Binary Samples Research Articles

Peculiar radio-bright behaviour of the Galactic black hole transient 4U 1543−47 in the 2021–2023 outburst

ABSTRACT Correlated behaviours between the radio emission and the X-ray emission in Galactic black hole X-ray binaries (BH XRBs) in the X-ray hard state are crucial to the understanding of disc-jet coupling of accreting black holes. The BH transient 4U 1543–47 went into outburst in 2021 following $\sim$19 yr of quiescence. We followed it up with $\sim$ weekly cadence with MeerKAT for about one year and a half until it faded into quiescence. Multi-epoch quasi-simultaneous MeerKAT and X-ray observations allowed us to trace the compact jet emission and its X-ray emission. In its hard spectral state across three orders of magnitude of X-ray luminosities above $\sim$10$^{34}$ ergs s$^{-1}$, we found the correlation between radio and X-ray emission had a power-law index of 0.82$\pm$0.09, steeper than the canonical value of $\sim$0.6 for BH XRBs. In addition, the radio versus X-ray correlation show a large range of the power-law normalization, with the maximum significantly larger than that obtained for most BH XRBs, indicating it can be particularly radio-bright and variable in the X-ray binary sample. The radio emission is unlikely diluted by discrete jet components. The observed peculiar radio-bright and variable behaviours provide the evidence for the relativistic effects of a variable Lorentz factor in the range between 1 and $\sim$2 of the compact jet.

Leukocyte segmentation based on DenseREU-Net

The detection of white blood cells provides important information in cellular research regarding infections, inflammation, immune function, and blood pathologies. Effective segmentation of WBCs in blood microscopic images not only aids pathologists in making more accurate diagnoses and early detections but is also crucial for identifying the types of lesions. Due to significant differences among various types of pathological WBCs and the complexities associated with cellular imaging and staining techniques, accurately recognizing and segmenting these different types of WBCs remains challenging. To address these challenges, this paper proposes a WBC segmentation technique based on DenseREU-Net, which enhances feature exchange and reuse by employing Dense Blocks and residual units. Additionally, it introduces mixed pooling and skip multi-scale fusion modules to improve the recognition and segmentation accuracy of different types of pathological WBCs. This study was validated on two datasets provided by DML-LZWH (Liuzhou Workers’ Hospital Medical Laboratory). Experimental results indicate that on the multi-class dataset, DenseREU-Net achieves an average IoU of 73.05% and a Dice coefficient of 80.25%. For the binary classification blind sample dataset, the average IoU and Dice coefficient are 83.98% and 90.41%, respectively. In both datasets, the proposed model significantly outperforms other advanced medical image segmentation algorithms. Overall, DenseREU-Net effectively analyzes blood microscopic images and accurately recognizes and segments different types of WBCs, providing robust support for the diagnosis of blood-related diseases.

Double-edged Sword: The Influence of Tidal Interaction on Stellar Activity in Binaries

Using the LAMOST DR7 low-resolution spectra, we carried out a systematic study of stellar chromospheric activity in both single and binary stars. We constructed a binary sample and a single-star sample, mainly using the binary belt and the main sequence in the Hertzsprung–Russell diagram, respectively. By comparing the S indices between single and binary stars within each color bin, we found for K-type stars, binaries exhibit enhanced activity compared to single stars, which could be attributed to the increase in spin rate caused by tidal synchronization or to the interactions of magnetic fields. Both single stars and binaries fall on a common sequence in the activity-period relation, indicating that the chromospheric activities of binaries are dominated by the more active components. More intriguingly, in some color ranges, a slight decline of the S index for smaller orbital periods was observed for binary stars. Although the possibility of sample selection effects cannot be excluded, this may mark the first example of supersaturation (i.e., caused by reduced active regions) being detected in chromospheric activity, or provide evidence of the suppressing effect on the magnetic dynamo and stellar activities by strong tidal interaction in very close binaries. Our study suggests that tidal interaction acts as a double-edged sword in relation to stellar activities.

