Estimation Of Thickness Research Articles

A Planar Capacitive Sensor for Detecting and Measuring Thickness and Depth of Oil Under Ice

Abstract Detecting and characterizing oil spills in arctic environments is challenging due to the presence of sea ice. Methods based on Ground-Penetrating Radars and acoustic sensors were used in the literature to detect oil in ice-covered waters; however, their implementation is costly, and their capabilities are limited in terms of oil-thickness estimation. To address this problem, we propose a new low-cost sensing system based on a planar capacitive sensor that can detect the presence of oil under ice sheets and measure its thickness and depth. Our proposed sensor is based on movable dual electrodes mounted next to each other on the same sensing plane. The electric field created between the electrodes extends beneath the sensing plane and is affected by the electric properties of the sensed material (ice, oil, or water). Changes in the mutual capacitance of the electrodes are related to changes in the thickness and depth of the embedded oil phase. The capacitance of the sensor is measured at two different excitation frequencies while changing the horizontal separation distance between the electrodes. These measurements are collected to create a dataset for training machine-learning-based classification and regression models to detect the presence of oil and measure its thickness and depth. In comparison with the available sensing techniques, our proposed sensor has several advantages, such as being non-invasive or non-intrusive, simple to manufacture, safe to operate, and having low cost and low maintenance requirements. The experimental evaluation described in this paper demonstrates the effectiveness of our proposed system, which showed a very high detection accuracy of more than 90% and an accurate thickness and depth estimation capability with a Mean Absolute Error (MAE) of around 0.5 cm for thickness and depth estimations for oil thicknesses ranging between 0.5 cm and 8 cm and for oil depths ranging between 2 and 5 cm.

Non-destructive GPR signal processing technique for thickness estimation of pavement, coal and ice layers: A review

Non-destructive GPR signal processing technique for thickness estimation of pavement, coal and ice layers: A review

Characteristics of the Albian Westgate Formation polygonal fault system

Borehole logs and 3-D seismic data are used to determine the characteristics of a polygonal fault system (PFS) in the Albian Westgate Formation in western Saskatchewan and eastern Alberta. The basal Upper Cretaceous formation is a siliceous siltstone to mudstone deposited in the Western Interior Seaway beneath the Great Plains of North America. The faulted zone is layerbound within the ~80 m thick Westgate Formation at Swift Current, Saskatchewan. Most faulting occurs along grabens approximately 125 m wide and 10 m deep. The grabens are interconnected, have random strike directions, and lengths up to 800 m. The continuous depositional environment of the Westgate Formation enables timing and compacted sediment thickness estimates for the PFS initiation. The faults appear to have started in ~15 m or more of compacted sediment within the first 270,000 years of the 1.5 Myr Westgate Formation interval. Interpreting the seismic dataset and accompanying wellbore data has resulted in a simple model that enables PFS identification using only wellbore data. Wellbore data interpretations from Alberta and Saskatchewan show the PFS identified at Swift Current may range across a large area. The implications for an extensive PFS identification in the Lower Cretaceous Westgate Formation and homotaxially equivalent Mowry Shale across central North America are discussed.

A closer look to dose assessment and radiation shielding characteristics of concrete doped magnetite irradiated with 252Cf mixed radiation radionuclide: A Watt Fission approach and Doppler effect

