Search Results (552)

The rapid global expansion of offshore wind energy (OWE) has established it as a critical component of the renewable energy transition; however, this development concurrently introduces significant underwater noise pollution into marine ecosystems. This paper provides a comprehensive review of the acoustic footprint of OWE across its entire lifecycle, rigorously distinguishing between the high-intensity, acute impulsive noise generated during pile-driving construction and the chronic, low-frequency continuous noise associated with decades-long turbine operation. We critically evaluate the engineering capabilities and limitations of current underwater acoustic monitoring architectures, including buoy-based real-time monitoring nodes, cabled high-bandwidth systems (e.g., cabled hydrophone arrays with DAQ/DSP and fiber-optic distributed acoustic sensing, DAS), and autonomous seabed archival recorders (PAM deployment). Furthermore, documented biological impacts are synthesized across diverse taxa, ranging from auditory masking and threshold shifts in marine mammals to the often-overlooked sensitivity of invertebrates and fish to particle motion—a key metric frequently missing from standard pressure-based assessments. Our analysis identifies a fundamental gap in current governance paradigms, which disproportionately prioritize the mitigation of short-term acute impacts while neglecting the cumulative ecological risks of long-term operational noise. This review synthesizes recent evidence on chronic operational noise and outlines a conceptual pathway from event-based compliance monitoring toward long-term, adaptive soundscape management. We propose the implementation of integrated, adaptive acoustic monitoring networks capable of quantifying cumulative noise exposure and informing real-time mitigation strategies. Such a paradigm shift is essential for optimizing mitigation technologies and ensuring the sustainable coexistence of marine renewable energy development and marine biodiversity. Full article

This study investigates the interface between cement hydration, low-field NMR relaxometry, and the incorporation of carbon-based fillers into cementitious materials. The objective is to provide NMR-based insights into how carbon black (CB) and an acrylic superplasticizer (SP) influence cement hydration and the resulting microstructural evolution. CB was integrated into white Portland cement (WPC) using both wet and dry mixing approaches, with water content and SP dosage varied independently. First, water-based “inks” containing different SP/CB weight ratios were prepared and evaluated through dynamic light scattering (DLS) and ζ-potential measurements to assess colloidal stability and dispersibility. For the wet-mixing route, an in situ NMR experiment was performed to monitor the progressive incorporation of carbon ink into cement pastes while increasing the water content. The ability to distinguish ink-related signals from those originating from the cement paste represents a promising step toward non-destructive assessments of carbon dispersion in fresh pastes. Separately, ex situ NMR measurements were performed on samples extracted from dry-mixed pastes with various SP dosages. These experiments mark the SP-induced delay in hydration and the refinement of the pore network that is also associated with improved particle dispersion. Complementary optical microscopy (OM) and ultrasonic pulse velocity (UPV) measurements on hardened samples corroborate the NMR findings. Full article

In this work we report the results of analysis of the acoustic signal generated by the interaction of a nanosecond laser pulse (30 mJ, 1064 nm) with various residues placed on a silica wafer. The signal was captured by a unidirectional microphone placed 30 mm from the laser-generated plasma. The examined sample classes, other than the clean wafer, included particles from soils and rocks, carbonates, nitro precursors, ash, coal, smeared diesel, and particles of explosives. We tested three types of explosives, namely PETN, RDX, and HMX, having different origins. For the explosives, the acoustic signal showed a faster rise, larger amplitude, different width, and attenuation compared with the other sample classes. By subtracting the acoustic signal from the wafer at the same position, obtained after four cleaning laser pulses, the contribution of echoes was eliminated and true differences between the residue and substrate became evident. Through four different features in the subtracted signal, it was possible to classify explosives without the presence of false positives; the estimated limit of detection was 15 ng, 9.6 ng, and 18 ng for PETN, RDX, and HMX, respectively, where the mass was extrapolated from nano-printed samples and LIBS spectra acquired simultaneously. Furthermore, HMX was distinguished from the other two explosives in 90% of the cases; diesel and coal were also recognized. We also found that explosives deposited through wet transfer behaved as inert substances for the tested masses up to 30 ng. Full article

