Intensity Variations Research Articles

Optimal segmentation of image datasets by genetic algorithms using color spaces

A vision system comprises several steps, with each step exerting a significant impact on the final outcome. One of these crucial steps is segmentation, which isolates the region of interest within an object and removes the background. Segmentation is vital because it enhances the quality of the isolated region, improves the accuracy of extracted features, and reduces the noise introduced by poor-quality features. Several segmentation techniques are available in the literature, each requiring one or more adjustable parameters. Selecting the most appropriate technique for segmenting a particular image dataset can be challenging. Several factors can affect the segmentation quality, including preprocessing, the chosen segmentation method, parameter fine-tuning approaches, and the characteristics of the dataset. Moreover, variations in lighting and intensity can further influence segmentation quality. At times, an expert may need to manually choose the segmentation technique and fine-tune its associated parameters. This paper presents the development of an automated algorithm for the selection of segmentation techniques and their associated parameters. The developed techniques are implemented and compared using diverse datasets, and the resulting experimental outcomes are thoroughly discussed and analyzed. The algorithm aims to streamline and simplify the process of selecting appropriate segmentation techniques, determining the required parameters, and selecting suitable pre-processing techniques.

Multiscale structural analyses of Mesozoic shallow-water carbonates, Viggiano Mt., southern Italy

The high-angle faults bounding the High Agri Valley Basin eastwards are well-exposed at the Viggiano Mt., southern Italy. There, these faults crosscut Mesozoic shallow-water carbonates and permit the multiscale analyses of fault and fracture geometry and distribution. Aiming at assessing the control exerted by carbonate lithofacies and scales of observation, we combine field and digital structural analyses to compute the values of 1D and 2D fracture density and intensity, and the dimensional properties of single fault and fracture sets. As a result, from outcrop to reservoir scales we document a scale-variant geometry of faults and fractures, and the great variation of both fracture density and intensity among the studied carbonate lithofacies. Furthermore, we compute a P21 dimensional scaling factor of ca. 20 for over 3 order magnitude, whereas inconsistent results are achieved for the P20 values. Not considering the control exerted by the single carbonate lithofacies, at a reservoir scale we document that the small-scale faults greatly impact the computed P21 values.

Interesting clues to detect hidden tidal disruption events in active galactic nuclei

ABSTRACT In the manuscript, effects of tidal disruption events (TDEs) are estimated on long-term AGN variability, to provide interesting clues to detect probable hidden TDEs in normal broad line AGN with apparent intrinsic variability which overwhelm the TDEs expected variability features, after considering the unique TDEs expected variability patterns. Based on theoretical TDEs expected variability plus AGN intrinsic variability randomly simulated by Continuous AutoRegressive process, long-term variability properties with and without TDEs contributions are well analysed in AGN. Then, interesting effects of TDEs can be determined on long-term observed variability of AGN. First, more massive BHs, especially masses larger than $10^7\, {\rm M_\odot }$, can lead to more sensitive and positive dependence of τTN on RTN, with τTN as variability time-scale ratio of light curves with TDEs contributions to intrinsic light curves without TDEs contributions, and RTN as ratio of peak intensity of TDEs expected variability to the mean intensity of intrinsic AGN variability without TDEs contributions. Secondly, stronger TDEs contributions RTN can lead to τTN quite larger than 5. Thirdly, for intrinsic AGN variability having longer variability time-scales, TDEs contributions will lead τTN to be increased more slowly. The results actually provide an interesting forward-looking method to detect probable hidden TDEs in normal broad-line AGN, due to quite different variability properties, especially different DRW/CAR process expected variability time-scales, in different epochs, especially in normal broad line AGN with shorter intrinsic variability time-scales and with BH masses larger than $10^7\, {\rm M_\odot }$.