Nuclear radiation emitted by fusion reactors, nuclear power plants, and medical establishments presents potential risks to living organisms personnel, necessitating the implementation of protective measures. To enhance radiation protection for patients workers, various materials can be utilized. Concrete, augmented with various additives, has historically acted as a shielding material. Hence, recent research has predominantly focused on enhancing concrete's ability to attenuate the harmful energy emitted by nuclear sources through modifications to its composition. Accordingly, in the present work, the dose evaluation and radiation shielding characteristics of a range of concrete magnetite (CM) formulations designated as CM-0 (control sample), CM-25, CM-50, CM-75, and CM-100 have been analyzed using MCNPX Monte Carlo (MC) approach and theoretical computations concerning 252Cf mixed radiation radionuclide. In this work, the Watt Fission distribution was employed to derive the neutron spectrum of CM samples, and findings have been thoroughly elucidated in the presence and absence of the specified samples. Then, utilizing the Doppler Effect, the gamma photon spectrum within shielding materials exposed to a spontaneous fission 252Cf source is extracted and characterized. Estimation of Half Value Thickness (HVT) and Mean Free Path (MFP) are provided across a broad spectrum of energy levels. The analysis confirms the successful development of a new type of concrete magnetite (CM) sample that exhibits lower radiation exposure compared to the control sample. This study offers valuable insights into the use of concrete in shielding against mixed radiation radionuclides and opens the door for future research involving similar materials. Specifically, the CM-100 sample demonstrated the lowest half-value thickness (HVT) and provided the most effective reduction of both neutron and gamma radiation. The findings suggest that increasing the concentration of magnetite in concrete greatly enhances its ability to shield against mixed neutron-gamma radiation. This innovation has promising potential for applications in radiation protection, particularly within nuclear reactors and medical facilities. The CM-100 sample showed a notable improvement, achieving an HVT of 0.012 cm and a dose rate reduction of 2.95 × 10−9 Sv.h−1, in contrast to the control sample (CM-0), which had an HVT of 10.358 cm and an equivalent dose rate of 2.84 × 10−9 Sv.h−1. These results underscore the superior shielding properties of the magnetite-doped concrete formulations.

Multidecadal decline in sea ice meltwater volume and Pacific Winter Water salinity in the Bering Sea revealed by ocean observations

Large amounts of freshwater and nutrients pass through the Bering Strait to the Arctic Ocean, making the Bering Sea a crucial marginal sea of the North Pacific Ocean. The hydrography and biological production of the Bering Sea are strongly influenced by the amount of sea ice produced and melted. The sea ice extent and production exhibited large interannual variability but no visible trend until 2016 when a strong decrease began. However, records of sea ice before 1979 and the beginning of satellite-based estimates do not exist. In this paper, we devised a methodology using historical temperature and salinity data, supplemented by historical oxygen isotope (δ18O) data, to estimate sea ice melt and its temporal variability in the Bering Sea from 1950 onward. Our results, consistent with estimates of sea ice thickness, indicate that the sea ice melt volume has declined significantly —following lower sea ice extent and production— with a decrease between 35 and 50 km3 (from 442 km3) between pre-1980 and post-1980 climatologies. In particular, our meltwater time series reveals a decline of 160 km3 between 2012 and 2018, which also reflects the strong decrease in sea ice volume between 2016 and 2018 that numerous previous studies have highlighted. We also evaluated the change in the salinity of the Pacific Winter Water (PWW), whose formation is also related to sea ice production. The time series of PWW salinity exhibits a strong decreasing trend, with a freshening of about 0.3 between the mid-1950 s and the mid-2010 s, that we attribute to a combination of a reduced sea ice production and the freshening of the Alaskan Coastal Current water. The decline in meltwater volume and PWW salinity that we observed strongly influences the stratification over the Bering shelf, with a significant weakening of the stratification in coastal polynya regions, and a stronger and increasingly temperature-controlled stratification in the rest of the shelf. These changes could have adverse consequences on the biological productivity of the northern Bering Sea.

A centralized frost detection and estimation scheme for Internet-connected domestic refrigerators

Frost accumulation on heat exchange units is a significant problem in refrigeration systems, adversely affecting their operating performance and thereby leading to increased power consumption. Therefore, timely detection and accurate quantification of frost are crucial for effective defrosting strategies. This study presents a novel centralized cloud-based IoT scheme for frost detection and thickness estimation. The image processing is performed on the cloud server to process evaporator coil images for frost thickness quantification. Experiments were conducted on a domestic refrigerator to assess the effectiveness of the proposed image-processing approach and determine latency and processing time. The presented scheme effectively quantifies frost thickness on the evaporator in the 1–5 mm range with a 10.8% error margin. The total inference time, which includes image acquisition, pre-processing, transmission latency, and frost thickness estimation, is approximately 5.15 seconds. The results demonstrate that the proposed image processing method performs comparably to conventional sensors and similar image processing techniques. Moreover, the centralized cloud-based IoT architecture presented effectively meets the scalability demands of consumer refrigerators.

