assigned to group H, 11 to group ARM, and 11 to group SCM. After isolating exosomes in milk by isoelectric precipitation and ultracentrifugation, the extracted RNA was sequenced to 50 bp long single reads, and these were mapped against Btau_5. 0.1. The resulting 225 miRNAs were uploaded to the miRNet suite, and target genes for Bos taurus were identified based on the miRTarBase and miRanda databases. The list of differentially expressed target genes resulting from the comparisons of the three groups was enriched using the Function Explorer of the Kyoto Encyclopedia of Genes and Genomes. A total of 38, 18, and 12 miRNAs were differentially expressed (DE, p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only 1 DE miRNA was shared among the three groups (bta-mir-221), 1 DE miRNA in the H vs. SCM comparison, 9 DE miRNAs in the ARM vs. SCM comparison, and 21 DE miRNAs in the H vs. ARM comparison. A comparison of the enriched pathways of target genes from the H, SCM, and ARM samples showed that 19 pathways were differentially expressed in the three groups, while 56 were expressed in the H vs. SCM comparison and 57 in the H vs. ARM comparison. Analyzing milk exosome miRNA cargos can be considered as a promising approach to study the complex molecular machinery set in motion in response to mastitis in dairy cows.
Bias Correction of Regional Climate Model Simulations in a Region of Complex Orography

AbstractThis study presents a method to correct regional climate model (RCM) outputs using observations from automatic weather stations. The correction applies a nonlinear procedure, which recently appeared in the literature, to both precipitation and temperature on a monthly basis in a region of complex orography. To assess the temporal stability of such a correction, the correcting parameters of each variable are investigated using different time periods within the observational record. The RCM simulations used in this study to evaluate the bias-correction method are the publicly available “Reg-CM3” experiments from the Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project. They provide daily precipitation and temperature time series on a raster with spatial resolution of 0.22°. The analysis is performed in the Rhone catchment, located in southwestern Switzerland and characterized by highly complex orography. The results show that the nonlinear bias correction increases dra.
An international Delphi consensus statement on metabolic dysfunction-associated fatty liver disease and risk of chronic kidney disease

Background With the rising global prevalence of fatty liver disease related to metabolic dysfunction, the association of this common liver condition with chronic kidney disease (CKD) has become increasingly evident. In 2020, the more inclusive term metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed to replace the term non-alcoholic fatty liver disease (NAFLD). The observed association between MAFLD and CKD and our understanding that CKD can be a consequence of underlying metabolic dysfunction support the notion that individuals with MAFLD are at higher risk of having and developing CKD compared with those without MAFLD. However, to date, there is no appropriate guidance on CKD in individuals with MAFLD. Furthermore, there has been little attention paid to the link between MAFLD and CKD in the Nephrology community. Methods and Results Using a Delphi-based approach, a multidisciplinary panel of 50 international experts from 26 countries reached a consensus on some of the open research questions regarding the link between MAFLD and CKD. Conclusions This Delphi-based consensus statement provided guidance on the epidemiology, mechanisms, management and treatment of MAFLD and CKD, as well as the relationship between the severity of MAFLD and risk of CKD, which establish a framework for the early prevention and management of these two common and interconnected diseases.
Vacuum radiation pressure on moving mirrors

We consider a perfectly reflecting plane mirror moving in the vacuum of the electromagnetic field. The motional modification of the Maxwell stress tensor is computed up to first order in the displacement of the mirror. The resulting dissipative force is shown to be related to the creation of travelling-wave low-frequency photons and to obey the fluctuation-dissipation theorem.
GENDER DIFFERENCES IN THE MOTIVES OF USING ONLINE SOCIAL NETWORKS BY UNIVERSITY STUDENTS

Recent studies show that university students are frequently using the online social networks (OSN) in order to get new information about friends, courses and university events, to maintain relationships with old colleagues or to search new friends. All these motives may differ depending on the gender of students. By understanding gender differences in students' motives to use social networks, teachers will know how to better encourage and improve the learning activities of students, by using the various tools offered by the OSNs. Facebook is one of the fastest growing online social networks, with more than 8 million Romanian users in 2016. This paper investigates the motives of its use and variations across gender. A total of 225 students from a Romanian university took part in this study. This research has two main objectives: (a) to analyze the measurement invariance across gender and (b) to analyze the gender differences along three dimensions: extending the social relations, information & collaboration and maintaining the social relations and. A Multi-Group Confirmatory Factor Analysis (MGCFA) has been conducted, to assess whether the scale is invariant across gender. The measurement invariance analysis show that the model exhibits factorial, metric, and structural invariance across gender groups. The gender differences analysis shows mean differences between male and female students as regards all three dimensions: extending the social relations, information & collaboration and maintaining the social relations. The results of this research contribute to a better understanding of the motives of Facebook use by university students. Second, this study provides a reliable evaluation instrument that performs well across gender.
The mechanism of edge-tone production

