Search Results (1,311)

Vascular wilt caused by Fusarium oxysporum f. sp. physali (Foph) severely limits cape gooseberry (Physalis peruviana L.) production in Andean regions, where management options are restricted and largely dependent on fungicides. Silicon (Si) has been proposed as a sustainable strategy to enhance tolerance to vascular pathogens; however, its role in the cape gooseberry–Foph pathosystem remains unknown. This study evaluated the effects of soil and foliar Si applications on disease development and physiological responses in cape gooseberry plants under greenhouse conditions. Three soil doses and three foliar doses were tested, including inoculated and non-inoculated controls without treatment. Si significantly reduced disease progression, decreasing the area under the disease progress curve (AUDPC) and disease severity index, with efficacy values of up to 69% in inoculated plants, particularly at 8 g kg⁻¹ soil application. Si also reduced vascular browning and mitigated pathogen-induced physiological impairment by maintaining higher stomatal conductance, relative chlorophyll content, maximum quantum efficiency of photosystem II, and plant growth. These findings indicate that Si, especially when soil-applied, enhances physiological tolerance to Foph and represents a promising complementary tool for its integrated management. Full article

This study explored the electronic and structural tunability of fullerene (C₆₀) derivatives via functionalization with heteroatoms (O, S, Se) in mono-, di-, and tri-bridged configurations, including covalently modeled dimers. Calculations were performed using density functional theory (DFT) at the B3LYP/6-31G(d,p) level. Electronic descriptors such as total dipole moments (TDMs), HOMO–LUMO energy gaps (ΔE), global reactivity descriptors, total density of states (TDOS), molecular electrostatic potential (MESP) and non-covalent interactions (NCIs) were analyzed to elucidate how functionalization alters reactivity and stability. Key findings indicate that TDM increases and ΔE decreases in all functionalized C₆₀; for example, the TDM increased from 0 Debye for C₆₀ to 2.156 Debye for C₆₀–O–S–Se, and ΔE decreased from 2.762 eV (C₆₀) to 2.532 eV (C₆₀–Se), indicating enhanced reactivity. This aligns with global reactivity descriptors such as reduced ionization energy and hardness. Mapped MESP surfaces showed activation around heteroatom sites. Quantum theory of atoms in molecules (QTAIM) and NCI analyses revealed that while mono-bridged structures retain covalent linkages, dimeric systems such as C₆₀–O–C₆₀ and C₆₀–S–C₆₀ relax into weak, van der Waals-type interactions. OPDOS (overlap population density of states) highlighted antibonding character between the fragments in the conduction region. These results demonstrate that heteroatom functionalization enhances the electronic properties of C₆₀, making it a promising candidate for optoelectronic, organic photovoltaic, and sensor applications. Full article

Two Zn(II) coordination compounds based on glaucine-derived Schiff bases were synthesized and investigated as potential materials for dye-sensitized solar cells (DSSCs). The structures of all compounds were established by X-ray diffraction analysis and quantum chemical modeling (DFT/TD-DFT). Their photophysical properties (absorption and luminescence spectra in solution and the solid state), electrochemical characteristics, and photovoltaic parameters in DSSC devices were studied. The highest power conversion efficiency (PCE ~5.18%) was demonstrated by the free ligands, which is attributed to their favorable absorption spectrum and optimal alignment of energy levels relative to the conduction band of TiO₂ and the redox couple of the electrolyte. The Zn(II) coordination compounds exhibited significantly lower efficiency (~2.1%). Impedance spectroscopy results indicated more efficient charge transfer at the TiO₂/dye/electrolyte interface for the organic derivatives. Full article

This paper outlines a simple theoretical argument for the possibility of a quantum linear Voigt effect at low temperatures in certain media in the optical regime. An unlikely starting point for the ensuing argument arises out of a long-established hydrodynamic Lorentz field-modified classical dispersion theory whose Voigt component of the optical conductivity, when subjected to the Uncertainty Principle, results in a modified form in the quantum region. In contrast to its classical, second-order counterpart, this quantum Voigt conductivity is shown to have a (modular) linear field dependence. Full article