Cortical Alterations Associated with Executive Function Deficits in Youth with a Congenital Heart Defect

Abstract Adolescents and young adults born with a complex congenital heart defect (CHD) are at risk for executive function (ExF) impairments, which contribute to the psychological and everyday burden of CHD. Cortical dysmaturation has been well described in fetuses and neonates with CHD and early evidence suggests that cortical alterations in thickness, surface area, and gyrification index are non-transient and can be observed in adolescents with CHD. However, cortical alterations have yet to be correlated with ExF deficits in youth with CHD. This study aims to use a data-driven approach to identify the most important cortical features associated with ExF deficits in adolescents and young adults with CHD. To do so, we combined two comparable datasets acquired at the Research Institute of the McGill University Health Centre and the University Children’s Hospital Zurich each including both youth with CHD and healthy controls. For each participant, a high-resolution T1-weighted magnetic resonance image, a self-reported ExF assessment (the Behaviour Rating Inventory of Executive Function— Adult Scale), and their clinical and demographic characteristics were available. Corticometric Iterative Vertex-Based Estimation of Thickness (CIVET) was used to extract cortical thickness, cortical surface area, and local gyrification index measures. Using orthogonal projective non-negative matrix factorization (OPNMF), we identified non-overlapping spatial components that integrate cortical thickness, cortical surface area, and local gyrification index and capture structural covariance across these features. Behavioural partial least squares correlation (bPLS) analysis was then used to compute correlations between the individual variability in the OPNMF covariance patterns and ExF outcomes for each subject. A total of 56 youth with CHD who underwent cardiopulmonary bypass surgery before three years of age and 56 age- and sex-matched healthy controls were included in our analyses. Cortical grey matter volume, cortical thickness, and cortical surface area were found to be significantly reduced in CHD patients compared to controls. OPNMF identified 12 stable cortex-wide components summarizing the inter-subject variability in cortical thickness, cortical surface area, and local gyrification index. bPLS revealed two significant latent variables (LV) accounting for a total of 82.8% of the variance in the sample, each describing distinct patterns between the brain and cognitive data. LV1 summarized a pattern of belonging to the CHD group, worse scores on most BRIEF-A scales, younger age at MRI, and female sex. This pattern was associated with increased cortical thickness, local gyrification index, and decreased cortical surface area in several OPNMF components. Finally, we identified a positive relationship between the LV1 brain-behaviour pattern and total aortic cross-clamp time in the CHD group, indicating that longer aortic cross-clamp time was associated with worse neurodevelopmental outcomes. In this study, we uncover novel multivariate relationships between ExF and alterations in cortical thickness, surface area, and local gyrification index in adolescents and young adults with CHD using a data-driven approach. Although our findings highlight the important role played by the cortex in higher order cognitive processes, future studies are needed to elucidate the individual contribution of individual and clinical attributes into the deficits observed in this population.

Optimising Interannual Sea Ice Thickness Variability Retrieved From CryoSat‐2

AbstractSatellite radar altimeters like CryoSat‐2 estimate sea ice thickness by measuring the return‐time of transmitted radar pulses, reflected from the sea ice and ocean surface, to measure the radar freeboard. Converting freeboard to thickness requires an assumption regarding the fractional depth of the snowpack from which the radar waves backscatter . We derive sea ice thickness from CryoSat‐2 radar freeboard data with incremental values for , for the 2010–2021 winter periods. By comparing these to sea ice thickness estimates derived from upward‐looking sonar moorings, we find that values between 35%–80% result in the best representation of interannual variability observed over first‐year ice, reduced to 55% over multi‐year ice. The underestimating bias in retrievals caused by optimizing this metric can be removed by reducing the waveform retracking threshold to 20%–50%. Our results pave the way for a new generation of ‘partial penetration’ sea ice thickness products from radar altimeters.

Arctic and Antarctic Sea Ice Thickness and Volume Changes From Observations Between 1994 and 2023

AbstractBoth Arctic and Antarctic sea ice are affected by climate change. While Arctic sea ice has been declining for several decades, Antarctic sea ice extent slowly increased until 2015, followed by a sharp drop in 2016. Quantifying sea ice changes is essential to assess their impacts on the ocean, atmosphere, ecosystems and Arctic communities. In this study, we combine sea ice thickness estimates from four satellite radar altimeters to derive the longest time series of homogeneous sea ice thickness for both hemispheres over 30 years (1994–2023). The record supports the rapid loss of sea ice in the Arctic for each month of the year and the heterogeneous changes in sea ice thickness in the Antarctic. The study confirms that most of the volume variability is due to the thickness variability, which holds true for both hemispheres. The sea ice thickness time series presented here offer new insights for models, in particular the possibility to evaluate sea ice reanalyses and to initialize forecasts, especially in the Antarctic, where the data set presented here has no equivalent in terms of spatial and temporal coverage.

