Search Results (76)

Background/Objectives: In the last few decades, the dengue virus, a prevalent flavivirus, has demonstrated various epidemiological, economic, and health impacts around the world. Dengue virus serotype 2 (DENV2) plays a vital role in dengue-associated mortality. The RNA-dependent RNA polymerase (RdRp) of DENV2 is a charming druggable target owing to its crucial function in viral reproduction. In recent years, streptomycetes natural products (NPs) have attracted considerable attention as a potential source of antiviral drugs. Methods: Seeking prospective inhibitors that inhibit the DENV2 RdRp allosteric site, in silico mining of the Streptome database was executed. AutoDock4.2.6 software performance in predicting docking poses of the inspected inhibitors was initially conducted according to existing experimental data. Upon the assessed docking parameters, the Streptome database was virtually screened against DENV2 RdRp allosteric site. The streptomycetes NPs with docking scores less than the positive control (68T; calc. −35.6 kJ.mol⁻¹) were advanced for molecular dynamics simulations (MDS), and their binding affinities were computed by employing the MM/GBSA approach. Results: SDB9818 and SDB4806 unveiled superior inhibitor activities against DENV2 RdRp upon MM/GBSA//300 ns MDS than 68T with ΔG_binding values of −246.4, −242.3, and −150.6 kJ.mol⁻¹, respectively. A great consistency was found in both the energetic and structural analyses of the identified inhibitors within the DENV2 RdRp allosteric site. Furthermore, the physicochemical characteristics of the identified inhibitors demonstrated good oral bioavailability. Eventually, quantum mechanical computations were carried out to evaluate the chemical reactivity of the identified inhibitors. Conclusions: As determined by in silico computations, the identified streptomycetes NPs may act as DENV2 RdRp allosteric inhibitors and mandate further experimental assays. Full article

Background/Objectives: In digital radiography imaging, dual-layer flat-panel detectors (DFDs), in which two flat-panel detector layers are stacked with a minimal distance between the layers and appropriate alignment, are commonly used in material decompositions as dual-energy applications with a single x-ray exposure. DFDs also enable more efficient use of incident photons, resulting in x-ray images with improved noise power spectrum (NPS) and detection quantum efficiency (DQE) performances as single-energy applications. Purpose: Although the development of DFD systems for material decomposition applications is actively underway, there is a lack of research on whether single-energy applications of DFD can achieve better performance than the single-layer case. In this paper, we experimentally observe the DFD performance in terms of the modulation transfer function (MTF), NPS, and DQE with discussions. Methods: Using prototypes of DFD, we experimentally measure the MTF, NPS, and DQE of the convex combination of the images acquired from the upper and lower detector layers of DFD. To optimize DFD performance, a two-step image registration is performed, where subpixel registration based on the maximum amplitude response to the transform based on the Fourier shift theorem and an affine transformation using cubic interpolation are adopted. The DFD performance is analyzed and discussed through extensive experiments for various scintillator thicknesses, x-ray beam conditions, and incident doses. Results: Under the RQA 9 beam conditions of 2.7 μGy dose, the DFD with the upper and lower scintillator thicknesses of 0.5 mm could achieve a zero-frequency DQE of 75%, compared to 56% when using a single-layer detector. This implies that the DFD using 75 % of the incident dose of a single-layer detector can provide the same signal-to-noise ratio as a single-layer detector. Conclusions: In single-energy radiography imaging, DFD can provide better NPS and DQE performances than the case of the single-layer detector, especially at relatively high x-ray energies, which enables low-dose imaging. Full article

