Abstract: We report here the efficacy of surface-enhanced Raman spectroscopy (SERS) measurements as a probe for molecular orientation. 4-Aminobenzoic acid (PABA) on a surface consisting of silver (Ag) nanoparticles (NPs) is investigated. We find that the orientation of the PABA molecule on the SERS substrate is estimated based on the relative change in the magnitude of the C-H stretching bands on the SERS substrate, and it is found that the molecule assumes a horizontal orientation on the Ag-NP surface. The strong molecule-metal interaction is determined by an abnormal enhanced SERS band appearing at 980 cm(-1), and the peak is assigned to an out-of-plane amine vibrational mode, which is supported by our ab initio calculations. DFT-based Raman activity calculations corroborate the SERS results, revealing that (i) the PABA molecule attaches to the surface of Ag-NPs with its alpha dimers rather than single-molecule binding and (ii) the molecule preserves its alpha dimers in an aqueous environment. Our results demonstrate that SERS can be used to gain deeper insights into the molecular orientation on metal nanoparticle surfaces.

Abstract: Purpose This paper aimed to investigate the determinants of loans and advances from commercial banks in the case of Ethiopian private commercial banks. Design/methodology/approach The study randomly selected seven commercial banks to represent the population stratified on their asset, deposit and paid-up capital amounts. The study utilized an unbalanced panel data model as each bank started operation at a different period of time and considered the period 1995-2016 for secondary details. Findings The findings showed that the deposit size, credit risk, portfolio investment, average lending rate, real gross domestic product (GDP) and inflation rate had significant and optimistic effects on the lending and advancement of private commercial banks. On the contrary, liquidity ratio had significant and negative effects on private commercial bank loans and advances. Finally, the study forwarded a feasible recommendation for concerned organs to focus on deposit size, credit risk, portfolio investment, average lending rate, real GDP, inflation rate and liquidity ratio. The results of this study will help banking industry policymakers and planners understand how to minimize inflation and unemployment by improving development and sustainable economic growth. Originality/value The findings of this study can also affect the general attitudes of a society by increasing knowledge and improve the quality of life for the general public.

Abstract: The combination of energy-dispersive X-ray spectroscopy (EDX) and electron tomography is a powerful approach to retrieve the 3D elemental distribution in nanomaterials, providing an unprecedented level of information for complex, multi-component systems, such as semiconductor devices, as well as catalytic and plasmonic nanoparticles. Unfortunately, the applicability of EDX tomography is severely limited because of extremely long acquisition times and high electron irradiation doses required to obtain 3D EDX reconstructions with an adequate signal-to-noise ratio. One possibility to address this limitation is intelligent denoising of experimental data using prior expectations about the objects of interest. Herein, this approach is followed using the deep learning methodology, which currently demonstrates state-of-the-art performance for an increasing number of data processing problems. Design choices for the denoising approach and training data are discussed with a focus on nanoparticle-like objects and extremely noisy signals typical for EDX experiments. Quantitative analysis of the proposed method demonstrates its significantly enhanced performance in comparison to classical denoising approaches. This allows for improving the tradeoff between the reconstruction quality, acquisition time and radiation dose for EDX tomography. The proposed method is therefore especially beneficial for the 3D EDX investigation of electron beam-sensitive materials and studies of nanoparticle transformations.

Abstract: Cholesterol plays a crucial role in major cardiovascular and neurodegenerative diseases, including Alzheimer’s disease and rare genetic disorders showing altered cholesterol metabolism. Cyclodextrins (CDs) have shown promising therapeutic efficacy based on their capacity to sequester and mobilise cholesterol. However, the administration of monomeric CDs suffers from several drawbacks due to their lack of specificity and poor pharmacokinetics. We present core-shell superparamagnetic iron oxide nanoparticles (SPIONs) functionalised with CDs appended to poly (2-methyl-2-oxazoline) polymers grafted in a dense brush to the iron oxide core. The CD-decorated nanoparticles (CySPIONs) are designed so that the macrocycle is specifically cleaved off the nanoparticle’s shell at a slightly acidic pH. In the intended use, free monomeric CDs will then mobilise cholesterol out of the lysosome to the cytosol and beyond through the formation of an inclusion complex. Hence, its suitability as a therapeutic platform to remove cholesterol in the lysosomal compartment. Synthesis and full characterization of the polymer as well as of the core-shell SPION are presented. Cholesterol-binding activity is shown through an enzymatic assay.

