Search Results (478)

During atmospheric reentry, a significant number of chemical reactions are produced inside the high-temperature shock wave formed upstream of the spacecraft. Chemical reactions can significantly alter the flowfield structure surrounding the vehicle and affect surface properties, including heat transfer, pressure, and skin friction coefficients. In this scenario, the primary goal of this investigation is to evaluate the Quantum-Kinetic chemistry model for computing rarefied reactive gas flow over simple and complex geometries. The results are compared with well-established reaction models available for the transitional flow regime. The study focuses on two configurations, a sphere and the Orion capsule, analyzed at different altitudes to assess the impact of chemical nonequilibrium across varying flow rarefaction levels. Including chemical reactions led to lower post-shock temperatures, broader shock structures, and significant species dissociation in both geometries. These effects strongly influenced the surface heat flux, pressure, and temperature distributions. Comparison with results from the literature confirmed the validity of the implemented QK model and highlighted the importance of including chemical kinetics when simulating hypersonic flows in the upper atmosphere. Full article

Curcuma spp. is a popular ornamental crop valued for its vibrant appearance and suitability for both regular and off-season production. As global emphasis on freshwater conservation increases and with a demand for compact potted plants, reducing water use while maintaining high aesthetic quality presents a key challenge for horticulturists. Potassium silicate (PS) has been proposed as a foliar spray to alleviate plant water stress. This study aimed to evaluate the effects of PS on growth, ornamental traits, and photosynthetic parameters of off-season potted Curcuma cv. ‘Jasmine Pink’ under deficit irrigation (DI). Plants were subjected to three treatments in a completely randomized design: 100% crop evapotranspiration (ETc), 50% ETc, and 50% ETc with 1000 ppm PS (weekly sprayed on leaves for 11 weeks). Both DI treatments (50% ETc and 50% ETc + PS) reduced plant height by 7.39% and 9.17%, leaf number by 16.99% and 7.03%, and total biomass by 21.13% and 20.58%, respectively, compared to 100% ETc. Notably, under DI, PS-treated plants maintained several parameters equivalent to the 100% ETc treatment, including flower bud emergence, blooming period, green bract number, effective quantum yield of PSII (ΔF/Fm′), and electron transport rate (ETR). In addition, PS application increased leaf area by 8.11% and compactness index by 9.80% relative to untreated plants. Photosynthetic rate, ΔF/Fm′, and ETR increased by 31.52%, 13.63%, and 9.93%, while non-photochemical quenching decreased by 16.51% under water-limited conditions. These findings demonstrate that integrating deficit irrigation with PS foliar application can enhance water use efficiency and maintain ornamental quality in off-season potted Curcuma, promoting sustainable water management in horticulture. Full article

Developing a new drug costs approximately one to three billion dollars and takes around ten years; however, this process has only a ten percent success rate. To address this issue, new technologies that combine artificial intelligence (AI) and quantum computing can be leveraged in the pharmaceutical industry. The RSA cryptographic algorithm, developed by Rivest, Shamir, and Adleman in 1977, is one of the most widely used public-key encryption schemes in modern digital security. Its security foundation lies in the computational difficulty of factoring the product of two large prime numbers, a problem considered intractable for classical computers when the key size is sufficiently large (e.g., 2048 bits or more). A future application of using a detailed structural model of a protein is that digital drug design can be used to predict potential drug candidates, thereby reducing or eliminating the need for time-consuming laboratory and animal testing. Knowing the molecular structure of a possible candidate drug can provide insights into how drugs interact with targets at an atomic level, at significantly lower expenditures, and with maximum effectiveness. AI and quantum computers can rapidly screen out potential new drug candidates, determine the toxicity level of a known drug, and eliminate drugs with high toxicity at the beginning of the drug development phase, thereby avoiding expensive laboratory and animal testing. The Food and Drug Administration (FDA) and other regulatory bodies are increasingly supporting the use of in silico to in vitro/in vivo validation methods and assessments of drug safety and efficacy. Full article

