Secondary Processes Research Articles

Визначення білків гострої фази в крові щурів після імплантації поліпропіленових хірургічних сіток із покриттям на основі танталу та його похідних

At present, more than 30 types of polypropylene surgical meshes are available in the world, but the statistics regarding the secondary inflammatory process after implantation still remain disappointing. Since polypropylene surgical meshes do not decompose well in the body, they can stimulate the surrounding tissuesto develop an inflammatory process that causes adhesions. For the past 50 years, tantalum has been successfully used to produce biocompatible medical implants in surgery, orthopedics, and dentistry. Its excellent anti-inflammatory and antibacterial properties have been repeatedly noted, indicating the possibility of its use as a coating for mesh implants. In order to better predict the outcome after implantation of biomedical materials, it is important to determine the content of acute phase proteins, namely C-reactive protein, haptoglobin and ceruloplasmin. The aim of the study is to determine the content of acute phase proteins, namely C-reactive protein, haptoglobin and ceruloplasmin in the blood of rats after implantation of surgical meshes coated on the basis of tantalum, tantalum oxide and tantalum nitride. Materials and methods. The experimental group included 40 male rats of the WAG population. With the help of surgical intervention, a polypropylene surgical mesh measuring 15x15 mm was implanted between the abdominal wall and various sections of the colon. 28 days after surgery, the experimental animals were decapitated by cervical dislocation. Blood samples were used to determine the content of C-reactive protein, the content of haptoglobin and the content of ceruloplasmin. Results and discussion. The content of C-reactive protein in the blood of rats was statistically 260 % higher in the experimental group implanted with uncoated surgical mesh and 228.8 % higher in the experimental group implanted with polypropylene surgical mesh with tantalum nitride coating in compared with the results in the group of intact animals. Haptoglobin content was statistically 110.5 % higher and ceruloplasmin was statistically 52.6 % higher in the uncoated surgical mesh group compared to the results of the intact animal group. We obtained similar results in the experimental group, which was implanted with a polypropylene surgical mesh with a coating based on tantalum nitride. The content of haptoglobin was 130 % higher and the content of ceruloplasmin was 50.6 % higher statistically compared to the results of the group of intact animals. The C-reactive protein content was 113.3 % and 95.5 % higher, respectively, in the groups implanted with polypropylene surgical meshes with a coating based on tantalum and tantalum oxide compared to the results in the group of intact animals. The content of haptoglobin in the tantalum-based coating group was 83.8 % higher and the content of ceruloplasmin was 32.6 % higher compared to the results obtained in the group of intact animals. In the tantalum oxide- based group, the haptoglobin content was 60.1 % higher and the ceruloplasmin content was 29.3 % higher compared to the results obtained in the intact animal group. Conclusion. Based on the results of the study, it was established that polypropylene surgical meshes coated with tantalum and tantalum oxide significantly reduce the inflammatory reaction compared to uncoated meshes and meshes coated with tantalum nitride. This is supported by lower levels of key inflammatory markers, indicating improved biocompatibility and anti-inflammatory effects of tantalum and tantalum oxide coatings.

Optimization methods in powder metallurgy for enhancing the mechanical properties: A systematic literature review

Abstract Powder metallurgy offers several advantages over traditional manufacturing methods, such as improved material utilization and waste reduction. The powder metallurgy process involves four primary steps, metal powder preparation, mixing, compaction, and sintering, followed by secondary operations such as forging, rolling, and extrusion. However, existing studies have predominantly focused on refining the primary processes, neglecting secondary processes that could further enhance mechanical properties. A systematic literature review following the Preferred Reporting Items for Systematic Review and Meta-Analysis method identified twenty-three relevant articles over a ten-year period, highlighting three main optimization methods, that are, the Taguchi method, Taguchi-based Grey Relational Analysis, and Response Surface Methodology. These methods effectively reduce experimental trials and optimize key parameters like compaction pressure and weight percentage, which significantly influence mechanical properties. The review emphasizes the key powder metallurgy process parameters that have a significant impact on mechanical properties, becoming the primary targets for optimization. It offers a focused examination of which process parameters require thorough investigation for optimization and the suitable optimization method to achieve optimal outcomes, whether for single or multiple responses, thereby enhancing the manufacturing process. However, inconsistencies in parameter significance across studies indicate the material-dependent nature of powder metallurgy materials. The review also identifies a gap in the literature regarding secondary process optimization and comparative analyses of optimization methods. Future research should explore optimizing secondary processes in powder metallurgy, conduct comparative studies of different optimization methods, and develop novel approaches for optimization to further enhance mechanical properties and process efficiency.