Quantitative Analysis of Amorphous Form in Indomethacin by Near Infrared Spectroscopy Combined with Partial Least Squares Regression Analysis.

Indomethacin (INDO) is a synthetic non-steroidal antipyretic, analgesic, and anti-inflammatory drug that commonly exists in both amorphous and crystalline states. Its amorphous state (A-INDO) is utilized by pharmaceutical companies as an active pharmaceutical ingredient (API) in the production of INDO drugs due to its higher apparent solubility and bioavailability. The crystal state also encompasses various crystal forms such as the α-crystal form (α-INDO) and γ-crystal form (γ-INDO), with the highly crystalline and insoluble γ-INDO being commercially available. A-INDO, existing in a thermodynamically high-energy state, is susceptible to several factors during the preparation, storage, and transportation of API leading to its conversion into γ-INDO, thus impacting the bioavailability and efficacy of INDO drugs. Therefore, quantitative analysis of the A-INDO/γ-INDO content in INDO API becomes essential for controlling the production quality of INDO. The primary objective of this study is to investigate the feasibility of NIR for the quantitative analysis of A-INDO in INDO API, and to further elucidate its quantitative analysis mechanism. The NIR spectral data were collected for A-INDO and γ-INDO binary mixture samples with different resolutions, and these spectra were then selected and reconstructed using the interval partial least square (iPLS) method. Different pretreatment methods were employed to enhance the reconstructed spectra by highlighting relevant eigen information while eliminating invalid information caused by environmental factors or physical characteristics of samples. The most suitable PLSR model for quantitative analysis of A-INDO within the range of 0.0000-100.0000% w/w% was established, screened, and validated. From various perspectives, including distribution of spectral effective information, impact of resolution on PLSR model performance, variance contribution/cumulative variance contribution of PLSR model principal components (PCs), PCI loadings, relationship between spectral scores, and A-INDO content, feasibility assessment was conducted for the quantitative analysis of A-INDO in INDO using NIR spectroscopy. Additionally, a detailed investigation on the quantitative analysis mechanism of the optimal PLSR model was undertaken including the correlation between the characteristic peaks of spectra and information regarding hydrogen groups or hydrogen bonds in A-INDO or γ-INDO molecules. This study aims to provide theoretical support for the quantitative analysis of A-INDO in INDO API as well as serve as a reliable reference method for API quantification and quality control in similar drugs.

Detection of Ovarian Tumors Using TVUS Imaging and Segmentation Techniques

Ovarian most cancers remains a giant health subject due to its regularly asymptomatic development until superior stages, where treatment options are confined. Early detection is critical for enhancing affected person outcomes and survival costs. This observe proposes a comprehensive technique leveraging superior photograph processing techniques for the early detection and category of ovarian tumors the usage of trans vaginal ultrasound (TVUS) snap shots. The method starts with preprocessing steps which include median filtering to do away with noise artifacts inclusive of salt and pepper noise from ultrasound photos. Ultimately, picture enhancement techniques are applied to enhance contrast and intensity, observed through binary sample evaluation to signify texture features vital for tumor identification. Photo segmentation is performed the use of okay- manner clustering and gray degree Co-prevalence Matrix (GLCM) analysis to isolate and analyze areas of interest within the ovarian photos. A Convolutional Neural community (CNN) is then hired for correct classification of ovarian tumors as regular, benign, or malignant primarily based on the extracted functions. This approach not handiest enhances the diagnostic accuracy but also minimizes affected person publicity to ionizing radiation, making it appropriate for ordinary medical applications. The proposed methodology represents a considerable advancement within the discipline of ovarian cancer detection, presenting a non-invasive and green way to evaluate ovarian health and facilitate timely intervention. Destiny research directions include refining the set of rules’s performance with large datasets and exploring additional imaging modalities for complete ovarian fitness evaluation.

