Regional Anomalies Research Articles

Optimizing anomaly detection in 3D MRI scans: The role of ConvLSTM in medical image analysis

The analysis of Medical Images (MI), particularly the detection and classification of anomalies in 3D MRI (Magnetic Resonance Imaging) scans, plays a critical part in timely intervention and personalized therapy plans. In our paper, a comprehensive methodology for anomaly detection in 3D MRI scans of the brain is proposed that combines advanced Deep Learning (DL) techniques, including Convolutional Long Short-Term Memory (ConvLSTM) model, with efficient statistical feature extraction from segmented anomaly regions. The data collection phase utilizes three main datasets namely the Brain Tumor Segmentation Challenge (BRATS), the Federated Tumor Segmentation Challenge (FETS), and the Medical Segmentation Decathlon (MSD). The research begins with preprocessing steps including image resizing, intensity normalization, and alignment of anomaly region segmentation masks. The targeted anomaly regions within the samples are segmented using U-Net architecture and then follow statistical feature extraction procedure. Dimensionality reduction methods such as Principal Component Analysis (PCA) and Recursive Feature Elimination (RFE) are utilized to streamline the feature space. The ConvLSTM is then used to classify the anomalies using both convolution and recurrent layers to capture spatiotemporal patterns in MRI data. The model is fine-tuned and iterated for better classification performance using Adam optimizer. The statistical evaluation results with accuracy of 98.9 % showed that the designed ConvLSTM method is more suitable for clinical diagnosis and treatment design in detecting anomalies in 3D MRI images.

Machine learning approach to predict flow fields induced by internal solitary waves acting on mid-water structures based on particle image velocimetry experiments

Mid-water structures (MWSs) have important applications in the ocean to minimize the effects of environmental factors in the surface ocean and to avoid the effects of high pressure on the seabed. However, their operational positions are vulnerable to internal solitary waves (ISWs), which poses a significant challenge to the safe functioning of MWSs. Consequently, there is a pressing need to explore the flow field characteristics surrounding MWSs under the action of ISWs to establish a reliable foundation for structural design. In this study, experimental investigations were conducted to analyze the flow fields induced by ISWs acting on MWSs, employing the particle image velocimetry (PIV) method. The intricate details of the flow fields around the structure were thoroughly analyzed, and the impact of the structure's submerged depth on the ISW-induced flow fields was discussed. A machine learning approach is utilized to develop an Artificial Neural Network (ANN) model aimed at predicting the flow fields of ISWs. The experimental results are compared and analyzed alongside the predicted outcomes, focusing on the anomaly region, the tail field region, and the occluded region. The results show that the presence of the structure complicates the flow characteristics in the tail flow regions, and the flow patterns are constantly changing. The characteristics of the ISW flow fields around the structure vary with the different submerged depths of the MWS. Positioning the MWS above the wave trough results in an ascending trend followed by a descending trend in the strength of the surrounding flow field with increasing submerged depth. The ANN predictions for different types of regions of the flow fields show satisfactory accuracy. The model closely matches the PIV results in predicting the extremes and positions of horizontal velocities in the tail flow fields at different stages of ISW trough propagation. The ANN model can be recommended for predicting the flow fields of ISWs acting on MWSs. This study offers comprehensive insights into the characteristics of the flow fields induced by ISWs acting on MWSs, emphasizing the valuable contribution of machine learning methods to the field of fluid dynamics.

