Ground Samples Research Articles

Drones for litter monitoring on coasts and rivers: suitable flight altitude and image resolution

Multirotor drones can be efficiently used to monitor macro-litter in coastal and riverine environments. Litter on beaches, dunes and riverbanks, along with floating litter on coastal and river waters, can be spotted and mapped from aerial drone images. Items detection and classification are prone to image resolution, which is expressed in terms of Ground Sampling Distance (GSD). The GSD is determined by drone flight altitude and camera properties. This paper investigates what is a suitable GSD value for litter survey. Drone flight altitude and camera setup should be chosen to obtain a GSD between 0.5 cm/px and 1.25 cm/px. Within this range, the lowest GSD allows litter categorization and classification, whereas the highest value should be adopted for a coarser litter census. In the vision of drawing up a global protocol for drone-based litter surveys, this work sets the ground for homogenizing data collection and litter assessments.

Temporal Irrigation Water Quality Monitoring and Analysis in Semiarid Tropics: Implication on Crop Production

Irrigation water quality analysis and monitoring is tricky task in semiarid tropics (SAT characterized) experiencing water scarcity. Conjunctive use of water in SAT have emphasizes on surface and ground water quality analysis for increase in agricultural production. Surface water quality analysis is carried out for reservoir water, canal flow, return flow and streams for a Devarabelakere, Village in Harihara Taluk in Davangere District of Karnataka State, India. It is located 12 Km towards west from Davanagere and 9 Km from Harihara. Devarabelakere pickup is constructed at downstreamof the Bhadra Reservoir at a distance of 136.00 Km. The total catchment area of this sub-project is 2106.90sq. Km. of which 1338.90 sq.Km SAT. Average Water quality index in the pre and post monsoon season for surface water was found between in the range of 51 to 75 and falls in the poor water quality status and suitable for irrigation and industrial purpose. Ground water sampling is also carried out at Deverabelekere command area and water quality index in pre and post monsoon seasons was found between the range 26 to 50 and falls in good water quality status and used for drinking, irrigation and industrial purpose. Although WQI shows many of the water samples were suitable or fit for irrigation, calculated other indices such Kelly’s Ratio (KR), Permeability Index (PI), Magnesium Absorption Ratio (MAR) with higher values covering all factors makes the water unsuitable which influences the irrigation water quality. In the study area the crops grown like Sugar cane in area of 28 ha, Plantation crop in area of 34 ha and Semi dry plant grow in 1152 ha and efficiency was found 37.03 % in post monsoon season for canal water and 44.38 % in pre monsoon due to temporal variations in season implicating the yield which is addressed by this paper.

Fluorene-naphthalene Schiff base as a smart pigment in invisible ink with multiple security features for advanced anticounterfeiting and forensic applications

Smart functional materials with captivating optical properties are of immense importance due to their versatile applicability in anticounterfeiting and forensic science. A fluorene-naphthalene Schiff base (FNH) that displays aggregation induced emission, mechanofluorochromism and excitation wavelength dependent fluorescence inherent to the pristine and ground samples is synthesized. Water/solvent-based invisible security inks for flexo/screen printing were formulated using FNH as a smart pigment to check the originality of documents/branded products etc. The prints with good photostability, adherence to substrate and rub resistance are invisible in daylight showcasing multiple non-destructive and destructive techniques to authenticate the document. The inked area on UV dull paper substrate exhibits a weak emission, which is observed by the forger under UVA light. However, the user can validate the authenticity of the document by rubbing the print with hard objects, especially using a metal coin or glass rod to perceive a human eye detectable intensification in the orange fluorescence under the same illumination source. The intensity of the orange fluorescence reverts to the original, which enables the reuse of the security document after originality check. Yet another nondestructive authentication method is to observe a cyan fluorescence from the print and orangish yellow fluorescence from the rubbed printed region when shined with a 270–400 nm light source, whereas a cyanish green fluorescence both from the unrubbed and rubbed regions of the print when illuminated with a visible light source ranging from 420 to 480 nm. An additional verification through a destructive technique is to perceive red and yellow fluorescence of the ink film upon contact with THF and NaOH/KOH, respectively and a penetrating red fluorescence from the rear side of the THF-exposed printed area of the paper. The multi-level security features that cannot be easily replicated by the forger but allows a simple and easy validation process by the user are unique to FNH, used as a single pigment in the inks. Further, the applicability of the ground FNH in forensic science is established to distinctly observe Level I to II details of latent fingerprints.