Tropical Pacific Modulation of the Asian Summer Monsoon Over the Last Millennium in Paleoclimate Data Assimilation Reconstructions

AbstractLarge uncertainties exist in climate model projections of the Asian summer monsoon (ASM). The El Niño‐Southern Oscillation (ENSO) is an important modulator of the ASM, but the ENSO‐ASM teleconnection is not stationary. Furthermore, teleconnections between ENSO and the East Asian versus South Asian subcomponents of the ASM exhibit distinct characteristics. Therefore, understanding the variability of the ENSO‐ASM teleconnection is critical for anticipating future variations in ASM intensity. To this end, we here use paleoclimate records to extend temporal coverage beyond the instrumental era by millennia. Recently, data assimilation techniques have been applied for the last millennium, which facilitates physically consistent, globally gridded climate reconstructions informed by paleoclimate observations. We use these novel data assimilation products to investigate variations in the ENSO‐ASM relationship over the last 1,000 years. We find that correlations between ENSO and ASM indices are mostly negative in the last millennium, suggesting that strong ASM years are often associated with La Niña events. During periods of weak correlations between ENSO and the East Asian summer monsoon, we observe an El Niño‐like sea surface temperature (SST) pattern in the Pacific. Additionally, SST patterns associated with periods of weak correlations between ENSO and South Asian summer monsoon rainfall are not consistent among data assimilation products. This underscores the importance of developing more precipitation‐sensitive paleoclimate proxies in the Indian subcontinental realm over the last millennium. Our study serves as a baseline for future appraisals of paleoclimate assimilation products and an example of informing our understanding of decadal‐scale ENSO‐ASM teleconnection variability using paleoclimate data sets.

Markers of schizophrenia at the prosody/pragmatics interface. Evidence from corpora of spontaneous speech interactions.

The speech of individuals with schizophrenia exhibits atypical prosody and pragmatic dysfunctions, producing monotony. The paper presents the outcomes of corpus-based research on the prosodic features of the pathology as they manifest in real-life spontaneous interactions. The research relies on a corpus of schizophrenic speech recorded during psychiatric interviews (CIPPS) compared to a sampling of non-pathological speech derived from the LABLITA corpus of spoken Italian, which has been selected according to comparability requirements. Corpora has been intensively analyzed in the Language into Act Theory (L-AcT) frame, which links prosodic cues and pragmatic values. A cluster of linguistic parameters marked by prosody has been considered: utterance boundaries, information structure, speech disfluency, and prosodic prominence. The speech flow of patients turns out to be organized into small chunks of information that are shorter and scarcely structured, with an atypical proportion of post-nuclear information units (Appendix). It is pervasively scattered with silences, especially with long pauses between utterances and long silences at turn-taking. Fluency is hindered by retracing phenomena that characterize complex information structures. The acoustic parameters that give rise to prosodic prominence (f0 mean, f0 standard deviation, spectral emphasis, and intensity variation) have been measured considering the pragmatic roles of the prosodic units, distinguishing prominences within the illocutionary units (Comment) from those characterizing Topic units. Patients show a flattening of the Comment-prominence, reflecting impairments in performing the illocutionary activity. Reduced values of spectral emphasis and intensity variation also suggest a lack of engagement in communication. Conversely, Topic-prominence shows higher values for f0 standard deviation and spectral emphasis, suggesting effort when defining the domain of relevance of the illocutionary force. When comparing Topic and Comment-prominences of patients, the former consistently exhibit higher values across all parameters. In contrast, the non-pathological group displays the opposite pattern.

Impact of Cavity Geometry on Microlaser Dynamics.

We experimentally investigate spatiotemporal lasing dynamics in semiconductor microcavities with various geometries, featuring integrable or chaotic ray dynamics. The classical ray dynamics directly impacts the lasing dynamics, which is primarily determined by the local directionality of long-lived ray trajectories. The directionality of optical propagation dictates the characteristic length scales of intensity variations, which play a pivotal role in nonlinear light-matter interactions. While wavelength-scale intensity variations tend to stabilize lasing dynamics, modulation on much longer scales causes spatial filamentation and irregular pulsation. Our results will pave the way to control the lasing dynamics by engineering the cavity geometry and ray dynamical properties.

