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Fusing three-dimensional (3D) and multispectral (MS) imaging data holds promise for high-throughput, comprehensive plant phenotyping to decipher genome-to-phenome knowledge. The acquisition of high-quality 3D multispectral point clouds (3DMPCs) of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with complex canopy structure. We proposed a novel 3D spatial-spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view (NBV) planning for adaptive data acquisition and Neural REference Field (NeREF) for radiometric calibration. Our approach was used to acquire 3DMPCs of perilla, tomato and rapeseed plants with diverse plant architecture and leaf morphological features and evaluated by the accuracy of chlorophyll content and equivalent water thickness (EWT) estimation. Results showed that the completeness of plant point clouds collected by our approach was improved by an average of 23.6% compared with the fixed viewpoints alone. The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error (RMSE) of 58.93% for extracted reflectance spectra. The RMSE for chlorophyll content and EWT predictions decreased by 21.25% and 14.13% using the partial least squares regression (PLSR) with the generated 3DMPCs. Our study provided an effective and efficient way to collect high-quality 3DMPCs of plants under the natural light condition, which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits and facilitates plant biology and genetic studies and breeding programs.

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The demand for sustainable development goals and the absence of systematic development and organised exploration for gold has prompted this study to integrate magnetic and radiometric datasets with lithology to evaluate the gold mineralisation potential in the Ilesha schist belt. This study considers 3168.72 km2 of the Ilesha schist belt in southwestern Nigeria, a frontier belt for gold deposits. The high-resolution airborne magnetic and radiometric datasets were processed using enhancement techniques, including the analytical signal, lineament density, and K/Th ratio. CET grid analysis, Euler deconvolution, and analytical signal depth estimation methods were used to aid the interpretation. The spatial integration and interpolation were performed using the Analytical Hierarchy Process (AHP) and weighted overlay analytical tools within the ArcGIS environment. The dominant structural controls for potential mineralisation are ENE-WSW and ESE-WNW trends. The depth of the magnetic sources revealed by the analytical signal ranged from 63.17 to 629.47 m, while depths ranging from 47.32 to 457.22 m were obtained from Euler deconvolution. The delineated highly magnetic edge sources, dense lineaments, radiometrically highlighted alteration zones, and lithological hosts for gold mineralisation were integrated to establish the gold mineralisation potential map. The AHP deductions reveal that 10.52% of the study site is within the high mineralisation potential class, a remarkable 60.39% falls within the moderate class, a significant portion (28.86%) falls within the poor class, and 0.23% is considered unfavourable. The result was optimised by validation using known mines, with 94% (i.e., 15 out of 16 mining sites) plotting within the high mineralisation potential class. This assessment provides invaluable insight for stakeholders and policymakers to embark on gold exploration and exploitation and promote sustainable mineral development.

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The potential zones of gold mineralization were identified in this study using aeromagnetic and aero-radiometric methods. The Nigerian Geological Survey Agency (NGSA) provided half-degree airborne magnetic and radiometric datasets covering the southern part of Kebbi State. Magnetic data were subjected to first vertical derivative (1VD), total gradient amplitude (TGA), total horizontal derivative (THD), source edge detection (SED), center for exploration targeting (CET), Euler deconvolution (ED) and source parameter imaging (SPI) to identify favourable structures to gold mineralization. Aero-radiometric data delineation of the region of hydrothermal alteration zones through the K/eTh ratio, K_deviation, F_parameters, and Ternary image analyses were successful. The results of the magnetic data techniques revealed the regions of major structures/or lineaments with gold mineralization attributes, trending in the NE to SW directions and the SE to NE parts of the study area. The depth to the structures of the magnetic source hosting gold mineralization was less than 5 m using algorithm ED and SPI techniques. Normalized radiometric data showed the area of anomalously high and moderate hydrothermal altered zones. The region's designation as a gold field is supported by major fault lines observed on the 1VD, a sequence of bristle fractures from the CET analysis, and high values of K_deviation and F_parameter, all of which are were visible on the Ternary images. The integrated results revealed zones of major structures and hydrothermal regions of gold fields at Agwara, Western Magama, Rijau, Fakai, Bukkuyum, and Borgu in the SE of the study area.

