Search Results (3,893)

Zinc oxide (ZnO) nanomaterials have attracted widespread attention from researchers due to their morphology-dependent properties, eco-friendly characteristics, and potential as a sustainable photocatalyst with a broad range of applications. Therefore, in this study, three different ZnO nanostructures—nanosheets (NSs), nanoflowers (NFs), and nanorods (NBs)—were synthesized via a controlled precipitation method. Among these, NFs exhibited the highest photocatalytic efficiency. The obtained samples exhibited broad optical absorption edges extending into the visible region (corresponding to apparent energies of 1.81–2.09 eV), which is attributed to the sub-bandgap states induced by oxygen vacancies rather than intrinsic bandgap narrowing—far lower than the bandgap of bulk ZnO (3.37 eV). Their photocatalytic performance was evaluated by the degradation of Methyl Blue (MB), Methyl Orange (MO), and Rhodamine B (RhB) under UV or sunlight. Notably, the NFs achieved rapid degradation of MB and RhB within 90 min under UV irradiation without the addition of any H₂O₂, demonstrating their effectiveness and cost-effectiveness for practical applications. Although H₂O₂ inhibited the degradation of MB and RhB, it promoted the decomposition of MO. Furthermore, the ZnO NFs exhibited excellent recyclability in five consecutive degradation cycles. The self-synthesized ZnO nanomaterials in this study, with their broad-spectrum absorption, high stability, and eco-friendly properties, demonstrate their potential as an efficient and low-cost photocatalyst for large-scale wastewater treatment. Full article

Cosmology is living through fascinating times, where new observations from ground and space telescopes are questioning the established paradigm, the so-called $\mathsf{\Lambda }$ Cold Dark Matter model. The particle nature of Dark Matter is severely constrained by underground experiments, while recent observations by galaxy surveys indicate that the cosmological constant ($\mathsf{\Lambda }$) may not be constant after all. Furthermore, observations at high redshift of fully formed galaxies with massive black holes at their centers by the James Webb Space Telescope, as well as black holes with unexpected properties observed by the LIGO-Virgo gravitational wave detectors, are driving an in-depth revision of our assumptions in models of structure formation and the evolution of the Universe. I propose exploring two new paradigms to account for Dark Matter and Dark Energy, based on known physics, without introducing new particles into the Standard Model of Particle Physics. I will extend the primordial spectrum of fluctuations to small scales with new statistical properties to provide a viable Primordial Black Hole scenario for Dark Matter, and will include non-equilibrium thermodynamics in the expanding Universe, in the form of General Relativistic Entropic Acceleration, to explain Dark Energy. My proposal could provide a unified explanation for a plethora of interrelated multi-epoch, multi-scale, and multi-probe observations from present and future Gravitational Wave detectors, Large Scale Structure observatories, and Cosmic Microwave Background experiments. It emphasizes the need to develop new theoretical ideas hand-in-hand with observations to acquire a deeper understanding of our universe. If these ideas are correct, they will open a new window into the early universe and a new fundamental understanding of gravity in the late universe. Full article

In order to validate the structure and ascertain its conformity with the stipulated design conditions, the responses and members’ internal forces of the finite element model of structures under artificial earthquakes must be simulated. There are a variety of methodologies to generate the artificial earthquake waveform that corresponds to the design response spectrum. The frequency domain method is intuitive and convenient for generating the artificial earthquake waveform that corresponds to the design response spectrum. However, fluctuations in energy within specific frequency bands influence the acceleration responses across all frequency ranges. This, in turn, impedes the convergence process during the generation of artificial earthquake waveforms. The present study proposes a refined procedure for the generation of artificial earthquake waveforms in the frequency domain. The procedure can be used to generate the artificial earthquake that occurred in the vicinity of the Maanshan Nuclear Power Plant in Taiwan. A comparison of the parameters effect, including the cover range of the weighted function and the peak ground acceleration of the initial guess, were conducted to ascertain the convergence properties of the proposed approach. Full article