Revealing inflow and wake conditions of a 6 MW floating turbine

Abstract. We investigate the characteristics of the inflow and the wake of a 6 MW floating wind turbine from the Hywind Scotland offshore wind farm, the world's first floating wind farm. We use two commercial nacelle-mounted lidars to measure the up- and downwind conditions with a fixed and a scanning measuring geometry, respectively. In the analysis, the effect of the pitch and roll angles of the nacelle on the lidar measuring location is taken into account. The upwind conditions are parameterized in terms of the mean horizontal wind vector at hub height, the shear and veer of the wind profile along the upper part of the rotor, and the induction of the wind turbine rotor. The wake characteristics are studied in two narrow wind speed intervals between 8.5–9.5 and 12.5–13.5 m s−1, corresponding to below and above rotor rated speeds, respectively, and for turbulence intensity values between 3.3 %–6.4 %. The wake flow is measured along a horizontal plane by a wind lidar scanning in a plan position indicator mode, which reaches 10 D downwind. This study focuses on the downstream area between 3 and 8 D. In this region, our observations show that the transverse profile of the wake can be adequately described by a self-similar wind speed deficit that follows a Gaussian distribution. We find that even small variations (∼1 %–2 %) in the ambient turbulence intensity can result in an up to 10 % faster wake recovery. Furthermore, we do not observe any additional spread of the wake due to the motion of the floating wind turbine examined in this study.

Experiment on the formaldehyde removal performance of TiO2 coating agent for finishing materials

As the frequency of indoor habitation escalates and advancements in building technology optimize airtightness, the importance of maintaining high-quality indoor air has grown increasingly critical. This urgency is further amplified by the proliferation of chemical building materials, necessitating more effective strategies for air pollutant abatement. To address this need, the current study explored the utility of titanium dioxide photocatalysts, which possess chemical decomposition capabilities, as a means of improving air quality within indoor environments. To verify the effectiveness of this approach, the research focused on the removal of formaldehyde—a quintessential indoor air pollutant—by incorporating a titanium dioxide photocatalyst into a coating agent commonly employed in construction materials. Notably, ultraviolet (UV) light, essential for activating the photocatalytic process, is generally absent in indoor settings. To mitigate this limitation, a consistent source of UV radiation was provided through the use of an UV lamp. Adhering to protocols outlined by the International Organization for Standardization, we employed a photoreactor to evaluate the photocatalytic efficiency of the composite material under varying intensities of UV radiation and reactor volumes. The results unequivocally confirmed that variations in UV radiation intensity and reactor volume significantly influenced the photocatalytic effectiveness of the material, resulting in a demonstrable reduction in pollutant concentrations. These findings suggest the feasibility of utilizing titanium dioxide photocatalysts for mitigating outdoor air pollutants, where natural UV radiation is more readily available. However, for indoor applications, the absence of naturally occurring UV radiation presents a considerable challenge. Overcoming this constraint could facilitate the indoor application of photocatalytic coatings, as informed by the optimal conditions of low pollutant reactivity and robust UV radiation revealed in this study, thereby substantially enhancing indoor air quality.

Stretchable hybrid platform‐enabled interactive perception of strain sensing and visualization