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In early stages of drug development, the absence of authentic metabolite standards often results in semi-quantitative measurements of metabolite formation in reaction phenotyping studies using mass spectrometry (MS), leading to inaccuracies in the determination of enzyme kinetic parameters, such as the Michaelis constant (Km). Moreover, it is impossible to ascertain the maximum rate of enzyme-catalyzed reactions (kcat or Vmax). The use of radiolabeled parent compounds can circumvent this problem. However, radiometric detection exhibits significantly lower sensitivity compared to MS. To address these challenges, we have developed a stepwise approach that leverages biosynthesized radiolabeled and non-radiolabeled metabolites as standards, enabling accurate determination of Km, kcat or Vmax without the need for authentic metabolite standards. This approach, using the carbon-14 [14C] labeled metabolite to calibrate the unlabeled metabolite (14C calibration method), combines radiometric with LC-MS/MS detection to generate both [14C]-labeled and unlabeled metabolite standard curves to ensure that the sample concentrations measured are accurately quantitated. Two case studies were presented to demonstrate the utility of this method. We first compared the accuracy of the 14C calibration method to the use of authentic standards for quantitating imipramine metabolites. Next, we biosynthesized and quantitated the metabolites of BI 894416 using 14C calibration method and evaluated the enzyme kinetics of metabolite formation. The Km values of the metabolite formation demonstrated substantially improved accuracy compared to MS semi-quantitation. Moreover, the 14C calibration method offers a streamlined approach to prepare multiple metabolite standards from a single biosynthesis, reducing the time required for structure elucidation and metabolite synthesis.

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The aim of this study was to compare the level of bone mass in digital orthopantomograms in two populations (medieval and current) using two radiomorphometric indexes, and to correlate the mandibular bone mass value, in the medieval mandible population, with stable isotope data δ13C and δ15N. An observational, cross-sectional, and analytical study on mandibles from two diachronic groups, 15 mandibles from the medieval settlement of La Torrecilla (Granada, Spain) and 15 mandibles from current patients at the Faculty of Dentistry of the University of Granada (Spain), matched by age and sex was conducted. The bone mass density was determined using the Mandibular Cortical Width Index (MCW) and the Mandibular Panoramic Index (PMI) in digital panoramic radiographs. In the medieval group, the values of bone mass density were correlated with those of two stable isotopes (δ13C and δ15N). The mean value of MCW in mm in the medieval group was 3.96 ± 0.60 (mean ± standard deviation) and in the current group was 4.02 ± 1.01. The PMI was 0.33 ± 0.06 and 0.35 ± 0.08 in the medieval and current groups respectively, with similar results in both groups (p = 0.820 and p = 0.575). A negative correlation was found between both morphometric indices and the δ15N isotope (rs = 0.56, p = 0.030 and rs = 0.61, p = 0.016, respectively). The bone mass density in mandibles belonging to the two compared populations, determined by two quantitative radiomorphometric indices, is similar. Within the medieval population, there is an inverse correlation between the δ15N value and bone mass density.

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Burullus lagoon is part of Egypt's protected area network. The lagoon serves as a reservoir for drainage water discharged from agricultural areas, and the lake's sediments provide a unique opportunity to record environmental behavior and reconstruct of the heavy metal contamination history. In the present study, the sediment chronology, sedimentation rates, and metal accumulation fluxes were estimated in four sediment cores using 210Pb dating models to evaluate how human activities have affected the coastal environment. Using the radioisotopes 210Pb and 137Cs, radiometric dating was carried out using gamma-ray spectrometry. At the Egypt Second Research Reactor (ETRR-2), the element concentrations were determined using the instrumented neutron activation analysis (INAA- k0 method). Our findings show that the constant rate of supply (CRS), which has been verified with the peak of artificial radionuclide 137Cs, is the best model performed for the chronology of Burullus Lagoon. The average sedimentation rate, according to 210Pb dating models, is 0.85 cm/year. The large variation in sedimentation rates, especially after the 1990s, is consistent with an increase in the anthropogenic flux of heavy metals. This may be led into a significant environmental problem such as reducing the size of the lake and degrading the quality the water in Burullus Lagoon. Enrichment factor (EF) of the studied elements displayed the following order: Cl > Ca > Na > Br > Zn > Ta > Ti > V > Cr > Sc > Mg > Mn > Fe > Hf which is higher than unity. Furthermore, the Nemerow pollution index (PI Nemerow) revealed that pollution was increasing in the direction of the drains and slightly polluted. Consequently, pollutant indices showed that urbanization and industrial development may have increased the depositional fluxes of the metals in sediments over time.