Tensile testing of Yttria-stabilized zirconia ceramic tapes for solid oxide cells

High temperature solid oxide cells (SOCs) play an important role in the worldwide green energy transition due to the high efficiency and great flexibility. For the cost and efficiency optimization of electrolyte-supported SOCs, a crucial property is the mechanical stability of the cell, which is mainly provided by the electrolyte. In this study, the authors investigate the tensile mechanical properties of 3% yittria-stabilized zirconia (3YSZ) ceramic electrolyte tapes, allowing the evaluation of a large material volume compared to the flexural test. A novel gripping system for misalignment minimization is developed. The sample machining is found to have an influence on the strength, as ground samples have an average strength above 1000 MPa, while the laser cut ones show strengths below 500 MPa. The influence of edge roughness and phase transformation during grinding is determined and the crack initiation point is examined.

NMR relaxometry – a new reliable and non-destructive method to estimate the fluid content of rock salt

Abstract. In the context of the site selection procedure for a high-level radioactive waste repository in Germany (StandAG, 2017), the fluid content of salt rocks is an important parameter to evaluate their barrier properties, i.e. the potential for gas formation (geoscientific weighing criteria 7 – geoWK-7) and the tendency to form fluid pathways (geoWK-6). Moreover, it can affect hydraulic conductivity (minimum requirement 1 – MA-1, geoWK-1 and geoWK-11), heat resistance (geoWK-8) and rock mechanical properties (geoWK-5), and it can be used for the spatial characterisation (geoWK-3) of the host rock (e.g. Kneuker et al., 2020). Fluids in rock salt (halite) are typically present in small, unconnected inclusions (commonly < 25 µm) located within crystals or arranged along crystal boundaries and fissures, and they can consist of brine, minor amounts of gases and hydrocarbons. When estimating the fluid content of rock salt, the main challenges are (i) the low fluid content (< 1 wt %), (ii) the low permeability of the bulk rock preventing fluid extraction and (iii) the spatial heterogeneous fluid distribution. In summary, the measurements are time intensive, and the results are highly dependent on the sample selection and preparation. Nuclear magnetic relaxation (NMR) relaxometry is an established petrophysical method in the oil and gas industry for the non-invasive characterisation of hydrocarbon host rocks and their fluids (e.g. Dunn et al., 2002), but it has not been used extensively for rock salt to date. We present the first results obtained from steeply inclined Zechstein rock salt (z2HS2) and compare them with a water content estimated by extensive grinding (< 30 µm) of the salt samples in dried acetone and the subsequent analysis of the extracted fluids using infrared spectroscopy (Mertineit et al., 2022). The first results show that NMR has promising features including (i) a low limit of detection (∼0.01 wt %), (ii) non-destructive and (iii) quick (5–10 min) measurements, (iv) no need for extensive sample preparation, and (v) the provision of an average fluid content over a large sample volume (100–900 mL).

Controllable factors affecting accuracy and precision of human identification of animals from drone imagery

AbstractSurveying animal populations using drones (unoccupied aircraft systems [UAS]) provides numerous advantages; however, few best practices exist to survey animal communities with drones. Among myriad factors that can affect human identification and counts of animals from drone images, we focused on three factors typically controlled in the study design or by the drone pilot: flight altitude, camera angle, and time of day. Identifying interactions and patterns among these three variables represents an important first step to determining best survey practices. We used a drone to survey known numbers of eight animal decoy species, representing a range of body sizes and colors, at four ground sampling distance (GSD) values (0.35, 0.70, 1.06, and 1.41 cm/pixel) representing equivalent flight altitudes (15.2, 30.5, 45.7, and 61.0 m) at two camera angles (45° and 90°) and across a range of times of day (morning to late afternoon). Expert human observers identified and counted animals from drone images to determine how the three controllable factors affected accuracy and precision. Observer precision was high and unaffected by tested factors. However, results for observer accuracy revealed an interaction among all three controllable factors. Increasing flight altitude resulted in decreased accuracy in animal counts overall; however, accuracy was best at midday than during the morning and afternoon, when decoy and structure shadows were present or more pronounced. Surprisingly, the 45° camera enhanced accuracy more than the 90° camera, but only when animals were most difficult to identify and count, such as at higher flight altitudes or during the early morning and late afternoon. We provide recommendations for improving human accuracy in identifying and counting animals from drone images used in monitoring animal populations and communities. These results should be incorporated into drone survey design in addition to considering funding, logistical, and animal behavior constraints.