As multiple-degree-of-freedom (3-DOF) wave energy converters (WECs) have demonstrated the ability to produce more power than single-degree-of-freedom devices, the challenge of designing buoys for efficient energy harvesting has increased in complexity. In this paper, a cylindrical WEC is designed to naturally resonate in surge, pitch, and heave modes at a specific target frequency of 0.2 Hz. By utilizing a penalty-based optimization method to balance buoyancy requirements with natural resonance, the design achieves minimal control force input, thereby reducing fluctuations in energy output and local energy storage requirements. The performance is evaluated under irregular sea states using a Bretschneider spectrum. Results indicate that a buoy optimized to naturally resonate at the modal frequency of a sea state provides consistent power with significantly reduced reactive power demand compared to non-optimized designs. Full article

Background: Radiotherapy is essential for skull base tumor management but carries the risk of radiation-induced brain injury (RIBI). This spectrum ranges from transient radiation-induced contrast enhancement (RICE) to irreversible necrosis. Distinguishing these entities from tumor progression is critical, particularly with the increasing adoption of proton therapy. Methods: A comprehensive narrative review of the peer-reviewed literature was conducted up to October 1, 2025. The search strategy focused on adult patients treated for skull base malignancies, synthesizing data on dose–volume metrics, incidence rates, and modality-specific toxicity profiles. Results: RIBI represents a pathophysiological continuum. (a) Descriptive imaging patterns: In prospective proton therapy series, focal RICE occured in 15% of patients, typically at a median of 12 months, and often resolved spontaneously. (b) Modality comparison: Although proton therapy reduces integral brain dose versus photon therapy, elevated linear energy transfer (LET) at the distal Bragg peak may contribute to focal radiation-associated image changes (RAIC), particularly in the temporal lobes. (c) Risk stratification and diagnosis: Risk increased when >1% of the healthy brain received >57.6 Gy (Relative Biological Energy (RBE)) or when V67Gy exceeded 0.17 cc. Advanced MRI and amino acid positron emission tomography (PET) improved differentiation between radiation effects and tumor recurrence. Conclusions: Post-radiation imaging changes are common and often benign. Distinguishing RICE from progression requires multimodal imaging and adherence to specific dose constraints. Management should prioritize surveillance for asymptomatic lesions. Full article

This review focuses on electromagnetic imaging methods widely used in urban geophysics and civil engineering. The rapid growth of the urban population and the increase in the frequency of extreme events related to climate change make novel approaches to the geophysical monitoring of urban areas and civil infrastructures essential in the context of programs for the sustainability and resilience of cities. In this scenario, there is a growing interest in using ground-based electromagnetic methods to investigate strategic infrastructures such as bridges, tunnels, dam embankments, power plants, energy plants and pipelines in a non-invasive way. The development of cost-effective, user-friendly sensor arrays, robust methodologies for tomographic data inversion, and AI-based and machine learning techniques has rapidly transformed these methods. This review critically analyzes the results relating to the application of ground-based electromagnetic methods in infrastructure monitoring and surveillance over the past 20 years by presenting a selection of best practice examples and studies planned to support programs for the resilience and maintenance of engineering infrastructures. The analysis reveals that these methods are highly effective in addressing a broad spectrum of monitoring issues in view of effective maintenance of civil infrastructures. In fact, these methods are essential for detecting the geometry of buried objects (e.g., bars and voids), enabling the early detection of degradation phenomena, and mapping water infiltration processes inside structures, as well as many other challenging applications. Finally, prospectives for development are identified in terms of using soft robot technologies, miniaturized sensors, and AI-based methods to acquire, process and interpret data as well as to design smart operational guidelines for infrastructure management. Full article