In fundamental physics, sensors operating below liquid helium temperatures are highly vulnerable to vibrations, which can affect the sensitivity, for example, of high-performance particle detectors. Pulse-tube refrigerators, while generating vibrations lower than those of conventional systems, may still introduce several disturbances. Hence, flexible thermal connections are a commonly used mechanical solution to mitigate these undesirable effects. Among the materials that can be used, ultra-high-purity aluminum (UHP-Al) has attracted the attention for low-amplitude-vibration cryogenic applications, including gravitational wave interferometry, quantum information systems, precision space instrumentation, and cryogenic resonators. Thus, the aim of the paper is the characterization of the mechanical and microstructure properties of three UHP-Als (i.e., 5N—99.999 wt%, 5N5—99.9995 wt% and 6N—99.9999 wt%) intended for the production of thermal flexible connections with low stiffness, specifically designed to reduce vibration transmission in cryogenic environments. Mechanical properties were evaluated through standard tensile tests from room (+25 °C) to low temperature (i.e., −150 °C), providing insights into yield strength, ultimate tensile strength, elongation and elastic modulus. In addition, the dynamic elastic modulus of material loads, at cryogenic conditions (i.e., about −180 °C), was determined by measuring the natural resonance frequency, thereby assessing the material’s response to vibrational. Moreover, an extensive microstructural analysis was conducted using electron backscatter diffraction and x-ray diffraction. The correlation between the observed microstructure and the elastic properties was systematically examined. The results underscore the pivotal role of microstructural characteristics in dictating the elastic behavior of UHP Als. Eventually, the analysis provides valuable guidelines for the materials employment inside cryogenic systems, where severe vibration control is critical to maintain high operational performance. Full article

Background: This paper investigates hybrid quantum–classical optimization approaches for addressing core supply chain management (SCM) problems. A unified hybrid framework is implemented and evaluated across five representative domains: vehicle routing, scheduling, facility location, inventory optimization, and demand forecasting. Methods: The framework integrates quantum algorithms—namely the Quantum Approximate Optimization Algorithm (QAOA), Quantum Annealing (QA), and the Variational Quantum Eigensolver (VQE)—with classical constraint-handling and local refinement procedures in an iterative workflow. Quantum solvers are employed for global solution exploration, while classical optimization ensures feasibility and convergence stability. Results: Experiments conducted on standardized synthetic benchmarks demonstrate that the proposed hybrid framework consistently outperforms classical-only and quantum-only baselines, achieving 12–18% reductions in operational costs and 20–35% faster convergence. In routing and fulfilment tasks, quantum-generated candidate solutions provide effective warm starts for classical refinement. Robustness analysis based on stochastic SCM simulations further indicates lower performance variance under uncertainty. Conclusions: These results demonstrate that hybrid quantum–classical optimization constitutes a practical and scalable strategy for near-term SCM decision-making under current Noisy Intermediate-Scale Quantum (NISQ) hardware constraints. Full article

The Internet of Medical Things (IoMT) has become a core component of modern healthcare infrastructures, enabling continuous patient monitoring, remote diagnostics, and data-driven clinical decision-making. Despite these advances, authentication in IoMT environments remains a critical security challenge, intensified by strict resource constraints of medical devices and the emerging threat posed by quantum computing to classical cryptographic techniques. This systematic review investigates authentication mechanisms in IoMT from both post-quantum and system-level perspectives. A structured literature review was conducted using a PRISMA-informed methodology across major scientific databases, including IEEE Xplore, ACM Digital Library, SpringerLink, ScienceDirect, and MDPI. From an initial set of 95 records, 63 studies were selected for qualitative synthesis following screening and eligibility assessment. To organise existing research, this study introduces a multi-dimensional classification framework that categorises authentication solutions according to cryptographic paradigm (classical, hybrid, and post-quantum), deployment architecture, system objectives, and clinical operational constraints. The comparative synthesis demonstrates important trade-offs between security strength, latency, computational overhead, and energy consumption that are frequently underexplored in the existing literature. Furthermore, the analysis identifies key research gaps related to scalability in heterogeneous medical environments, trust establishment across administrative and clinical domains, usability under strict timing constraints, and resilience against quantum-capable adversaries. Based on these findings, future research directions are outlined toward adaptive, lightweight, and context-aware post-quantum authentication frameworks designed for real-world IoMT deployments. Limitations of this review include restriction to English-language publications and selected databases. This study received no external funding, and the review protocol was not formally registered. Full article