Wastewater treatment facilities of a diameter of approximately 15 m or more provide the opportunity to process large volumes of stormwater. The current report investigates the operation of a stormwater radial precipitator, without an impeller, working with particles of various sizes. A distinguishing feature is that the two-phase flow is solely gravity-driven, which leads to reduced energy requirements. This entails the necessity of a facility in which the linear and the local losses are minimized as much as possible. Linear losses can be reduced by decreasing the precipitator’s size. The initially proposed 15 m diameter proved to be ineffective since the sand only reached a certain zone and could not flow further to the outlet due to the insufficient energy. Therefore, it was necessary to reduce the size of the radial precipitator, which resulted in a shorter path for the sand particles and the water, which, in turn, reduced the linear resistance. As for the local losses, it turned out that many areas of the precipitator construction could be geometrically modified to significantly reduce the energy loss of the sand–water mixture. The boundary layer cannot be removed. However, it is possible the size and the number of vortex structures inside the settler to be reduced in order to create an optimal working environment. Full article

In soils, it is key to not simply determine the behavior of the major elements but also understand the fate of trace and ultra-trace elements that can often have disproportionate effects on these complex systems. Soils, including agricultural soils, constitute a reservoir of nanoparticles and natural colloids of multiple origins. Nonetheless, only limited information is available on the concentrations and fate of nanoparticles in soils, due largely to the difficulty of distinguishing anthropogenically generated particles from the complex soil matrices in which they are found. Bulk measurements are often unable to quantify the key contributions of trace pollutants (i.e., needle in a haystack); however, single particle techniques have recently become available for studying complex agricultural systems, including soils. For example, the characterization of engineered nanoparticles or incidentally generated particulate pollutants within a natural soil or sediment is now possible using techniques such as single particle inductively coupled plasma mass spectrometry (SP-ICP-MS). Nonetheless, in order to exploit the single particle techniques, it is first necessary to representatively sample the soils. The approach presented here has been designed to help better understand the impact of incidental and engineered nanoparticles on agricultural soils. In this study, we examine two approaches for extracting colloidal particles (CP) from soils in order to facilitate their characterization by single particle inductively coupled plasma mass spectrometry using a sector field- (SP-ICP-SF-MS) and time-of-flight- (SP-ICP-ToF-MS) based instruments. A novel sampling methodology consisting of an ultrasound-assisted continuous-flow extraction (USCFE) was developed and compared to a commonly used batch extraction procedure. Metal containing colloidal particles (M–CP) were quantified and characterized following their extraction in ultrapure water and tetrasodium pyrophosphate (TSPP). At least five successive extraction cycles of 18 h each were required to optimally extract Si–CP (ca. 6 × 10¹⁵ kg⁻¹) using the batch extraction approach, whereas similarly high numbers of CP could be extracted by USCFE in about 3 h. The combined use of continuous flow, ultrasound and TSPP improved the sampling of colloidal particles and nanoparticles from an agricultural soil. Due to its higher sensitivity, SP-ICP-SF-MS was used to measure the smallest detectable M–CP in the soil extracts. SP-ICP-ToF-MS was used to determine the multi-elemental composition of the extracted colloidal particles. Full article

Understanding the fluid dynamics of fluidized beds loaded with biomass pellets is of significant value for the design of wood waste gasifiers. In the present study, cylindrical wood pellets are loaded into a lab-scale cold gasifier unit at 2.5 vol% and 7.5 vol% concentrations and studied at superficial air velocities of 0.25, 0.282, and 0.344 m/s (corresponding to 80, 90, and 110 SCFM). Measurements of bubbles, sand particles, and biomass pellets are taken at a 45 cm height from the distributor plate, and at 9, 12, 15, 18, and 21 cm radial positions from the column wall by employing the CREC-GS-Optiprobes, a valuable integrated fiber optic-laser tool system. A new data processing methodology is established using laser signals that are reflected from the outer surface of aluminum-foil-wrapped cylindrical wood pellets. In addition, a new algorithm is implemented to distinguish pellet-reflected signals from those of bubbles and emulsion-phase particles. On this basis, for the first time, a Phenomenological Probabilistic Predictive Model (PPPM), is considered to predict Bubble Axial Chords (BACs) and Bubble Rise Velocities (BRVs), in a sand fluidized bed loaded with biomass pellets. This is accomplished within a set band of values accounting for three standard deviations from their means or including 85.9% of the bubbles measured. Thus, it is demonstrated that the PPPM is adequate to establish the constrained random motion of bubbles in sand fluidized beds, under the influence of uniformly distributed biomass pellets. It is anticipated that the findings of the present study will be of significant value for the design of sand biomass gasifiers of different scales. Full article