Abstract: We calculate the Curie temperature of layered ferromagnets, chromium tri-iodide (CrI3), chromium tri-bromide (CrBr3), chromium germanium tri-telluride (CrGeTe3), and the Ned temperature of a layered antiferromagnet iron di-chloride (FeCl2), using first-principles density functional theory calculations and Monte Carlo simulations. We develop a computational method to model the magnetic interactions in layered magnetic materials and calculate their critical temperature. We provide a unified method to obtain the magnetic exchange parameters (J) for an effective Heisenberg Hamiltonian from first principles, taking into account both the magnetic ansiotropy as well as the out-of-plane interactions. We obtain the magnetic phase change behavior, in particular the critical temperature, from the susceptibility and the specific-heat, calculated using the three-dimensional Monte Carlo (METROPOLIS) algorithm. The calculated Curie temperatures for ferromagnetic materials (CrI3, CrBr3, and CrGeTe3), match well with experimental values. We show that the interlayer interaction in bulk CrI3 with R (3) over bar stacking is significantly stronger than the C2/m stacking, in line with experimental observations. We show that the strong interlayer interaction in R (3) over bar CrI3 results in a competition between the in-plane and the out-of-plane magnetic easy axes. Finally, we calculate the Ned temperature of FeCl2 to be 47 +/- 8 K and show that the magnetic phase transition in FeCl2 occurs in two steps with a high-temperature intralayer ferromagnetic phase transition and a low-temperature interlayer antiferromagnetic phase transition.

Abstract: Multiple myeloma (MM) is a hematological malignancy characterized by plasma cells’ uncontrolled growth. The major barrier in treating MM is the occurrence of primary and acquired therapy resistance to anticancer drugs. Often, this therapy resistance is associated with constitutive hyperactivation of tyrosine kinase signaling. Novel covalent kinase inhibitors, such as the clinically approved BTK inhibitor ibrutinib (IBR) and the preclinical phytochemical withaferin A (WA), have, therefore, gained pharmaceutical interest. Remarkably, WA is more effective than IBR in killing BTK-overexpressing glucocorticoid (GC)-resistant MM1R cells. To further characterize the kinase inhibitor profiles of WA and IBR in GC-resistant MM cells, we applied phosphopeptidome- and transcriptome-specific tyrosine kinome profiling. In contrast to IBR, WA was found to reverse BTK overexpression in GC-resistant MM1R cells. Furthermore, WA-induced cell death involves covalent cysteine targeting of Hinge-6 domain type tyrosine kinases of the kinase cysteinome classification, including inhibition of the hyperactivated BTK. Covalent interaction between WA and BTK could further be confirmed by biotin-based affinity purification and confocal microscopy. Similarly, molecular modeling suggests WA preferably targets conserved cysteines in the Hinge-6 region of the kinase cysteinome classification, favoring inhibition of multiple B-cell receptors (BCR) family kinases. Altogether, we show that WA’s promiscuous inhibition of multiple BTK family tyrosine kinases represents a highly effective strategy to overcome GC-therapy resistance in MM.

Abstract: We introduce single-shot x-ray tomography that aims to estimate the target image from a single cone-beam projection measurement. This linear inverse problem is extremely under-determined since the measurements are far fewer than the number of unknowns. Moreover, it is more challenging than conventional tomography, where a sufficiently large number of projection angles forms the measurements, allowing for a simple inversion process. However, single-shot tomography becomes less severe if the target image is only composed of known shapes. This paper restricts analysis to target image function that can be decomposed into known compactly supported non-negative-valued functions termed shapes. Hence, the shape prior transforms a linear ill-posed image estimation problem to a non-linear problem of estimating the roto-translations of the shapes. We circumvent the non-linearity by using a dictionary of possible roto-translations of the shapes. We propose a convex program CoShaRP, to recover the dictionary coefficients successfully. CoShaRP relies on simplex-type constraints and can be solved quickly using a primal-dual algorithm. The numerical experiments show that CoShaRP recovers shape stably from moderately noisy measurements.