Modelling lung infection with Klebsiella pneumoniae after murine traumatic brain injury

Pneumonia is a common comorbidity in patients with severe traumatic brain injury (TBI), and is associated with increased morbidity and mortality. In this study, we established a model of intratracheal Klebsiella pneumoniae administration in young adult male and female mice, at 4 days following an experimental TBI, to investigate how K. pneumoniae infection influences acute post-TBI outcomes. A dose-response curve determined the optimal dose of K. pneumoniae for inoculation (1 x 10^6 colony forming units), and administration at 4 days post-TBI resulted in transient body weight loss and sickness behaviors (hypoactivity and acute dyspnea). K. pneumoniae infection led to an increase in pro-inflammatory cytokines in serum and bronchoalveolar lavage fluid at 24 h post-infection, in both TBI and sham (uninjured) mice. By 7 days, when myeloperoxidase + neutrophil numbers had returned to baseline in all groups, lung histopathology was observed with an increase in airspace size in TBI + K. pneumoniae mice compared to TBI + vehicle mice. In the brain, increased neuroinflammatory gene expression was observed acutely in response to TBI, with an exacerbated increase in Ccl2 and Hmox1 in TBI + K. pneumoniae mice compared to either TBI or K. pneumoniae alone. However, the presence of neuroinflammatory immune cells in the injured brain, and the extent of damage to cortical and hippocampal brain tissue, was comparable between K. pneumoniae and vehicle-treated mice by 7 days. Examination of the fecal microbiome across a time course did not reveal any pronounced effects of either injury or K. pneumoniae on bacterial diversity or abundance. Together, these findings demonstrate that K. pneumoniae lung infection after TBI induces an acute and transient inflammatory response, primarily localized to the lungs with some systemic effects. However, this infection had minimal impact on secondary injury processes in the brain following TBI. Future studies are needed to evaluate the potential longer-term consequences of this dual-hit insult.

Modification of the Dielectric and Thermal Properties of Organic Frameworks Based on Nonterminal Epoxy Liquid Crystal with Silicon Dioxide and Titanium Dioxide

A nonterminal liquid crystal epoxy monomer is used to create an epoxy–amine network with a typical diamine 4,4′diaminodiphenylmethane. The plain matrix is compared to matrices modified with inorganic fillers: TiO2 or SiO2. Conditions of the curing reaction and glass transition temperatures in the cured products are determined through differential scanning calorimetry and broadband dielectric spectroscopy. The curing process is also followed through optical and electrical observations. The dielectric response of all investigated networks reveals a segmental α-process related to structural reorientation (connected to the glass transition). In all products, a similar process associated with molecular motions of polar groups also appears. The matrix modified with TiO2 exhibits two secondary relaxation processes (β and γ). Similar processes were observed in the pure monomer. An advantage of the network with the TiO2 filler is a shorter time or lower temperature required for optimal curing conditions. The physical properties of cured matrices depend on the presence of a nematic phase in the monomer and nonterminal functional groups in the aliphatic chains. In effect, such cured matrices can have more flexibility and internal order than classical resins. Additional modifiers used in this work shift the glass transition above room temperature and influence the fragility index in both cases.

Simulating the seeder–feeder impacts on cloud ice and precipitation over the Alps