Polyhalite, K₂SO₄•MgSO₄•2CaSO₄•2H₂O, a ternary evaporite mineral, is commonly found in evaporitic rock salt strata, where it acts as an indicator mineral for potash evaporite deposits. As a directly exploitable mineral potash fertilizer, polyhalite serves as an important substitute for potassium resources. The thermodynamic properties of polyhalite remain poorly characterized experimentally; consequently, current estimates predominantly rely on predictive modeling and indirect experimental approaches. The Raman spectra of free SO₄²⁻ vibrational modes in various sulfate minerals are sensitive to the local symmetry and hydrogen-bonding environment within crystal hydrates, and are directly influenced by the surrounding crystal field. This sensitivity makes Raman spectroscopy a powerful tool for investigating and identifying the crystal structures of sulfate minerals. In this work, the thermodynamic and Raman vibrational properties of polyhalite were investigated using density functional theory (DFT). Phonon calculations at the optimized geometry were employed to compute polyhalite’s key thermodynamic properties—specific heat, entropy, enthalpy, Gibbs free energy, and Debye temperature—over a temperature range of 0–1000 K. The results showed that: (1) the computed volume exhibited minimal error, approximately 0.87%, compared to experimental data; (2) the calculated values for the isobaric heat capacity and entropy were 420.72 and 531.39 J·mol⁻¹·K⁻¹ at 298.15 K, respectively; and (3) the calculated value for the free energy of formation at 298.15 K was −5670 kJ·mol⁻¹. The computed Raman spectrum results showed that the typical spectral features of polyhalite are: (1) ν1 for 1024 cm⁻¹, symmetric stretching mode; (2) ν2 for 464 cm⁻¹, symmetry bending mode; and (3) ν4 for 627 cm⁻¹, anti-symmetry bending mode. Full article

This Data Descriptor presents an anonymized, shuffled dataset of creatinine-normalized urinary metabolite measurements from 73 Bulgarian children with autism spectrum disorder (ASD), released to support reuse in secondary analyses and cross-cohort comparisons. The public release represents a pathway-oriented 24-marker subset from a broader urinary diagnostic panel, assembled as a self-contained resource for investigators working in these metabolic domains. Spot urine results are provided as individual-level values after creatinine normalization; for trimethylamine, values below the limit of quantification (LOQ) were replaced with LOQ/2. The deposit contains measurements for 24 urinary markers grouped into three functional classes (neurotransmitters and aromatic amino acid precursors; one-carbon/methylation and vitamin-related metabolites; and energy metabolism/organic acids with microbiome-related amines). The underlying cohort comprised children aged 3–13 years, and no contemporaneous neurotypical control group was enrolled. Second-morning, midstream, acid-stabilized spot urine samples were collected within the provider’s workflow; metabolites were measured by LC–MS/MS, and spot urinary creatinine was measured enzymatically for normalization. The release includes the results table in both XLSX and CSV formats, a reference limits and units file for contextual interpretation, a data dictionary, a README, a changelog, and SHA-256 checksums for integrity verification. The public files contain de-identified analytical variables only and omit individual-level demographics, dates, standalone urinary creatinine, and richer clinical metadata to preserve anonymity. Full article

To enable non-destructive quantitative characterization of constituent content in C/C–SiC ceramic-matrix composites, this study develops a physics-guided framework based on multispectral photon-counting X-ray detection. In practical photon-counting measurements, multispectral attenuation features are jointly distorted by detector-response non-idealities, including charge sharing, K-escape, and finite energy resolution, as well as by beam-hardening effects from the polychromatic X-ray source. To address this coupled problem, a Geant4 11.2-based detector-response model was incorporated into a unified correction workflow together with beam-hardening compensation, so that physically consistent multispectral attenuation vectors could be recovered for subsequent constituent inversion rather than merely for spectrum restoration. On this basis, a fine-grained theoretical database covering different SiC mass fractions was established, and quantitative constituent inversion was achieved by matching the corrected attenuation features to the database. Experimental results show that the proposed framework effectively suppresses thickness-dependent bias in attenuation measurements and yields an average relative error below 3% for pure aluminum. For C/C–SiC composites, the SiC mass fraction can be quantified with an accuracy better than 3 wt%. These results demonstrate that the proposed method provides a practical non-destructive route for constituent-content characterization in heterogeneous ceramic-matrix composites and is valuable for manufacturing quality control and in-service assessment. Full article