The development of novel platinum-based anticancer agents remains a critical objective in medicinal inorganic chemistry, particularly in light of resistance and toxicity limitations associated with cisplatin. In this study, the synthesis, structural characterization, quantum chemical analysis, and cytotoxic evaluation of four new acetylplatinum(II) complexes (cis-[Pt(COMe)₂(PASO₂)₂], cis-[Pt(COMe)₂(DAPTA)₂], trans-[Pt(COMe)Cl(DAPTA)₂], and trans-[Pt(COMe)Cl(PASO₂)]: 1–4, respectively) bearing cage phosphine ligands PASO₂ (2-thia-1,3,5-triaza-phosphaadamantane 2,2-dioxide) and DAPTA (3,7-diacetyl-1,3,7-triaza-5-phosphabicyclo[3.3.1]nonane) are presented. The coordination geometries and NMR spectral features of the cis/trans isomers were elucidated through multinuclear NMR and DFT calculations at the B3LYP/6-311++G(d,p)/LanL2DZ level, with strong agreement between experimental and theoretical data. Quantum Theory of Atoms in Molecules (QTAIM) analysis was applied to investigate bonding interactions and assess the covalent character of Pt–ligand bonds. Cytotoxicity was evaluated against five human cancer cell lines. The PASO₂-containing complex in cis-configuration, 1, demonstrated superior activity against thyroid (8505C) and head and neck (A253) cancer cells, with potency surpassing that of cisplatin. The DAPTA complex 2 showed enhanced activity toward ovarian (A2780) cancer cells. These findings highlight the influence of ligand structure and isomerism on biological activity, supporting the rational design of phosphine-based Pt(II) anticancer drugs. Full article

This article reconsiders the double-slit experiment by establishing a new type of relationship between it and the concept of entanglement. While the role of entanglement in the double-slit experiment has been considered, this particular relationship appears to have been missed in preceding discussions of the experiment, even by Bohr, who extensively used it to support his argument concerning quantum physics. The main reason for this relationship is the different roles of the diaphragm with slits in two setups, S1 and S2, defining the double-slit experiment as a quantum experiment. In S1, in each individual run of the experiment one can in principle (even if not actually) know throughout which slit the quantum object considered has passed; in S2 this knowledge is in principle impossible, which impossibility is coextensive with the appearance of the interference pattern, once a sufficient number of individual runs of the experiment have taken place. The article offers the following argument based on two new concepts, an “experimentally quantum object” and an “ontologically quantum object.” In S1 the diaphragm can be treated as part of an observational arrangement and thus considered as a classical object, while the object passing through one or the other slit is considered as an “ontologically quantum object,” defined as an object necessary to establish a quantum phenomenon. By contrast, in S2, the diaphragm can, via the concept of Heisenberg-von-Neumann cut, be treated as an “experimentally quantum object,” defined as an object treatable by quantum theory, even while possibly being an ontologically classical object. This interaction is not an observation but a quantum entanglement between these two quantum objects, one ontologically and one experimentally quantum. This argument is grounded in a particular interpretation of quantum phenomena and quantum theory, which belongs to the class of interpretations designated here as “reality without realism” (RWR) interpretations. The article also argues that wave-particle complementarity, with which the concept of complementarity is often associated, plays little, if any, role in quantum physics, or in Bohr’s thinking, and may be misleading in considering the double-slit experiment, often explained by using this complementarity. Full article

The main objective of this study is to improve heat transfer in hydrocarbon- and geothermal-energy coproduction systems using carbon quantum dots (CQDs). Two types of 0D nanoparticles (synthesized and commercial CQDs) were used for the formulation of nanofluids to increase the heat transfer from depleted wells for the coproduction of oil and electrical energy. The synthesized and commercial CQDs were characterized in terms of their morphology, zeta potential, density, size, and heat capacity. The nanofluids were prepared using brine from an oil well of interest and two types of CQDs. The effect of the CQDs on the thermophysical properties of the nanofluids was evaluated based on their thermal conductivity. In addition, a mathematical model based on heat transfer principles to predict the effect of nanofluids on the efficiency of the organic Rankine cycle (ORC) was implemented. The synthesized and commercial CQDs had particle sizes of 25 and 16 nm, respectively. Similarly, zeta potential values of 36 and 48 mV were obtained. Both CQDs have similar functional groups and UV absorption, and the fluorescence spectra show that the study CQDs have a maximum excitation–emission signal around 360–460 nm. The characterization of the nanofluids showed that the addition of 100, 300, and 500 mg/L of CQDs increased the thermal conductivity by 40, 50, and 60 %, respectively. However, the 1000 mg/L incorporated decreased the thermal conductivities of the nanofluids. The observed behavior can be attributed to the aggregate size of the nanoparticles. Furthermore, a new thermal conductivity model for CQD-based nanofluids was developed considering brine salinity, particle size distribution, and agglomeration effects. The model showed a remarkable fit with the experimental data and predicted the effect of the nanofluid concentration on the thermal conductivity and cycle efficiency. Coupled with an ORC cycle model, CQD concentrations of approximately 550 mg/L increased the cycle efficiency by approximately 13.8% and 18.6% for commercial and synthesized CQDs, respectively. Full article