Accuracy and consistency of space-based vegetation height maps for forest dynamics in alpine terrain

Monitoring and understanding forest dynamics is essential for environmental conservation and management. This is why the Swiss National Forest Inventory (NFI) provides countrywide vegetation height maps at a spatial resolution of 0.5 m. Its long update time of 6 years, however, limits the temporal analysis of forest dynamics. This can be improved by using spaceborne remote sensing and deep learning to generate large-scale vegetation height maps in a cost-effective way. In this paper, we present an in-depth analysis of these methods for operational application in Switzerland. We generate annual, countrywide vegetation height maps at a 10-m ground sampling distance for the years 2017–2020 based on Sentinel-2 satellite imagery. In comparison to previous works, we conduct a large-scale and detailed stratified analysis against a precise Airborne Laser Scanning reference dataset. This stratified analysis reveals a close relationship between the model accuracy and the topology, especially slope and aspect. We assess the potential of deep learning-derived height maps for change detection and find that these maps can indicate changes as small as 250 m2. Larger-scale changes caused by a winter storm are detected with an F1-score of 0.77. Our results demonstrate that vegetation height maps computed from satellite imagery with deep learning are a valuable, complementary, cost-effective source of evidence to increase the temporal resolution for national forest assessments.

2chADCNN: A Template Matching Network for Season-Changing UAV Aerial Images and Satellite Imagery

Visual navigation based on image matching has become one of the most important research fields for UAVs to achieve autonomous navigation, because of its low cost, strong anti-jamming ability, and high performance. Currently, numerous positioning and navigation methods based on visual information have been proposed for UAV navigation. However, the appearance, shape, color, and texture of objects can change significantly due to different lighting conditions, shadows, and surface coverage during different seasons, such as vegetation cover in summer or ice and snow cover in winter. These changes pose greater challenges for feature-based image matching methods. This encouraged us to overcome the limitations of previous works, which did not consider significant seasonal changes such as snow-covered UAV aerial images, by proposing an image matching method using season-changing UAV aerial images and satellite imagery. Following the pipeline of a two-channel deep convolutional neural network, we first pre-scaled the UAV aerial images, ensuring that the UAV aerial images and satellite imagery had the same ground sampling distance. Then, we introduced attention mechanisms to provide additional supervision for both low-level local features and high-level global features, resulting in a new season-specific feature representation. The similarity between image patches was calculated using a similarity measurement layer composed of two fully connected layers. Subsequently, we conducted template matching to estimate the UAV matching position with the highest similarity. Finally, we validated our proposed method on both synthetic and real UAV aerial image datasets, and conducted direct comparisons with previous popular works. The experimental results demonstrated that our method achieved the highest matching accuracy on multi-temporal and multi-season images.

Magnetic non-destructive evaluation of microstructural and mechanical characteristics of hardened AISI H13 die steel upon sustainable grinding