A generative model for Gaia astrometric orbit catalogs: selection functions for binary stars, giant planets, and compact object companions

Astrometry from {} DR3 has produced a sample of $$170,000 Keplerian orbital solutions, with many more anticipated in the next few years. These data have enormous potential to constrain the population of binary stars, giant planets, and compact objects in the Solar neighborhood. But in order to use the published orbit catalogs for statistical inference, it is necessary to understand their selection function: what is the probability that a binary with a given set of properties ends up in a catalog? We show that such a selection function for the {} DR3 astrometric binary catalog can be forward-modeled from the {} scanning law, including individual 1D astrometric measurements, the fitting of a cascade of astrometric models, and quality cuts applied in post-processing. We populate a synthetic Milky Way model with binary stars and generate a mock catalog of astrometric orbits. The mock catalog is quite similar to the DR3 astrometric binary sample, suggesting that our selection function is a sensible approximation of reality. Our fitting also produces a sample of spurious astrometric orbits similar to those found in DR3; these are mainly the result of scan angle-dependent astrometric biases in marginally resolved wide binaries. We show that {} sensitivity to astrometric binaries falls off rapidly at high eccentricities, but only weakly at high inclinations. We predict that DR4 will yield ∼1 million astrometric orbits, mostly for bright ( G≲15) systems with long periods ( d). We provide code to simulate and fit realistic {} epoch astrometry for any data release and determine whether any hypothetical binary would receive a cataloged orbital solution.

Measurements of the Low-acceleration Gravitational Anomaly from the Normalized Velocity Profile of Gaia Wide Binary Stars and Statistical Testing of Newtonian and Milgromian Theories

Low-acceleration gravitational anomaly is investigated with a new method of exploiting the normalized velocity profile v˜≡vp/vc of wide binary stars as a function of the normalized sky-projected radius s/r M, where v p is the sky-projected relative velocity between the pair, v c is the Newtonian circular velocity at the sky-projected separation s, and r M is the MOND radius. With a Monte Carlo method, Gaia observed binaries and their virtual Newtonian counterparts are probabilistically distributed on the s/r M versus v˜ plane, and a logarithmic velocity ratio parameter Γ is measured in the bins of s/r M. With three samples of binaries covering a broad range in size, data quality, and implied fraction of hierarchical systems including a new sample of 6389 binaries selected with accurate distances and radial velocities, I find a unanimous systematic variation from the Newtonian flat line. With Γ = 0 at s/r M ≲ 0.15 or s ≲ 1 kau, I get Γ = 0.068 ± 0.015 (stat) −0.015+0.024 (syst) for s/r M ≳ 0.7 or s ≳ 5 kau. The gravitational anomaly (i.e., acceleration boost) factor given by γ g = 102Γ is measured to be γg=1.37−0.09+0.10 (stat) −0.09+0.16 (syst). With a reduced χ 2 test of Newtonian and Milgromian nonrelativistic theories, I find that Newtonian gravity is ruled out at 5.8σ ( χν2=9.4 ) by the new sample (and 9.2σ by the largest sample used). The Milgromian AQUAL theory is acceptable with 0.7≲χν2≲3.1 . These results agree well with earlier results with the “acceleration-plane analysis” for a variety of samples and the “stacked velocity profile analysis” for a pure binary sample.

X-Ray study of Mo-W-O, Ti-W-O and Cu-W-O catalysts

<p class="Mabstract">An X-ray study of the phase composition of Mo-W-O, Ti-W-O, and Cu-W-O catalysts was carried out. Analysis of X-ray diffraction patterns of the Mo-W-O catalytic system showed that in all samples, mainly the phases of molybdenum and tungsten oxides, namely MoO<sub>3</sub> and WO<sub>3</sub>, are formed. It is shown that, in contrast to Mo-W-O catalysts, in addition to the initial titanium and tungsten oxides, the samples of the Ti-W-O catalytic system also contain phases of chemical compounds. So, in Ti-W-O samples, there are phases of titanium oxide (anatase), titanium oxide (rutile), and tungsten oxide. It has been established that the degree of crystallinity of binary titanium-tungsten oxide samples decreases with increasing titanium content in the catalyst composition from 83.4% to 70.2%. In the case of copper-tungsten oxide catalysts, in addition to the initial oxides of copper and tungsten also contain phases of the chemical compound of copper tungstate, and crystallinity degrees of binary copper-tungsten oxide samples changes in the ranges from 85.7% to 41.3%.<strong></strong></p>