In this work, we present a training method for a Fully Quantum Neural Network (FQNN) based entirely on quantum circuits. The model processes data exclusively through quantum operations, without incorporating classical neural network layers. In the proposed architecture, the roles of classical neurons and weights are assumed, respectively, by qubits and parameterized quantum gates: input features are encoded into quantum states of qubits, while the network weights correspond to the rotation angles of quantum gates that govern the system’s state evolution. The optimization of gate parameters is performed using directional gradient estimation, where gradients are numerically approximated via finite differences, eliminating the need for analytic derivation. The training objective is defined as the quantum-state fidelity, which measures the similarity between the network’s output state and a reference state representing the correct class. Experiments were conducted using the Qiskit AerSimulator, which allows for the accurate simulation of quantum circuits on a classical computer. The proposed approach was applied to the classification of the Iris dataset. The experimental results demonstrate that the FQNN is capable of effectively learning to distinguish between classes based on input features, achieving stable test accuracy across runs. These findings confirm the feasibility of constructing fully quantum classifiers without relying on hybrid quantum—classical architectures. The FQNN architecture consists of multiple quantum layers, each incorporating parameterized rotation operations and entanglement between qubits. The number of layers is determined by the ratio of quantum parameters (weights) to the number of input features. Each layer functions analogously to a hidden layer in a classical neural network, transforming the quantum-state space into a richer feature representation through controlled quantum operations. As a result, the network is capable of dynamically modeling dependencies among input features without the use of classical activation functions. Full article

Classical ghost imaging (CGI), an extension of quantum ghost imaging (QGI), enables object reconstruction by leveraging the spatial correlation between a pair of beams. Traditionally, CGI requires a camera or point scan to capture the spatial information of the illumination source with intensity fluctuations. In this work, we propose a novel CGI scheme that utilizes an incoherent source to illuminate both the object and the modulations, without introducing any mutual interference between them. Through theoretical analysis and experimental validation, we demonstrate that the reconstruction process relies solely on the modulations and correlation signals of two single-pixel detectors. Concurrently, this scheme is also extended to ghost diffraction, verifying the correlation between two planes that are Fourier transform pairs of the speckle field. Moreover, our study reveals the intricate relationships between the speckle field, modulations, and object, and experimentally verifies the impact of speckle fields on image quality. Notably, this work provides a more comparable framework between CGI and QGI, offering a promising avenue to explore the classical–quantum relationship. Full article

Sadi Carnot’s seminal work laid the foundation for exploring the effects of thermodynamics across diverse domains of physics, stretching from quantum to cosmological scales. Here, we build on the principles of the original Carnot heat engine, and apply it in the context of a particular toy model black brane. This theoretical construct of an effectively two-dimensional, stable, and stationary gravitational object in four-dimensional spacetime derives from a hypothetical flat planet collapsed under the influence of gravity. By constructing a thermodynamic cycle involving three such black branes, we explore the possibility of energy extraction or mining, driven by the temperature gradients and gravitational potential differences characteristic of curved spacetime. Analytic solutions obtainable within this toy model illuminate key aspects of black hole thermodynamics in general, particularly for spacetimes that are not asymptotically flat. Central to these findings is the relation between gravitationally induced temperature ratios and entropy changes, which collectively offer a novel perspective on obtainable energy transfer processes around gravitational structures. This analysis highlights potential implications for understanding energy dynamics in gravitational systems in general, including for black hole evaporation and experimentally implemented black hole analogues. The presented findings not only emphasise the universality of the thermodynamic principles first uncovered by Carnot, but also suggest future research directions in gravitational thermodynamics. Full article