Abstract. The ice phase impacts many cloud properties as well as cloud lifetime. Ice particles that sediment into a lower cloud from an upper cloud (external seeder–feeder process) or into the mixed-phase region of a deep cloud from cirrus levels (internal seeder–feeder process) can influence the ice phase of the lower cloud, amplify cloud glaciation and enhance surface precipitation. Recently, numerical weather prediction modeling studies have aimed at representing the ice crystal number concentration in mixed-phase clouds more accurately by including secondary ice formation processes. The increase in the ice crystal number concentration can impact the number of ice particles that sediment into the lower cloud and alter its composition and precipitation formation. In the Swiss Alps, the orography permits the formation of orographic clouds, making it ideal for studying the occurrence of multi-layered clouds and the seeder–feeder process. We present results from a case study on 18 May 2016, showing the occurrence frequency of multi-layered clouds and the seeder–feeder process. About half of all observed clouds were categorized as multi-layered, and the external seeder–feeder process occurred in 10 % of these clouds. Between cloud layers, ≈60 % of the ice particle mass was lost due to sublimation or melting. The external seeder–feeder process was found to be more important than the internal seeder–feeder process with regard to the impact on precipitation. In the case where the external seeder–feeder process was inhibited, the average surface precipitation and riming rate over the domain were both reduced by 8.5 % and 3.9 %, respectively. When ice–graupel collisions were allowed, further large reductions were seen in the liquid water fraction and riming rate. Inhibiting the internal seeder–feeder process enhanced the liquid water fraction by 6 % compared to a reduction of 5.8 % in the cloud condensate, therefore pointing towards the de-amplification in cloud glaciation and a reduction in surface precipitation. Adding to the observational evidence of frequent seeder–feeder situations, at least over Switzerland, our study highlights the extensive influence of sedimenting ice particles on the properties of feeder clouds as well as on precipitation formation.

Estimating Stage-Frequency Curves for Engineering Design in Small Ungauged Arctic Watersheds

The design of hydraulic structures in the Arctic is complicated by shallow relief, which cause unique runoff processes that promote snow-damming and refreeze of runoff. We discuss the challenges encountered in modeling snowmelt runoff into two coastal freshwater lagoons in Utqiaġvik, Alaska. Stage-frequency curves with quantified uncertainty were required to design two new discharge gates that would allow snowmelt runoff flows through a proposed coastal revetment. To estimate runoff hydrographs arriving at the lagoons, we modeled snowpack accumulation and ablation using SnowModel which in turn was used to force a physically-based hydraulic runoff model (HEC-RAS). Our results demonstrate the successful development of stage-frequency curves by incorporating a Monte Carlo simulation approach that quantifies the variability in runoff timing and volume. Our process highlights the complexities of Arctic hydrology by incorporating significant delays in runoff onset due to localized snow accumulation and melting processes. This methodology not only addresses the uncertainty in snow-damming and refreeze processes which affect the arrival time of snowmelt inflow peaks, but is also adaptable for application in other challenging environments where secondary runoff processes are predominant.

Possibility of Secondary i- and s-processes Following r-process in the Collapsar Jet

The slow and intermediate neutron-capture processes, s- and i-processes, are believed to occur in asymptotic giant branch stars to provide half of the heavy atomic nuclei with A ≥ 90. We suggest a possibility that certain types of outflows found in the collapsar, which is a supernova generated by a rapidly rotating massive star undergoing core collapse, leaving behind a black hole and emitting relativistic jets, can provide conditions that are viable for s- and i-processes as secondary processes following the rapid neutron-capture process, r-process. We propose that the pronounced odd–even effect in the mass abundance pattern near rare earth elements in metal-deficient halo stars could be an observational hint for the s- and i-processes in the collapsar.

Study on the secondary oxidation behavior and microscopic characteristics of oxidized coal gangue.

Spontaneous combustion of coal gangue (CG) hills has caused varieties of secondary disasters that seriously endanger the ecological environment of the world. The emission law of index gases and their oxidation kinetics during the secondary oxidation process of CG with different ranks of oxidation were studied by using the temperature programmed device and online mass spectrometer (MS). Fourier transform infrared spectroscopy (FTIR) was used to reveal the changes of the CG internal active functional groups. The results showed that the energy required for the combustion of CG with low rank of pre-oxidation was significantly lower than that of the raw sample. However, as the oxidation rank increased, due to amounts of volatile components were released in the process of oxidation reaction, the CG in the combustion process of the emission of index gases and its oxygen consumption rate gradually reduced; the rapid oxidation stage shifted to the direction of the high temperature. In this study, the risk of spontaneous combustion of CG after oxidation at 80℃ under 3% oxygen concentration was the strongest. The results of this paper are of great guiding significance for exploring the spontaneous combustion characteristics of CG hills and their prevention by traditional covering method.