Accurate wind-speed prediction plays an important role in improving the operation stability of wind-power generation systems. However, the inherent complexity of meteorological dynamics poses a major challenge to forecasting accuracy. In order to overcome these limitations, we propose a new hybrid framework, which combines variational mode decomposition (VMD) for signal processing, enhanced quantum particle swarm optimization (e-QPSO), an improved walking optimization algorithm (IHOA) for feature selection and the long short-term memory (LSTM) network, and which finally establishes a reliable prediction architecture. The purpose of this paper is to optimize VMD by using the e-QPSO algorithm to improve the problems of excessive filtering or error filtering caused by parameter problems in VMD, as the noise signal cannot be filtered completely, and the number of sources cannot be accurately estimated. The IHOA algorithm is used to find the optimal hyperparameters of LSTM to improve the learning efficiency of neurons and improve the fitting ability of the model. The proposed e-QPSO-VMD-IHOA-LSTM model is compared with six established benchmark models to verify its predictive ability. The effectiveness of the model is verified by experiments using the hourly wind-speed data measured in four seasons in Changchun in 2023. The MAPE values of the four datasets were 0.0460, 0.0212, 0.0263, and 0.0371, respectively. The results show that e-QPSO-VMD effectively processes the data and avoids the problem of error filtering, while IHOA effectively optimizes the LSTM parameters and improves prediction performance. Full article

This article examines a hybrid generation of cryptographic keys, whose novelty lies in the fusion of a multiscale subkey generation with prime sieve and subkeys inspired by quantum mechanics. It combines number theory with techniques emulated and inspired by quantum mechanics, also based on two demons capable of dynamically modifying the cryptographic model. The integration is structured through the JDL. In fact, a specific information fusion model is used to improve security. As a result, the resulting key depends not only on the individual components, but also on the fusion path itself, allowing for dynamic and cryptographically agile configurations that remain consistent with quantum mechanics-inspired logic. The proposed approach, called quantum and prime information fusion (QPIF), couples a simulated quantum entropy source, derived from the numerical solution of the Schrödinger equation, with a multiscale prime number sieve to construct multilevel cryptographic keys. The multiscale sieve, based on recent advances, is currently among the fastest available. Designed to be compatible with classical computing environments, the method aims to contribute to cryptography from a different perspective, particularly during the coexistence of classical and quantum computers. Among the five key generation algorithms implemented here, the ultra-optimised QRNG offers the most effective trade-off between performance and randomness. The results are validated using standard NIST statistical tests. This hybrid framework can also provide a conceptual and practical basis for future work on PQC aimed at addressing the challenges posed by the quantum computing paradigm. Full article

Quantum neural networks (QNNs) represent an emerging technology that uses a quantum computer for neural network computations. The QNNs have demonstrated potential advantages over classical neural networks in certain tasks. As a core component of a QNN, the parameterized quantum circuit (PQC) plays a crucial role in determining the QNN’s overall performance. However, quantum circuit architectures designed manually based on experience or using specific hardware structures can suffer from inefficiency due to the introduction of redundant quantum gates, which amplifies the impact of noise on system performance. Recent studies have suggested that the advantages of quantum evolutionary algorithms (QEAs) in terms of precision and convergence speed can provide an effective solution to quantum circuit architecture-related problems. Currently, most QEAs adopt a fixed rotation mode in the evolution process, and a lack of an adaptive updating mode can cause the QEAs to fall into a local optimum and make it difficult for them to converge. To address these problems, this study proposes an adaptive quantum evolution algorithm (AQEA). First, an adaptive mechanism is introduced to the evolution process, and the strategy of combining two dynamic rotation angles is adopted. Second, to prevent the fluctuations of the population’s offspring, the elite retention of the parents is used to ensure the inheritance of good genes. Finally, when the population falls into a local optimum, a quantum catastrophe mechanism is employed to break the current population state. The experimental results show that compared with the QNN structure based on manual design and QEA search, the proposed AQEA can reduce the number of network parameters by up to 20% and increase the accuracy by 7.21%. Moreover, in noisy environments, the AQEA-optimized circuit outperforms traditional circuits in maintaining high fidelity, and its excellent noise resistance provides strong support for the reliability of quantum computing. Full article