Aiming to address the problem of extracting the remote sensing FTIR spectral characteristics of the hot jet of a certain type of aero-engine under different working conditions, this paper proposes a feature construction algorithm for the remote sensing FTIR spectral characteristics of the aero-engine hot jet based on the fusion of the original spectral features and the deep spectral features. The infrared spectrum was collected at a distance of 280 m, covering the spectral range of 2.5–15 μm with a resolution of 1 cm⁻¹. The Neighborhood–Autoencoder Integration Dual-Branch Network (NAIDN) feature construction algorithm is proposed. This algorithm contains a neighborhood integration branch and an autoencoder branch. The neighborhood integration branch converts the radiation intensity values of discrete wavenumber points into local energy aggregation features through a sliding window, accurately extracting the key physical information in the original spectrum. The autoencoder branch uses a three-layer fully connected neural network architecture to mine the deep spectral features of the spectral data. The algorithms of the two branches not only retain the physical interpretability of spectral analysis but also capture the multi-parameter coupling information hidden in the hot jet spectrum through the representation learning ability of the autoencoder, achieving feature fusion across spatial dimensions. Compared with traditional feature construction algorithms, the dual-branch feature construction algorithm proposed in this paper has stronger comprehensive representation capabilities. The content of carbon dioxide (CO₂) and cyanide groups (-C≡N) in the hot jet under different operating conditions varies significantly. In the experiment, an unsupervised clustering algorithm, the Agglomerative Clustering classifier, is selected, and the classification accuracy of the features extracted by the algorithm in this paper reaches 92.97% on this classifier, thereby verifying the effectiveness of the algorithm in this paper. Full article

Heterogeneous photocatalysis is one of the most versatile and widely studied photochemical approaches for the degradation of recalcitrant pollutants. Owing to its favorable physicochemical properties, titanium dioxide (TiO₂) remains one of the most investigated semiconductor photocatalysts. However, its wide band-gap energy (3.2 eV) restricts its photoactivity to the UV region, which represents only a small fraction of the solar spectrum. A major challenge in this field is therefore the development of TiO₂-based materials capable of operating efficiently under visible light irradiation, enabling the use of solar energy as a sustainable primary source. Several strategies have been explored to extend the optical response of TiO₂, among which elemental doping remains one of the most effective and commonly applied. In this work, we conducted systematic comparative analysis to evaluate the photocatalytic performance of TiO₂ modified through different doping approaches. Sixty-one scientific reports published between 2015 and 2025 were analyzed, comparing three categories of dopants: (i) metal dopants, (ii) non-metal dopants, and (iii) co-doping systems. In the first section, we discuss fundamental concepts of photocatalysis and recent advances in doping strategies and surface modifications aimed at enhancing the photocatalytic performance of TiO₂. In the second section, we present a comparative analysis based on 61 scientific reports focusing on TiO₂ doping and co-doping processes. Finally, this study summarizes the different categories of doped TiO₂ photocatalysts by comparing the photocatalytic performance employing an alternative performance metric. Full article

Rare earth elements (REEs) play an important role in emerging renewable energy technology, the production of advanced materials, energy conservation, and high-end manufacturing industries, making them an irreplaceable strategic resource. The diagnostic spectral absorption features of REEs in the visible and near-infrared spectrum can be effectively used for identifying the occurrences of REEs on the Earth’s surface. This study systematically compared three airborne hyperspectral sensors—HyMap, CASI-1500h, and AisaFENIX 1K—for detecting REEs in the Bayan Obo area of Inner Mongolia, China. The CASI-1500h imagery performed most effectively in identifying the locations of REEs among the three sensors evaluated here. Additionally, this study proposed a hyperspectral workflow for REE identification, which enabled the detection of REE-bearing minerals regardless of the host rock types—including carbonatites and associated dikes, fenite-syenites, and metamorphic feldspar-quartz sandstone. Laboratory-based spectroscopy and mineral chemistry analyses indicated that the absorption features of the REE-bearing mineral monazite within the 400–1000 nm range can be ascribed to Nd³⁺. This study demonstrates the potential of airborne hyperspectral technology for efficient and large-scale exploration of REE deposits. Full article