Identification of complex crude oil categories in ultra-deep petroleum systems based on a new fluorescence analysis method: An example from the southwestern Tabei Uplift, Tarim Basin, China

Ultra-deep crude oils have become one of the most important targets for petroleum exploration. In ultra-deep petroleum systems, differential hydrocarbon generation of various source rocks and multistage oil accumulation and secondary alteration processes led to the coexistence of crude oils with diverse sources and formation mechanisms. How to effectively identify complicated crude oil categories is a difficult issue confronted with ultra-deep petroleum exploration. Because crude oils are generally fluorescent, fluorescence analysis methods exhibit great application potential for classifying ultra-deep crude oils. However, due to the lack of other restrictive parameters, previous methods based on fluorescence color and fluorescence spectra limit the geological application of fluorescence analysis methods in ultra-deep petroleum systems. Based on the combination of fluorescence spectral parameters and fluorescence lifetimes, this study innovatively provides a new fluorescence analysis method for identifying complex crude oil categories in ultra-deep petroleum systems. Moreover, the sources and formation mechanisms of the ultra-deep crude oil can be further identified by combining fluorescence parameters with physical and geochemical parameters. By applying the above method, this study effectively identified three categories of crude oils and revealed their sources and formation mechanisms in the ultra-deep petroleum system of the southwestern Tabei Uplift, Tarim Basin, China. The new fluorescence analysis method may have practical significance for revealing the sources and formation mechanisms of ultra-deep crude oils.

Unbiased Insights into the Multiplicity of the CYP46A1 Brain Effects in 5XFAD Mice Treated with Low Dose Efavirenz

CYP46A1 is the CNS-specific cholesterol 24-hydroxylase that controls cholesterol elimination and turnover in the brain. In mouse models, pharmacologic CYP46A1 activation with low dose efavirenz (EFV) or by gene therapy mitigates the manifestations of various brain disorders, neurologic and non-neurologic, by affecting numerous, apparently unliked biological processes. Accordingly, CYP46A1 is emerging as a promising therapeutic target; however, the mechanisms underlying the multiplicity of the brain CYP46A1 activity effects are currently not understood. We proposed the chain reaction hypothesis, according to which CYP46A1 is important for the three primary (unifying) processes in the brain (sterol flux through the plasma membranes, acetyl-CoA and isoprenoid production), which in turn affect a variety of secondary processes. We already identified several processes secondary to changes in sterol flux and herein undertook a multiomics approach to compare the brain proteome, acetylproteome, and metabolome of 5XFAD mice (an Alzheimer's disease model), control and treated with low dose EFV. We found that the latter had increased production of phospholipids from the corresponding lysophospholipids and a globally increased protein acetylation (including histone acetylation). Apparently, these effects were secondary to increased acetyl-CoA production. Signaling of small GTPases due to their altered abundance or abundance of their regulators could be affected as well, potentially via isoprenoid biosynthesis. In addition, the omics data related differentially abundant molecules to other biological processes either reported previously or new. Thus, we obtained unbiased mechanistic insights and identified potential players mediating the multiplicity of the CYP46A1 brain effects and further detailed our chain reaction hypothesis.

Design optimization of integral stiffeners for 3D woven composite preforms

Although 3D orthogonal textile woven composite panels demonstrate good impact damage resistance, they often have relatively low bending stiffness. Typically, stiffeners are added to improve the bending resistance through fabrication processes such as sewing and panel/flange joining through matrix adhesion. These secondary processes can be undesirable, adding expense and potential weak points to the structure. Inspired by bio-structures such as peanut shells with surface ridges and graded through-thickness densities, we seek to develop embedded stiffeners for 3D orthogonal textile woven composite panels at sub-component scale to enhance the bending stiffness. Such stiffened textile architecture can be integrally fabricated in an orthogonal loom using standard weaving methods and provides a balance between improving structural bending stiffness and the manufacturing cost and maintaining good impact damage resistance. Utilizing a manufacturing-based parameterization method, a low-fidelity evaluation tool based on the iso-strain method is developed and a straightforward design methodology is proposed to implement these novel composite structures. Numerical design optimization examples are demonstrated.