Former theories of the production of edge tones are reviewed and a new theory is put forward which accounts in a qualitative manner for the phenomena described in the preceding paper. The effect of the wake of a disturbance on the portion of the jet immediately following it is considered, and it is concluded that the compressibility and structure of the surrounding medium must be taken into account, and that, for low velocities, wake disturbance is the controlling factor, whilst for higher velocities the effect of the sound emitted must be taken into account. An attempt is made also to account for the differential sensitivity to frequency found in sensitive jets in a former research.
Deep Surface Photometry of M87 with 13 Optical Bands

Multicolor surface photometry of M87 was undertaken with the Beijing-Arizona-Taiwan-Connecticut photometric system, which contains 13 optical bands covering a range from 3800 to 10000 Å. Radial profiles have been derived for surface brightness, ellipticity, position angle, and the residuals from the fitted ellipses. The results show a good agreement with pure elliptical isophotes for M87, and no obvious substructure or dust is detected out to r = 500″, corresponding to 40 kpc from the center. The surface brightness profile at r < 190″ is well fitted by the de Vaucouleurs law. Moreover, a cD envelope is detected outside that radius. Given the surface brightness profiles of the 13 bands, the spectral energy distribution (SED) of M87 is obtained as a function of semimajor axis (SMA). By fitting the observed SEDs to synthetic ones derived from the PEGASE model, we explored the star formation history (SFH) of this giant elliptical galaxy. In the hypothesis that the evolution time T of M87 is the same as the mean age of its globular clusters, about 14 Gyr, we find that the characteristic timescale τ of the SFH increases monotonically from 2 to 7 Gyr as a function of SMA, while the luminosity-weighted mean stellar ages range from about 11 to 9 Gyr in a mild decrease, and the mean stellar metallicity Z drops from 0.017 to 0.014 as the SMA increases to r = 500″. In the range 40″ < r < 190″, the metallicity gradient Δ[Fe/H]/Δ[log r] = -0.04, while in the range 190″ < r < 400″, the metallicity gradient Δ[Fe/H]/Δ[log r] = -0.17.
Forebrain E-I balance controlled in cognition through coordinated inhibition and inhibitory transcriptome mechanism

Introduction Forebrain neural networks are vital for cognitive functioning, and their excitatory-inhibitory (E-I) balance is governed by neural homeostasis. However, the homeostatic control strategies and transcriptomic mechanisms that maintain forebrain E-I balance and optimal cognition remain unclear. Methods We used patch-clamp and RNA sequencing to investigate the patterns of neural network homeostasis with suppressing forebrain excitatory neural activity and spatial training. Results We found that inhibitory transmission and receptor transcription were reduced in tamoxifen-inducible Kir2.1 conditional knock-in mice. In contrast, spatial training increased inhibitory synaptic connections and the transcription of inhibitory receptors. Discussion Our study provides significant evidence that inhibitory systems play a critical role in the homeostatic control of the E-I balance in the forebrain during cognitive training and E-I rebalance, and we have provided insights into multiple gene candidates for cognition-related homeostasis in the forebrain.
STARDUST FROM ASYMPTOTIC GIANT BRANCH STARS

The formation of dust in the outflows of low- and intermediate-mass stars on the first giant branch and asymptotic giant branch (AGB) is studied and the relative contributions of stars of different initial masses and metallicities to the interstellar medium (ISM) at the instant of solar system formation are derived. These predictions are compared with the characteristics of the parent stars of presolar dust grains found in primitive meteorites and interplanetary dust particles (IDPs) inferred from their isotopic compositions. For this purpose, model calculations for dust condensation in stellar outflows are combined with synthetic models of stellar evolution on the first giant branch and AGB and an evolution model of the Milky Way for the solar neighborhood. The dust components considered are olivine, pyroxene, carbon, SiC, and iron. The corresponding dust production rates are derived for the solar vicinity. From these rates and taking into account dust destruction by supernova shocks in the ISM, the contributions to the inventory of presolar dust grains in the solar system are derived for stars of different initial masses and metallicities. It is shown that stars on the first giant branch and the early AGB are not expected to form dust, in accord with astronomical observations. Dust formation is concentrated in the last phase of evolution, the thermally pulsing AGB. Due to the limited lifetime of dust grains in the ISM only parent stars from a narrow range of metallicities are expected to contribute to the population of presolar dust grains. Silicate and silicon carbide dust grains are predicted to come from parent stars with metallicities not less than about Z ≈ 0.008 (0.6 × solar). This metallicity limit is higher than that inferred from presolar SiC grain isotope data. The population of presolar carbon dust grains is predicted to originate from a wider range of metallicities, down to Z ≈ 0.004. Masses of AGB stars that produce C-rich dust are in the range ≈1.5–4 M☉, in good agreement with what was inferred from the isotope data of presolar grains. The mass distribution of AGB stars that produce O-rich dust is essentially bimodal, with roughly equal contributions from stars in the ranges 1.3–2.5 M☉ and ≈4–8 M☉. These model predictions are in conflict with the O-isotope data of presolar grains that indicate contributions essentially only from 1 to 2.5 M☉ AGB stars.
Space–time characteristics of a compliant wall in a turbulent channel flow