As a branch of nondestructive testing (NDT), Pulsed Eddy Current Testing (PECT) is characterized by its wide frequency spectrum and high penetration depth. After years of development, it has been widely applied to defect detection and material characterization of key components in industries such as petrochemicals, new energy, and aerospace. With the large-scale application of new energy sources like liquefied natural gas (LNG), methanol, and liquid hydrogen, the demand for NDT of non-ferromagnetic materials (e.g., austenitic stainless steel) has surged. However, challenges such as electromagnetic leakage caused by low magnetic permeability and the lift-off effect induced by protective layers impose stricter requirements on inspection technologies, driving the evolution of PECT towards adaptability in complex scenarios. This paper systematically reviews the latest advances in PECT technology, covering detection sensors, modeling methods, detection signal processing, and engineering applications. With a particular emphasis on research outcomes from the past decade, this paper also proposes potential directions for future development, aiming to provide a reference for innovative research and the industrial promotion of PECT technology. Full article

Many patients with primary or metastatic lung cancer are not candidates for surgery, additional radiation, or further systemic therapy due to advanced age or comorbidities; this creates a need for minimally invasive locoregional options. Image-guided thermal ablation (IGTA) is being applied across a broader spectrum of lesions, while bronchial artery chemoembolization (BACE) is emerging as a therapy option for treatment-refractory advanced disease. Recent studies in thermal ablation have focused on optimizing energy delivery and protocols, as well as improving ablation zone predictability and analysis. Advances in lesion targeting, including cone beam CT fusion, electromagnetic guidance, and robotic-assisted ablation, allow for treatment of subcentimeter and ground-glass lesions in anatomically challenging locations. Growing clinical experience supports IGTA for intrathoracic oligoprogression and as salvage therapy after recurrence. In the endovascular space, improved imaging, microcatheters, and drug-eluting microspheres have expanded the use of BACE for disease and symptom control in advanced lung cancer. Multimodal strategies combining minimally invasive locoregional treatments with systemic therapies and radiation are being explored, with early data showing improvements in survival without increased toxicity. This narrative review synthesizes emerging techniques, clinical data, and indications for percutaneous and endovascular lung cancer treatments and underscores the need for prospective and randomized trials to refine patient selection, treatment sequencing, and long-term outcomes. Full article

Light quality plays a decisive role in controlled-environment agriculture, shaping plant morphology, physiology, and productivity. This study investigated the impact of far-red (FR) light on Cannabis sativa L. by comparing two different application strategies: continuous FR supplementation throughout 12 h of the photoperiod and end-of-day (EOD) FR exposure applied only at the end of the light period. In both treatments, FR was added to a background spectrum of red and blue (RB) light, while a control group grown under RB light alone was included to assess the specific effects of FR on plant growth, physiological responses, and flowering. Continuous FR exposure induced pronounced shade-avoidance traits, increasing plant height by 9% and petiole length by 17% relative to the control, and raised leaf dry weight to 12.9 g, 9% higher than under EOD (11.7 g) and 16.3% higher than under RB alone (10.8 g). Besides plant height and petiole length, both FR and EOD treatment induced limited morphological adjustments but increased chlorophyll content by 9%, resulting in greater canopy expansion and photosynthetic potential. However, flowering time was unaffected by spectral treatment, confirming that Cannabis floral induction is tightly regulated by photoperiod rather than light quality. Energy-use analysis revealed that EOD supplementation achieved many of the benefits of continuous FR while reducing overall consumption, but energy-use efficiency analysis proved FR as the more efficient treatment. These findings highlight the potential of FR light, particularly when applied continuously, to optimize vegetative growth and canopy physiology in controlled-environment Cannabis cultivation, while EOD strategies offer a practical compromise between cost savings and physiological benefits. Full article