Development of transferable interaction potentials for water. V. Extension of the flexible, polarizable, Thole-type model potential (TTM3-F, v. 3.0) to describe the vibrational spectra of water clusters and liquid water

We present a new parametrization of the flexible, polarizable Thole-type model for water [J. Chem. Phys. 116, 5115 (2002); J. Phys. Chem. A 110, 4100 (2006)], with emphasis in describing the vibrational spectra of both water clusters and liquid water. The new model is able to produce results of similar quality with the previous versions for the structures and energetics of water clusters as well as structural and thermodynamic properties of liquid water evaluated with classical and converged quantum statistical mechanical atomistic simulations. At the same time it yields accurate redshifts for the OH vibrational stretches of both water clusters and liquid water.     

Shrinking droplets in electrospray ionization and their influence on chemical equilibria

We investigated how chemical equilibria are affected by the electrospray process, using simultaneous in situ measurements by laser-induced fluorescence (LIF) and phase Doppler anemometry (PDA). The motivation for this study was the increasing number of publications in which electrospray ionization mass spectrometry is used for binding constant determination. The PDA was used to monitor droplet size and velocity, whereas LIF was used to monitor fluorescent analytes within the electrospray droplets. Using acetonitrile as solvent, we found an average initial droplet diameter of 10 microm in the electrospray. The PDA allowed us to follow the evolution of these droplets down to a size of 1 microm. Rhodamine B-sulfonylchloride was used as a fluorescent analyte within the electrospray. By spatially resolved LIF it was possible to probe the dimerization equilibrium of this dye. Measurements at different spray positions showed no influence of the decreasing droplet size on the monomer-dimer equilibrium. However, with the fluorescent dye pair DCM and oxazine 1 it was shown that a concentration increase does occur within electrosprayed droplets, using fluorescence resonance energy transfer as a probe for the average pair distance.     

A fully validated method for the determination of lacosamide in human plasma using gas chromatography with mass spectrometry: Application for therapeutic drug monitoring

A simple gas chromatographic method with mass spectrometry detection was developed and validated for the determination of lacosamide in human plasma. Lacosamide and the internal standard, levetiracetam‐d₆, were extracted from 200 μL plasma, by a solid‐phase extraction through HF Bond Elut C₁₈ columns, and derivatized using N‐methyl‐N‐tert‐butyldimethylsilyltrifluoroacetamide with 1% tert‐butyldimethylsilylchloride in acetonitrile. The limit of quantification was found to be 0.20 μg/mL and the assay was linear up to 20.0 μg/mL with correlation coefficient ≥0.994. The intra‐ and interday precision values were <4.1% in terms of relative standard deviation (%) and the values of intra‐ and interday accuracy were found to be within –7.2 and 5.3% in terms of relative error (%). Absolute recovery of the method for lacosamide was determined at three concentration levels and ranged from 92.5 to 97.6%. The developed method uses small volumes of plasma and proved to be simple, rapid, and sensitive for the determination of lacosamide in plasma. This method can be used in routine every day analysis of plasma samples obtained from patients who follow respective antiepileptic treatment and for the investigation of clinical and forensic cases where lacosamide is involved.     

Palladium embedded in SnO2 enhances the sensitivity of flame-made chemoresistive gas sensors

Microchimica Acta - This review (with 187 refs.) summarizes the progress that has been made in the design of lateral flow biosensors (LFBs) based on the use of micro- and nano-materials. Following...     

Some Parameterized Quantum Midpoint and Quantum Trapezoid Type Inequalities for Convex Functions with Applications

Quantum information theory, an interdisciplinary field that includes computer science, information theory, philosophy, cryptography, and entropy, has various applications for quantum calculus. Inequalities and entropy functions have a strong association with convex functions. In this study, we prove quantum midpoint type inequalities, quantum trapezoidal type inequalities, and the quantum Simpson’s type inequality for differentiable convex functions using a new parameterized q-integral equality. The newly formed inequalities are also proven to be generalizations of previously existing inequities. Finally, using the newly established inequalities, we present some applications for quadrature formulas.     

Existence and Controllability Results for First-and Second-Order Functional Semilinear Differential Inclusions with Nonlocal Conditions

In this paper, we prove existence and controllability results for first- and second-order semilinear differential inclusions in Banach spaces with nonlocal conditions.     

Fractional order nonlinear mixed coupled systems with coupled integro-differential boundary conditions

We study the existence and uniqueness of solutions for a class of coupled fractional differential equations involving both Riemann-Liouville and Caputo fractional derivatives, and coupled integro-differential boundary conditions. We derive the desired results with the aid of modern methods of functional analysis. An example illustrating the abstract results is also presented.     

Scaling-up the Production of Nanosized SiO2-particles in a Double Diffusion Flame Aerosol Reactor

Synthesis of nanophase silica (SiO₂) from hexamethyldisiloxane (HMDS) oxidation in a co-flow diffusion flame reactor at atmospheric pressure is investigated focusing on high production rates of powder. A new experimental set-up is introduced, including a diffusion burner which is operated with a ring-shape double diffusion flame. Significantly high HMDS concentrations are used resulting in SiO₂ production rates of up to 130g/h. Deposition of silica powder on the burner face is eliminated by the design of a special diffusion burner and higher collection rates are achieved using a baghouse filter. The specific surface area and the product powder composition are analyzed. Carbon black coated silica particles were produced at high production rates (130g/h) at low oxygen flow rates or using a mixture of nitrogen and oxygen as oxidant. The size of the product particles was controlled in the range of 15–170nm.     

The Effect of Hydrolysis Temperature on Synthesis of Bimodally Nanostructured Porous Titania

Bimodally porous (2–4 and 20–100 nm) titania powders were prepared by hydrolysis of titanium tetraisopropoxide (TTIP), and the effect of hydrolysis temperature on the phase transformation and pore structure was investigated. The phase transformation was slightly retarded with increasing hydrolysis temperature, when the initial water concentration was small. The evolution of particle phase composition from amorphous to crystalline anatase and rutile was largely proportional to the calcination temperature and the initial water concentration. The pore size distribution was bimodal with fine intra-particle pores (2–4 nm in diameter) and larger inter-particle pores (20–100 nm). The intra-particle pores decreased in diameter at the hydrolysis temperature of 20°C. The specific surface area (SSA) of the dried powders ranged from 253 to 587 m²/g and the highest SSA was obtained at the hydrolysis temperature of 20°C.     

Explainable AI: A Review of Machine Learning Interpretability Methods

Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption, with machine learning systems demonstrating superhuman performance in a significant number of tasks. However, this surge in performance, has often been achieved through increased model complexity, turning such systems into “black box” approaches and causing uncertainty regarding the way they operate and, ultimately, the way that they come to decisions. This ambiguity has made it problematic for machine learning systems to be adopted in sensitive yet critical domains, where their value could be immense, such as healthcare. As a result, scientific interest in the field of Explainable Artificial Intelligence (XAI), a field that is concerned with the development of new methods that explain and interpret machine learning models, has been tremendously reignited over recent years. This study focuses on machine learning interpretability methods; more specifically, a literature review and taxonomy of these methods are presented, as well as links to their programming implementations, in the hope that this survey would serve as a reference point for both theorists and practitioners.