Study of mesomorphic, thermal and optical properties of 4-pentylbenzoic acid (5BA) and 4-n-alkyl-4́-cyanobiphenyl (nCB; n = 5, 6) supramolecular hydrogen bonded mesogenic complexes

Within the scope of this study, the process of producing and analyzing a liquid crystalline substance (supramolecular hydrogen-bonded mesogen) is presented. The formation of this mesogen involves the use of two chemicals, namely 4-pentylbenzoic acid (5BA) and 4-n-alkyl-4́-cyanobiphenyl (nCB; n = 5, 6). Equimolar (1:1) 5BA/5CB and 5BA/6CB binary combination samples have been organized by using one at a time mixing 5CB and 6CB liquid crystal chemical substances with 5BA. Differential scanning calorimetry (DSC) and polarized optical microscopy (POM) are employed for the examination of phase transitions, and liquid crystalline phase texture properties of the produced mesogens. The phase transformation sequence that occurred during heating and cooling is Crystal (Cr) ↔ Smectic A (SmA) ↔ Nematic (N) ↔ Isotropic (I) with the 1st order or weakly 1st order transition. The nematic range value observed for 5BA/6CB is considerably smaller than the nematic range value observed for 5BA/5CB, but the thermal mesophase range value for both is approximately the same. Fourier-transform infrared (FTIR) evaluation of 5BA, 5CB, and their hydrogen-bonded combos (5BA/nCB; n = 5, 6) confirmed attribute peaks. The X-ray diffraction (XRD) study revealed that the produced mesogens possess a crystalline structure. In addition, UV–Vis experiments demonstrated that the increase in alkyl chain length in the combination resulted in a decrease in absorbance and wavelength values, while leading to an increase in absorbency and band gap energy values. These results propose workable purposes for the synthesized substances in liquid crystal displays and other optoelectronic devices. Overall, the findings display the feasibility and viability of these novel hydrogen-bonded liquid crystalline mesogens in various technological applications.

A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey

With the continuous development of large optical surveys, a large number of light curves of late-type contact binary systems (CBs) have been released. Deriving parameters for CBs using the the Wilson–Devinney program and the PHOEBE program poses a challenge. Therefore, this study developed a method for rapidly deriving light curves based on the Neural Networks model combined with the Hamiltonian Monte Carlo (HMC) algorithm (NNHMC). The neural network was employed to establish the mapping relationship between the parameters and the pregenerated light curves by the PHOEBE program, and the HMC algorithm was used to obtain the posterior distribution of the parameters. The NNHMC method was applied to a large contact binary sample from the Catalina Sky Survey, and a total of 19,104 late-type contact binary parameters were derived. Among them, 5172 have an inclination greater than 70° and a temperature difference less than 400 K. The obtained results were compared with the previous studies for 30 CBs, and there was an essentially consistent goodness-of-fit (R 2) distribution between them. The NNHMC method possesses the capability to simultaneously derive parameters for a vast number of targets. Furthermore, it can provide an extremely efficient tool for the rapid derivation of parameters in future sky surveys involving large samples of CBs.