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This study concerns the applied use of the natural radioactivity in soils. The relevance of airborne radiometric (gamma ray) survey data to peat mapping is now well established and such data have been used in a stand-alone sense and as covariates in machine learning algorithms. Here we present a method to use these data to accurately map the boundaries of peat (raised bogs). This has the potential to assist with the estimation of carbon stocks using a property-based assessment of soil. The significance of such regionally-uniform survey data lies in the subsurface information carried by the measurement which contrasts with the surficial nature of many other covariates. Soils attenuate radiometric flux by virtue of their bulk density (and associated carbon content) and water saturation level. The high attenuation levels in low density, wet peat materials give rise to a distinctive soil response. Here an entirely physics-based assessment of flux attenuation is carried out both theoretically and empirically. Radiometric data from the ongoing Tellus airborne survey of Ireland are used. The study area is characterised by an extensive assemblage of discrete raised peat bogs in a framework of largely mineral soils. Peat is detected by a property contrast with adjacent soils and so we consider all soils within the study area. The relatively low lateral resolution of the airborne data is demonstrated by modelling and we examine the behaviour of a combined spatial derivative of the data. The procedure allows the identification of the edges of the 128 peat polygons considered and indicates other additional potential areas of subsurface peat. The data appear to resolve the differences that exist across three available soil/peat databases that are used for the validation of the results obtained.

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Relative radiometric normalization (RRN) is a critical pre-processing step that enables accurate comparisons of multitemporal remote-sensing (RS) images through unsupervised change detection. Although existing RRN methods generally have promising results in most cases, their effectiveness depends on specific conditions, especially in scenarios with land cover/land use (LULC) in image pairs in different locations. These methods often overlook these complexities, potentially introducing biases to RRN results, mainly because of the use of spatially aligned pseudo-invariant features (PIFs) for modeling. To address this, we introduce a location-independent RRN (LIRRN) method in this study that can automatically identify non-spatially matched PIFs based on brightness characteristics. Additionally, as a fast and coregistration-free model, LIRRN complements keypoint-based RRN for more accurate results in applications where coregistration is crucial. The LIRRN process starts with segmenting reference and subject images into dark, gray, and bright zones using the multi-Otsu threshold technique. PIFs are then efficiently extracted from each zone using nearest-distance-based image content matching without any spatial constraints. These PIFs construct a linear model during subject-image calibration on a band-by-band basis. The performance evaluation involved tests on five registered/unregistered bitemporal satellite images, comparing results from three conventional methods: histogram matching (HM), blockwise KAZE, and keypoint-based RRN algorithms. Experimental results consistently demonstrated LIRRN's superior performance, particularly in handling unregistered datasets. LIRRN also exhibited faster execution times than blockwise KAZE and keypoint-based approaches while yielding results comparable to those of HM in estimating normalization coefficients. Combining LIRRN and keypoint-based RRN models resulted in even more accurate and reliable results, albeit with a slight lengthening of the computational time. To investigate and further develop LIRRN, its code, and some sample datasets are available at link in Data Availability Statement.

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Irazú is one of the largest and most active volcanoes in Costa Rica. We present the tephro-chronostratigraphy of the last 2.6 ka of the Irazú volcano based on detailed field work and C14 radiometric dating, as well as a revision of the geological and historical records. In the stratigraphic record we identified at least 30 tephra units. Eight of them corresponding to the historical period (i.e., after 1700 A.D.), separated by repose periods of different durations. The distribution of the deposits, the volcanic morphologies (craters and pyroclastic cones) and the radiometric ages indicate that most of this recent eruptive activity has occurred from the summit of Irazú along an E-W fissure (~ 4 km long). Toward the west of the summit, near the Sapper hill may be the source of the oldest eruptions at 200 A.D., while the La Laguna cone, located to the east of the summit, could have formed around 1540 A.D., and Main Crater to the west could have formed around sixteenth-seventeenth century. Since then, the historical eruptions (i.e., 1723-1724, 1917-1921, 1924, 1928, 1930, 1933, 1939-1940 and 1963-1965) have been sourced from this crater, but not all of them are registered in the stratigraphy. The eruption frequency of Irazú during this period ranges from 23 to 100 years, with a major event about every 80 years. Irazu's eruptions have been mainly phreatomagmatic and Strombolian, including some phreatic explosions. We present a detailed tephro-chronostratigraphy that will help to building temporal analysis for hazard assessment and risk management plans to face future eruptions at Irazú.