Unlocking waste potential: A neural network approach to forecasting sustainable acetaldehyde production from ethanol upcycling in biomass waste gasification

The upcycling of biomass waste gasification process for ethanol and acetaldehyde production has been augmented by integrating secondary and tertiary processes. A simulation model using Aspen Plus, developed from experimental investigations to assess the viability of this proposed system. Furthermore, this model has been utilized to create an Artificial Neural Network (ANN) prediction model. Process sustainability analysis demonstrated an energy efficiency of 64 % while economic viability up to 80 % process efficiency with an Internal Rate of Return (IRR) of 6 % and a payback period of 2107 days. An optimization strategy and an artificial neural network (ANN)-based predictive model have been developed. Optimization results revealed that a gasifier temperature of around 600 °C, a gasifying agent ratio of 2.0, and an acetaldehyde reactor temperature of 300 °C yield better process outcomes and revenue. The ANN model exhibited robust performance with coefficient of determination (R2) values ranging from 0.92 to 0.98 for acetaldehyde, hydrogen, and total revenue. Mean absolute error (MAE) and mean absolute percentage error (MAPE) fell within the range of 0.03–0.1 and 0.1–1.12 %, respectively. Consequently, given the favorable sustainability and predictive model performance, this study can be used for similar endeavors.

Accuracy Assessment of Geometric-Distortion Identification Methods for Sentinel-1 Synthetic Aperture Radar Imagery in Highland Mountainous Regions.

SAR imagery plays a crucial role in geological and environmental monitoring, particularly in highland mountainous regions. However, inherent geometric distortions in SAR images often undermine the precision of remote sensing analyses. Accurately identifying and classifying these distortions is key to analyzing their origins and enhancing the quality and accuracy of monitoring efforts. While the layover and shadow map (LSM) approach is commonly utilized to identify distortions, it falls short in classifying subtle ones. This study introduces a novel LSM ground-range slope (LG) method, tailored for the refined identification of minor distortions to augment the LSM approach. We implemented the LG method on Sentinel-1 SAR imagery from the tri-junction area where the Xiaojiang, Pudu, and Jinsha rivers converge at the Yunnan-Sichuan border. By comparing effective monitoring-point densities, we evaluated and validated traditional methods-LSM, R-Index, and P-NG-against the LG method. The LG method demonstrates superior performance in discriminating subtle distortions within complex terrains through its secondary classification process, which allows for precise and comprehensive recognition of geometric distortions. Furthermore, our research examines the impact of varying slope parameters during the classification process on the accuracy of distortion identification. This study addresses significant gaps in recognizing geometric distortions and lays a foundation for more precise SAR imagery analysis in complex geographic settings.

Computational insights into gas atomization of FeCoNiCrMoBSi high-entropy alloy: From droplet formation to rapid solidification

The intricate processes governing the gas atomization of molten metal droplets and their subsequent solidification hold paramount significance in materials science. Computational fluid dynamics simulations have emerged as indispensable tools for unraveling the complexities inherent in metal melt atomization. This study employed the volume of fluid method and the shear-stress transport k-ω turbulence model to simulate the primary atomization process of a FeCoNiCrMoBSi high-entropy alloy. Subsequently, the discrete phase model and Taylor analogy breakup model, based on the gas Weber number and incorporating primary atomization outcomes as initial conditions, were utilized to simulate droplet formation during the secondary atomization process. Analysis of the particle size distribution at the outlet of the geometric model demonstrated excellent agreement with experimental data for gas-atomized FeCoNiCrMoBSi high-entropy alloy powder. Furthermore, comprehensive characterization analyses were conducted to probe the phase constitution and structure of FeCoNiCrMoBSi powder produced by gas atomization. The results revealed that, irrespective of particle size, the powder exhibited a face-centered cubic structure and distinctive eutectic microstructural characteristics. The numerical simulation provided insights into the solidification process of secondary droplets by integrating inverse pole figure data for gas-atomized powder across varying particle sizes. The estimated cooling rate of secondary droplets ranged from 1.22 × 104 K/s to 2.64 × 105 K/s. These findings significantly advance the understanding of the gas atomization mechanism of the FeCoNiCrMoBSi high-entropy alloy, paving the way for the development of more efficient manufacturing processes for advanced materials.

