Measurement of the thermal conductivity of MWCNT-CuO/water hybrid nanofluid using artificial neural networks (ANNs)

Journal of Thermal Analysis and Calorimetry - In this paper, artificial neural networks (ANNs) are developed to predict the thermal conductivity ( $$k_{\text{nf}}$$ ) of multi-walled carbon...     

From Oncogenic Signaling Pathways to Single-Cell Sequencing of Immune Cells: Changing the Landscape of Cancer Immunotherapy

Over the past decade, there have been remarkable advances in understanding the signaling pathways involved in cancer development. It is well-established that cancer is caused by the dysregulation of cellular pathways involved in proliferation, cell cycle, apoptosis, cell metabolism, migration, cell polarity, and differentiation. Besides, growing evidence indicates that extracellular matrix signaling, cell surface proteoglycans, and angiogenesis can contribute to cancer development. Given the genetic instability and vast intra-tumoral heterogeneity revealed by the single-cell sequencing of tumoral cells, the current approaches cannot eliminate the mutating cancer cells. Besides, the polyclonal expansion of tumor-infiltrated lymphocytes in response to tumoral neoantigens cannot elicit anti-tumoral immune responses due to the immunosuppressive tumor microenvironment. Nevertheless, the data from the single-cell sequencing of immune cells can provide valuable insights regarding the expression of inhibitory immune checkpoints/related signaling factors in immune cells, which can be used to select immune checkpoint inhibitors and adjust their dosage. Indeed, the integration of the data obtained from the single-cell sequencing of immune cells with immune checkpoint inhibitors can increase the response rate of immune checkpoint inhibitors, decrease the immune-related adverse events, and facilitate tumoral cell elimination. This study aims to review key pathways involved in tumor development and shed light on single-cell sequencing. It also intends to address the shortcomings of immune checkpoint inhibitors, i.e., their varied response rates among cancer patients and increased risk of autoimmunity development, via applying the data from the single-cell sequencing of immune cells.     

Phase diagrams for the system water/butyric acid/propylene carbonate at <Emphasis Type="Italic">T</Emphasis> = 293.2–313.2 K and <Emphasis Type="Italic">p</Emphasis> = 101.3 kPa

Phase diagrams for the system water/butyric acid/propylene carbonate were plotted at T = 293.2, 303.2, 313.2 K and p = 101.3 kPa. Acidimetric titration and refractive index methods were used to determine tie-line data. Solubility data revealed that the studied system exhibits type-1 behavior of liquid–liquid equilibrium. The experimental data were regressed and acceptably correlated using the UNIQUAC and NRTL models. As a result, propylene carbonate is a suitable separating agent for aqueous mixture of butyric acid.     

Palladium‐mediated Cleavage of S–C Bonds: Preparation and Characterization of Palladium(II) Complexes of 2, 6‐Diformyl‐4‐tert‐butylthiophenol Dioxime

The synthesis of air‐sensitive 2, 6‐diformyl‐4‐tert‐butylthiophenol dioxime H₃L3 was achieved by a Pd‐mediated S–C cleavage of the corresponding S‐tert‐butyl protected thioether. The novel ligand forms a dinuclear, neutral Pd^II₂ complex, which is stabilized by two N ··· HO hydrogen bonds to give a pseudo‐macrocyclic structure. The crystal structure of a Pd^II complex of an oxidized isothiazole derivative of H₃L3 is also reported.     

The effect of wavy leading edges on aerofoil–gust interaction noise

High-order accurate numerical simulations are performed to investigate the effects of wavy leading edges (WLEs) on aerofoil–gust interaction (AGI) noise. The present study is based on periodic velocity disturbances predominantly in streamwise and vertical directions that are mainly responsible for the surface pressure fluctuation of an aerofoil. In general, the present results show that WLEs lead to reduced AGI noise. It is found that the ratio of the wavy leading-edge peak-to-peak amplitude (LEA) to the longitudinal wavelength of the incident gust (_λg${\lambda }_g$) is the most important factor for the reduction of AGI noise. It is observed that there exists a tendency that the reduction of AGI noise increases with LEA/_λg$\mathrm{LEA}/{\lambda }_g$ and the noise reduction is significant for LEA/_λg≥0.3$\mathrm{LEA}/{\lambda }_g\ge 0.3$. The present results also suggest that any two different cases with the same LEA/_λg$\mathrm{LEA}/{\lambda }_g$ lead to a strong similarity in their profiles of noise reduction relative to the straight leading-edge case. The wavelength of wavy leading edges (LEW), however, shows minor influence on the reduction of AGI noise under the present gust profiles used. Nevertheless, the present results show that a meaningful improvement in noise reduction may be achieved when 1.0≤LEW/_λg≤1.5$1.0\le \mathrm{LEW}/{\lambda }_g\le 1.5$. In addition, it is found that the beneficial effects of WLEs are maintained for various flow incidence angles and aerofoil thicknesses. Also, the WLEs remain effective for gust profiles containing multiple frequency components. It is discovered in this paper that WLEs result in incoherent response time to the incident gust across the span, which results in a decreased level of surface pressure fluctuations, hence a reduced level of AGI noise.     

Effect of the “inversion” of a scattering medium in layers of close-packed titanium dioxide nanoparticles

The features of the behavior of the diffuse transmission of layers of close-packed titanium dioxide nanoparticles in the visible and near infrared spectral ranges with an increase in the volume fraction f of the particles in a layer have been analyzed. It has been found that an increase in f for layers of small particles (about 25 nm) with a relatively low volume fraction (0.20–0.25) is accompanied by the expected decrease in diffuse transmission. At the same time, an increase in f for layers of large particles (about 100 nm) with a volume fraction of 0.45–0.50 results in a strong increase in transmission. The described phenomenon has been interpreted in terms of the concepts of inverse scattering systems, where the main scattering centers are air nanocavities in a TiO₂ matrix rather than TiO₂ particles in an air matrix.     