Innovative and Cost‐Effective Approaches to the Measurement of Sediment Levels in Small Water Reservoirs

ABSTRACTSedimentation in small water reservoirs poses a critical challenge with significant environmental, economic, and social implications. To address this issue, this study will employ three measurement techniques—GNSS RTK Trimble R8s, Echolot HDS LIVE 7 with Active Imaging 3‐in‐1, and the Mivardi Carp Scout bait boat—to assess sediment levels in Žebětínský Pond in Brno, Czech Republic. The research reveals that each method offers distinct advantages and limitations. Through measurement and triangulated networks, the study creates a digital terrain model that facilitates the determination of reservoir volume and sediment levels. The comparison shows that the cost‐effective alternatives, Echolot HDS LIVE 7 and Mivardi Carp Scout, provide sufficiently accurate results. The evaluation shows that while the GNSS RTK Trimble R8s has the highest level of accuracy and is unique in its ability to measure both along the shoreline of the reservoir and the hard bottom, it comes with increased costs and logistical challenges. The Echolot HDS LIVE 7 and Mivardi Carp Scout offer efficient, cost‐effective solutions that are suitable for a quick estimate of sediment thickness. This research contributes to the use of reliable mathematical models and water management strategies, advocating for a pragmatic approach to the selection of methods based on the project characteristics. The study provides valuable insights into sediment measurement techniques, guiding future endeavors in reservoir management and environmental conservation. It is also used to easily indicate the loss of arable land in the catchment upstream of the reservoir.

Baltic sea ice thickness estimation based on X-band SAR data and background information

Abstract In this study an operational sea ice thickness (SIT) estimation algorithm, based on HH-polarized X-band synthetic aperture radar (SAR) data, background information from the most recent, typically from the previous day, available daily Baltic Sea ice chart and the operational Finnish Meteorological Institute (FMI) thermodynamic ice model, was developed and evaluated. The algorithm was designed to complement the C-band SAR SIT algorithm developed earlier at FMI and applied daily as part of the operational Copernicus Marine Service (CMS). The X-band SIT algorithm was developed by utilizing the sea ice thickness measurements made onboard the Finnish and Swedish ice breakers during two winters seasons: 2021–2022 and 2022–2023. The former season measurements were used for defining the algorithm parameters and the later season for evaluation of the algorithm performance. According to the evaluation metrics the X-band algorithm performance is slightly better than that of the operational CMS C-band SAR SIT algorithm, indicating its suitability for operational use in CMS.

Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy.

Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication. Here, evaluated the utility of MRI-based cortical atrophy as a predictor of longitudinal clinical decline in a sample of PCA patients. PCA patients were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit PCA Program. All patients had cortical thickness estimates from baseline MRI scans, which were used to predict longitudinal change in clinical impairment assessed by the CDR Sum-of-Boxes (CDR-SB) score. Multivariable linear regression was used to estimate the magnitude of cortical atrophy in PCA patients relative to a group of amyloid-negative cognitively unimpaired participants. Linear mixed-effects models were used to test hypotheses about the utility of baseline cortical atrophy for predicting longitudinal clinical decline. Data acquired from 34 PCA patients (mean age = 65.41 ± 7.90, 71% females) and 24 controls (mean age = 67.34 ± 4.93, 50% females) were analyzed. Sixty-two percent of the PCA patients were classified as having mild cognitive impairment (CDR 0.5) at baseline, with the rest having mild dementia (CDR 1). Each patient had at least one clinical follow-up, with the mean duration of 2.78 ± 1.62 years. Relative to controls, PCA patients showed prominent baseline atrophy in the posterior cortical regions, with the largest effect size observed in the visual network of the cerebral cortex. Cortical atrophy localized to the dorsal attention network, which supports higher-order visuospatial function, selectively predicted the rate of subsequent clinical decline. These results demonstrate the utility of a snapshot measure of cortical atrophy of the dorsal attention network for predicting the rate of subsequent clinical decline in PCA. If replicated, this topographically-specific MRI-based biomarker could be useful as a clinical prognostication tool that facilitates personalized care planning.