A population of neutron star candidates in wide orbits from Gaia astrometry

We report discovery and spectroscopic follow-up of 21 astrometric binaries containing solar-type stars and dark companions with masses near 1.4 M⊙. The simplest interpretation is that the companions are dormant neutron stars (NSs), though ultramassive white dwarfs (WDs) and tight WD+WD binaries cannot be fully excluded. We selected targets from Gaia DR3 astrometric binary solutions in which the luminous star is on the main sequence and the dynamically-implied mass of the unseen companion is (a) more than 1.25M⊙ and (b) too high to be any non-degenerate star or close binary. We obtained multi-epoch radial velocities (RVs) over a period of 670 days, spanning a majority of the orbits’ dynamic range in RV. The RVs broadly validate the astrometric solutions and significantly tighten constraints on companion masses. Several systems have companion masses that are unambiguously above the Chandrasekhar limit, while the rest have masses between 1.25 and 1.4 M⊙. The orbits are significantly more eccentric at fixed period than those of typical WD + MS binaries, perhaps due to natal kicks. Metal-poor stars are overrepresented in the sample: 3 out of 21 objects (14%) have [Fe/H] ∼−1.5 and are on halo orbits, compared to ∼0.5% of the parent Gaia binary sample. The metal-poor stars are all strongly enhanced in lithium. The formation history of these objects is puzzling: it is unclear both how the binaries escaped a merger or dramatic orbital shrinkage when the NS progenitors were red supergiants, and how they remained bound when the NSs formed. Gaia has now discovered 3 black holes (BHs) in astrometric binaries with masses above 9 M⊙, and 21 NSs with masses near 1.4M⊙. The lack of intermediate-mass objects in this sample is striking, supporting the existence of a BH/NS mass bimodality over 4 orders of magnitude in orbital period.

Highly efficient strategy of lipopolysaccharide (LPS) decontamination from rHBsAg: synergistic effect of enhanced magnetic nanoparticles (MNPs) as an LPS affinity adsorbent (LAA) and surfactant as a dissociation factor

The interaction of lipopolysaccharide with a recombinant protein is a serious bottleneck, particularly in the purification step of bioprocessing. Recombinant hepatitis B surface antigen (rHBsAg), the active ingredient of the hepatitis B vaccine, is probably contaminated by extrinsic LPS like other biopharmaceuticals. This research intends to eliminate LPS from its mixture with rHBsAg efficiently. Immobilized polymyxin B on magnetic nanoparticles (PMB-MNPs) was synthesized and implemented as an enhanced LPS affinity adsorbent (LAA). The 20–80 EU/dose binary samples with and without surfactant were applied to PMB-MNPs. Formerly, dynamic light scattering (DLS) and transmission electron microscopy (TEM) were examined on the samples to qualitatively show the dissociation effect of the surfactant. Considering the high potential interaction of LPS with HBsAg, the dissociation effects of 0.5 and 1.5% Tween 20 on the binary samples were assessed using immunoaffinity chromatography (IAC) as a quantification tool. The dissociation effect of Tween 20 substantially diminished the interaction, leading to a proportional increase of free LPS up to 66%. The synergetic effect of Tween 20 and privileged LAA was highly effective in eliminating more than 80% of LPS with a remarkable LPS clearance factor of 5.8 and a substantial protein recovery rate of 97%.

MALWARE IMAGE PREDICTION AND CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK

Without users' permission, malware software can infect computers or other devices. Through these loopholes, criminals commit a range of illegal and criminal offences that violate the legitimate rights and interests of the nation. Traditional malware categorization techniques fall into two categories: static analysis and dynamic analysis. It is usually not necessary to execute malware binary samples in order to perform static analysis techniques, and disassembly makes it simple to recover important data such as text lists, routines, and hash values. The static analysis methods offer a high accuracy rate and a simple operation with a low consumption time. Static analysis tools, however, are limited to analyzing malware binary samples at the surface level, where they are readily influenced by deformation and other means of confusion. Furthermore, it is challenging to identify and categorize unknown malware. Methods of dynamic analysis are not impacted by obfuscation and can operate in a virtual environment. It has the ability to recognize newly discovered malware samples and track the dynamic alterations of malware binary samples over time. Nevertheless, it's an extremely intricate and time-consuming process. Malware has become one of the largest security threats in recent years due to its rapid growth. But feature engineering makes it difficult to handle large amounts of malware and readily limits the use of standard machine learning methods for malware categorization. However, dynamic analysis methodologies are not appropriate for efficiently categorizing large amounts of malware due to their complexity and high cost. In light of this, we propose a novel static malware detection method based on the convolutional neural network (CNN) employed in this work. Unlike existing methods, we use the data enhancement method to fix the unbalanced datasets, turn every viral byte into a colour image, and provide a better design.