This paper describes the potential of non-destructive techniques such as micro-magnetic Barkhausen noise (MBN) to assess the grinding burn flaws in terms of microstructural and mechanical indices of hardened AISI H13 die steel. To overcome this grinding burn issue, minimum quantity lubrication grinding with eco-friendly machining fluids like paraffin oil (PO) and castor oil (CO) was adopted and compared its performance with well-established conventional grinding like wet and dry. Ground surface integrity with castor oil (CO) was found to be significantly improvement in surface quality including lower surface roughness (Rα: 0.23 μm and Rz: 1.83 μm) with uniform surface topography, absence of oxidization and carbonization film, and negligible change in microhardness and microstructure. The reason is strong and uniform anti-friction and anti-wear tribo-film was produced by castor oil, which minimizes heat penetration through limited ploughing and rubbing action. The MBN outcome i.e., root mean square (RMS) has followed a linear relation with microhardness and temperature of the ground sample with a correlation coefficient of 0.993 and 0.981. Besides, lower amplitude and wide peak envelope get shifted towards a higher magnetic field in the MQL-CO grinding caused by poor thermal softening effect on the ground sample, which restricts magnetic domain wall movement and rotation. These outcomes could guide tooling industries for efficient sustainable grinding with faster thermal damage assessment, which helps to minimize production cycle time and back to clean environment.

Correlated EPR and optical study of charge trapping phenomena in tellurite glasses. The role of barium oxide

Tellurite glasses of the compositions TeO2(60%)-ZnO(40%) and TeO2(60%)-ZnO(20%)-BaO(20%) were prepared in the bulk form with following grinding into powders. The samples were X-ray irradiated. The created charge trapping centers were studied in both types of samples using electron paramagnetic resonance (EPR) spectroscopy. The O− defect and two types of F+ centers were discovered. One of the F+ center remained unchanged whereas the other one as well as the O− defect were affected by the presence of BaO. Moreover, photo-, radio- and thermoluminescence (PL, RL, TL, respectively) methods were applied as well. The discovered charge trapping centers have been proven to influence luminescence properties as well – improving them in the TeO2(60%)-ZnO(40%) and vice versa degrading them in the TeO2(60%)-ZnO(20%)-BaO(20%) glasses. The effect was even stronger in the grinded samples as compared to the bulk ones. The role of the BaO has been disclosed as supporting oxygen leakage from the host.

Estimation of Soil Moisture Using Multi-Source Remote Sensing and Machine Learning Algorithms in Farming Land of Northern China

Soil moisture is a key parameter for the circulation of water and energy exchange between surface and the atmosphere, playing an important role in hydrology, agriculture, and meteorology. Traditional methods for monitoring soil moisture suffer from spatial discontinuity, time-consuming processes, and high costs. Remote sensing technology enables the non-destructive and efficient retrieval of land information, allowing rapid soil moisture monitoring to schedule crop irrigation and evaluate the irrigation efficiency. Satellite data with different resolutions provide different observation scales. Evaluating the accuracy of estimating soil moisture based on open and free satellite data, as well as exploring the comprehensiveness and adaptability of different satellites for soil moisture temporal and spatial observations, are important research contents of current soil moisture monitoring. The study utilized three types of satellite data, namely GF-1, Landsat-8, and GF-4, with respective temporal and spatial resolutions of 16 m (every 4 days), 30 m (every 16 days), and 50 m (daily). The gray relational analysis (GRA) was employed to identify vegetation indices that selected sensitivity to soil moisture at varying depths (3 cm, 10 cm, and 20 cm). Then, this study employed random forest (RF), Extra Tree (ETr), and linear regression (LR) algorithms to estimate soil moisture at different depths with optical satellite data sources. The results showed that the accuracy of soil moisture estimation was different at different growth stages. The model accuracy exhibited an upward trend during the middle and late growth stages, coinciding with higher vegetation coverage; however, it demonstrated a decline in accuracy during the early and late growth stages due to either the absence or limited presence of vegetation. Among the three satellite images, the vegetation indices derived from GF-1 exhibited were more sensitive to vegetation characteristics and demonstrated superior soil moisture estimation accuracy (with R2 ranging 0.129–0.928, RMSE ranging 0.017–0.078), followed by Landsat-8 (with R2 ranging 0.117–0.862, RMSE ranging 0.017–0.088). The soil moisture estimation accuracy of GF-4 was the worst (with R2 ranging 0.070–0.921, RMSE ranging 0.020–0.140). Thus, GF-1 is suitable for vegetated areas. In addition, the ETr model outperformed the other models in both accuracy and stability (ETr model: R2 ranging from 0.117 to 0.928, RMSE ranging from 0.021 to 0.091; RF model: R2 ranging from 0.225 to 0.926, RMSE ranging from 0.019 to 0.085; LR model: R2 ranging from 0.048 to 0.733, RMSE ranging from 0.030 to 0.144). Utilizing GF-1 is recommended to construct the ETr model for assessing soil moisture variations in the farming land of northern China. Therefore, in cases where there are limited ground sample data, it is advisable to utilize high-spatiotemporal-resolution remote sensing data, along with machine learning algorithms such as ETr and RF, which are suitable for small samples, for soil moisture estimation.