Children had smaller brain volumes and cortical surface areas after prenatal opioid maintenance therapy exposure.

The studies have shown that infants with prenatal OMT exposure had smaller brain volumes than non-exposed controls, but long-term outcome data are lacking. We examined 5-13-year-old OMT-exposed children with brain MRI and tested motor and visual-motor functions and possible associations between brain morphology and outcome. To this retrospective cohort study, we recruited 55 children with prenatal OMT exposure and 59 age- and gender-matched controls. They were examined with brain MRI, Movement-ABC and Beery-VMI. MRI images were processed with the Free Surfer® software to obtain volumetrics and estimates of cortical surface area and thickness. We used a general linear regression model (GLM) to calculate group differences. The children in the OMT group had smaller mean total intracranial volume (ICV), 1407 cm3 (CI 95% 1379-1434) versus 1450 cm3 (CI 95% 1423-1476) in the control group (p = 0.026). After adjusting for ICV, significant group differences persisted for volumes of amygdala, basal ganglia and mid-posterior part of corpus callosum. Cortical surface area was smaller in the left caudal middle frontal gyrus and the right inferior parietal lobule in the OMT-group. Visual-motor function was significantly correlated with ICV. Prenatal OMT exposure may alter early brain development with possible negative long-term functional consequences.

Characterizing the evolution of the Daguangbao landslide nearly 15 years after the 2008 Wenchuan earthquake by InSAR observations

The Daguangbao landslide (DGBL), the largest landslide triggered by the 2008 Ms 8.0 Wenchuan earthquake, has received much attention, but its long-term post-earthquake evolution and driving force of activity are still poorly understood. As the evolutionary behavior of the DGBL is complicated by the influence of mainshock, aftershocks and rainfall, it is of great significance to study the dynamics of the landslide. In this study, a systematic and comprehensive framework for assessing the long-term stability and risk of co-seismic landslides was proposed. Based on ALOS-1 and Sentinel-1 data, time-series InSAR technology was used to reveal the nearly 15-year post-seismic evolution characteristics of the DGBL at different stages, followed by the prediction of the stabilization time, the estimation of the landslide thickness and risk assessment. The first stage was identified as three years after the earthquake (2008–2011). During this stage, ALOS-1 results show that the deformation of DGBL was intense (300 mm/year) with uneven spatial distribution, and an aftershock (Ms 5.3), along with increased rainfall, triggered its acceleration in 2009. The second stage was the period from 2014 to 2022. For this stage, we used the mass conservation approach to invert the thickness of the DGBL, revealing that a new sliding surface and thickness center had formed following the co-seismic failure in 2008. Sentinel-1 time series results indicated that the DGBL remains active even 15 years after the Wenchuan earthquake, but the deformation of DGBL has significantly slowed down (50 mm/year). The stabilization time for different segments of DGBL was predicted to range from 2027 to 2040 according to an exponential model. Beyond the overall trend of recovery, seasonal movements (including localized acceleration in 2021) closely related to rainfall remained evident, but the impact of aftershocks on the DGBL was severely weakened over time. UAV and field survey results suggested that the risk of localized debris flows at DGBL still exists. Our study improves our understanding of the long-term evolutionary pattern of DGBL and provides an important reference for post-earthquake landslide risk assessment and disaster prevention.