Environmentally persistent free radicals from residential raw coal combustion and association with chemical components

Emerging environmental persistent free radicals (EPFRs), can generate reactive oxygen species (ROS), posing potential exposure risks to human health. Incomplete coal combustion is a major source of EPFRs. Organic carbonaceous fractions are essential and important players in the formation of EPFRs during coal combustion. However, relationship between individual organic carbonaceous and non-carbon fractions with EPFRs in such emissions are not well known. This paper investigated the characteristics of EPFRs discharged from simulated coal combustion. Our results showed that the concentration of EPFRs was major concentrated on PM1.1 (51.66–81.85 %), and more easily oxidized by oxygen resulting in producing more oxygen-centered radicals (semiquinone-type) in PM1.1. The mean of line width (ΔHp-p) was 5.87 ± 0.41G higher than that of biomass combustion, indicating more free radical species were emitted from coal combustion. Humic-like substances-carbon (HULIS-C) was the major contributor of the formation of EPFRs and facilitate the generated of EPFRs. Secondary processes have also contributed to the formation of EPFRs during the coal combustion. Our result also noted that there was no relationship between transition metals and EPFRs, may be due to the variability and complexity of the chemical properties and composition of PM. This is critical for the prediction of geochemical behavior and risk assessment of EPFRs, which can provide basic data to support policy development to address rural air pollutant emissions.

An overlooked source of false positives in eDNA-based biodiversity assessment and management

Biodiversity conservation and management in urban aquatic ecosystems is crucial to human welfare, and environmental DNA (eDNA)-based methods have become popular in biodiversity assessment. Here we report a highly overlooked source of significant false positives for eDNA-based biodiversity assessment in urban aquatic ecosystems supplied with treated wastewater - eDNA pollution originating from treated wastewater represents a noteworthy source of false positives. To investigate whether eDNA pollution is specific to a certain treatment or prevalent across methods employed by wastewater treatment plants, we conducted tests on effluent treated using three different secondary processes, both before and after upgrades to tertiary treatment. We metabarcoded eDNA collected from effluent immediately after full treatment and detected diverse native and non-native, commercial and ornamental fishes (48 taxa) across all treatment processes before and after upgrades. Thus, eDNA pollution occurred irrespective of the treatment processes applied. Release of eDNA pollution into natural aquatic ecosystems could translate into false positives for eDNA-based analysis. We discuss and propose technical solutions to minimize these false positives in environmental nucleic acid-based biodiversity assessments and conservation programs.

Evolutionary analysis of MADS-box genes in buckwheat species and functional study of FdMADS28 in flavonoid metabolism

The MADS-box gene family is a transcription factor family that is widely expressed in plants. It controls secondary metabolic processes in plants and encourages the development of tissues like roots and flowers. However, the phylogenetic analysis and evolutionary model of MADS-box genes in Fagopyrum species has not been reported yet. This study identified the MADS-box genes of three buckwheat species at the whole genome level, and conducted systematic evolution and physicochemical analysis. The results showed that these genes can be divided into four subfamilies, with fragment duplication being the main way for the gene family expansion. During the domestication process from golden buckwheat to tartary buckwheat and the common buckwheat, the Ka/Ks ratio indicated that most members of the family experienced strong purification selection pressure, and with individual gene pairs experiencing positive selection. In addition, we combined the expression profile data of the MADS genes, mGWAS data, and WGCNA data to mine genes FdMADS28/48/50 that may be related to flavonoid metabolism. The results also showed that overexpression of FdMADS28 could increase rutin content by decreasing Kaempferol pathway content in hairy roots, and increase the resistance and growth of hairy roots to PEG and NaCl. This study systematically analyzed the evolutionary relationship of MADS-box genes in the buckwheat species, and elaborated on the expression patterns of MADS genes in different tissues under biotic and abiotic stresses, laying an important theoretical foundation for further elucidating their role in flavonoid metabolism.

The last 1100 years of activity of La Fossa caldera, Vulcano Island (Italy): new insights into stratigraphy, chronology, and landscape evolution