This research presents the results of a combined numerical and experimental study of the thermal decomposition behavior of copolymers based on polypropylene glycol fumarate phthalate. The thermal decomposition of polymers plays a key role in various fields, such as waste recycling and energy recovery, and in the development of new materials. The objective of this study is to model the degradation kinetics using thermogravimetric data, matrix-based numerical methods, and quantum chemical calculations. To solve the resulting systems of linear algebraic equations (SLAEs), matrix decomposition algorithms (QR, SVD, and Cholesky) were employed, which enabled the determination of activation energy values for the process. Comparison of the activation energy (E_a) results obtained using the decomposition method of Cholesky (207.21 kJ/mol), normal equations (205.22 kJ/mol), singular value decomposition (206.23 kJ/mol), and QR decomposition (206.23 kJ/mol) showed minor changes that were associated with the features of each method. Quantum chemical calculations based on density functional theory (DFT) at the B3LYP/6-31G(d) level were performed to analyze the molecular structure and interpret the IR spectra. This study establishes that the content of functional groups (ether and ester) and the type of chemical bonds exert critical influences on the decomposition mechanism and associated thermal parameters. The results confirm that the polymer’s structural architecture governs its thermal stability. The scientific novelty of this work lies in the integration of numerical approximation methods and quantum chemical analysis for investigating the thermal behavior of polymers. This approach is applied for the first time to copolymers of this composition and may be employed in the design of heat-resistant materials for agricultural and environmental applications. Full article

The objective of this study is to develop a mathematical model capable of correctly displaying the dynamics of an individual’s cognitive activity under conditions of external information influence of different modalities. The adequacy of the model is verified by comparing the results of numerical analysis and experimental data. The mathematical basis of such a model is the apparatus of self-oscillating quantum mechanics. To describe algorithms for the processes of transmission, processing, and generation of information, the theory of information images/representations is used. Methods. This article provides a brief description of the proposed theory. The cognitive activity of an individual is represented mathematically as a one-dimensional potential hole with finite walls of different sizes. The internal potential barrier in this model can model the boundary between consciousness and subconsciousness. The authors developed a parameterization of the systems under study taking into account the proposed theory. Next, a mathematical model was developed based on the apparatus of self-oscillatory quantum mechanics. The authors formulated an equation that describes the function of the state of an information image in the process of human cognitive activity. Computer modeling of various variations of information impact was carried out. The authors also conducted a specially designed experiment. Conclusions. The authors have identified characteristic patterns of such processes and shown the oscillating nature of changes in the state function of information images and the appearance of characteristic threshold effects. A comparison of the obtained model and experimental data showed the adequacy of the developed tool (the coincidence of the general dynamics and characteristic patterns was shown). Full article

In recent years, optimization algorithms have developed rapidly, especially those which introduce quantum ideas, which perform excellently. Inspired by quantum thought, this paper proposes a quantum dynamics framework (QDF) which converts optimization problems into the problem of the constrained ground state of the quantum system and analyzes optimization algorithms by simulating the dynamic evolution process of physical optimization systems in the ground state. Potential energy equivalence and Taylor expansion are performed on the objective function to obtain the basic iterative operations of optimization algorithms. Furthermore, a quantum dynamics framework based on the quantum tunneling effect (QDF-TE) is proposed which adopts dynamic multiple group collaborative sampling to improve the quantum tunneling effect of the QDF, thereby increasing the population diversity and improving algorithm performance. The probability distribution of solutions can be visually observed through the evolution of the wave function, which also indicates that the QDF-TE can strengthen the tunneling effect. The QDF-TE was evaluated on the CEC 2017 test suite and shown to be competitive with other heuristic optimization algorithms. The experimental results reveal the effectiveness of introducing a quantum mechanism to analyze and improve optimization algorithms. Full article

Background/Objectives: Fructose-driven metabolic disorders, such as obesity, non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and type 2 diabetes, are significant global health challenges. Ketohexokinase C (KHK-C), a key enzyme in fructose metabolism, is a promising therapeutic target. α-Mangostin, a naturally occurring prenylated xanthone, has been identified as an effective KHK-C inhibitor, prompting exploration of its analogs for enhanced efficacy. This study aimed to identify α-Mangostin analogs with improved inhibitory properties against KHK-C to address these disorders. Methods: A library of 1383 analogs was compiled from chemical databases and the literature. Molecular docking, binding free energy calculations, pharmacokinetic assessments, molecular dynamics simulations, and quantum mechani–cal analyses were used to screen and evaluate the compounds. α-Mangostin’s binding affinity (37.34 kcal/mol) served as the benchmark. Results: Sixteen analogs demonstrated binding affinities superior to α-Mangostin (from −45.51 to −61.3 kcal/mol), LY-3522348 (−45.36 kcal/mol), and reported marine-derived inhibitors (from −22.74 to −51.83 kcal/mol). Hits 7, 8, 9, 13, and 15 not only surpassed these benchmarks in binding affinity, but also exhibited superior pharmacokinetic properties compared to α-Mangostin, LY-3522348, and marine-derived inhibitors, indicating strong in vivo potential. Among these, hit 8 emerged as the best performer, achieving a binding free energy of −61.30 kcal/mol, 100% predicted oral absorption, enhanced metabolic stability, and stable molecular dynamics. Conclusions: Hit 8 emerged as the most promising candidate due to its superior binding affinity, favorable pharmacokinetics, and stable interactions with KHK-C. These findings highlight its potential for treating fructose-driven metabolic disorders, warranting further experimental validation. Full article