Розробка цифрових карт модуля індукції геомагнітного поля для території України

Knowledge of Ukraine`s geomagnetic field is based on magnetic surveys of the geomagnetic field induction module B and its power and angular components, as well as on observations or calculations of their anomalous values. The article describes the methods for constructing a digital map of the induction module of the geomagnetic field B. The map of module B for the epoch of 1969.5 is developed, which is the ground to create the maps of module B and its anomalies ΔB for an arbitrary epoch. The results of the ground absolute magnetic survey of 1969-1972, the analytical model of the main geomagnetic field BIGRF, as well as the map of the anomalous magnetic field on a scale of 1: 1,000,000 were used to construct the map of the geomagnetic field induction module B. The digital map of the module and anomalies of the geomagnetic field induction module B for the 1969.5 epoch was obtained by calculating the correction based on their difference values at the points of the absolute reference network. It was spread by interpolation according to the 1x1km matrix to the entire data array for the territory of Ukraine. The geomagnetic field induction module B for the 2005.5 epoch was calculated by adding to its values in the 1969.5 epoch the calculated values of the field dynamics ВIGRF and the "magnetizing" effect of anomalies of the induction module ΔΔB. The developed map is an approximate representation of the magnetic field modulus, since the amount of remanent magnetization was not taken into account during the calculation, which may cause minor deviations of the calculated and observed field values. The induction module of the geomagnetic field B in the epoch of 1969.5 varies in the range of 46,500÷62,000 nT, and in the epoch of 2005.5 ‒ 47,000÷63000 nT, increasing from the southwest to the northeast of the territory of Ukraine. Its maximum values are observed in the areas of regional and local magnetic anomalies, in particular in the area of the Kryvyi Rih-Kremenchuk anomalous strip and the southeastern edge of the Kursk anomaly. The dynamics of the BIGRF field for the period of 1969.5÷2005.5 is characterized by values from 700 nT in the east of the territory of Ukraine to 950 nT in the west, and the magnitude of the magnetizing effect ΔΔB varies within ±10 nT, reaching maximum values (up to 100-190 nT) in the regions of intense magnetic anomalies. The digital map of the geomagnetic field induction module B, developed in 2005.5, has been verified. This was done by measuring the values of module B in the magnetic observatories of Kyiv, L’viv, and Odesa, as well as in the Repeat Stations of the Ist and IInd classes. The results showed that there was only a small difference (-20 ÷ 40 nT) between the calculated and measured values of modulus B. Their most significant differences are spatially correlated with areas of modern activation of the Earth's crust on the territory of Ukraine and electrical conductivity anomalies.

Ionospheric Channel Impulse Response Measurement System for NVIS Propagation Mode Over Java Island Based on Low‐Cost SDR Platform

AbstractThe development of a digital high‐frequency (HF) radio communication system requires an ionospheric channel model from the channel impulse response (CIR) measurement. Although the Watterson ionosphere channel model has been available and used for a long time, several CIR measurements have been conducted in all regions of the Earth in an attempt to validate or replace the Watterson channel model with a suitable model for their region. However, only a few CIR measurements were conducted in low‐latitude regions, especially over Indonesia. In this study, we develop the CIR measurement system for the near vertical incidence skywave (NVIS) propagation mode over Java Island based on the software defined radio platform to meet low‐cost and simple operation requirements. The specification of the system is based on the International Telecommunication Union ionospheric channel characteristic document and increased in order to be able to capture higher values. Results from a 1‐week campaign measurement period show the ability of the system to measure the root mean square of time delay within the range of 0.2–1.3 ms and the Doppler shift within the range of 0.7–1.1 Hz in the quiet conditions of the ionosphere. Further measurements will be conducted to obtain a comprehensive ionosphere CIR that is useful for designing the NVIS‐HF digital communication in Indonesia, which is located beneath the crest region of an equatorial ionospheric anomaly.

Westward PPEF Plays Important Role in the Suppression of Post‐Midnight Plasma Irregularities: A Case Study of the November 2021 Geomagnetic Storm

AbstractWe use multiple instruments data to investigate the behavior of the equatorial and low‐latitude ionosphere during the geomagnetically active and quiet period of November 1–6, 2021. In this context, total electron content (TEC) data obtained from the Global Positioning System (GPS) receivers in the equatorial and low‐latitude regions of Asia, Africa, and America are used to assess variations in plasma density during the storm. The storm‐time ionization levels were found to vary significantly in the crests of the Equatorial Ionization Anomaly (EIA) region over the 3 longitudes. The Rate of Change TEC Index (ROTI) derived from GPS receiver measurements, is used to study the equatorial/low‐latitude ionospheric plasma irregularities at various longitudes under geomagnetically quiet and disturbed conditions. Observations showed longitudinal variations in the ionospheric irregularities under both quiet and disturbed conditions. Some days exhibit a decrease in the strength of the midnight plasma irregularities toward the East, that is, the irregularities are more pronounced in West America, less common in East America, and almost non‐existent in Africa and Asia. Our investigations show this storm prevented the occurrence of plasma irregularities at the equatorial/low‐latitude region in the American sector during the night following the main phase. In general, no significant storm effects were observed at the target locations in Africa and Asia. The existence of westward Prompt Penetration Electric Field (PPEF) and the Equatorial Electrojet (EEJ) during the main phase, from midnight to noon, is clearly related with the constriction of plasma diffusion and the consequent suppression of plasma irregularities. Thus, the longitudinal dependence for the generation of midnight plasma irregularities during this storm is mainly influenced by local time occurrence of maximum ring current, and the ionospheric electric fields.