A novel cement-based interface functional material for application onto shotcrete-rock interface of tunnel in cold regions

In cold regions, the “natural weak zone”+“frost heave cracking” problems at the interface between shotcrete and rock will superimpose damage to the shotcrete-surrounding rock support system structure. However, there is no direct and effective technique to improve the bond strength and frost resistance of shotcrete for infrastructure such as tunnels in cold regions. Based on this, this study innovatively proposes the pretreatment technology of the interface between shotcrete and surrounding rock in tunnels in cold regions, and tries to investigate the fracture evolution of the binary and the distribution characteristics of the interface transition zone (ITZ) in cold regions under the action of interface functional material (IFM) by relying on the techniques of mechanical strength test, morphology analysis, and microstructure test. The study showed that: (1) the optimal mix ratio of IFM was designed as cement (10)+water (4)+calcium acrylate(1.5 %)+bamboo liquefied binder (4 %)+acrylate laminating adhesive (8 %)+ICA (2 %). At room temperature, the shear strength of the binary sample pretreated with the IFM was elevated by 1.56 MPa compared with that of the normal sample, and this increase could be raised to 1.64 MPa under freeze-thaw cycles (FTC). (2) As the freeze-thaw effect intensifies, the number of sandstone particles adhering to the failure surface of the binary increases correspondingly, and the morphology of the failure surface also becomes more undulating. This is due to the fact that after a certain FTC, more cracks are deflected towards the sandstone side due to the higher degradation of the sandstone compared to the ITZ. (3) Under FTC, the application of IFM will lead to an increase in the proportion of sandstone adhering to the failure surface and the fractal dimension of the failure surface, and this phenomenon becomes more pronounced with the intensification of FTC. (4) In the ITZ space, the hydration products and pore structure of the area closer to the sandstone are worse, the use of IFM can optimize this phenomenon. The new idea of utilizing the surrounding rock surface pretreatment technology to improve the bond strength and frost resistance of shotcrete proposed in this study has good application prospects in the construction of tunnels and other infrastructures in cold regions.

Room-Temperature Formation of CdTeSe Magic-Size Clusters from Oleate-Capped CdTe Precursor Compounds via CdSe Monomer Substitution.

We report the first room-temperature synthesis of ternary CdTeSe magic-size clusters (MSCs) that have mainly the surface ligand oleate (OA). The MSCs display sharp optical absorption peaking at ∼399 nm and are thus referred to as MSC-399. They are made from prenucleation-stage samples of binary CdTe and CdSe, which are prepared by two reactions in 1-octadecene (ODE) of cadmium oleate (Cd(OA)2) and tri-n-octylphosphine chalcogenide (ETOP, E = Te and Se) at 25 °C for 120 min and 80 °C for 15 min, respectively. When the two binary samples are mixed at room temperature and dispersed in a mixture of toluene (Tol) and octylamine (OTA), the CdTeSe MSC-399 develops. Also, when the CdSe sample is added to CdTe MSC-371 in a dispersion, the transformation from CdTe MSC-371 to CdTeSe MSC-399 is seen. We propose that the MSCs develop from their precursor compounds (PCs) that are relatively transparent in optical absorption, such as CdTeSe MSC-399 from CdTeSe PC-399 and CdTe MSC-371 from CdTe PC-371. The formation of CdTeSe PC-399 undergoes monomer substitution and not anion exchange, which is the reaction of CdTe PC-371 and the CdSe monomer to produce CdTeSe PC-399 and the CdTe monomer. Our study provides evidence of monomer substitution for the transformation from binary CdTe to ternary CdTeSe PCs.