Light availability drives Stevia rebaudiana productivity, yet how incident radiation interacts with genotype and site under tropical field conditions remains unclear. We evaluated four genotypes (L020, L102, L082, and ‘Morita II’) across three Caribbean locations in Colombia under two contrasting light levels (600 vs. 1800 μmol photons m⁻² s⁻¹) using a split-plot randomised complete block design with four replicates. Incident photosynthetic photon flux density (PPFD) was logged and, at 85 days after transplanting (DAT), net CO₂ assimilation, stomatal conductance, transpiration, and intercellular CO₂ concentration were measured alongside light-adapted chlorophyll fluorescence parameters, including the effective quantum yield of photosystem II (ΦPSII), the maximum efficiency of PSII in the light (Fv′/Fm′), photochemical quenching (qP), and electron transport rate (ETR); biomass and leaf yield were quantified at harvest. Data were analysed using factorial analysis of variance (ANOVA) and complementary multivariate approaches, including Pearson correlation analysis and principal component analysis (PCA). Radiation responses were strongly site-dependent: under 1800 μmol photons m⁻² s⁻¹, net CO₂ assimilation increased by 90.2% at El Carmen de Bolívar and 21.5% at Polonuevo but decreased by 36.4% at Montería. Leaf yield was highest in El Carmen de Bolívar (1951.46 ± 182.03 kg ha⁻¹), followed by Montería (1510.94 ± 173.75 kg ha⁻¹) and Polonuevo (576.31 ± 42.36 kg ha⁻¹). Genotype rankings shifted with environment and radiation, with L102 reaching 3256.25 ± 126.39 kg ha⁻¹ under direct radiation in El Carmen de Bolívar and ‘Morita II’ showing strong responsiveness in Montería. These results demonstrate that photosynthetic plasticity and leaf yield in S. rebaudiana depend on genotype × radiation × environment interactions, supporting location-tailored radiation management combined with targeted genotype deployment. Full article

Glassy carbon electrodes (GCEs) have gained increased attention for the sensitive electrochemical detection of heavy metals due to their excellent chemical stability, wide potential window, and good electrical conductivity. These characteristics make GCEs an effective platform for sensor development. In particular, nanomaterial-modified GCEs have emerged as a promising strategy, offering enhanced sensitivity, selectivity, and faster response compared to conventional analytical techniques. This review summarizes recent advances over the past five years in the use of GCEs modified with chemically synthesized nanoparticles for the simultaneous detection of multiple heavy metal ions, including cadmium, lead, mercury, and chromium. It also includes how quantum chemical methods have aided our understanding of these phenomena. Heavy metals pose significant environmental and public health risks, with well-documented neurological, cardiovascular, reproductive, and carcinogenic effects, highlighting the need for accurate and rapid monitoring methods. Regulatory limits established by organizations such as the World Health Organization and the Environmental Protection Agency further emphasize the demand for highly sensitive detection technologies. This review examines the fundamental properties of GCEs, common nanomaterial modification techniques, and their application in multi-ion detection systems. Key advantages such as cost-effectiveness, portability, and adaptability to diverse sample matrices are highlighted. Current challenges, including electrode fouling, selectivity, and matrix interference, are also addressed, along with future perspectives for improving GCE-based sensors for real-world environmental monitoring. Full article

The emergence of quantum computing poses a significant threat to the security of traditional encryption methods employed in satellite communication. To mitigate this vulnerability and enhance cybersecurity in the next generation of communication systems, a novel physical-layer solution is presented. This approach centers on enhancing satellite link security through the analysis of stochastic atmospheric scintillation, facilitated by machine learning (ML). The proposed method safeguards ground stations against Machine-in-the-Middle (MITM) attacks perpetrated from aerial platforms (AP) such as drones or Unmanned Aerial Vehicles (UAVs). The underlying principle leverages the distinct statistical parameters inherent to received signals. These parameters are contingent upon the specific propagation channel, which is influenced by rapid tropospheric scintillation. As signals from legitimate satellites and malicious drones traverse separate spatial paths within the dynamic atmosphere, they exhibit demonstrably divergent scintillation statistics. Wavelet filtering is employed to extract these statistics from the incoming signal. The extracted data is subsequently processed through an ML algorithm, enabling the differentiation between satellite signals and potential spoofing signals emanating from drones. Extensive simulations have been conducted, illustrating the efficacy and robustness of the proposed architecture, consistently achieving an authentication rate exceeding 98% across diverse scenarios. Additionally, experimental results obtained from measurement data collected from Nilesat and Eutelsat satellites at a ground station in Israel provide empirical validation for this innovative approach. Full article

Accurate estimation of the state of charge (SOC) is essential for the safe and efficient operation of lithium-ion batteries. Conventional Adaptive Unscented Kalman Filter (AUKF) methods often exhibit limited accuracy, primarily due to the empirical selection of process and measurement noise covariance matrices. To overcome this limitation, this study proposes a QPSO-AUKF algorithm based on a second-order RC equivalent circuit model, which integrates Quantum-behaved Particle Swarm Optimization (QPSO) with online parameter identification. In this approach, the QPSO algorithm optimizes the noise covariance matrices, which are subsequently used within the AUKF framework for SOC estimation. MATLAB R2020a simulations conducted on the Maryland and Wisconsin datasets demonstrate that the QPSO-AUKF reduces the root mean square error (RMSE) by more than 60% compared with the conventional AUKF, indicating a significant improvement in SOC estimation accuracy. Full article