Exploring ionospheric plasma density trends in the Indian equatorial crest region under varying solar activity conditions

Long-term trends in the evolution of ionospheric plasma at Hyderabad (17.38∘N, 78.48∘E; 8.52∘N Magnetic Latitude), a near-equatorial anomaly (EIA) crest region of the Indian ionospheric sector, have been studied using 9 years of vertical Total Electron Content (TEC) data from 2004 to 2009 and 2011 to 2013 using global positioning satellites (GPS) measurements. The study examined the mean diurnal, monthly, seasonal, and yearly variations of TEC during geomagnetic quiet days in different seasons from 2004 to 2013. The findings reveal that the daytime TEC at the anomaly crest region exhibits semi-annual variations throughout the study period, while midnight TEC shows semi-annual variation only during the high solar activity years of 2011–2013. The winter anomaly was observed in 2004 and 2006. The study also assessed the performance of the International Reference Ionosphere (IRI) 2016 model in reproducing GPS TEC variability at the equatorial crest region. The diurnal and seasonal variation patterns in IRI-TEC show a good correlation with GPS TEC. However, the IRI 2016 model tends to overestimate TEC values during low solar activity conditions (2006–2009) but represents TEC variations reasonably well during high solar activity periods (2011–2013). Nevertheless, the IRI model fails to capture the wide plateau-like structure in the peak TEC, typically occurring between 1200–1600 IST at Hyderabad. Additionally, IRI-TEC consistently indicates very low TEC values during the early morning hours, whereas GPS-TEC measurements suggest a significant presence of plasma density. The study suggests a strong influence of the solar cycle on TEC variations at Hyderabad, evident from the positive correlation (R2= 0.71) with the F10.7 cm index. This characteristic is also well represented by the IRI 2016 model.

Precipitation patterns and their variability in the southern region of Brazil

Climate change is a long-term transformation of climate patterns, which can be natural or anthropogenic. Signs of climate change can manifest themselves in different ways: through the occurrence of extreme events, rising ocean levels, melting glaciers, among others. Negative impacts are produced by climate change and are one of humanity's biggest concerns, since its effects reach the entire planet with different consequences. Considering the need for actions aimed at contributing to the process of mitigating climate change, the importance of knowing changes in regional climate patterns is emphasized. This study aims to analyze changes in precipitation patterns over time in the southern region of Brazil, including variability, trends, anomalies, droughts and excess rainfall. Daily precipitation data from 1961 to 2020 were used, collected at 15 meteorological stations in the region. Various statistical analyzes were carried out, such as averages, maximum and minimum values, seasonal and annual anomalies, frequency distribution, Mann-Kendall trend tests and the Normalized Precipitation Index (SPI). The results indicate that climate change trends are positive in terms of increasing rainfall volumes, altering rainfall dispersion patterns (volume). In other words, rainfall is more irregular in terms of distribution throughout the seasons. The big highlight was Florianópolis -SC, which during the summer had the highest volume of rain among the meteorological stations studied.

Revisiting the Ionospheric Disturbances Over Low Latitude Region of China During Super Typhoon Hato