Background/Objectives: The vestibular labyrinth is classically viewed as a sensor of low-frequency head motion—linear acceleration for the otoliths and angular velocity/acceleration for the semicircular canals. However, there is now substantial evidence that air-conducted sound (ACS) can also activate vestibular receptors and afferents in mammals and other vertebrates. This sound sensitivity underlies sound-evoked vestibular-evoked myogenic potentials (VEMPs), sound-induced eye movements, and several clinical phenomena in third-window pathologies. The cellular and biophysical mechanisms by which a pressure wave in the cochlear fluids is transformed into a vestibular neural signal remain incompletely integrated into a single framework. This study aimed to provide a narrative synthesis of how ACS activates the vestibular labyrinth, with emphasis on (1) the anatomical and biophysical specializations of the maculae and cristae, (2) the dual-channel organization of vestibular hair cells and afferents, and (3) the encoding of fast, jerk-rich acoustic transients by irregular, striolar/central afferents. Methods: We integrate experimental evidence from single-unit recordings in animals, in vitro hair cell and calyx physiology, anatomical studies of macular structure, and human clinical data on sound-evoked VEMPs and sound-induced eye movements. Key concepts from vestibular cellular neurophysiology and from the physics of sinusoidal motion (displacement, velocity, acceleration, jerk) are combined into a unified interpretative scheme. Results: ACS transmitted through the middle ear generates pressure waves in the perilymph and endolymph not only in the cochlea but also in vestibular compartments. These waves produce local fluid particle motions and pressure gradients that can deflect hair bundles in selected regions of the otolith maculae and canal cristae. Irregular afferents innervating type I hair cells in the striola (maculae) and central zones (cristae) exhibit phase locking to ACS up to at least 1–2 kHz, with much lower thresholds than regular afferents. Cellular and synaptic specializations—transducer adaptation, low-voltage-activated K⁺ conductances (K_LV), fast quantal and non-quantal transmission, and afferent spike-generator properties—implement effective high-pass filtering and phase lead, making these pathways particularly sensitive to rapid changes in acceleration, i.e., mechanical jerk, rather than to slowly varying displacement or acceleration. Clinically, short-rise-time ACS stimuli (clicks and brief tone bursts) elicit robust cervical and ocular VEMPs with clear thresholds and input–output relationships, reflecting the recruitment of these jerk-sensitive utricular and saccular pathways. Sound-induced eye movements and nystagmus in third-window syndromes similarly reflect abnormally enhanced access of ACS-generated pressure waves to canal and otolith receptors. Conclusions: The vestibular labyrinth does not merely “tolerate” air-conducted sound as a spill-over from cochlear mechanics; it contains a dedicated high-frequency, transient-sensitive channel—dominated by type I hair cells and irregular afferents—that is well suited to encoding jerk-rich acoustic events. We propose that ACS-evoked vestibular responses, including VEMPs, are best interpreted within a dual-channel framework in which (1) regular, extrastriolar/peripheral pathways encode sustained head motion and low-frequency acceleration, while (2) irregular, striolar/central pathways encode fast, sound-driven transients distinguished by high jerk, steep onset, and precise spike timing. Full article

Our Sun is the closest X-ray astrophysical source to Earth. As such, it makes for a strong case study to better understand astrophysical processes. Solar flares are particularly interesting as they are linked to coronal mass ejections as well as magnetic field reconnection sites in the solar atmosphere. Flares can therefore provide insightful information on the physical processes at play on their production sites but also on the emission and acceleration of energetic charged particles towards our planet, making it an excellent forecasting tool for space weather. While solar flares are critical to understanding magnetic reconnection and particle acceleration, their hard X-ray polarization—key to distinguishing between competing theoretical models—remains poorly constrained by existing observations. To address this, we present the CUbesat Solar Polarimeter (CUSP), a mission under development to perform solar flare polarimetry in the 25–100 keV energy range. CUSP consists of a 6U-XL platform hosting a dual-phase Compton polarimeter. The polarimeter is made of a central assembly of four 4 × 4 arrays of plastic scintillators, each coupled to multi-anode photomultiplier tubes, surrounded by four strips of eight elongated GAGG scintillator bars coupled to avalanche photodiodes. Both types of sensors from Hamamatsu are, respectively, read out by the MAROC-3A and SKIROC-2A ASICs from Weeroc. In this manuscript, we present the preliminary spectral performances of single plastic and GAGG channels measured in a laboratory using development boards of the ASICs foreseen for the flight model. Full article