The argument of this article is threefold. First, the article argues that from its rise in the sixteenth century to our own time, the advancement of modern physics as mathematical-experimental science has been defined by the invention of new mathematical structures. Second, the article argues that quantum theory, especially following quantum mechanics, gives this thesis a radically new meaning by virtue of the following two features: on the one hand, quantum phenomena are defined as essentially different from those found in all previous physics by purely physical features; and on the other, quantum mechanics and quantum field theory are defined by purely mathematical postulates, which connect them to quantum phenomena strictly in terms of probabilities, without, as in all previous physics, representing or otherwise relating to how these phenomena physically come about. While these two features may appear discordant, if not inconsistent, I argue that they are in accord with each other, at least in certain interpretations (including the one adopted here), designated as “reality without realism”, RWR, interpretations. This argument also allows this article to offer a new perspective on a thorny problem of the relationships between continuity and discontinuity in quantum physics. In particular, rather than being concerned only with the discreteness and continuity of quantum objects or phenomena, quantum mechanics and quantum field theory relate their continuous mathematics to the irreducibly discrete quantum phenomena in terms of probabilistic predictions while, at least in RWR interpretations, precluding a representation or even conception of how these phenomena come about. This subject is rarely, if ever, discussed apart from previous work by the present author. It is, however, given a new dimension in this article which introduces, as one of its main contributions, a new principle: the mathematical complexity principle. Full article

This paper is devoted to an experimental investigation of cognitive contextuality inspired by quantum contextuality research. This contextuality is related to, but not identical to context-sensitivity which is well-studied in cognitive psychology and decision making. This paper is a part of quantum-like modeling, i.e., exploring the methodology of quantum theory outside of physics. We examined the bistable perception of cup-like objects, which strongly depends on experimental contexts. Our experimental data confirmed the existence of cognitive hysteresis, the important role of memory, and the non-commutative structure of cognitive observables. In physics, quantum contextuality is assessed using Bell-CHSH inequalities, and their violation is incorrectly believed to imply the nonlocality of Nature. The violation of Bell-type inequalities in cognitive and social science strongly indicates that the metaphysical implications of these inequalities are quite limited. In our experiments, modified Leggett–Garg inequalities were also significantly violated, but this only means that experimental data from experiments performed in different contexts cannot be modeled by a unique set of noncontextual, jointly distributed random variables. In our experiments, we know the empirical probability distributions measured in different contexts; thus, we can obtain much more detailed and reliable information about contextuality in human cognition by performing nonparametric compatibility tests. Full article

In recent times, interest in the chemistry of conjugated nitrodienes is still significantly increasing. In particular, the application of these compounds as building blocks to obtain heterocycles is a popular object of research. Therefore, in continuation of our research devoted to the topic of conjugated nitrodienes, experimental and quantum-chemical studies of a cycloaddition reaction between (1E,3E)-1,4-dinitro-1,3-butadiene and N-methyl azomethine ylide have been investigated. The computational results present that the tested reaction is realized through a pdr-type polar mechanism. In turn, the experimental study shows that in a course of this cycloaddition, only one reaction product in the form of 1-methyl-3-(trans-2-nitrovinyl)-Δ³-pyrroline is created. The constitution of this compound has been confirmed via spectroscopic methods. Finally, ADME analysis indicated that the synthesized Δ³-pyrroline exhibits biological potential, and it is a good drug candidate according to Lipinski, Veber and Egan rules. Nevertheless, PASS simulation showed that the compound exhibits weak antimicrobial, inhibitory and antagonist properties. Preliminary in silico research shows that although the obtained Δ³-pyrroline is not a good candidate for a drug, the presence of a nitrovinyl moiety in its structure indicates that the compound is an initial basis for further modifications. Full article