Combined cognitive assessment and automated MRI volumetry improves the diagnostic accuracy of detecting MCI due to Alzheimer's disease

BackgroundMild cognitive impairment (MCI) confers a high annual risk of 10–15 % of conversion to Alzheimer's disease (AD) dementia. MRI atrophy patterns derived from automated ROI analysis, particularly hippocampal subfield volumes, were reported to be useful in diagnosing early clinical stages of Alzheimer's disease. ObjectiveThe aim of the present study was to combine automated ROI MRI morphometry of hippocampal subfield volumes and cortical thickness estimates using FreeSurfer 6.0 with cognitive measures to predict disease progression and time to conversion from MCI to AD dementia. MethodsBaseline (Neuropsychology, MRI) and clinical follow-up data from 62 MCI patients were analysed retrospectively. Individual cortical thickness and volumetric measures were obtained from T1-weighted MRI. Linear discriminant analysis (LDA) of both, cognitive measures and MRI measures (hippocampal subfields, temporal and parietal lobe volumes), were performed to differentiate MCI converters from stable MCI patients. ResultsOut of 62 MCI patients 21 (34 %) converted to AD dementia within a mean follow-up time of 74.7 ± 36.8 months (mean ± SD, range 12 to 130 months). LDA identified temporal lobe atrophy and hippocampal subfield volumes in combination with cognitive measures of verbal memory, verbal fluency and executive functions to correctly classify 71.4.% of MCI subjects converting to AD dementia and 92.7 % with stable MCI. Lower baseline GM volume of the subiculum and the superior temporal gyrus was associated with faster disease progression of MCI converters. ConclusionCombining cognitive assessment with automated ROI MRI morphometry is superior to using a single test in order to distinguish MCI due to AD from non converting MCI patients.

Field trial of a seismoacoustic method for ice cover parameters monitoring on the Franz Josef Land archipelago

Among the physical parameters of the freezing seas ice cover, ice thickness is of key importance, and its measurement is one of the most important tasks. The increased interest in the state of the sea ice cover as an indicator of global climatic changes, as well as the growth of comprehensive development of the Arctic shelf has caused intensive development of technical and methodological bases for ice observations. Despite the great variety of approaches to ice thickness estimation, all of them are not without weaknesses. Thus, most contact methods imply direct human presence, which significantly complicates the procedure, taking into account, among other factors, the rough weather conditions of the Arctic. Remote methods depend on weather conditions and cannot always provide high spatial resolution. In this connection, it is promising to use satellite observations coupled with the results of autonomous “ground” measurements, which can be seismoacoustic data containing information on the characteristics of elastic waves propagating in the ice-covered sea, is promising. The purpose of this work is to experimentally test a new passive method for monitoring ice cover parameters along long profiles based on the analysis of natural seismoacoustic fields. The article analyzes the data of a full-scale seismoacoustic experiment with a multichannel group of geophones placed on the floating ice of Alexandra Island in the Franz Josef Land archipelago within the framework of a complex expedition of the Russian Geographical Society. The demonstrates that it is in principle possible to use flexural-gravity waves propagating in the floating ice to estimate its characteristics, both in the active mode and by analyzing the ambient noise, is demonstrated. The results of ice parameter reconstruction obtained in a nondestructive manner using seismoacoustic waves and averaged over long profiles are compared with the data of direct contact measurements. This can be further used for monitoring seasonal and multiyear variability of sea ice thickness of freezing seas, including shelf zones.

Tension-based abdominal aortic aneurysm rupture risk assessment improves its accuracy and reduces the time of analysis

The biomechanical rupture risk assessment (BRRA) of abdominal aortic aneurysms (AAA) has higher sensitivity than maximal diameter criterion (DSEX) but its estimation is time-consuming and relies on an uncertain estimation of wall thickness. The aim of this study is to test tension-based criterion in the BRRA of AAA which removes the necessity of wall thickness measurement and should be faster. For that, we retrospectively analyzed 99 patients with intact AAA (25 females). Nineteen of them experienced a rupture later. BRRA was performed with wall tension PRRIT as a primary criterion. The ability of criterion to separate intact and ruptured AAAs at 1,3,6,9 and 12 months was estimated. Next, the receiver operating characteristics and the percentage of true negative cases for a different time to an outcome were estimated. Finally, the computational time was recorded. The results were compared to stress-based criterion PRRI and DSEX which served as a reference. All three criterions were able to discriminate between intact and ruptured AAAs up to 9 months (p < 0.05) while none of them could do for a 12 month prediction. PRRIT exhibited a significantly higher percentage of true negatives for 12 and 9 month predictions (45 % and 20 % respectively) and similar to other criteria for other prediction times. The mean computational time for estimating PRRIT was 19 h per patient compared to 67 h for PRRI. The tension- based BRRA of AAA leads to better outcomes for a 9 and 12 month prediction while the computational time drops by more than 70 % compared to PRRI.