In January 2025, multiple wildfires erupted across the Los Angeles region, fueled by prolonged dry conditions and intense Santa Ana winds. Southern California has faced increasingly frequent and severe wildfires in recent years, driven by prolonged drought, high temperatures, and the expanding wildland–urban interface. These fires have caused major loss of life, extensive property damage, mass evacuations, and severe air-quality decline in this densely populated, high-risk region. This study integrates passive and active satellite observations to characterize the spatiotemporal and vertical distribution of wildfire emissions and assesses their impact on air quality. TROPOMI (Sentinel-5P) and the recently launched TEMPO geostationary instrument provide hourly high temporal-resolution mapping of trace gases, including nitrogen dioxide (NO₂), carbon monoxide (CO), formaldehyde (HCHO), and aerosols. Vertical column densities of NO₂ and HCHO reached 40 and 25 Pmolec/cm², respectively, representing more than a 250% increase compared to background climatological levels in fire-affected zones. TEMPO’s unique high-frequency observations captured strong diurnal variability and secondary photochemical production, offering unprecedented insights into plume evolution on sub-daily scales. ATLID (EarthCARE) lidar profiling identified smoke layers concentrated between 1 and 3 km altitude, with optical properties characteristic of fresh biomass burning and depolarization ratios indicating mixed particle morphology. Vertical profiling capability was critical for distinguishing transported smoke from boundary-layer pollution and assessing radiative impacts. These findings highlight the value of combined passive–active satellite measurements in capturing wildfire plumes and the need for integrated monitoring as wildfire risk grows under climate change. Full article

Over the last decade, numerical simulations and experiments have confirmed the existence of a novel class of vibrationally excited solid-particle attractors in cubic cavities containing a fluid in non-isothermal conditions. The diversity of emerging particle structures, in both morphology and multiplicity, depends strongly on the uni- or multi-directional nature of the imposed temperature gradients. The present study seeks to broaden this theoretical framework by further increasing the complexity of the thermal “information” coded along the external boundary of the fluid container. In particular, in place of the thermal inhomogeneities located in the center of otherwise uniformly cooled or heated walls, here, a cubic cavity with temperature boundary conditions satisfying the D₂h (in Schoenflies notation) or “mmm” (in Hermann–Mauguin notation) symmetry is considered. This configuration, equivalent to a bipartite vertex coloring of a cube leading to a total of 24 thermally controlled planar surfaces, possesses three mutually perpendicular twofold rotation axes and inversion symmetry through the cube’s center. To reduce the problem complexity by suppressing potential asymmetries due to fluid-dynamic instabilities of inertial nature, the numerical analysis is carried out under the assumption of dilute particle suspension and one-way solid–liquid phase coupling. The results show that a kaleidoscope of new particle structures is enabled, whose main distinguishing mark is the essentially one-dimensional (filamentary) nature. These show up as physically disjoint or intertwined particle circuits in striking contrast to the single-curvature or double-curvature spatially extended accumulation surfaces reported in earlier investigations. Full article

Microplastic pollution of ecosystems is considered a modern problem. Freshwater ecosystems, despite the interest shown in their study, remain poorly understood. Lake Baikal (Russia) is one of the least studied freshwater ecosystems in this regard. This large lake is distinguished from others by its high level of biodiversity and clean drinking water. The aim of this study is a multi-matrix investigation of microplastic pollution in one of the lake’s bay. The following matrices are used: surface water, water column, sediment, macrophytes, macroinvertebrates, and fish, as well as ice and snow during the winter. The results show that certain locations exhibit high concentrations of microplastic particles. In some cases, this was due to the properties or characteristics of these locations (littoral zones near the water’s edge, macrophytes with mucus sheaths, ice and snow (potentially, the near-surface water layer after ice melt)), while in others, it was due to localized pollution (pier and ship mooring areas). An analysis of the polymer types of the detected microplastic particles reveals the presence of both common (polypropylene, polyethylene terephthalate, polystyrene, polyethylene, polyvinyl chloride) and rare (polyvinyl alcohol and alkyd resin). Moreover, in some locations, the latter two polymers predominate, a phenomenon rarely observed in other studies. Further research was recommended to focus on the chronic effects of microplastic particles on organisms associated with areas of elevated particle concentrations. Full article

The application of advanced Artificial Intelligence (AI) techniques in astroparticle experiments represents a major advancement in both data analysis and experimental design. As space missions become increasingly complex, integrating AI tools is essential for optimizing system performance and maximizing scientific return. This study explores the use of Graph Neural Networks (GNNs) within the tracking systems of space-based experiments. A key challenge in track reconstruction is the high level of noise, primarily due to backscattering tracks, which can obscure the identification of primary particle trajectories. We propose a novel GNN-based approach for node-level classification tasks, specifically designed to distinguish primary tracks from backscattered ones within the tracker. In this framework, AI is employed as a powerful tool for pattern recognition, enabling the system to identify meaningful structures within complex tracking data and to discriminate signal from backscattering with higher precision. By addressing these challenges, our work aims to enhance the accuracy and reliability of data interpretation in astroparticle physics through the advanced deep learning techniques. Full article