Oblique Vibratory Surface Grinding-Experimental Study.

The article reports the results of experimental study of vibratory surface grinding in the range of low excitation frequencies and variable directions of excited vibrations in the plane of the table, and investigates the effect of these directions on the roughness and waviness of the ground surface. The tests were conducted on a production surface grinder with a vibrating table on which the samples were mounted. The table made it possible to change the direction for the introduction of vibrations to the workpiece (longitudinally, transversely, and obliquely to the longitudinal feed of the table) and the parameters of the introduced vibrations, frequency and amplitude. In the course of the study, selected parameters of surface roughness and waviness of samples ground conventionally and with vibrations introduced on the workpiece were compared. The results show an improvement in the roughness and waviness parameters of the vibration-ground surfaces compared to surfaces ground without vibration (conventionally). The profile of the ground surface was subjected to Fourier analysis and the harmonic components of the surface shape of the ground samples were determined to characterize the effect of the introduced vibrations on the surface roughness. It was determined that the direction of vibration introduction, which is most favorable in terms of the parameters of the geometric structure of the ground surface, is the direction perpendicular to the longitudinal feed of the grinding table. In other directions of vibration introduction, the simultaneous effect of improving both parameters of the geometric structure of the ground surface profile was not obtained.

Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas

Abstract. Information on snow depth and its spatial distribution is important for numerous applications, including natural hazard management, snow water equivalent estimation for hydropower, the study of the distribution and evolution of flora and fauna, and the validation of snow hydrological models. Due to its heterogeneity and complexity, specific remote sensing tools are required to accurately map the snow depth distribution in Alpine terrain. To cover large areas (>100 km2), airborne laser scanning (ALS) or aerial photogrammetry with large-format cameras is needed. While both systems require piloted aircraft for data acquisition, ALS is typically more expensive than photogrammetry but yields better results in forested terrain. While photogrammetry is slightly cheaper, it is limited due to its dependency on favourable acquisition conditions (weather, light conditions). In this study, we present photogrammetrically processed high-spatial-resolution (0.5 m) annual snow depth maps, recorded during the peak of winter over a 5-year period under different acquisition conditions over a study area around Davos, Switzerland. Compared to previously carried out studies, using the Vexcel UltraCam Eagle Mark 3 (M3) sensor improves the average ground sampling distance to 0.1 m at similar flight altitudes above ground. This allows for very detailed snow depth maps in open areas, calculated by subtracting a snow-off digital terrain model (DTM, acquired with ALS) from the snow-on digital surface models (DSMs) processed from the airborne imagery. Despite challenging acquisition conditions during the recording of the UltraCam images (clouds, shaded areas and fresh snow), 99 % of unforested areas were successfully photogrammetrically reconstructed. We applied masks (high vegetation, settlements, water, glaciers) to increase the reliability of the snow depth calculations. An extensive accuracy assessment was carried out using check points, the comparison to DSMs derived from unpiloted aerial systems and the comparison of snow-free DSM pixels to the ALS DTM. The results show a root mean square error of approximately 0.25 m for the UltraCam X and 0.15 m for the successor, the UltraCam Eagle M3. We developed a consistent and reliable photogrammetric workflow for accurate snow depth distribution mapping over large regions, capable of analysing snow distribution in complex terrain. This enables more detailed investigations on seasonal snow dynamics and can be used for numerous applications related to snow depth distribution, as well as serving as a ground reference for new modelling approaches and satellite-based snow depth mapping.

Fast screening of total nutrient contents in strawberry leaves and spent growing media using NIRS.