Abstract: Photocatalytic transformation of biomass into value-added chemicals coupled with co-production of hydrogen provides an explicit route to trap sunlight into the chemical bonds. Here, we demonstrate a rational design of Zn1-xCdxS solidsolution homojunction photocatalyst with a pseudo-periodic cubic zinc blende (ZB) and hexagonal wurtzite (WZ) structure for efficient glucose conversion to simultaneously produce hydrogen and lactic acid. The optimized Zn0.6Cd0.4S catalyst consists of a twinning superlattice, has a tuned bandgap, and displays excellent efficiency with respect to hydrogen generation (690 +/- 27.6 mu mol.h(-1).g(cat).(-1)), glucose conversion (similar to 90%), and lactic acid selectivity (similar to 87%) without any co-catalyst under visible light irradiation. The periodic WZ/ZB phase in twinning superlattice facilitates better charge separation, while superoxide radical (center dot O-2(-)) and photogenerated holes drive the glucose transformation and water oxidation reactions, respectively. This work demonstrates that rational photocatalyst design could realize an efficient and concomitant production of hydrogen and value-added chemicals from glucose photocatalysis.

Abstract: To gain full control over the growth of carbon nanotubes (CNTs) using plasma-enhanced chemical vapor deposition (PECVD), a thorough understanding of the underlying plasma-catalyst mechanisms is required. Oxygen-containing species are often used as or added to the growth precursor gas, but these species also yield various radicals and ions, which may simultaneously etch the CNT during the growth. At present, the effect of these reactive species on the growth onset has not yet been thoroughly investigated. We here report on the etching mechanism of incipient CNT structures from OH and O radicals as derived from combined (reactive) molecular dynamics (MD) and force-bias Monte Carlo (tfMC) simulations. Our results indicate that the oxygen-containing radicals initiate a dissociation process. In particular, we show how the oxygen species weaken the interaction between the CNT and the nanocluster. As a result of this weakened interaction, the CNT closes off and dissociates from the cluster in the form of a fullerene. Beyond the specific systems studied in this work, these results are generically important in the context of PECVD-based growth of CNTs using oxygen-containing precursors.

Abstract: The characteristics of confined magnetoelastic waves in nanoscale ferromagnetic magnetostrictive waveguides have been investigated by a combination of analytical and numerical calculations. The presence of both magnetostriction and inverse magnetostriction leads to the coupling between confined spin waves and elastic Lamb waves. Numerical simulations of the coupled system have been used to extract the dispersion relations of the magnetoelastic waves as well as their mode profiles.

Abstract: Direct experimental measurement of thermal expansion coefficient without substrate effects is a challenging task for two-dimensional (2D) materials, and its accurate estimation with large-scale ab initio molecular dynamics is computationally very expensive. Machine learning-based interatomic potentials trained with ab initio data have been successfully used in molecular dynamics simulations to decrease the computational cost without compromising the accuracy. In this study, we investigated using Gaussian approximation potentials to reproduce the density functional theory-level accuracy for graphene within both lattice dynamical and molecular dynamical methods, and to extend their applicability to larger length and time scales. Two such potentials are considered, GAP17 and GAP20. GAP17, which was trained with pristine graphene structures, is found to give closer results to density functional theory calculations at different scales. Further vibrational and structural analyses verify that the same conclusions can be deduced with density functional theory level in terms of the reasoning of the thermal expansion behavior, and the negative thermal expansion behavior is associated with long-range out-of-plane phonon vibrations. Thus, it is argued that the enabled larger system sizes by machine learning potentials may even enhance the accuracy compared to small-size-limited ab initio molecular dynamics.

Abstract: Recent advances in the development of electron and X-ray detectors have opened up the possibility to detect single events from which its time of arrival can be determined with nanosecond resolution. This allows observing time correlations between electrons and X-rays in the transmission electron microscope. In this work, a novel setup is described which measures individual events using a silicon drift detector and digital pulse processor for the X-rays and a Timepix3 detector for the electrons. This setup enables recording time correlation between both event streams while at the same time preserving the complete conventional electron energy loss (EELS) and energy dispersive X-ray (EDX) signal. We show that the added coincidence information improves the sensitivity for detecting trace elements in a matrix as compared to conventional EELS and EDX. Furthermore, the method allows the determination of the collection efficiencies without the use of a reference sample and can subtract the background signal for EELS and EDX without any prior knowledge of the background shape and without pre-edge fitting region. We discuss limitations in time resolution arising due to specificities of the silicon drift detector and discuss ways to further improve this aspect.