A detailed study of past eruptive activity is crucial to understanding volcanic systems and associated hazards. We present a meticulous stratigraphic analysis, a comprehensive chronological reconstruction, thorough tephra mapping, and a detailed analysis of the interplay between primary and secondary volcanic processes of the post-900 AD activity of La Fossa caldera, including the two main systems of La Fossa volcano and Vulcanello cones (Vulcano Island, Italy). Our analyses demonstrate how the recent volcanic activity of La Fossa caldera is primarily characterized by effusive and Strombolian activity and Vulcanian eruptions, combined with sporadic sub-Plinian events and both impulsive and long-lasting phreatic explosions, all of which have the capacity to severely impact the entire northern sector of Vulcano island. We document a total of 30 eruptions, 25 from the La Fossa volcano and 5 from Vulcanello cones, consisting of ash to lapilli deposits and fields of ballistic bombs and blocks. Volcanic activity alternated with significant erosional phases and volcaniclastic re-sedimentation. Large-scale secondary erosion processes occur in response to the widespread deposition of fine-grained ash blankets, both onto the active cone of La Fossa and the watersheds conveying their waters into the La Fossa caldera. The continuous increase in ground height above sea level, particularly in the western sector of the caldera depression where key infrastructure is situated, is primarily attributed to long-term alluvial processes. We demonstrate how a specific methodological approach is key to the characterization and hazard assessment of low-to-high intensity volcanic activity, where tephra is emitted over long time periods and is intercalated with phases of erosion and re-sedimentation.

Investigation of a haze-to-dust and dust swing process at a coastal city in northern China part II: A study on the solubility of iron and manganese across aerosol sources and secondary processes

The soluble fractions of iron (FeS) and manganese (MnS) in atmospheric aerosols potentially impact human health and ocean ecosystems. This study investigated a persistent haze-to-dust process observed in winter Qingdao, a coastal city in Northern China, focusing on the aerosol sources and acidification process affecting the dissolution of Fe and Mn. It was found that FeS in PM2.5 peaked during the intermingling of dust plumes with local haze, while other species of Fe and Mn reached their maximal levels coinciding with PM10. Positive Matrix Factorization (PMF) analysis determined that aged dust was the main source of FeS in PM2.5, accounting for 44.0%, while fresh dust contributed just 1.9%. Conversely, fresh dust played a more significant role in PM10, contributing 8.9% to FeS. Similar trends were observed in the initial dust and dust swing periods, aged dust was the dominant contributor to FeS, but fresh dust accounted for a higher fraction in PM10 (11.5%) than in PM2.5 (4.9%). In contrast, MnS levels, with high solubility (%MnS), were mainly from fresh dust (27.9% and 63.2% in PM2.5 and PM10, respectively). The PMF estimated %MnS in fresh dust at 17.0% for PM2.5 and 19.4% for PM10, considerably higher than Fe solubility (%FeS) at 0.3% and 0.1% in the corresponding particulate sizes. Additionally, %FeS correlated more strongly with sulfate and nitrate per unit Fe mass (R2 = 0.68 and 0.79 in PM2.5 and PM10) than %MnS (R2 = 0.49 and 0.50), suggesting a more profound impact of acidification on Fe dissolution. Further analysis suggests liquid water content rather than pH played a more critical role during the acidification process within fine particles. This study successfully estimated the solubility of Fe and Mn within various aerosols, providing valuable information and advancing our understanding of their dissolution and potential health and ecosystem impacts.

Precipitation behavior and properties change of Cu–3Ti–2Ni alloy during aging process

The microstructural evolution of Cu–3Ti–2Ni alloy under primary and secondary cold rolling combined aging was investigated through various characterization techniques including transmission electron microscopy (TEM), scanning electron microscope (SEM), and X-ray diffraction (XRD). Additionally, the electrical and mechanical properties during different stages of aging were examined to reveal the organizational changes and performance variations of Cu–3Ti–2Ni alloy under primary and secondary aging. This study revealed that the alloy exhibited optimal primary aging performance at 450 °C for 4 h, with a strength of 954 MPa and an electrical conductivity of 21.5 %IACS (International Annealed Copper Standard for Conductivity). In comparison to primary aging, both strength and electrical conductivity were effectively improved under secondary aging conditions. The optimum secondary aging process was determined to be aging at 400 °C for 3 h, resulting in a strength of 1133 MPa and an electrical conductivity of 24.2 %IACS. During the aging process, the matrix witnessed the formation of numerous elliptical disc-shaped NiTi and Ni3Ti phases. Notably, the interface of NiTi phases exhibited a stronger coherency effect compared to Ni3Ti. β′-Cu4Ti precipitated uniformly within the matrix during aging, enhancing the alloy's strength. A recovery and recrystallization process occurred during aging, leading to the formation of sub-grains within the matrix.