AbstractHuman–machine interactive platforms that can sense mechanical stimuli visually and digitally are highly desirable. However, most existing interactive devices cannot satisfy the demands of tactile feedback and extended integration. Inspired by the mechanoluminescence (ML) function of cephalopod skin and the sensitive perception of microcracked slit‐organs, a bioinspired stretchable interactive platform is developed by designing a stretchable poly(styrene‐block‐butadiene‐block‐styrene)/fluorescent molecule (SFM) composite followed by the in situ polymerization of pyrrole (Py) and deposition of carbon nanotubes (CNTs), which possesses a simple multilayered structure and quantitatively senses the applied strains via the variations of digital electrical resistance and visual fluorescence intensity. Using the strain‐dependent microstructures derived from the synergistic interactions of the rigid PPy/CNTs functional layer and SFM, the SFM/PPy/CNTs‐based platforms exhibit excellent strain‐sensing performance manifested by a high gauge factor (GF = 2.64 × 104), wide sensing range (~270%), fast response/recovery time (~155/195 ms), excellent stability (~15,000 cycles at 40% strain), and sensitive ML characteristics under ultraviolet illumination. Benefiting from the novel fusion of digital data and visual images, important applications, including the detection of wrist pulses and human motions, and information dual‐encryption, are demonstrated. This study demonstrates the superiority of advanced structures and materials for realizing superior applications in wearable electronics.

Enhanced Intensity of Interannual Variability of May Drought in Northeast China After 2000 and Its Connection With the Barents Sea Ice

AbstractUsing the standardized precipitation evapotranspiration index, this article demonstrates that the intensity of interannual variability (IIV) of May drought in Northeast China has enhanced remarkably after entering into the 21st century. Relative to 1980–1999, the percentage increase of IIV reaches 70% during 2000–2016. Such an enhancement is well supported by the intensification of IIVs in the East Asian polar front jet stream (EAPJ), East Asian subtropical jet stream (EASJ), and lower‐level anticyclonic circulation anomaly over Northeast China. Remarkable impact from the Barents Sea ice in April is also highlighted. With respect to the former period, a substantial increase occurs as well in the IIV of April Barents Sea ice during 2000–2016. Due to larger IIV in the latter period, the decline of April Barents Sea ice can exert evident effects on heat fluxes, consequently resulting in a significant increase of surface air temperature (SAT) in situ in May. The increased SAT further induces a wave train propagating southeastward to the East Asian region from the Barents Sea, which leads to a strengthened EAPJ and a weakened EASJ in the upper level, concomitant with an anomalous anticyclonic circulation covering Northeast China in the lower level. These atmospheric circulation anomalies link to the drought variability over Northeast China. Thus, the increase in the IIV of April Barents Sea ice favors the enhanced IIV of May drought in Northeast China.

Deep Semi-calibrated Near-field Photometric Stereo

Light calibration plays a crucial role in near-field photometric stereo for accurate surface normal estimation. It comprises light position calibration and light intensity calibration. In industrial applications, the light position calibration is typically performed once, as the facility remains fixed. However, the light intensity calibration needs to be repeated for real industrial scenes with variations in light intensity and fails for autoexposure industrial scenes. This study introduces a deep semi-calibrated near-field photometric stereo technique that achieves precise surface normal estimation without light intensity calibration. The technique consists of two parts: the near-field light intensity calibration network (NFLICN) and the near-field normal estimation network (NFNEN). NFLICN utilizes a point light model to self-calibrate pixel-wise light intensity. NFNEN, on the other hand, takes the calibrated light intensity as input and effectively utilizes local image features to estimate the surface normal. Experimental results on both synthetic testing datasets and the benchmark LUCES dataset confirm the state-of-the-art accuracy of our proposed method in surface normal estimation, even without light intensity calibration.

Evaluation of Electromagnetic Fields of Extremely Low-Frequency Horizontal Electric Dipoles at Sea–Air Boundaries