Twisted graphene/hexagonal boron nitride (TG/hBN) bilayers, with their tunable moiré potential and atomically clean interfaces, offer an ideal platform for high-performance single-electron transistors (SET). Combining quantum transport simulations with first-principles calculations, we systematically investigate how stackings (AA, AB, BA), twist angles, quantum dot sizes, and gate-island coupling jointly modulate SET performance. Our central finding reveals a clear hierarchy: quantum dot size and stacking configuration dominate charge stability and transport, while twist angle introduces precise control of charge state. All stackings exhibit sharp, symmetric Coulomb blockade peaks, confirming stable single-electron tunneling, and gate coupling remains highly linear across parameters. Strikingly, only AA-stacked devices show a systematic twist-angle-dependent shift in conductance peaks, a direct signature of its perfect atomic registry and extreme angular sensitivity. This work establishes an idealized “size-, stacking-, and twist-angle modulation” design principle and theoretical roadmap based on TG/hBN, providing fundamental insights for future experimental exploration of tunable, low-noise quantum-electronic devices from twisted 2D heterostructures. Full article

The convergence of cyber-physical systems (CPSs), operational technologies (OTs), industrial control systems (ICSs), and quantum computing poses unprecedented challenges for the security and resilience of critical infrastructures (CIs). As quantum capabilities progress, classical cryptographic mechanisms such as RSA and ECC face increasing risks from quantum algorithms (Shor and Grover), while CPS and OT remain constrained by long life cycles, heterogeneity, and limited upgrade capabilities. This study conducts a systematic literature review (SLR) following a GQM-PICO-PRISMA methodological framework to examine 66 primary studies, selected from 1.522 records identified in seven scientific databases and published between 2005 and 2025. The review identifies dominant research domains, ranging from IoT/IIoT security to machine learning-based intrusion detection in CPS/OT environments, and synthesizes key challenges. Findings reveal significant fragmentation in CPS taxonomies, limited integration of post-quantum cryptography (PQC) into OT/ICS protocols, a scarcity of real-world datasets, and insufficient quantum threat modeling (QTM). This work consolidates and structures prior evidence into a literature-derived classification of quantum-era CPS/OT cybersecurity topics and distills a prioritized research agenda for advancing quantum-resilient architectures. Full article

Iodine is a non-essential element for plants, yet recent studies have shown that it plays a role in mitigating abiotic stress. Heat stress (HS) and water stress (WS) impair maize growth and development, especially during the reproductive phase. This study evaluated whether iodine applications could mitigate HS and combined HS + WS during maize flowering. The experiment was conducted under greenhouse conditions, growing maize plants in pots containing 3 kg of Oxisol. Treatments included foliar or soil applications of iodine under two stress conditions (HS and HS + WS). Iodine was applied to the soil via top dressing and as a foliar application at the start of flowering. On the last day of stress, chlorophyll levels, specific enzyme activity, compatible osmotic solutes, relative water content (RWC), and Fv:Fm (photosynthetic quantum efficiency) were measured. Grain yield was determined at the end of the crop. There was no mitigation of stress with iodine application under combined stress (HS + WS). Under HS, foliar application of iodine, compared with no iodine application mitigated stress, increasing Fv:Fm by 58% (values of 0.73 for foliar iodine application versus 0.02 for no iodine application), RWC by 83% (values of 99% for foliar iodine application), and grain yield by 35%, along with higher levels of chlorophyll a (+28%), chlorophyll b (+73%), total chlorophyll (+31%), and superoxide dismutase activity (SOD). This was also associated with a reduction in sucrose, reducing sugars, total soluble sugars, and total free amino acids. This increase in chlorophyll levels suggests greater photosynthetic capacity, while the higher SOD activity indicates a strengthened antioxidant system under HS. These mechanisms together maintain carbon assimilation and reproductive development, thereby increasing grain yield. Thus, it was concluded that iodine could help reduce HS effects during maize flowering. Full article

The 1626 nm laser is an essential component for conducting superlattice research on the strontium atomic clock platform. The superlattice constructed with the 1626 nm and 813 nm lasers will facilitate cutting-edge quantum information research focused on topological quantum states transport. We demonstrate an idler-resonant optical parametric oscillator that achieves 1626 nm laser output based on pump enhancement technology. Through a well-designed external cavity, a laser output of 127 mW at 1626 nm has been achieved, with a corresponding pump quantum conversion efficiency of 50% and a pump threshold of 110 mW. The long-term power stability of the output laser is ±1.5% per hour. Variations in the pump cavity modes under different experimental conditions have been measured, and the impedance matching process of the pump light within the cavity has been discussed. The 1626 nm laser and the associated technologies reported in this manuscript will provide optical support for the investigation of superlattice physics on the strontium optical lattice clock platform. Full article