Abstract: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with 85% of all lung cancer reported as NSCLC. Moreover, there are no effective treatments in advanced NSCLC. This study shows for the first time that oral administration of plasma-treated water (PTW) can cure advanced NSCLC. The cold plasma in water generates a cocktail of reactive species, and oral administration of this cocktail to mice showed no toxicities even at the highest dose of PTW, after a single dose and repeated doses for 28 d in mice. In vivo studies reveal that PTW showed favorable anticancer effects on chemo-resistant lung cancer, similarly to gefitinib treatment as a reference drug in a chemo-resistant NSCLC model. The anticancer activities of PTW seem to be involved in inhibiting proliferation and angiogenesis and enhancing apoptosis in the cancer cells. Interestingly, the PTW contributes to enhanced immune response and improved cachexia in the model.

Abstract: Wall paintings make up an important section of cultural heritage. They resemble time portals that can be used to travel back into the past and witness the life of our ancestors. In these paintings, the ancient artists depicted the different aspects of their life, such as cooking, baking, farming, manufacturing, as well as thoughts and beliefs. Unfortunately, wall paintings are susceptible to degradation over time in the form of the accumulations of dirt and deposits on the painted surfaces and loss of adhesion of the paint layers at the surface. Therefore, the removal of these deposits is one of the primary duties of conservator-restorers. Such operations are intended to restore the painted surface to a condition close enough to its original state. Since cleaning artworks may cause undesirable physicochemical alterations and is nonreversible, the proper cleaning procedure should be adopted. In this regard, numerous gels have been developed and exploited for the cleaning of various artwork surfaces. Lately, polyvinyl alcohol-borax (PVA-B) and agarose (AG) hydrogels have been widely employed as cleaning materials by conservator-restorers. However, both hydrogels have shown limitations in specific cleaning practices. In this work, we investigated a new double network hydrogel based on blending PVA-B and agarose to avoid the limitations posed by the constituting hydrogels. For this reason, a detailed characterization of the PVA–B/AG double network hydrogel was performed, including chemical structure, liquid phase retention, mechanical strength, rheological behavior, and self-healing behavior of various PVA-B/AG hydrogels. These new hydrogels revealed better properties than PVA-B and agarose hydrogels and obviated their limitations. A laboratory experiment on the removal of deteriorated Paraloid® B72 proved that the PVA-B/AG hydrogel loaded 10%/10% MEK/1-PeOH was able to remove these layers efficiently. Therefore, the hydrogel was tested on a wall painting from the Temple of Seti I in Abydos – Egypt. It removed the glossy/darkened consolidant from the wall painting and restored the original matt appearance of the painted surface. In another application on the painted ceiling of the same temple, the hydrogel was tested for removing thick soot layers. The hydrogel formulation (loaded with 5% ammonia, 0.3% ammonium carbonate, and 0.3% EDTA) removed these layers with no noticeable damage to the paint layers. In a wide-scale application of the hydrogel (loaded with 10% propylene carbonate), it removed a highly deteriorated varnish layer from a 19-c wall painting. All the traditional cleaning methods employed caused damage to the paint layers, proving that gel cleaning can be a safer cleaning alternative in some cases.

Abstract: We study the effect of structural inversion asymmetry, induced by the presence of substrates or by external electric fields, on charge transport in magnetic topological ultra-thin films. We consider general orientations of the magnetic impurities. Our results are based on the Boltzmann formalism along with a modified relaxation time scheme. We show that the structural inversion asymmetry enhances the charge transport anisotropy induced by the magnetic impurities and when only one conduction subband contributes to the charge transport a dissipationless charge current is accessible. We demonstrate how a substrate or gate voltage can control the effect of the magnetic impurities on the charge transport, and how this depends on the orientation of the magnetic impurities.