The technologies of undersea detection and communication, seabed sensor networks, and geophysical detection using electromagnetic waves have emerged as research focal points within the field of marine science and engineering. However, most studies have focused on the propagation of electromagnetic fields over long distances within the shallow “sea-seabed” environment. This paper introduces a quasi-static approximation method to address the Sommerfeld numerical integration challenge within the near-field region, employing the horizontal electric dipole (HED) as a model. It derives the Sommerfeld numerical integral expressions under conditions where the wave-number ratio at the “seawater-air” boundary does not adhere to the requirement of |k0/k1| << 1 (where subscripts 0 and 1 denote seawater and air media, respectively). Building upon this, the paper simplifies the Bessel-Fourier infinite integral term within the integral expression to obtain Sommerfeld numerical integral approximations for the propagation of electromagnetic fields in the near region of extremely low frequency (ELF) within seawater. The study further conducts simulations and calculations to determine amplitude variations in electromagnetic field intensity generated by an ELF HED at different frequencies, dipole heights, and observation point depths. It concludes with an analysis of electromagnetic field propagation characteristics at the seawater-air boundary. Experimental findings highlight the lateral wave as the primary mode of electromagnetic wave propagation at this interface.

Influence of oxidation, acetylation and hydrothermal treatment on structure and functionality of common buckwheat starch

The set aim of present work was to investigate the effects of acetylation, oxidation and heat moisture treatment on physicochemical, pasting, gel texture, structural, thermal and morphological properties of common buckwheat starch. Swelling power and solubility of starches reduced after modification except acetylation. Color of buckwheat starch improved after oxidation and acetylation. Paste clarity increased while syneresis reduced following modification with the exception of oxidation. Pasting properties of buckwheat starch revealed increased peak viscosity and breakdown viscosity following modification treatments. Gel texture analysis depicted increased hardness and reduced springiness, chewiness and cohesiveness for modified starches of buckwheat. Diffractograms of starches showed variation in intensity of some bands. Heat moisture treatment increased agglomeration and oxidation caused slight depression on surface of some granules. Relative crystallinity reduced following oxidation and hydrothermal treatment of starch. The gelatinization temperatures were increased in hydrothermal treated starch samples while oxidation and acetylation reduced the gelatinization temperature. The findings of this work would favor the new applications of modified starch from common buckwheat.

Probing the electron trap-depth distribution in Sr4Al14O25:Eu2+,Dy3+

Sr4Al14O25:Eu2+,Dy3+ is a superluminous persistent luminescence phosphor. Owing to its intrinsic and extrinsic point defects, it tends to luminescence incessantly after excitation, in some cases doing so for as long as 20 h. We report analysis for the energy distribution of its electron traps. The study was done using thermoluminescence (TL) measured on a sample irradiated to 2 Gy at 20 °C. A glow curve measured at 1 °C/s shows two glow peaks at 64 °C (labelled as P1) and at 252 °C (P2). The variation of intensity of peak P1 as a function of heating rate is consistent with competing radiative and non-radiative recombination processes. When the heating rate is faster than 1 °C/s, non-radiative recombinations dominate and the luminescence efficiency drops sharply beyond 70 °C. The activation energy for thermal quenching is estimated to be 0.69±0.06 eV. Once corrected for thermal quenching, the glow curves show a secondary peak (P1A) on the high temperature end of P1. The so-called Tm-Tstop method shows that peaks P1 and P2 gradually shift towards high temperature with preheating temperature Tstop. Indeed, the peak position Tm of both peaks increases with irradiation temperature Tirr. Together, these results suggest that peaks P1 and P2 are each composed of closely spaced overlapping peaks. Analysis of the fractional area between a pair of glow curves measured from the sample irradiated at different temperatures (Tirr) shows that the trap distribution associated with peak P2 is Gaussian whereas that associated with peak P1 follows a non-Gaussian distribution. The activation energy of the electron traps responsible for P1 are estimated to be in the range 0.63–0.68 eV. On the other hand, the Gaussian distribution of trap energy levels responsible for peak P2 suggests that most of the traps have an activation energy of ∼1.58 eV.

When less is more: coy display behaviours and the temporal dynamics of animal courtship.