AbstractThe ionosphere exhibits complex variations due to the influences from above and below. To distinguish the source of ionospheric disturbances is important for understanding the variation process and the coupling mechanism among different regions. Using the ionospheric total electron content (TEC) derived from Global Navigation Satellite System observations, the ionospheric disturbances during the super typhoon Hato in 2017 that was accompanied by a weak geomagnetic storm are revisited, including the ionospheric deviation and traveling ionospheric disturbances (TIDs). It is found that the ionospheric TEC in the low‐latitude region of China experienced a significant enhancement (200% compared to the quiet geomagnetic day) on Hato landing day. This enhancement covers the northern and southern equatorial ionization anomaly (EIA) region from 80°E to 180°E. Considering the geomagnetic condition, the hmF2 and the O/N2 ratio in thermosphere, it is concluded that this enhancement is not related to the typhoon, but to the coinciding weak geomagnetic storm. Additionally, several medium‐scale TIDs are verified from differential TEC data in China low latitude region during Hato period. Most of them occur after sunset and their propagating direction is southwest that often occur in East‐Asian sector in summer months, which are not related to the typhoon. While a few TIDs with concentric wavefront (Concentric TIDs) are also observed on the day before Hato landfall that should be excited in the deep convective region of the typhoon. Because the ionosphere is affected by disturbances both from above and below, it should be careful to determine the source of the ionospheric disturbances.

Global Precipitation for the Year 2023 and How It Relates to Longer Term Variations and Trends

Global Precipitation for the Year 2023 and How It Relates to Longer Term Variations and Trends

Unraveling thermodynamic anomalies of water: A molecular simulation approach to probe the two-state theory with atomistic and coarse-grained water models.

Thermodynamic and dynamic anomalies of water play a crucial role in supporting life on our planet. The two-state theory attributes these anomalies to a dynamic equilibrium between locally favored tetrahedral structures (LFTSs) and disordered normal liquid structures. This theory provides a straightforward, phenomenological explanation for water's unique thermodynamic and dynamic characteristics. To validate this two-state feature, it is critical to unequivocally identify these structural motifs in a dynamically fluctuating disordered liquid. In this study, we employ a recently introduced structural parameter (θavg) that characterizes the local angular order within the first coordination shell to identify these LFTSs through molecular dynamics simulations. We employ both realistic water models with a liquid-liquid critical point (LLCP) and a coarse-grained water model without an LLCP to study water's anomalies in low-pressure regions below 2 kbar. The two-state theory consistently describes water's thermodynamic anomalies in these models, both with and without an LLCP. This suggests that the anomalies predominantly result from the two-state features rather than criticality, particularly within experimentally accessible temperature-pressure regions.

In Vivo Assessment of Retinal Phenotypes in Axenfeld-Rieger Syndrome.

Axenfeld-Rieger syndrome (ARS) is characterized by ocular anomalies including posterior embryotoxon, iridocorneal adhesions, corectopia/iris hypoplasia, and developmental glaucoma. Although anterior segment defects and glaucoma contribute to decreased visual acuity, the role of potential posterior segment abnormalities has not been explored. We used high-resolution retinal imaging to test the hypothesis that individuals with ARS have posterior segment pathology. Three individuals with FOXC1-ARS and 10 with PITX2-ARS completed slit-lamp and fundus photography, optical coherence tomography (OCT), OCT angiography, and adaptive optics scanning light ophthalmoscopy (AOSLO). Quantitative metrics were compared to previously published values for individuals with normal vision. All individuals demonstrated typical anterior segment phenotypes. Average ganglion cell and inner plexiform layer thickness was lower in PITX2-ARS, consistent with the glaucoma history in this group. A novel phenotype of foveal hypoplasia was noted in 40% of individuals with PITX2-ARS (but none with FOXC1-ARS). Moreover, the depth and volume of the foveal pit were significantly lower in PITX2-ARS compared to normal controls, even excluding individuals with foveal hypoplasia. Analysis of known foveal hypoplasia genes failed to identify an alternative explanation. Foveal cone density was decreased in one individual with foveal hypoplasia and normal in six without foveal hypoplasia. Two individuals (one from each group) demonstrated non-foveal retinal irregularities with regions of photoreceptor anomalies on OCT and AOSLO. These findings implicate PITX2 in the development of the posterior segment, particularly the fovea, in humans. The identified posterior segment phenotypes may contribute to visual acuity deficits in individuals with PITX2-ARS.

