Numerical Modelling of Moisture Loss during Controlled Drying of Marine Archaeological Wood

If left to dry uncontrollably following excavation, marine archaeological wood suffers significant and irreparable damage. Conservation treatments are required to consolidate degraded wood and to remove residual water. Drying must be controlled to eliminate erratic and heterogeneous water removal. Monitoring and understanding the drying process progression is invaluable information to garner real-time knowledge to correlate with chemical and physical material properties, and to develop future conservation strategies. Here, polyethylene glycol (PEG) consolidated marine archaeological wood was periodically sampled during drying to determine the moisture content as a function of location, time, and sample depth. The heterogeneous nature of the material leads to significant noise across spatial and temporal measurements, making it challenging to elucidate meaningful conclusions from visual observation of the raw data. Therefore, the spatiotemporal data was computationally analysed to produce a representative model of the ship’s drying, illustrated by a dynamic simulation. From this we can quantitatively predict the drying rate, determine the depth-dependence of drying, and estimate the resulting equilibrium moisture content. This is the first time such simulations have been carried out on this material and conservation process, demonstrating the power of applying numerical modelling to further our understanding of complex heritage data.

Revisiting five decades of ²³⁴Th data: a comprehensive global oceanic compilation

We present here a global oceanic compilation of 234Th measurements that collects results from researchers and laboratories over a period exceeding 50 years. The origin of the 234Th sampling in the ocean goes back to 1967, when Bhat et al. (1969) initially studied 234Th distribution relative to its parent 238U in the Indian Ocean. However, it was the seminal work of Buesseler et al. (1992) – in which it was proposed that particulate organic carbon (POC) flux could be calculated from 234Th distributions if the ratio of POC to 234Th measured on sinking particles (POC : 234Th) at the desired depth was known – that drove the extensive use of the 234Th-238U radioactive pair to evaluate the efficiency with which photosynthetically fixed carbon is exported from surface ocean by means of the biological pump. Since then, a large number of 234Th depth profiles have been collected using a variety of sampling instruments and strategies that have changed the past 50 years. The present compilation is made of a total 223 datasets: 214 from studies published either in articles in referred journals, PhD thesis or repositories, and 9 unpublished datasets. The data were compiled from over 5000 locations spanning all the oceans for total 234Th profiles, dissolved and particulate 234Th concentrations, and POC : 234Th ratios (both sediment traps and filtration methods that include two sizes classes; 1–53 µm and < 53 µm). A total of 379 oceanographic expeditions and more than 56000 234Th and 18000 238U data points have been gathered in a single open-access, long-term and dynamic repository. This paper introduces the dataset along with informative and descriptive graphics. Appropriate metadata have been included, including geographic location, date, and sample depth, among others. When available, we also include water temperature, salinity, 238U data and particulate organic nitrogen data. Data sources and methods information (including 238U and 234Th) are also detailed along with valuable information for future data analysis such as bloom stage and steady/non-steady state conditions at the sampling moment. The data are archived on PANGAEA repository, with the dataset’s DOI doi.pangaea.de/10.1594/PANGAEA.918125 (Ceballos-Romero et al., 2021). This provides a valuable resource to better understand and quantify how the contemporary oceanic carbon uptake functions and how it will change in future.

Study on the Penetration Depth of Light into Wheat Flour by Hyperspectral Imaging

The penetration depth of light into wheat flour is the basis for the effective detection of additives in wheat flour using hyperspectral imaging. To determine the effective penetration depth of light into different gluten flours in hyperspectral image collection, the partial least squares-discriminant analysis (PLS-DA) method was used. Double-layer samples were prepared by placing flour layers with different thicknesses on top of the benzoyl peroxide (BPO) layer. PLS-DA classification model was established by using the diffuse reflectance spectra of each pixel in the double-layer sample image, and the classification accuracy was used to evaluate the results. The results show that the average accuracy of 1 and 1.5 mm models after smoothing pretreatment is above 95%. Therefore, a 1.5 mm sample depth for the detection of mixed samples of flour and additives is recommended. The selected sample depth was used for the detection of mixed samples containing different concentrations of BPO in flour, and the percentage of detected BPO pixels was positively correlated with BPO concentration, which could be used for subsequent quantitative analysis. The results lay a foundation for the effective detection additives in wheat flour by using hyperspectral imaging technology.

Computational Modeling of Ultrasound C-Scan Imaging Using Transmitted Signal Peak Density

Ultrasound measurement is a relatively inexpensive and commonly used imaging tool in the health sector. The through-transmission process of ultrasound measurement has been extensively evaluated for detecting abnormalities in tissue pathology. Compared to standard imaging parameters such as amplitude and time of flight, quantitative ultrasound parameters in the frequency domain can provide additional details regarding tissue microstructures. In this study, pressure magnitude or amplitude variation in the frequency spectrum of the received signal was evaluated as a potential imaging technique using the spectral peak density parameter. Computational C-scan imaging analysis was developed through a finite element model. The magnitude variation in the received signal showed different patterns while interacting with and without inclusions. Images were reconstructed based on peak density values that varied with the presence of solid structure. The computational results were verified with the experimental C-scan imaging results from the literature. It was found that magnitude variation can be an effective parameter for C-scan imaging of thin structures. The feasibility of the study was further extended to identify the structure’s relative position along with the sample depth during C-scan imaging. While moving the structure in the direction of the sample depth, the pressure magnitude variation strongly followed a second-degree polynomial trend.