Sexual selection research has been dominated by the notion that mate choice selects for the most vigorous displays that best reflect the quality of the courter. However, courtship displays are often temporally structured, containing different elements with varying degrees of intensity and conspicuousness. For example, highly intense movements are often coupled with more subtle components such as static postures or hiding displays. Here, we refer to such subtle display traits as 'coy', as they involve the withholding of information about maximal display capabilities. We examine the role of intensity variation within temporally dynamic displays, and discuss three hypotheses for the evolution of coy courtship behaviours. We first review the threat reduction hypothesis, which points to sexual coercion and sexual autonomy as important facets of sexual selection. We then suggest that variation in display magnitude exploits pre-existing perceptual biases for temporal contrast. Lastly, we propose that information withholding may leverage receivers' predispositions for filling gaps in information-the 'curiosity bias'. Overall, our goal is to draw attention to temporal variation in display magnitude, and to advocate possible scenarios for the evolution of courtship traits that regularly occur below performance maxima. Throughout, we highlight novel directions for empirical and theoretical investigations.

Using spatial point process models, clustering and space partitioning to reconfigure fire stations layout

AbstractFire stations (FS) are typically non-uniformly distributed across space, and their service area is, in general, defined based on administrative boundaries. Since the location of FS may considerably influence the readiness and the effectiveness of the provided services, national and regional governments need research-based information to adequately plan where to establish firefighting facilities. In this study, we propose a method to reconfigure the fire stations layout using spatial point process models, clustering and space partitioning. First, modelling fire intensity variation across space through a point process model enables to replicate the process independently by simulation. Subsequently, for each simulation, the k-means algorithm is used to define a siting location, minimizing the total within distance between the fire occurrences and the new position. This method allows to obtain a set of locations from which the respective distribution is inferred. Assuming a bivariate normal spatial distribution, we further define confidence siting regions. Ultimately, new FS service areas are defined by Voronoi tessellation. To exemplify the application of the method, we apply it to reconfigure the fire station layout at Aveiro, Portugal.

Influence of Transparent Envelope Parameters on Office Building Energy Use Intensity in the Different Thermal Climate Regions of China

The role of the transparent envelope in energy savings is crucial as it accounts for a significant proportion of the total energy loss (between 30 and 40%). This paper focuses on the identification of reasonable parameters for the transparent envelope in different climatic regions. To achieve this goal, typical urban office buildings from four different climatic regions are used as research objects. A total of 1600 scenarios were simulated to investigate the variation of energy use intensity, including transparent envelope parameters, meteorological parameters and different types of glazing. The results show that for south-facing transparent envelope facades, type D glazing is the most energy efficient in severe cold regions, type C in colder regions and type B in the other two climatic regions. No solar shading is required in the very cold region. Horizontal shading can be an effective method for saving energy in colder climates, while comprehensive shading can be beneficial in other regions. Deep shading is particularly energy efficient if it meets lighting requirements. For example, in Guangzhou, energy savings of 13.46%, 15.47%, 7.01% and 7.02% can be achieved in the east, west, south and north directions, respectively, using B-type glazing and a comprehensive shading depth of 900 mm.

Diagnosing Tropical Cyclone Intensity Variations from the Surface Wind Field Evolution