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Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions. Supplementary Information: The online version contains supplementary material available at 10.1007/s13157-023-01722-2.

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The drug metabolism and drug degradation pathways may overlap, resulting in the formation of similar constituents. Therefore, the metabolism data can be helpful for deriving safe levels of degradation impurities and improving the quality of respective pharmaceutical products. The present article contains considerations on possible links between metabolic and degradation pathways for new antidiabetic drugs such as glutides, gliflozins, and gliptins. Special attention was paid to their reported metabolites and identified degradation products. At the same time, many interesting analytical approaches to conducting metabolism as well as degradation experiments were mentioned, including chromatographic methods and radioactive labeling of the drugs. The review addresses the analytical approaches elaborated for examining the metabolism and degradation pathways of glutides, i.e., glucagon like peptide 1 (GLP-1) receptor agonists, and gliflozins, i.e., sodium glucose co-transporter 2 (SGLT2) inhibitors. The problems associated with the chromatographic analysis of the peptide compounds (glutides) and the polar drugs (gliflozins) were addressed. Furthermore, issues related to in vitro experiments and the use of stable isotopes were discussed.

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Significance: The quantification of protoporphyrin IX (PpIX) in skin can be used to study photodynamic therapy (PDT) treatments, understand porphyrin mechanisms, and enhance preoperative mapping of non-melanoma skin cancers. Aim: We aim to develop a smartphone-based imager for performing simultaneous radiometric fluorescence (FL) and white light (WL) imaging to study the baseline levels, accumulation, and photobleaching of PpIX in skin. Approach: A smartphone-based dual FL and WL imager (sDUO) is introduced alongside new radiometric calibration methods for providing SI-units of measurements in both pre-clinical and clinical settings. These radiometric measurements and corresponding PpIX concentration estimations are applied to clinical measurements to understand mechanistic differences between PDT treatments, accumulation differences between normal tissue and actinic keratosis lesions, and the correlation of photosensitizer concentrations to treatment outcomes. Results: The sDUO alongside the developed methods provided radiometric FL measurements (nW/cm2) with a demonstrated sub nanomolar PpIX sensitivity in 1% intralipid phantoms. Patients undergoing PDT treatment of actinic keratosis (AK) lesions were imaged, capturing the increase and subsequent decrease in FL associated with the incubation and irradiation timepoints of lamp-based PDT. Furthermore, the clinical measurements showed mechanistic differences in new daylight-based treatment modalities alongside the selective accumulation of PpIX within AK lesions. The use of the radiometric calibration enabled the reporting of detected PpIX FL in units of nW/cm2 with the use of liquid phantom measurements allowing for the estimation of in-vivo molar concentrations of skin PpIX. Conclusions: The phantom, pre-clinical, and clinical measurements demonstrated the capability of the sDUO to provide quantitative measurements of PpIX FL. The results demonstrate the use of the sDUO for the quantification of PpIX accumulation and photobleaching in a clinical setting, with implications for improving the diagnosis and treatment of various skin conditions.

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Thermography is probably the most used method of measuring surface temperature by analyzing radiation in the infrared part of the spectrum which accuracy depends on factors such as emissivity and reflected radiation. Contrary to popular belief that thermographic images represent temperature maps, they are actually thermal radiation converted into an image, and if not properly calibrated, they show incorrect temperatures. The objective of this study is to analyze commonly used image processing techniques and their impact on radiometric data in thermography. In particular, the extent to which a thermograph can be considered as an image and how image processing affects radiometric data. Three analyzes are presented in the paper. The first one examines how image processing techniques, such as contrast and brightness, affect physical reality and its representation in thermographic imaging. The second analysis examines the effects of JPEG compression on radiometric data and how degradation of the data varies with the compression parameters. The third analysis aims to determine the optimal resolution increase required to minimize the effects of compression on the radiometric data. The output from an IR camera in CSV format was used for these analyses, and compared to images from the manufacturer's software. The IR camera providing data in JPEG format was used, and the data included thermographic images, visible images, and a matrix of thermal radiation data. The study was verified with a reference blackbody radiation set at 60 °C. The results highlight the dangers of interpreting thermographic images as temperature maps without considering the underlying radiometric data which can be affected by image processing and compression. The paper concludes with the importance of accurate and precise thermographic analysis for reliable temperature measurement.