Atmospheric and Oceanic Factors Related to the Increasing Summer High Temperature Extremes on the Tibetan Plateau under the Background of Global Warming

Abstract The related atmospheric and oceanic factors are investigated in this analysis to understand the natural attributes responsible for the significant increase of the high temperature extremes (HTEs) on the Tibetan Plateau (TP) in summer. It is found that a stronger-than-normal South Asian high (SAH) and corresponding weaker-than-normal East Asian jet, an anomalous anticyclone and intensified midlevel westerly wind over the TP, and a more extensive, stronger, farther westward- and northward-stretching western Pacific subtropical high motivate more occurrences of HTEs over the TP on the interannual time scale. From 1961 to 2021, these crucial circulation patterns show a significant changing trend favorable for the occurrence of HTEs and thus contribute to its great increase. Further, the significant warmings of sea surface temperature (SST) in the tropical western Indian, northern North Pacific, and western North Atlantic Oceans make great contributions through different air–sea interactive processes as the Matsuno–Gill response, zonal vertical circulation cell, and mid- to high-latitude teleconnection wave train, respectively. Meanwhile, the interdecadal variability plays an important role. A breakpoint at the early twenty-first century is detected in the occurrence of summer HTEs on the TP. Both the crucial circulation patterns and the SST anomalies in the key oceanic regions experienced significant interdecadal transition to favor the occurrence of HTEs. In particular, the Atlantic multidecadal oscillation (AMO) is significantly and positively correlated with the interdecadal variation of summer HTEs on the TP. The zonal teleconnection wave train triggered by AMO forms a stronger-than-normal SAH and strengthened midlevel westerly airflow over the TP, conducive to the increase of summer HTEs on the TP.

Perisylvian and Hippocampal Anomalies in Individuals With Pathogenic GRIN2A Variants.

Pathogenic variants in GRIN2A are associated with a spectrum of epilepsy-aphasia syndromes (EASs). Seizures as well as speech and language disorders occur frequently but vary widely in severity, both between individuals and across the life span. The link between this phenotypic spectrum and brain characteristics is unknown. Specifically, altered brain networks at the root of speech and language deficits remain to be identified. Patients with pathogenic variants in GRIN2A offer an opportunity to interrogate the impact of glutamate receptor dysfunction on brain development. We characterized brain anomalies in individuals with pathogenic GRIN2A variants and EASs, hypothesizing alterations in perisylvian speech-language regions and the striatum. We compared structural MRI data from 10 individuals (3 children and 7 adults, 3 female) with pathogenic GRIN2A variants with data from age-matched controls (N = 51 and N = 203 in a secondary analysis). We examined cortical thickness and volume in 4 a priori hypothesized speech and language regions (inferior frontal, precentral, supramarginal, and superior temporal) and across the whole brain. Subcortical structures (hippocampus, basal ganglia, thalamus) and the corpus callosum were also compared. Individuals with pathogenic GRIN2A variants showed increased thickness and volume in the posterior part of Broca's area (inferior frontal gyrus, pars opercularis). For thickness, the effects were bilateral but more pronounced in the left (large effect size, η2 = 0.37) than the right (η2 = 0.12) hemisphere. Both volume and thickness were also higher in the bilateral superior temporal region while the supramarginal region showed increased thickness only. Whole-brain analyses confirmed left-sided thickness increases in Broca's area, with additional increases in the occipital and superior frontal cortices bilaterally. Hippocampal volume was reduced in the left hemisphere. There were no age-dependent effects or corpus callosum group differences. Anomalies in perisylvian regions, with largest differences in Broca's area, suggest an altered development of classical speech-language networks in GRIN2A-related EAS. Left hippocampal reduction suggests a role for this structure in early speech and language development and is consistent with GRIN2A gene expression in that region. Overall, elucidating the neural correlates of EAS provides insights into the impact of GRIN2A dysfunction, opening avenues for targeted intervention in developmental syndromes with compromised speech-language development.