Visualizing Acidophilic Microorganisms in Biofilm Communities Using Acid Stable Fluorescence Dyes

Bacteria in acidophilic biofilm communities, i.e. acid streamers and snottites, obtained from a subsurface mine in Königstein were visualized by fluorescence microscopy using four new fluorescent dyes (DY-601XL, V07-04118, V07-04146, DY-613). The pH of the bulk solution in which these bacteria thrive was pH 2.6 to 2.9. The new fluorescent dyes were all able to clearly stain and microscopically visualize in-situ the bacteria within the biofilm community without changing pH or background ion concentration. The commonly used fluorescent dyes DAPI and SYTO 59 were also applied for comparison. Both dyes, however, were not able to visualize any bacteria in-situ, since they were not stable under the very acid conditions. In addition, dye V07-04118 and dye DY-613 also possess the ability to stain larger cells which were presumably eukaryotic origin and may be attributed to yeast cells or amoeba-like cells. PCR analyses have shown that the dominant bacterial species in these acidophilic biofilm communities was a gram negative bacterium of the species Ferrovum myxofaciens. The presented four new dyes are ideal for in-situ investigations of microorganisms occurring in very acid conditions, e.g. in acidophilic biofilm communities when in parallel information on pH sensitive incorporated fluorescent heavy metals should be acquired.     

1‐Methoxyhexane‐3‐thiol,a Powerful Odorant of Clary Sage (Salvia sclarea L.)

The peculiar and highly diffusive odor signal of flowering clary‐sage plants (Salvia sclarea L.) was identified to derive from trace amounts of 1‐methoxyhexane‐3‐thiol ( 1 ) by mass‐spectrometry analysis and confirmed by comparison with synthetic racemic thiol (±)‐ 1 . The enantiomers (S)‐ and (R)‐ 1 were prepared by enantioselective synthesis, and the absolute configuration of (S)‐ 1 was fully corroborated by X‐ray‐diffraction analysis of the crystalline thioester (1′S,1S)‐ 2 . Compound (S)‐ 1 is one of the most powerful odorants known, with a detection threshold of 0.04⋅10⁻³ ng/l air, and is, with its herbaceous‐green, alliaceous, and perspiration profile, key to the fragrance of clary‐sage flowers and of the freshly distilled essential oil. As a consequence of its unique odor, 1 was also suspected to be part of the volatiles of a Ruta species where it was subsequently identified together with its homologue, 1‐methoxyheptane‐3‐thiol ( 3 ), 1‐methoxy‐4‐methylpentane‐3‐thiol ( 4 ), and the known 4‐methoxy‐2‐methylbutane‐2‐thiol ( 5 ). The syntheses of (±)‐ 3 and (±)‐ 4 as well as of the enantiomer (R)‐ 4 are described. In both natural fractions, the ratio (S)‐ 1 /(R)‐ 1 was slightly in favor of the (S)‐enantiomer. Natural 4 has (R)‐configuration.     

Training Multilayer Perceptron with Genetic Algorithms and Particle Swarm Optimization for Modeling Stock Price Index Prediction

Predicting stock market (SM) trends is an issue of great interest among researchers, investors and traders since the successful prediction of SMs’ direction may promise various benefits. Because of the fairly nonlinear nature of the historical data, accurate estimation of the SM direction is a rather challenging issue. The aim of this study is to present a novel machine learning (ML) model to forecast the movement of the Borsa Istanbul (BIST) 100 index. Modeling was performed by multilayer perceptron–genetic algorithms (MLP–GA) and multilayer perceptron–particle swarm optimization (MLP–PSO) in two scenarios considering Tanh (x) and the default Gaussian function as the output function. The historical financial time series data utilized in this research is from 1996 to 2020, consisting of nine technical indicators. Results are assessed using Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and correlation coefficient values to compare the accuracy and performance of the developed models. Based on the results, the involvement of the Tanh (x) as the output function, improved the accuracy of models compared with the default Gaussian function, significantly. MLP–PSO with population size 125, followed by MLP–GA with population size 50, provided higher accuracy for testing, reporting RMSE of 0.732583 and 0.733063, MAPE of 28.16%, 29.09% and correlation coefficient of 0.694 and 0.695, respectively. According to the results, using the hybrid ML method could successfully improve the prediction accuracy.     

Third-Order Optical Nonlinearity in Two-Dimensional Transition Metal Dichalcogenides

We present a detailed calculation of the linear and nonlinear optical response of four types of monolayer twodimensional (2D) transition-metal dichalcogenides (TMDCs), having the formula MX2 with M=Mo, W and X=S, Se.The calculations are based on 6-band tight-binding model of TMDCs, and then performing a semi-classical perturbation analysis of response functions. We numerically calculate the linearχ(1)μν(-ω;ω) and nonlinear surface susceptibility tensorsχ(3)μνζη(-ωΣ;ωr,ωs,ωt) withωΣ=ωr+ωs+ωt. Both non-degenerate and degenerate cases are studied for thirdharmonic generation and nonlinear refractive index, respectively. Computational results obtained with no external fitting parameters are discussed regarding two recent reported experiments on Mo S2, and thus we can confirm the extraordinarily strong optical nonlinearity of TMDCs. As a possible application, we demonstrate generation of aπ/4-rotated squeezed state by means of nonlinear response of TMDCs, in a silica micro-disk resonator covered with the 2D material. Our proposed method will enable accurate calculations of nonlinear optical response, such as four-wave mixing and highharmonic generation in 2D materials and their heterostructures, thus enabling study of novel functionalities of 2D photonic integrated circuits.