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Radiometric Terrain Corrected (RTC) gamma nought backscatter, which was introduced around a decade ago, has evolved into the standard for analysis-ready Synthetic Aperture Radar (SAR) data. While working with RTC backscatter data is particularly advantageous over undulated terrain, it requires substantial computing resources given that the terrain flattening is more computationally demanding than simple orthorectification. The extra computation may become problematic when working with large SAR datasets such as the one provided by the Sentinel-1 mission. In this study, we examine existing Sentinel-1 RTC pre-processing workflows and assess ways to reduce processing and storage overheads by considering the satellite's high orbital stability. By propagating Sentinel-1's orbital deviations through the complete pre-processing chain, we show that the local contributing area and the shadow mask can be assumed to be static for each relative orbit. Providing them as a combined external static layer to the pre-processing workflow, and streamlining the transformations between ground and orbit geometry, reduces the overall processing times by half. We conducted our experiments with our in-house developed toolbox named wizsard, which allowed us to analyse various aspects of RTC, specifically run time performance, oversampling, and radiometric quality. Compared to the Sentinel Application Platform (SNAP) this implementation allowed speeding up processing by factors of 10-50. The findings of this study are not just relevant for Sentinel-1 but for all SAR missions with high spatio-temporal coverage and orbital stability.

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Polarization is one of the fundamental properties of light, which has a wide range of applications and is developing rapidly. To meet the needs of polarization detection, different types of polarization instruments came into being. The precision of the polarization detection instruments is vital to the result analysis. In this paper, a full polarization imager is designed, and the radiometric calibration and polarization calibration of this instrument are studied. In radiometric calibration, the different numbers lights are set to verify the light intensity response of the imager. The mathematical model was constructed for numerical fitting, and the correlation between the fitted values and the measured values in the 490 nm, 550 nm, and 670 nm bands was above 0.99. Fixed the radiance of the integrating sphere, and adjusted exposure times. The correlation of the three bands is above 0.99, which verifies that the radiative stability of the imager is good. The polarimetric calibration system adopts the adjustable degree of polarization reference light source (APOL). The theoretical and measured values of the degree of polarization of reference light sources in three different bands are analyzed. The results show that the measurement accuracy of the 490 nm band is less than 2%. The precision of polarization measurement in the 550 nm band is less than 1.5%, and the precision of polarization calibration in the 670 nm band is less than 1%. The imager is verified to have high polarization calibration accuracy and meets the requirements of high-precision polarization detection.

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Airborne infrared optical systems equipped with multiple cooled infrared cameras are commonly utilized for quantitative radiometry and thermometry measurements. Radiometric calibration is crucial for ensuring the accuracy and quantitative application of remote sensing camera data. Conventional radiometric calibration methods that consider internal stray radiation are usually based on the assumption that the entire system is in thermal equilibrium. However, this assumption leads to significant errors when applying the radiometric calibration results in actual mission scenarios. To address this issue, we analyzed the changes in optical temperature within the system and developed a simplified model to account for the internal stray radiation in the non-thermal equilibrium state. Building upon this model, we proposed an enhanced radiometric calibration method, which was applied to the absolute radiometric calibration procedure of the system. The radiometric calibration experiment, conducted on the medium-wave channel of the system within a temperature test chamber, demonstrated that the proposed method can achieve a calibration accuracy exceeding 3.78% within an ambient temperature range of -30 °C to 15 °C. Additionally, the maximum temperature measurement error was found to be less than ±1.01 °C.

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This paper is part II of the review on metabolism and chemical degradation of new antidiabetic drugs from glutides, gliflozins and gliptins. It is well known that metabolism data can be helpful for deriving safe levels of degradation impurities and their qualifying as far as toxicological aspects are concerned. As a result, it could link the quality of respective pharmaceutical products to clinical practice and patients. Some overlapping pathways of transformations of these important drugs of different chemical structures and different mechanisms of action were discussed. At the same time, the paper summarized interesting analytical tools for conducting modern drug metabolism as well as drug degradation experiments. The methods described here include liquid chromatography (LC) and liquid chromatography coupled with mass spectrometry (LC-MS or LC-MS/MS), which are widely used for detection and quantitative measurements of the drugs, their metabolites and degradants, as well as radiometric methods that are suitable for pharmacokinetic experiments. Special attention was paid to dedicated types of packing in chromatographic columns, as well as to special solutions in the LC-MS procedures. The present part addresses the analytical approaches elaborated for examining the metabolism and degradation pathways of gliptins that are dipeptidyl peptidase 4 (DPP-4) inhibitors.