Supplemental Material: Authigenic berthierine and incipient chloritization in shallowly buried sandstone reservoirs: Key role of the source-to-sink context

Table S1 displaying sample description and petrographical/mineralogical composition (sample list, well location projection WGS84, sample depth, petrographical and clay mineral quantifications).

Supplemental Material: Authigenic berthierine and incipient chloritization in shallowly buried sandstone reservoirs: Key role of the source-to-sink context

Table S1 displaying sample description and petrographical/mineralogical composition (sample list, well location projection WGS84, sample depth, petrographical and clay mineral quantifications).

Frictional properties of exhumed fault gouges in DFDP-1 cores, Alpine Fault, New Zealand

Principal slip zone gouges recovered during the Deep Fault Drilling Project (DFDP-1), Alpine Fault, New Zealand, were deformed in triaxial friction experiments at temperatures, T, of up to 350°C, effective normal stresses, σn′, of up to 156 MPa, and velocities between 0.01 and 3 μm/s. Chlorite/white mica-bearing DFDP-1A blue gouge, 90.62 m sample depth, is frictionally strong (friction coefficient, μ, 0.61-0.76) across all experimental conditions tested (T = 70-350°C, σn′ = 31.2-156 MPa); it undergoes a transition from positive to negative rate dependence as T increases past 210°C. The friction coefficient of smectite-bearing DFDP-1B brown gouge, 128.42 m sample depth, increases from 0.49 to 0.74 with increasing temperature and pressure (T = 70-210°C, σn′ = 31.2-93.6 MPa); the positive to negative rate dependence transition occurs as T increases past 140°C. These measurements indicate that, in the absence of elevated pore fluid pressures, DFDP-1 gouges are frictionally strong under conditions representative of the seismogenic crust.

Frictional properties of exhumed fault gouges in DFDP-1 cores, Alpine Fault, New Zealand

Principal slip zone gouges recovered during the Deep Fault Drilling Project (DFDP-1), Alpine Fault, New Zealand, were deformed in triaxial friction experiments at temperatures, T, of up to 350°C, effective normal stresses, σn′, of up to 156 MPa, and velocities between 0.01 and 3 μm/s. Chlorite/white mica-bearing DFDP-1A blue gouge, 90.62 m sample depth, is frictionally strong (friction coefficient, μ, 0.61-0.76) across all experimental conditions tested (T = 70-350°C, σn′ = 31.2-156 MPa); it undergoes a transition from positive to negative rate dependence as T increases past 210°C. The friction coefficient of smectite-bearing DFDP-1B brown gouge, 128.42 m sample depth, increases from 0.49 to 0.74 with increasing temperature and pressure (T = 70-210°C, σn′ = 31.2-93.6 MPa); the positive to negative rate dependence transition occurs as T increases past 140°C. These measurements indicate that, in the absence of elevated pore fluid pressures, DFDP-1 gouges are frictionally strong under conditions representative of the seismogenic crust.

Phylogenetic diversity of bacteria in rock salt of the Verkhnekamskoe deposit (Perm Krai)

New data on the phylogenetic diversity of bacteria in the salt of the Verkhnekamskoe deposit (Perm Krai) have been obtained using molecular genetic methods. Analysis of the 16S rRNA genes of total DNA from the rock salt sample (depth intervals of 239.7-239 m) evinces the presence of bacteria belonging to the classes: Actinobacteria (closely related to the genera Rhodococcus, Demequina), Gammaproteobacteria (the genera Pseudomonas, Serratia, Shigella), Betaproteobacteria (the genus Ralstonia) and Alphaproteobacteria (the genus Phyllobacterium). In addition, we identified two phylotypes of the Alphaproteobacteria (clone 66BA (GenBank MH410136) and clone 12BA (GenBank MH410128) that show lower similarity in 16S rRNA genes (98.46%) with the closest type strains of the genus Mesorhizobium (M. alhagi CCNWXJ12-2T) and the genus Chelativorans (C. multitrophicus DSM9103T). The identified phylotypes may represent new taxonomic units.

Automated Sample Depth Targeting with Low kV Cleaning by Focused Ion Beam Microscopy for Atom Probe Tomography

Focused ion beam (FIB) microscopy is an essential technique for the site-specific sample preparation of atom probe tomography (APT). The site specific APT and automated APT sample preparation by FIB have allowed increased APT sample volume. In the workflow of APT sampling, it is very critical to control depth of the sample where exact region of interest (ROI) for accurate APT analysis. Very precise depth control is required at low kV cleaning process in order to remove the damaged layer by previous high kV FIB process steps. We found low kV cleaning process with 5 kV and followed by 2kV beam conditions delivers better control to reached exact ROI on Z direction. This understanding is key to make APT sample with fully automated fashion.