The primary objective of this paper is to derive a non-relativistic system of equations for a spin-2 particle in the presence of an external Coulomb field, solve these equations, and determine the corresponding energy spectra. We begin with the known radial system of 39 equations formulated for a free spin-2 particle and modify it to incorporate the effects of the Coulomb field. By eliminating the 28 components associated with vector and rank-3 tensor fields, we reduce the system to a set of 11 second-order equations related to scalar and symmetric tensor components. In accordance with parity constraints, this system naturally groups into two subsystems consisting of three and eight equations, respectively. To perform the non-relativistic approximation, we employ the method of projective operators constructed from the matrix ${\Gamma }^0$ of the original matrix equation. This approach allows us to derive two non-relativistic subsystems corresponding to the parity restrictions, comprising two and three coupled differential equations. Through a linear similarity transformation, we further decouple these into five independent equations with a Schrödinger-type non-relativistic structure, leading to explicit energy spectra. Special attention is given to the case of the minimal quantum number of total angular momentum, $j=0$, which requires separate consideration. Full article

Buckwheat (Fagopyrum esculentum Moech) is a “gluten-free” pseudocereal with high-quality proteins and human health properties, increasing its cultivation worldwide. However, the role of nitrogen (N) in plant growth and yield components has received little attention in buckwheat. This study evaluated N’s effect on plant traits, photosynthetic performance, and grain yield components in buckwheat under field conditions. For this, Buckwheat cv. “Mancan” seeds were sown using five N rates: 0, 30, 45, 60, and 90 kg N ha⁻¹. Then, physiological performance and grain yield components were evaluated at harvest. Our study revealed that buckwheat plants subjected to 0 and 30 kg N ha⁻¹ showed the greatest chlorophyll fluorescence a parameters including maximum quantum yield of PSII (Fv′/Fm′), effective quantum yield of PSII (ФPSII), and electron transport rate (ETR) among N treatments; meanwhile, at higher N rates (60 and 90 kg N ha⁻¹), these parameters decayed. Similarly, plants treated with 90 kg N ha⁻¹ showed the lowest CO₂ assimilation among N treatments. In general, stomatal conductance (g_s), transpiration (E), and intrinsic water use efficiency (WUE_i) showed no significant changes among N treatments, with the exception of 30 kg N ha⁻¹, which exhibited the highest WUE_i. Concerning plant traits, plants grown under 60 and 90 kg N ha⁻¹ exhibited the greatest plant height, number of branches, shoot biomass, and internode per plant among N treatments. By contrast, 30 kg N ha⁻¹ showed the highest grain number, yield per plant, and grain yield among N treatments in F. esculentum plants. Based on the physiological and productive parameters, F. esculentum seems to have a low N requirement, exhibiting better results under the lowest N rates (30 kg N ha⁻¹). Therefore, F. esculentum could be considered as an alternative for gluten-free food production with low N requirements in agricultural systems of southern Chile. Nonetheless, more studies are required to understand the effect of N biochemical and molecular regulation on plant traits and grain yield components in buckwheat. Full article

In this work, we undertake a comprehensive study of the functional measure of gravitational path integrals within a general framework involving non-trivial configuration spaces. As in Riemannian geometry, the integration over non-trival configuration spaces requires a metric. We examine the interplay between the functional measure and the dynamics of spacetime for general configuration-space metrics. The functional measure gives an exact contribution to the effective action at the one-loop level. We discuss the implications and phenomenological consequences of this correction, shedding light on the role of the functional measure in quantum gravity theories. In particular, we describe a mechanism in which the graviton acquires a mass from the functional measure without violating the diffeomorphism symmetry nor including Stückelberg fields. Since gauge invariance is not violated, the number of degrees of freedom goes as in general relativity. For the same reason, Boulware–Deser ghosts and the vDVZ discontinuity do not show up. The graviton thus becomes massive at the quantum level while avoiding the usual issues of massive gravity. Full article