Abstract Tropical cyclone (TC) intensity fluctuations remain a challenge for TC forecasters. Occurring through a wide range of processes, such as vortex contraction, eyewall replacements, or emission of vortex Rossby waves, they are inherently multiscale, transient, and asymmetric. In a recent study, estimates of surface wind field inner-core properties from high-resolution satellite observations were spotted as valuable for the improvement of intensity variations statistical predictability. The present study evaluates how the temporal evolution of the vortex structure, at scales ranging from O(1) km to vortexwide, further provides insights on the modulation of intensity. The study is based on a set of seven realistic TC simulations with 1-km grid spacing. The surface wind field structure is studied through an original set of descriptors that characterize the radial profile, the azimuthal asymmetries, and their spectral distribution. While radial gradients evolve concurrently with intensity, the azimuthal variability of the inner core shows a stronger connection with shorter-scale intensity modulation. The increase of high-wavenumber asymmetries distributed around the ring of maximum winds is shown to precede phases of rapid (re)intensification by 5–6 h, while the concentration of asymmetry in wavenumbers 1 and 2 leads to intensity weakening. A machine learning classification finally highlights that the classification of intensification phases (i.e., intensification or weakening) can be improved by at least 11% (thus reaching ∼75%) when accounting for the evolution of the radial wind gradient and the variance distribution among scales in the ring of maximum wind, relative to the sole use of vortex-averaged parameters. Significance Statement The purpose of this study is to relate changes in the surface wind field structure of tropical cyclones to their intensity variations. We design an original set of parameters to characterize the inner- and near-core contraction and asymmetry, and evaluate their connection with TC intensity modulations in a set of realistic high-resolution numerical simulations. The main outcome of our study is that opposite trends in high- and low-wavenumber variance tend to occur prior to intensity changes on short time scales, with more widespread and local-scale asymmetry corresponding to intensification, and vortex-scale polarized asymmetry corresponding to weakening. These diagnoses are shown to improve the classification of intensification and weakening phases. These results advocate for enhancing real-time high-resolution observations of surface wind fields under TCs, and using asymmetry distribution as predictors in statistical forecast models.

Meridional Variation of the Mascarene High and Atmospheric Transient Eddy Dynamical Forcing over the Southern Indian Ocean in Austral Winter

Abstract This study reveals a close relation between the Mascarene high (MH), atmospheric transient eddies (hereafter transient eddies or eddies for short), and the sea surface temperature (SST) front over the southern Indian Ocean in austral winter. Climatologically, the subpolar westerly jet couples well with transient eddies via eddy–mean flow interaction and the anticyclonic vorticity to its north helps with anchoring the MH. On the interannual time scale, the MH exhibits a dominant meridional variation accompanied by intensity variability. When the MH moves poleward and intensifies, positive quasi-barotropic geopotential height anomalies associated with a warm temperature feature the southern flank of MH. As a result of the modified mean temperature gradient, the subpolar jet and transient eddies’ activity are enhanced near the jet exit; in contrast, the subtropical westerly jet and eddies are weakened over the jet entrance, mainly via the baroclinic energy conversion. As feedback, the anomalous transient eddies can trigger the poleward shift of MH by diverging the extended Eliassen–Palm (E-P) flux from subpolar to subtropical region and thus the intensification of subpolar jet and weakness of subtropical jet. Such positive feedback between the meridional variation of MH and transient eddies could be attributed to the underlying SST anomalies. Early SST warming appears over the southwestern Indian Ocean 3 months prior and shifts the Agulhas SST front poleward. The poleward Agulhas SST front could further induce a southward displacement of the activity of transient eddies by changing the low-level atmospheric baroclinicity. Hence, the SST anomalies over the southern Indian Ocean may trigger the meridional variation of MH via the positive eddies–mean flow feedback.

3D Brain Tumour Segmentation Using UNet with Quantitative Analysis of the Tumour Features

Brain tumours are abnormal cells that grow within the brain and may cause severe harm to an individual. The diagnosis of tumours often requires a manual review of Magnetic Resonance (MR) images by a skilled radiologist, which is a laborious task. The study aims to use a deep learning-based approach to segment the brain tumour and quantitatively evaluate the performance of the model by comparing the statistical distribution of five textural and four non-textural feature differences between the ground truth and the prediction. Textural features were extracted from a Grey Level Co-occurrence Matrix (GLCM) and averaged over four different directions. A UNet model was constructed with MONAI using BraTS 2020 dataset. Due to hardware constraints, the model was trained over a short epoch range of 100 but managed to achieve a mean Dice similarity coefficient (DSC) of 0.86. The quantitative analysis showed that the ground truth and the prediction had low differences in most features, except for percentage variation in signal intensity, energy, correlation and Hausdorff distance, which could be attributed to false positive voxels that are far from the ground truth. The textural properties of homogeneity, entropy, and correlation had an average absolute percentage difference of less than 5% from the ground truth.