A comparison of ionospheric TEC between the South Atlantic anomaly region and the Indian Ocean region based on TIEGCM simulations in 2002

Using the Thermosphere-Ionosphere-Electrodynamic General Circulation Model (TIEGCM), a comparison of the ionospheric total electron content (TEC) between the South Atlantic anomaly (SAA) and the Indian Ocean (IO) at solar maximum is performed in this study. The results show that the average total electron content in the SAA is greater than that in the Indian Ocean in general. In order to further analyze the difference between the two regions, the empirical orthogonal function (EOF) are used to investigate the temporal and spatial characteristics of TEC. The empirical orthogonal function method separate part of the global four-peak structure (an equatorial ionization anomaly structure, distributed in Southeast Asia, South America, Africa, and central Pacific) and spatial variations in both regions. Moreover, the first mode of EOF shows the different distribution of Equatorial ionization anomaly in South America and central Pacific caused by deviation of geomagnetic field and tides between two regions, and the enhancement of TEC in SAA region at dusk is emphasized, but the enhancement of TEC in IO region at dawn is emphasized. The second mode performs the distribution of EIA in Africa related to solar radiation and E×B drift. The third mode indicates the similar spatiotemporal variations from the geomagnetic field. Besides, the correlation between TEC and Dst in two regions indicate that there are some deficiencies in simulation to the specificity of SAA, and the deficiencies are likely caused by the model’s inaccurate simulation of the magnetic field and particle deposition in the SAA region.

Annual study of gravity anomalies in oceanic regions by altimeter satellite data

Annual study of gravity anomalies in oceanic regions by altimeter satellite data

Comparative analysis of the rapid intensification of two super cyclonic storms in the Arabian Sea

A comparative analysis of the rapid intensification (RI) of super cyclonic storms Chapala (2015) and Kyarr (2019) in the Arabian Sea is conducted using the North Indian Ocean tropical cyclone data, microwave sounding images, the NOAA OISST data and the ERA5 reanalysis data. Results show that the subtropical westerly jet stream and the Southern Hemisphere anticyclonic circulation led to the formation of an obvious double-channel outflow from the northern and southern sides of the two storm centers, and the substantial inflow appeared at the eastern boundary layer of both storms. These promoted the vertical ascent motion and release of the latent heat of condensation. A warm sea surface is a necessary but not dominant factor for the RI of cyclonic storms in the Arabian Sea. During the RI of Chapala and Kyarr, the deep vertical wind shear was less than 10 m s−1; moreover, the mid-level humidity conditions favored the RI of the two cyclonic storms. Chapala had a single warm core, whereas Kyarr had double warm cores in the vertical direction. The impacts of the latent heat of fusion is more obvious for Chapala, and the potential vorticity in its inner core increases from 4.4 PVU to 8.8 PVU, whereas the potential vorticity and vorticity in the inner core of Kyarr do not change significantly. Microwave detection images show that both Chapala and Kyarr were accompanied by the formation of eyewalls during the RI phase, and the radius of maximum wind decreased and the maximum wind speed increased during the eyewall-thinning process. Both Chapala and Kyarr passed through a positive anomaly region of maximum potential intensity during the RI phase, which increases the possibility to develop to higher intensity after genesis.

Capturing COPD heterogeneity: anomaly detection and parametric response mapping comparison for phenotyping on chest computed tomography.

Chronic obstructive pulmonary disease (COPD) poses a substantial global health burden, demanding advanced diagnostic tools for early detection and accurate phenotyping. In this line, this study seeks to enhance COPD characterization on chest computed tomography (CT) by comparing the spatial and quantitative relationships between traditional parametric response mapping (PRM) and a novel self-supervised anomaly detection approach, and to unveil potential additional insights into the dynamic transitional stages of COPD. Non-contrast inspiratory and expiratory CT of 1,310 never-smoker and GOLD 0 individuals and COPD patients (GOLD 1-4) from the COPDGene dataset were retrospectively evaluated. A novel self-supervised anomaly detection approach was applied to quantify lung abnormalities associated with COPD, as regional deviations. These regional anomaly scores were qualitatively and quantitatively compared, per GOLD class, to PRM volumes (emphysema: PRMEmph, functional small-airway disease: PRMfSAD) and to a Principal Component Analysis (PCA) and Clustering, applied on the self-supervised latent space. Its relationships to pulmonary function tests (PFTs) were also evaluated. Initial t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the self-supervised latent space highlighted distinct spatial patterns, revealing clear separations between regions with and without emphysema and air trapping. Four stable clusters were identified among this latent space by the PCA and Cluster Analysis. As the GOLD stage increased, PRMEmph, PRMfSAD, anomaly score, and Cluster 3 volumes exhibited escalating trends, contrasting with a decline in Cluster 2. The patient-wise anomaly scores significantly differed across GOLD stages (p < 0.01), except for never-smokers and GOLD 0 patients. In contrast, PRMEmph, PRMfSAD, and cluster classes showed fewer significant differences. Pearson correlation coefficients revealed moderate anomaly score correlations to PFTs (0.41-0.68), except for the functional residual capacity and smoking duration. The anomaly score was correlated with PRMEmph (r = 0.66, p < 0.01) and PRMfSAD (r = 0.61, p < 0.01). Anomaly scores significantly improved fitting of PRM-adjusted multivariate models for predicting clinical parameters (p < 0.001). Bland-Altman plots revealed that volume agreement between PRM-derived volumes and clusters was not constant across the range of measurements. Our study highlights the synergistic utility of the anomaly detection approach and traditional PRM in capturing the nuanced heterogeneity of COPD. The observed disparities in spatial patterns, cluster dynamics, and correlations with PFTs underscore the distinct - yet complementary - strengths of these methods. Integrating anomaly detection and PRM offers a promising avenue for understanding of COPD pathophysiology, potentially informing more tailored diagnostic and intervention approaches to improve patient outcomes.