Non-evolutionary effects on period change in Magellanic Cepheids

Context. Period change studies offer a novel way to probe the evolution and dynamics of Cepheids. While evolutionary period changes have been well studied both observationally and theoretically, non-evolutionary period changes lack a systematic and quantitative description. Here, we deal with one such aspect of non-evolutionary period changes related to a crucial property, namely, the binarity-based nature of a Cepheid. With the advent of long-term photometry surveys covering Magellanic fields, the census of classical Cepheids in binary (or multiple) systems outside the Milky Way is timely. This may have implications for crucial aspects such as the period-luminosity relationship calibrations and our understanding of the nature of Cepheid companions. Aims. The overall objective is to have a quantitative understanding of the full picture of non-evolutionary period changes in Cepheids to develop a formalism to disentangle it from the secular evolutionary period change. In the first paper in the series, we aim to conduct a systematic search for non-evolutionary period changes to look for Cepheids in likely binary configurations and quantify their incidence rates in the Magellanic Clouds. Methods. We collected more than a decade-long time-series photometry from the publicly available, Optical Gravitational Lensing Experiment (OGLE) survey, with more than 7200 Cepheids altogether from the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC). Our sample contains both fundamental-mode and first-overtone mode Cepheids. Then, we calculate d the observed minus calculated (O–C) diagrams to reveal the light-travel time effect (LTTE). Finally, we calculated the minimum companion masses of the Cepheids and compared them with the predictions from Cepheid population synthesis results. Results. In our search, out of an overall sample of more than 7200 Cepheids, we found 52 candidate Cepheid binary systems in the LMC (30 fundamental and 22 first-overtone mode) and 145 in the SMC (85 fundamental and 60 first-overtone mode). The majority of the sample is characterized by orbital periods of 2000–4000 d and eccentricities of 0.2–0.5. Moreover, we report two candidates in each galaxy with the Cepheid likely existing with a giant companion. The incidence rate ratio for SMC to LMC calculated from our sample is in agreement with binary Cepheid population synthesis predictions. Conclusions. In our attempt to quantify the non-evolutionary period change connected with the LTTE, our systematic search has enriched the Cepheid binary sample by a factor of about 2 in both galaxies. The future spectroscopic follow-up can confirm the binarity nature of our sample and constrain the orbital parameters.

Thermodiffusion, diffusion and Soret coefficients of binary polymeric mixtures in toluene and cyclohexane

Abstract We present the results of experimental study on measuring the thermodiffusion, molecular diffusion and Soret coefficients of polystyrene (4,880 g/mol) in the pure solvents toluene and cyclohexane at 298 K and atmospheric pressure. The experiments have been carried out for a wide range of concentrations, starting from the diluted state with 2 % polystyrene mass fraction (proposed in the DCMIX4 project) up to the semidilute regime of 20 % polystyrene mass fraction. In addition, we present a complete characterisation of the thermophysical properties of the analysed mixtures. Thermodiffusion, molecular diffusion and Soret coefficients of binary polymeric samples have been measured by combining the traditional thermogravitational column technique, the thermogravitational microcolumn and the optical beam deflection method. In toluene, the obtained experimental results are consistent with literature, showing that the magnitude of the mass transport thermoproperties decrease significantly with increasing polystyrene concentration, which is a first indication of an approaching glass transition in the concentrated regime. The results for thermodiffusion and molecular diffusion coefficients in cyclohexane as a function of concentration exhibit a similar trend. Nevertheless, the Soret coefficient seems to show an opposite tendency for the two solvents, increasing in magnitude for cyclohexane, at least up to the analysed polystyrene concentration.

Infrared Photodissociation Spectroscopy of Water-Tagged Ions with a Widely Tunable Quantum Cascade Laser for Planetary Science Applications.