Abstract The space–time characteristics of a compliant wall in a turbulent channel flow are investigated using direct numerical simulation (DNS). The compliant wall is modelled as a homogeneous plane supported by spring-and-damper arrays and is passively driven by wall-pressure fluctuations. The frequency/wavenumber spectra and convection velocities of the wall-pressure fluctuations, wall displacement and wall velocity are obtained from the present simulation. As the spring, damping, and tension coefficients decrease, the wall becomes softer and the wall displacement and velocity fluctuations increase. For a relatively stiff compliant wall (i.e. large spring, damping and streamwise tension coefficients), there are few changes in the skin-friction drag and near-wall turbulence structures. However, when a compliant wall is soft (i.e. small spring, damping and streamwise tension coefficients), the wall moves in the form of a large-amplitude quasi-two-dimensional wave travelling in the downstream direction. This wave is generated by the resonance of the wall property and the near-wall flow is significantly activated by this wall motion. The power spectra of wall variables show distinct peaks near the resonance frequencies. The convection velocities of the wall motion and wall-pressure fluctuations become smaller with a softer wall.
A Covariate Selection Criterion for Estimation of Treatment Effects

We study how to select or combine estimators of the average treatment effect (ATE) and the average treatment effect on the treated (ATT) in the presence of multiple sets of covariates. We consider two cases: (1) all sets of covariates satisfy the unconfoundedness assumption and (2) some sets of covariates violate the unconfoundedness assumption locally. For both cases, we propose a data-driven covariate selection criterion (CSC) to minimize the asymptotic mean squared errors (AMSEs). Based on our CSC, we propose new average estimators of ATE and ATT, which include the selected estimators based on a single set of covariates as a special case. We derive the asymptotic distributions of our new estimators and propose how to construct valid confidence intervals. Our Monte Carlo simulations show that in finite samples, our new average estimators achieve substantial efficiency gains over the estimators based on a single set of covariates. We apply our new estimators to study the impact of inherited control on firm performance.
Histories approach to general relativity: II. invariance groups

In this paper we show in detail how the histories description of general relativity carries representations of both the spacetime diffeomorphism group and the Dirac algebra of constraints. We show that the introduction of metric-dependent equivariant foliations leads to the crucial result that the canonical constraints are invariant under the action of spacetime diffeomorphisms. Furthermore, there exists a representation of the group of generalized spacetime mappings that are functionals of the 4-metric: this is a spacetime analogue of the group originally defined by Bergmann and Komar in the context of the canonical formulation of general relativity. Finally, we discuss the possible directions for the quantization of gravity in histories theory.
Coronal mass ejections observed during the Solar Maximum Mission: Latitude distribution and rate of occurrence

Sixty-five coronal mass ejections have been identified in a systematic examination of white-light coronal images obtained between March and September 1980 by the coronagraph/polarimeter flown on the solar maximum mission spacecraft. These ejections were more uniformly distributed in position angle (or “projected” solar latitude) than the similar events observed during the Skylab mission in 1973–1974; 27% of the solar maximum mission mass ejections were centered at positions more than 45° from the solar equator. The average rate of occurrence of the observed mass ejections for the entire solar maximum mission epoch, based on the assumption that one coronagraph image per spacecraft orbit is sufficient for detection, was 0.9±0.15 per 24-hour day. Application of the same sampling assumption to the Skylab data set leads to a rate of 0.75 per 24-hour day and thus a change in this rate from the Skylab era (on the declining phase of sunspot cycle 20) to solar maximum mission (near the maximum of sunspot cycle 21) of only ∼20%.
Nucleic Acid Quantification by Multi-Frequency Impedance Cytometry and Machine Learning

Determining nucleic acid concentrations in a sample is an important step prior to proceeding with downstream analysis in molecular diagnostics. Given the need for testing DNA amounts and its purity in many samples, including in samples with very small input DNA, there is utility of novel machine learning approaches for accurate and high-throughput DNA quantification. Here, we demonstrated the ability of a neural network to predict DNA amounts coupled to paramagnetic beads. To this end, a custom-made microfluidic chip is applied to detect DNA molecules bound to beads by measuring the impedance peak response (IPR) at multiple frequencies. We leveraged electrical measurements including the frequency and imaginary and real parts of the peak intensity within a microfluidic channel as the input of deep learning models to predict DNA concentration. Specifically, 10 different deep learning architectures are examined. The results of the proposed regression model indicate that an R_Squared of 97% with a slope of 0.68 is achievable. Consequently, machine learning models can be a suitable, fast, and accurate method to measure nucleic acid concentration in a sample. The results presented in this study demonstrate the ability of the proposed neural network to use the information embedded in raw impedance data to predict the amount of DNA concentration.
Fuzzy optimal control using simple inference method and function type inference method

By considering fuzzy optimal control problems as problems of finding the minimum (maximum) value of the cost (benefit) function, the existence of fuzzy optimal control is shown by applying the simple inference method and function type inference method to fuzzy systems. To show that, we prove Lipschitz's continuity of these inference method on the state in the control and continuity of them on the fuzzy rule.