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An estimate of the radiogenic heat production (RHP) across the different petrologic units of northeastern, Nigeria was previously not performed. Hence, their geothermal potentials are not widely known. However, an airborne radiometric data of equivalent uranium, (eU), equivalent thorium (eTh,) and percentage potassium (% K) acquired by Nigerian geological survey agency (NGSA) in the year 2009 was deployed in the evaluation of the RHP across the major petrologic outcrops of northeastern, Nigeria. The objective of this study is to estimate the quantity of RHP across the 13 petrologic units of the northeastern Nigerian terrain via the use of an empirical equation (RHP=ρ(0.0952Cu+0.0256CTh+0.0348Ck)). The petrologic units studied are; medium-coarse grained biotite-hornblende granites (OGe), porphyritic biotite-hornblende granites (OGp), banded gneiss (bG), charnokytes (Ch), ignimbrites (JYG), migmatites-gneiss (MG), basalts (bb), Gombe sandstones (GS), Pindiga Formation (PS), Yolde Formation (YL), Bima sandstones (BS), Keri-Keri Formation (KK), and alluvium (AL). Basic/preliminary processing such as; signal integration, signal validation, and examination of spurious data were applied prior to the RHP computation. The results of the heat production analysis performed show the range of RHP to be from 1.11µW/m3 to 3.35µW/m3 Hence, the maximum heat production value of 3.35µW/m3 was recorded along porphyritic biotite-hornblende granites (OGp) rock block, while the least value of 1.11µW/m3 was recorded over alluvium (AL) rock outcrops. Furthermore, the spatial distribution of the RHP values over the study location shows a gradual increase from the middle, low heat production (sedimentary zones) to the high heat producing areas (granitic and metamorphic zones) around eastern and western parts. The petrologic units arranged in order of decreasing magnitude of radiogenic heat generation are; OGp > MG > OGe/bG > bb > GS > Ch > JYG > BS > PS/YL > KK > AL. On a general note, the petrologic units studied were classified as low in terms of geothermal character based on comparison with other previous global RHP studies.

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Tracking sediment movement is typically done with artificial radionuclides. However, this can be environmentally harmful and does not allow for sediment classification. Naturally occurring radionuclides are consequently offered as an alternative. In this study, a mobile Delta Underwater Gamma System (DUGS) capable of measuring low levels of natural radionuclides in sediment was deployed in an estuary, and a radiometric map of the sediment was constructed. Spatial autocorrelation using the Moran's I statistic was used to investigate the spatial distribution patterns of natural radionuclides in the sediments. Hotspot analysis using Getis-Ord* was used to validate and map areas that had been identified as clustered by the Moran's I statistic. The Moran's I analysis indicated that 40K displayed a positive spatial autocorrelation with a value of 0.4 and a standardized Z score of 16, thus indicating that the clustering was significant. 238U and 232Th displayed a low Moran's I value but a strong positive correlation, hence indicating some spots of clustering in the river channel. Further analysis of hotspots confirmed that the identified clusters were areas with relatively high radionuclide concentrations. This proved that the hotspot areas identified have a high deposition of sediment. In situ radiometric measurements of sediment, as well as spatial analysis, are consequently useful tools to model and study spatial structure and sediment.

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Stereo matching in binocular endoscopic scenarios is difficult due to the radiometric distortion caused by restricted light conditions. Traditional matching algorithms suffer from poor performance in challenging areas, while deep learning ones are limited by their generalizability and complexity. We introduce a non-deep learning cost volume generation method whose performance is close to a deep learning algorithm, but with far less computation. To deal with the radiometric distortion problem, the initial cost volume is constructed using two radiometric invariant cost metrics, the histogram of gradient angle and amplitude descriptors. Then we propose a new cross-scale propagation framework to improve the matching reliability in small homogenous regions without increasing the running time. The experimental results on the Middlebury Version 3 Benchmark show that the performance of the combination of our method and Local-Expansion, an optimization algorithm, ranks top among non-deep learning algorithms. Other quantitative experimental results on a surgical endoscopic dataset and our binocular endoscope show that the accuracy of the proposed algorithm is at the millimeter level which is comparable to the accuracy of deep learning algorithms. In addition, our method is 65 times faster than its deep learning counterpart in terms of cost volume generation.