The current study presents the results of a methodical investigation into the ionization of rare gas atoms, specifically focusing on argon. In this study, two configurations are examined: ionization via a near-infrared (NIR) laser field alone, and ionization caused by extreme ultraviolet (XUV) radiation in the presence of a strong, synchronized NIR pulse. The theoretical investigation is conducted using an ab initio method to solve the time-dependent Schrödinger equation within the single active electron (SAE) approximation. The simulation results show a sequence of above-threshold ionization (ATI) peaks that shift to lower energies with increasing laser intensity. This behavior reflects the onset of the Stark effect, which modifies atomic energy levels and increases the number of photons required for ionization. An examination of the two-color photoionization spectrum, which includes sideband structures and harmonic peaks, shows how the ionization probability is redistributed between the direct path (single XUV photon absorption) and sideband pathways (XUV ± n × IR) as the intensity of the infrared field increases. Quantum interference between continuum states is further revealed by the photoelectron angular distribution, clearly indicating the control of ionization dynamics by the IR field. Full article

Photodynamic therapy (PDT) is a non-invasive therapeutic method with over a century of medical use, especially in dermatology, ophthalmology, dentistry, and, notably, cancer treatment. With an increasing number of clinical trials, there is growing demand for innovation in PDT. Despite being a promising treatment for cancer and bacterial infections, PDT faces limitations such as poor water solubility of many photosensitizers (PS), limited light penetration, off-target accumulation, and tumor hypoxia. This review focuses on chlorins—well-established macrocyclic PSs known for their strong activity and clinical relevance. We discuss how nanotechnology addresses PDT’s limitations and enhances therapeutic outcomes. Nanocarriers like lipid-based (liposomes, micelles), polymer-based (cellulose, chitosan, silk fibroin, polyethyleneimine, PLGA), and carbon-based ones (graphene oxide, quantum dots, MOFs), and nanospheres are promising platforms that improve chlorin performance and reduce side effects. This review also explores their use in Antimicrobial Photodynamic Therapy (aPDT) against multidrug-resistant bacteria and in oncology. Recent in vivo studies demonstrate encouraging results in preclinical models using nanocarrier-enhanced chlorins, though clinical application remains limited. Full article

Belle II is a particle physics experiment working at an high luminosity collider within a hard irradiation environment. The Time-Of-Propagation detector, aimed at the charged particle identification, surrounds the Belle II tracking detector on the barrel part. This detector is composed by 16 modules, each module contains a finely fused silica bar, coupled to microchannel plate photomultiplier tube (MCP-PMT) photo-detectors and readout by high-speed electronics. The MCP-PMT lifetime at the nominal collider luminosity is about one year, this is due to the high photon background degrading the quantum efficiency of the photocathode. An alternative to these MCP-PMTs is multi-pixel photon counters (MPPC), known as silicon photomultipliers (SiPM). The SiPMs, in comparison to MCP-PMTs, have a lower cost, higher photon detection efficiency and are unaffected by the presence of a magnetic field, but also have a higher dark count rate that rapidly increases with the integrated neutron flux. The dark count rate can be mitigated by annealing the damaged devices and/or operating them at low temperatures. We tested SiPMs, with different dimensions and pixel sizes from different producers, to study their time resolution (the main constraint that has to satisfy the photon detector) and to understand their behavior and tolerance to radiation. For these studies we irradiated the devices to radiation up to $5\times {10}^{11}1$ MeV neutrons equivalent (neq) per cm² fluences; we also started studying the effect of annealing on dark count rates. We performed several measurements on these devices, on top of the dark count rate, at different conditions in terms of overvoltage and temperatures. These measurements are: IV-curves, amplitude spectra, time resolution. For the last two measurements we illuminated the devices with a picosecond pulsed laser at very low intensities (with a number of detected photons up to about twenty). We present results mainly on two types of SiPMs. A new SiPM prototype developed in collaboration with FBK with the aim of improving radiation hardness, is expected to be delivered in September 2025. Full article