This work presents a benchtop method for collecting the room temperature gas phase infrared (IR) action spectra of protonated amino acids and their isomers. The adopted setup uses a minimally modified commercial electrospray ionization linear ion trap mass spectrometer (ESI-LIT-MS) coupled to a broadband continuous wave (cw) quantum cascade laser (QCL) source. This approach leverages messenger assisted action spectroscopic techniques using water-tagged molecular ions with complex formation, irradiation, and subsequent analysis, all taking place within a single linear ion trap stage. This configuration thus circumvents the use of multiple mass selection and analysis stages, cryogenic buffer cells, and complex high-power laser systems typically called upon to execute these techniques. The benchtop action spectrometer is used to collect the 935-1600 cm-1 (6.2-10.7 μm) IR action spectrum of a collection of amino acids and a dipeptide with results cross referenced against literature examples obtained with a free electron laser source. Recorded IR spectra are used for the analysis of binary mixture samples composed of constitutional isomers α-alanine and β-alanine with ratios determined to ∼4% measurement uncertainty without the aid of a front-end separation stage. This turn-key QCL-based approach is a major step in showing the viability of tag-based action spectroscopic techniques for use in future in situ planetary science sensors and general analytical applications.

Investigating Mass Segregation of the Binary Stars in the Open Cluster NGC 6819

We search for mass segregation in the intermediate-aged open cluster NGC 6819 within a carefully identified sample of probable cluster members. Using photometry from Gaia, Pan-STARRS, and the Two Micron All Sky Survey as inputs for a Bayesian statistics software suite, BASE-9, we identify a rich population of (photometric) binaries and derive posterior distributions for the cluster age, distance, metallicity, and reddening, as well as star-by-star photometric membership probabilities, masses, and mass ratios (for binaries). Within our entire sample, we identify 2632 cluster members and 777 binaries. We then select a main-sequence “primary sample” with 14.85 <G < 19.5, containing 1342 cluster members and 250 binaries with mass ratios q > 0.5, to investigate mass segregation. Within this primary sample, we find the binary radial distribution is significantly shifted toward the cluster center as compared to the single stars, resulting in a binary fraction that increases significantly toward the cluster core. Furthermore, we find that within the binary sample, more massive binaries have more centrally concentrated radial distributions than less massive binaries. The same is true for the single stars. We verify the expectation of mass segregation for this stellar sample in NGC 6819 through both relaxation time arguments and by investigating a sophisticated N-body model of the cluster. Importantly, this is the first study to investigate mass segregation of the binaries in the open cluster NGC 6819.

Evaluation of different operating parameters in the photocatalytic oxidative desulfurization process to degrade dibenzothiophene sulfur compound in the presence of BiOI/CeO2/NaY zeolite heterojunction

In this study, BiOI/CeO2/NaY zeolite composite was applied to remove sulfur compounds in gasoline model fuel to reduce environmental pollution and increase clean fuel production. First, the parent NaY zeolite was transformed into mesoporous zeolite during the sequential dealumination-desilication process. Then, the binary structures of BiOI/NaY zeolite and BiOI/Meso NaY zeolite were successfully synthesized by hydrothermal method. Next, in order to increase the photocatalytic performance in the desulfurization process, cerium ion was impregnated on the synthesized binary samples, so that the ternary combination of BiOI/CeO2/Meso NaY zeolite was investigated for the first time in the application of photocatalytic oxidative desulfurization in the presence of air as an oxidant. Furthermore, XRD, XPS, FT-IR, FE-SEM, EDS-MAP, TEM, BET, UV–vis DRS, PL and EIS analyzes were used to identify the structure, evaluate the compounds and determine the performance of the synthesized samples. In addition, the effect of operational parameters in the photocatalytic oxidative desulfurization process including photocatalyst dosage, model fuel concentration, reaction temperature, type of oxidant, type of extractant, the volume ratio of model fuel to extractant, different sulfur compounds, reusability and scavengers were assessed. The results showed that the BiOI/CeO2/Meso NaY zeolite ternary sample with an amount of 50 mg at the temperature of 25 ℃ and the concentration of 500 ppm of the sulfur compound was able to eliminate 98.8 % of the pollutant in 30 min. Moreover, the effect of the active species in the process was evaluated using various electron-removing agents to remove the sulfur compound from the fuel on an industrial scale.