Machine learning-aided thermography for autonomous heat loss detection in buildings

Efficient inspection of heat loss from building façades is an active research area, driven by the need for improved auditing and monitoring solutions. Thermography is a valuable tool for identifying anomalous heat patterns. This paper presents a novel method for autonomous inspection of heat loss from building façades by combining thermal camera-based imaging, advanced deep learning with YOLOv7 for anomaly detection, and a mathematical model for heat flow quantification. The methodology achieved a mean average precision (mAP@0.5) of 0.770 for anomaly detection when tested on thermal data collected from a multi-unit residential building in an extremely cold climate. The highest heat loss measured at 1533.73 W was from the south façade, while the largest area of heat loss, covering 15.65 m2, was identified on the southeast façade. The study identified 28 regions of thermal anomaly on the building façades, and heat loss from these regions was quantified for inspection.

Improved capabilities of global ocean reanalyses for analysing sea level variability near the Atlantic and Gulf of Mexico Coastal U.S.

Realistic representation of monthly sea level anomalies in coastal regions has been a challenge for global ocean reanalyses. This is especially the case in coastal regions where sea levels are influenced by western boundary currents such as near the U.S. Atlantic Coast and the Gulf of Mexico. For these regions, most ocean reanalyses compare poorly to observations. Problems in reanalyses include errors in data assimilation and horizontal resolutions that are too coarse to simulate energetic currents like the Gulf Stream and Loop Current System. However, model capabilities are advancing with improved data assimilation and higher resolution. Here, we show that some current-generation ocean reanalyses produce monthly sea level anomalies with improved skill when compared to satellite altimetry observations of sea surface heights. Using tide gauge observations for coastal verification, we find the highest skill associated with the GLORYS12 and HYCOM ocean reanalyses. Both systems assimilate altimetry observations and have eddy-resolving horizontal resolutions (1/12°). We found less skill in three other ocean reanalyses (ACCESS-S2, ORAS5, and ORAP6) with coarser, though still eddy-permitting, resolutions (1/4°). The operational reanalysis from ECMWF (ORAS5) and their pilot reanalysis (ORAP6) provide an interesting comparison because the latter assimilates altimetry globally and with more weight, as well as assimilating ocean observations over continental shelves. We find these attributes associated with improved skill near many tide gauges. We also assessed an older reanalysis (CFSR), which has the lowest skill likely due to its lower resolution (1/2°) and lack of altimetry assimilation. ACCESS-S2 likewise does not assimilate altimetry, although its skill is much better than CFSR and only somewhat lower than ORAS5. Since coastal flooding is influenced by sea level anomalies, the recent development of skilful ocean reanalyses on monthly timescales may be useful for better understanding the physical processes associated with flood risks.

Altitude Behavior of Subrelativistic Electron Fluxes in the Region of the South Atlantic Anomaly According to Measurements on the SiriusSat-1 Satellite

Altitude Behavior of Subrelativistic Electron Fluxes in the Region of the South Atlantic Anomaly According to Measurements on the SiriusSat-1 Satellite