In closed-loop soilless cultivation, the main nutrient sinks are nutrients retained either by the crop or in spent growing media. Measurement of nutrients in spent growing media and in the aboveground vegetative plant biomass at crop termination can be a tool for assessing and optimizing nutrient efficiency. The first aim of this study was to test the potential of near-infrared reflectance spectroscopy (NIRS) to forecast the various nutrient contents in strawberry leaves, which would then allow for assessment of crop nutrient status and total nutrient uptake by strawberry plants. The second aim was to test NIRS as a high throughput technique for assessing the N, K, Ca, Mg and organic matter (OM) content and the pH, EC and C:N and C:P ratios for a dataset of composts, plant fibers and spent growing media. The NIRS prediction model for fast screening of the total nutrient contents in spent growing media was compared with a single extraction method. A database with 369 dried and ground strawberry leaf samples with known contents of N, P, K, Ca, and Mg were scanned using NIRS. The database covered a range of leaf contents of 6-35 g N/kg dry matter (DM), 0.7-6.3 g P/kg DM and 2-29 g K/kg DM. A dataset of 458 samples of different types of materials used in growing media was validated with a dataset of 109 samples. Validation for the strawberry leaves indicated potential for this application, with R2 values of 0.90 or higher for N, K and Ca, and R2 values higher than 0.85 for P and Mg. Validation for the dataset of composts, plant fibers and spent growing media also indicated the potential for this application, with R2 values of 0.90 or higher for organic matter, and with R2 values of 0.85 or higher for total Ca, pH and C:N. A first test indicated potential for the calibration based on fresh samples of compost, plant fiber as well as spent growing media or dried (not ground) samples. Use of NIRS on fresh samples would eliminate the need for drying and grinding the samples and would reduce screening time. The ammonium acetate extraction is a reliable alternative to NIRS for fast screening of the total P, K, Ca, and Mg contents in composts, plant fibers and spent growing media.

Effect of varying UAV height on the precise estimation of potato crop growth.

A phenotyping pipeline utilising DeepLab was developed for precisely estimating the height, volume, coverage and vegetation indices of European and Japanese varieties. Using this pipeline, the effect of varying UAV height on the precise estimation of potato crop growth properties was evaluated. A UAV fitted with a multispectral camera was flown at a height of 15m and 30m in an experimental field where various varieties of potatoes were grown. The properties of plant height, volume and NDVI were evaluated and compared with the manually obtained parameters. Strong linear correlations with R2 of 0.803 and 0.745 were obtained between the UAV obtained plant heights and manually estimated plant height when the UAV was flown at 15m and 30m respectively. Furthermore, high linear correlations with an R2 of 0.839 and 0.754 were obtained between the UAV-estimated volume and manually estimated volume when the UAV was flown at 15m and 30m respectively. For the vegetation indices, there were no observable differences in the NDVI values obtained from the UAV flown at the two heights. Furthermore, high linear correlations with R2 of 0.930 and 0.931 were obtained between UAV-estimated and manually measured NDVI at 15m and 30m respectively. It was found that UAV flown at the lower height had a higher ground sampling distance thus increased resolution leading to more precise estimation of both the height and volume of crops. For vegetation indices, flying the UAV at a higher height had no effect on the precision of NDVI estimates.

Impact of wet-dry cycles on enhanced rock weathering of brucite, wollastonite, serpentinite and kimberlite: Implications for carbon verification