The fifth-order nonlinear polarizability has been extensively studied in the field of quantum communication due to its ease of manipulation. By adjusting the relative size of the Rabi frequency and dephasing rate of the dressing field, natural non-Hermitian exceptional points can be generated, and further evolution can be achieved by varying the types of dressing fields. However, as the demand for information capacity in quantum communication continues to increase, research on the higher-order seventh-order nonlinear polarizability, based on four-photon states, and the number of coherent channels and resonance positions has gradually come to the forefront. This paper focuses on the simultaneous generation of a seventh-order nonlinear polarizability through a spontaneous eight-wave mixing (SEWM) process in an atomic medium involving four photons. Compared to the fifth-order nonlinear polarizability, the seventh-order polarizability shows an exponential increase in coherent channels and resonance positions due to its strong dressing effect. Additionally, the interaction between the four photons is stronger than that between three photons, making it possible for even the difficult-to-dress eigenvalues to be influenced by the dressing field and dephasing rate, resulting in more complex coherent channels. These are manifested as more complex, damped Rabi oscillations, with periods that can be controlled by the dressing field. These findings may contribute to a promising new method for quantum communication. Full article

In multi-criteria group decision making, decision makers are commonly regarded as independent. However, in practice, heterogeneous backgrounds and complex cognitive processes lead to mutual interference among their judgments. To address this gap, a novel multi-criteria quantum group decision-making model is proposed that explicitly incorporates opinion interference effects. First, type-2 fuzzy numbers are employed to represent evaluation information, and a specialized Euclidean distance measure for them is introduced. Second, an extended distance-based criteria importance through an inter-criteria correlation method incorporating Deng entropy is developed to derive robust criteria weights under uncertainty. Third, the TODIM method integrates cumulative prospect theory to capture decision makers’ risk perceptions and computes prospect-based dominance degrees. Fourth, a quantum-inspired aggregation mechanism models the mutual interference in group opinions. Finally, a case study on FinTech startup investment demonstrates the model’s practical applicability, while sensitivity analysis and comparisons to established methods confirm its robustness and effectiveness. Full article

Hydroponic cultivation offers a promising solution to water scarcity by using less water than traditional soil-based agriculture. Although the integration of silicon (Si) in hydroponic systems is still limited, its foliar application is crucial for optimizing plant growth, enhancing resilience, and improving productivity. Therefore, this study aims to explore the effects of silicon foliar application on growth, yield parameters, and photosynthetic activity of one of the most important fruit vegetables worldwide—tomatoes (Solanum lycopersicum L.)—cultivated in a closed hydroponic system. Tomato plants were subjected to a weekly silicon foliar spray (1 mM Na₂SiO₃) over a period of 10 weeks. Our results demonstrate that silicon foliar spray in hydroponically grown tomatoes significantly improved photosynthetic pigment concentration and enhanced the photochemical efficiency of the photosystems, particularly the quantum yields Y(I) and Y(II). Moreover, silicon treatment resulted in reduced energy dissipation within the photosystems, as indicated by decreases in Y(NPQ), Y(NO), and Y(ND), along with enhanced oxidation of PSI (P700ox). These physiological improvements were directly linked to increased stem width and length, and a substantial boost in plant dry weight compared with untreated controls. Consequently, the silicon foliar spray resulted in a significant increase in the number of racemes, flowers, and fruits. Ultimately, these enhancements culminated in a 69% increase in fruit biomass yield (r² = 0.70; p < 0.01), highlighting the positive impact of silicon on tomato productivity in hydroponic systems. These findings suggest that silicon foliar application optimizes growth and photosynthetic efficiency while reducing energy dissipation. Consequently, silicon supplementation enhances tomato productivity in hydroponic systems, offering a promising solution for increasing yields in water-efficient agriculture. Full article