An unmanned ground vehicle phenotyping-based method to generate three-dimensional multispectral point clouds for deciphering spatial heterogeneity in plant traits

Fusing three-dimensional (3D) and multispectral (MS) imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge. Acquiring high-quality 3D MS point clouds (3DMPCs) of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure. Here, we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field (NeREF) for radiometric calibration. This approach was used to acquire 3DMPCs of perilla, tomato, and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness (EWT) estimation. The results showed that the completeness of plant point clouds collected by this 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 partial least squares regression with the generated 3DMPCs. Collectively, our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions, which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits, and thus will facilitate plant biology and genetic studies as well as crop breeding.

A - 1 Informant Report of Practical Judgment Is Associated with Mild Cognitive Impairment and Measures of Brain Structure in a Nondemented Sample of Older Adults

Abstract Objective Given the potential risks associated with compromised judgment in older adulthood, we examined whether informant-reported practical judgment abilities were associated with cognitive impairment and measures of brain structure. Method 97 community-dwelling older adults with informants (Mage = 74.64 ± 7.42, Medu = 15.76 ± 2.42, 74%female, 92%white) underwent neuropsychological evaluation, including the Test of Practical Judgment-Informant (TOP-J-INF), a 15-item informant-reported scale of judgment ability. Participants were diagnosed with mild cognitive impairment (MCI; n = 33) or as neuropsychologically unimpaired (n = 64). Participants completed an MRI study including T1-weighted image processed with FreeSurfer software (v 6.0.0) to obtain estimates of gray matter volume and cortical thickness (parcellated with the Desikan-Killiany atlas). Logistic and linear models analyzed the association of TOP-J-INF with MCI diagnosis and brain volume/thickness (in separate models). To better support the exploratory nature of this analysis of associations with structural brain variables, we did not apply correction for multiple comparisons. Results Each additional point on the TOP-J-INF increased the odds of MCI diagnosis by 16.8% (OR = 1.168, p = 0.004). Worse judgment was associated with reduced brain volume in the right parahippocampal gyrus (β = −11.688, p = 0.032), superior temporal gyrus (β = −51.330, p = 0.040), rostral anterior cingulate cortex (β = −25.704, p = 0.004); and reduced thickness of the left transverse temporal gyrus (β = −0.010, p = 0.041). Conclusions To our knowledge, this is the first study to investigate the relationship between informant report of judgment and measures of brain structure, providing support that informant concerns about a loved one’s compromised judgment is associated with volume/thickness reduction in key brain regions. Assessing practical judgment abilities via informants could provide critical clinical information when working with vulnerable older individuals.

Aufeis thickness and volume estimations from stereo satellite imagery and terrestrial photographs: Evidence from Central Ladakh, India

Aufeis – a phenomenon associated with permafrost and the cold arid region of Ladakh – serves as a critical water resource for local communities. In several tributaries of the Indus River, aufeis accumulation is enhanced in ice reservoirs (commonly known as “artificial glaciers”) to store winter baseflow for crop irrigation during the water-scarce period in spring. This study investigates aufeis thickness and volume across four study sites in the Trans-Himalaya of Central Ladakh: the ice reservoirs of Phuktse and Igoo and the catchments of Gya and Sasoma, where natural aufeis fields occur. Aufeis thickness and volume estimates were derived via differencing of digital elevation models calculated from very high-resolution stereo Pléiades imagery and terrestrial photographs. The study revealed ice thickness up to a maximum of 3 m and could further demonstrate the amplification effect of the walls of the ice reservoirs on aufeis accumulation in both, differenced elevation from Pléiades and terrestrial photographs. Aufeis volumes across the four study sites range from 34,106 ± 13,440 m3 in Phuktse up to 105,790 ± 28,511 m3 in Sasoma, indicating substantial amounts that need to be considered in future hydrological studies in the region. While the approach with terrestrial photographs is especially suitable for local studies, the results from very high-resolution stereo satellite data are promising for aufeis studies on large spatial scales. It represents an important contribution for the understanding of spatial aufeis patterns in the Trans-Himalaya and affected regions worldwide.