Enhanced rock weathering is a proposed CO2 removal strategy for mitigating climate change; its implementation can be facilitated by improving carbon verification methods. In this study, weathering experiments exposed brucite, wollastonite skarn, serpentinite, and kimberlite residues (Venetia Diamond Mine, South Africa), to wetting and drying cycles (4/day) for 1 yr to elucidate reaction pathways and rates while evaluating carbon verification tools, including mineral quantification, total inorganic carbon (TIC), and stable and radiogenic carbon isotopes. Two primary reaction pathways were identified: A) silicate and hydroxide dissolution leading to carbonate precipitation (desirable), and B) dissolution and reprecipitation of carbonates (undesirable). The kimberlite residues, containing serpentine (19–33 wt%) and calcite (4–5 wt%), experienced variable and minor changes in total inorganic carbon. The δ13C and δ18O values of the carbonate minerals approached those expected for atmospheric-derived CO2 and are best explained by the exchange of carbonate CO2 with atmospheric CO2 (pathway A) as opposed to net CO2 sequestration. In contrast, the reaction of brucite (1.22% to 5.98%) and wollastonite skarn (0.22% to 1.01%) with atmospheric CO2 was substantial, as indicated by the increases in TIC (pathway B) yet decreases in δ13C values were inconsistent with the incorporation of atmospheric CO2 as a result of kinetic isotope fractionation due to carbonation being CO2 supply limited. The pulverized serpentinite experience insufficient carbonation to be detected by TIC. Unweathered (blue ground) and naturally weathered (yellow ground) kimberlite from the Voorspoed Diamond Mine, South Africa were compared to kimberlite residues used in experiments. Yellow ground contained twice the TIC content compared to blue ground whereas quantitative scanning electron microscopy revealed calcite veinlets that are characteristic of secondary mineralization. While the blue and yellow ground samples were essentially radiocarbon dead (0.03 and 0.05 F14C, respectively), substantial modern carbon was incorporated into the kimberlite (up to +0.27 F14C; CO2 exchange), brucite (+0.55 F14C), and wollastonite skarn (+0.53 F14C; CO2 sequestration) powders during weathering experiments. Although stable and radiogenic carbon isotopes have been used to verify the mineralization of atmospheric CO2, these methods are affected by CO2 exchange and kinetic fractionation effects during weathering that can be misleading and, thus, should not be relied on as sole methods for carbon verification.

Monitoring cadmium concentrations in cacao: inter-laboratory variation and the effect of sample size on variability among ready-for-sale beans

Since the implementation of new EU limits on cadmium (Cd) in cacao-derived products, reliable measurements of the Cd concentration in cacao samples have become even more important. This study was set up to analyse the robustness of the measured Cd concentrations in cacao as affected by sampling strategy and by the laboratory receiving these samples. Six different homogenised cacao liquor samples were sent to 25 laboratories, mainly located in Latin America. On average, only 76% of the laboratories reported acceptable results per sample using internationally accepted criteria. More unreliable data was obtained when Atomic Absorption Spectroscopy (AAS) rather than Inductively Coupled Plasma (ICP) instruments were used or where concentrations were outside the calibration range. Subsequently, four commercial lots in Ecuadorian warehouses were sampled to identify the variation among beans, bags and replicate chemical analyses of ground samples. Simulations indicate that a composite sample should be made from at least 10 bags on a pallet and at least 60 beans should be ground prior to analysis to obtain an acceptable CV below 15%. This study shows that current Cd analyses in cacao on the market are neither sufficiently accurate nor precise and that more control on laboratory certifications is needed for reliable screening of Cd in cacao.

Architecture for a Mobile Robotic Camera Positioning System for Photogrammetric Data Acquisition in Hydroelectric Tunnels.

The structural condition of hydroelectric tunnels is important to the overall performance, safety, and longevity of generating stations. Significant effort is required to inspect, monitor, and maintain these tunnels. Photogrammetry is an effective method of collecting highly accurate visual and spatial data. However, it also presents the complex challenge of positioning a camera at thousands of difficult-to-reach locations throughout the large and varying-diameter tunnels. A semi-automated robotic camera positioning system was developed to enhance the collection of images within hydroelectric tunnels for photogrammetric inspections. A continuous spiral image network was developed to optimize the collection speed within the bounds of photography and capture-in-motion constraints. The positioning system and image network optimization reduce the time and effort required while providing the ability to adapt to different and varying tunnel diameters. To demonstrate, over 28,000 images were captured at a ground sampling distance of 0.4 mm in the 822 m long concrete-lined section of the Grand Falls Generating Station intake tunnel.