Adeno-associated viruses (AAVs) are a leading vector for gene therapy, yet their clinical utility is limited by the lack of robust quality control methods to distinguish between empty (AAV_empty), partially loaded (AAV_partial), and fully DNA loaded (AAV_full) capsids. Current analytical techniques provide partial insights but remain limited in sensitivity, throughput, or resolution. Here we present a multimodal plasmonic nanopore sensor that integrates optical trapping with electrical resistive-pulse sensing to characterize AAV9 capsids at the single-particle level in tens of μL sample volumes and fM range concentrations. As a model system, we employed AAV9 capsids not loaded with DNA, capsids loaded with a self-complementary 4.7 kbp DNA (AAV_scDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAV_ssDNA). Ground-truth validation was performed with analytical ultracentrifugation (AUC). Nanosensor data were acquired concurrently for optical step changes (occurring at AAV trapping and un-trapping) both in transmittance and reflectance geometries, and electrical nanopore resistive pulse signatures, making for a total of five data dimensions. The acquired data was then filtered and clustered by Gaussian mixture models (GMMs), accompanied by spectral clustering stability analysis, to successfully separate between AAV species based on their DNA load status (AAV_empty, AAV_partial, AAV_full) and DNA load type (AAV_scDNA versus AAV_ssDNA). The motivation for quantifying the AAV_empty and AAV_partial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAV_scDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAV_scDNA and AAV_ssDNA despite their identical masses. In contrast, AUC could not differentiate between AAV_scDNA and AAV_ssDNA. An equimolar mixture of AAV_scDNA, AAV_ssDNA and AAV_empty was also measured with the sensor, and the results showed the expected population fractions, supporting the capacity of the method to differentiate AAV load status in heterogeneous solutions. In addition, less common optical and electrical signal signatures were identified in the acquired data, which were attributed to debris, rapid entry re-entry to the optical trap, or weak optical trap exits, representing critical artifacts to recognize for correct interpretation of the data. Together, these findings establish plasmonic nanopore sensing as a promising platform for quantifying AAV DNA loading status and genome type with the potential to extend ultra-sensitive single-particle characterization beyond the capabilities of existing methods. Full article

Black crusts are degradation features found on stone buildings, offering valuable insights into local pollution sources. Their composition and structure reflect environmental conditions, making them important indicators for environmental and conservation studies. In this study, black crusts collected from funerary monuments in the Monumental Cemetery of Milan were comprehensively characterized using SEM-EDX, Raman spectroscopy, LIBS, and oxidative potential (OP) assays. SEM-EDX and Raman spectroscopy revealed extensive degradation of the substrate and the incorporation of pollutant-derived particles, with heavy metals such as Fe, Zn, and Pb detected in more than 90% of the samples. Correlation analysis proved effective in distinguishing major pollution sources, primarily vehicular and railway traffic, indicated by strong associations such as Zn–Mn (r = 0.896), Fe–Zn (r = 0.734), and Fe–Mn (r = 0.655), from minor sources linked to industrial emissions, reflected in correlations including Ti–Pb (r = 0.589), Pb–Cl (r = 0.702), and S–Pb (r = 0.661). Instead, LIBS analysis confirmed stratigraphic penetration of these elements beyond the surface layers, suggesting long-term accumulation. OP assays, applied here for the first time to black crusts, showed values between 0.5 and 3.0 pmol min⁻¹ µg⁻¹, indicating moderate oxidative reactivity linked to metal content. Overall, the findings contribute to a deeper understanding of pollution-driven stone decay and support the development of more effective diagnostic and conservation strategies. Full article

We have developed mold matrices that can be employed to distinguish between enantiomers (D- and L-glucose) and structural isomers (n- and iso-stearic acid) in matrix-assisted laser desorption/ionization mass spectrometry. Utilizing a temperature-responsive polymer, a molecular structure recognition film was created around metal or semiconductor particles, such as silver (Ag) or cadmium telluride (CdTe), forming the core. Molecules that fit the template structure were selectively ionized. To elucidate the properties of the mold matrix, the relationship between molecular recognition rate and peak intensity of analyte ion was investigated by varying polymer film thickness around the core. The relationship between molecular recognition rate and hydrophobicity of the template molecule was also examined. It was found that increasing the amount of polymer forming the molecular recognition film improved the molecular recognition rate. However, the peak intensity of the analyte ion decreased. It was also found that using highly hydrophobic molecules as template molecules resulted in high molecular recognition rates. In addition, a water-splitting photocatalyst was synthesized and utilized to fabricate the mold matrix. It was applicable to both positive and negative ion generation while recognizing the molecular structure of the analyte. Full article