Enhancement of Fluorescence Emission Intensity in a Sulfonyl Hydrazide Derivative of tri(biphenyl‐4‐yl)amine via Solid‐state Grinding with Various Metal Salts: Combined Experimental and Computational Studies

AbstractSolid‐state fluorescent materials are in huge demand owing to their potential applications in sensors, imaging, and LEDs. The molecular aggregations in the solid state limit their usage in practical applications. Typically, J‐aggregates show enhanced emission, while H‐aggregates show quenching in the solid state. Few supramolecular approaches (like creating hydrogen bonds) were developed to disturb the π–π and other supramolecular interactions in solid‐state H‐aggregates. Herein, we are reporting a p‐toulenesulfonyl hydrazide derivative of tri(biphenyl‐4‐yl)amine (TBA‐THZ) in the solid state showed negligible emission while grinding with M+X− (M+=alkali and alkali earth metal) salts showed enhanced emission. Existing supramolecular interactions were disturbed by dipole‐ion interactions between S=O⋅⋅⋅M+. The micro/nanometer‐sized salt crystal particles serve as templates for the TBA‐THZ molecules, and in the broad sense, the salt crystal surfaces act as a “solid‐state solvent.” The TBA‐THZ ground with various metal salts showed varied emission intensities; the BaCl2 ⋅ 2H2O salt ground sample exhibited the maximum emission intensity. The KPF6+18‐Crown‐6 sample showed 84 times enhanced emission than the pristine TBA‐THZ. The role of 18‐crown‐6 ether was observed as a donor type for K+ ions. The expected S=O⋅⋅⋅K+ dipole‐ion interactions were elucidated through FT‐IR and computational modelling. The slight change in emission wavelength to the higher side after grinding with metal salt indicates that dipole‐ion interactions might slightly modify the chromophore's electronic structure, encouraging radiative decay and higher emission intensity. In contrast, a similar molecule, TBA‐PH, with no sulfonyl functional group, was silent in emission intensity. The TBA‐PH solid has no significant emission even after grinding with metal salts. The emission capacity of the TBA‐THZ salt‐ground powder remained unchanged at higher temperatures and in a highly humid environment. The fluorescent active salt ground matrix of the TBA‐THZ responded admirably to HCl acid fumes and was regenerated upon exposure to ammonia vapours.

The Copper(II)-Thiodiacetate (tda) Chelate as Efficient Receptor of N9-(2-Hydroxyethyl)Adenine (9heade): Synthesis, Molecular and Crystal Structures, Physical Properties and DFT Calculations of [Cu(tda)(9heade)(H2O)]·2H2O.

Considering that Cu(tda) chelate (tda: dithioacetate) is a receptor for adenine and related 6-aminopurines, this study reports on the synthesis, molecular and crystal structures, thermal stability, spectral properties and DFT calculations related to [Cu(tda)(9heade)(H2O)]·2H2O (1) [9heade: N9-(2-hydroxyethyl)adenine]. Concerning the molecular recognition of (metal chelate)-(adenine synthetic nucleoside), 1 represents an unprecedented metal binding pattern (MBP) for 9heade. However, unprecedentedly, the Cu(tda)-9heade molecular recognition in 1 is essentially featured in the Cu-N1(9heade) bond, without any N6-H⋯O(carboxyl tda) interligand interaction. Nevertheless, N1 being the most basic donor for N9-substituted adenines, this Cu-N1 bond is now assisted by an O2-water-mediated interaction (N6-H⋯O2 and O2⋯Cu weak contact). Also, in the crystal packing, the O-H(ol) of 9heade interacts with its own adenine moiety as a result of an O3-water-mediated interaction (O(ol)-H⋯O3 plus O3-H36⋯π(adenine moiety)). Both water-mediated interactions seem to be responsible for serious alterations in the physical properties of crystalline or grounded samples. Density functional theory calculations were used to evaluate the interactions energetically. Moreover, the quantum theory of atoms-in-molecules (QTAIM), in combination with the noncovalent interaction plot (NCIPlot), was used to analyze the interactions and rationalize the existence and relative importance of hydrogen bonding, chalcogen bonding and π-stacking interactions. The novelty of this work resides in the discovery of a novel binding mode for N9-(2-hydroxyethyl)adenine. Moreover, the investigation of the important role of water in the solid state of 1 is also relevant, along with the chalcogen bonding interactions demonstrated by the density functional theory (DFT) study.