Constant Distribution Research Articles

A new method for assessing coarse particle flotation performance Part I − On the deconvolution of the flotation response

Crompton et al. (2023) developed a new algorithm for describing the performance of coarse particle flotation. They used the flotation rate constant, k, normalised by the maximum rate constant, kmax, for the pure mineral, as a proxy for the fractional surface liberation. The algorithm was used to produce the partition curve for a separation performed by a novel device, the CoarseAIR™. Part I of this new study re-visits the former work, particularly the batch mechanical flotation responses of the steady state samples from the CoarseAIR™. The flotation responses were deconvolved to the corresponding distributions of rate constants for the three streams, and in turn used to produce the partition curve for the coarse particle flotation. The algorithm used to produce the distribution of rate constants was driven towards a simple functional form by minimising its overall curvature. The steady state samples from any coarse particle flotation system can be assessed in this way. Part II of this study focuses on the reproducibility of the approach, and hence the uncertainty, using a batch mechanical cell to simulate the coarse particle flotation, and in turn the steady state feed, product and reject samples.

Complete Asymptotic Expansions for the Normalizing Constants of High-Dimensional Matrix Bingham and Matrix Langevin Distributions

For positive integers $d$ and $p$ such that $d \ge p$, let $\mathbb{R}^{d \times p}$ denote the set of $d \times p$ real matrices, $I_p$ be the identity matrix of order $p$, and $V_{d,p} = \{x \in \mathbb{R}^{d \times p} \mid x'x = I_p\}$ be the Stiefel manifold in $\mathbb{R}^{d \times p}$. Complete asymptotic expansions as $d \to \infty$ are obtained for the normalizing constants of the matrix Bingham and matrix Langevin probability distributions on $V_{d,p}$. The accuracy of each truncated expansion is strictly increasing in $d$; also, for sufficiently large $d$, the accuracy is strictly increasing in $m$, the number of terms in the truncated expansion. Lower bounds are obtained for the truncated expansions when the matrix parameters of the matrix Bingham distribution are positive definite and when the matrix parameter of the matrix Langevin distribution is of full rank. These results are applied to obtain the rates of convergence of the asymptotic expansions as both $d \to \infty$ and $p \to \infty$. Values of $d$ and $p$ arising in numerous data sets are used to illustrate the rate of convergence of the truncated approximations as $d$ or $m$ increases. These results extend recently-obtained asymptotic expansions for the normalizing constants of the high-dimensional Bingham distributions.

Evaluating interseismic deformation patterns in the North Tabriz Fault (Iran) using enhanced fitting of velocity field and analysis of surface deformation

Understanding the mechanisms and locations of interseismic strain accumulation along faults is essential for assessing earthquake hazards. However, the mechanical response during the transition from deep fault locking to creep behavior remains uncertain. Estimating the slip deficit within these transition zones is challenging. This study challenges the assumption of a constant depth distribution of interseismic slip rate along the fault over time and proposes variable locking depths as an alternative model. By rejecting the constant locking depth assumption, singularity issues during stress theorem resolution are resolved. To address this, we employ a methodology considering creep propagation within a fully elastic medium. This approach incorporates long-term deformation resulting from viscoelastic flow in the upper mantle and lower crust. Including viscoelastic effects improves the fit to interseismic deformation rates, yielding lower locking depths compared to fully elastic models. To conduct the investigation, the GPS velocity field is recovered using the forward problem and the boundary element method. Subsequently, a physics-based inversion approach, deep interseismic creep, is employed to determine interseismic deformation patterns on a strike-slip fault. Furthermore, this study examined the correlation between the dislocation parameters and their relationship, as well as established the probability distributions associated with each faulting parameter. This research highlights the importance of considering variable locking depths in understanding interseismic strain accumulation and the transition to creep behavior along faults. The findings contribute to improved earthquake hazard assessment and mitigation strategies by providing valuable insights into fault behavior mechanics along the North Tabriz Fault.

Deep Learning-Based Electric Field Enhancement Imaging Method for Brain Stroke

In clinical settings, computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) are commonly employed in brain imaging to assist clinicians in determining the type of stroke in patients. However, these modalities are associated with potential hazards or limitations. In contrast, microwave imaging emerges as a promising technique, offering advantages such as non-ionizing radiation, low cost, lightweight, and portability. The primary challenges faced by microwave tomography include the severe ill-posedness of the electromagnetic inverse scattering problem and the time-consuming nature and unsatisfactory resolution of iterative quantitative algorithms. This paper proposes a learning electric field enhancement imaging method (LEFEIM) to achieve quantitative brain imaging based on a microwave tomography system. LEFEIM comprises two cascaded networks. The first, based on a convolutional neural network, utilizes the electric field from the receiving antenna to predict the electric field distribution within the imaging domain. The second network employs the electric field distribution as input to learn the dielectric constant distribution, thereby realizing quantitative brain imaging. Compared to the Born Iterative Method (BIM), LEFEIM significantly improves imaging time, while enhancing imaging quality and goodness-of-fit to a certain extent. Simultaneously, LEFEIM exhibits anti-noise capabilities.

Insights into phthalocyanine blue pigment dispersion: Modeling particle size distribution and grinding rate constants

The study presents an advanced mathematical model aimed at enhancing the understanding of pigment dispersion processes, with a particular focus on analyzing the dynamics of particle size distribution and determining grinding rate constants. Pigmented dispersions are crucial in various industries, including paints, coatings, and inks, where achieving optimal particle size distribution is vital for product quality. This investigates the relationship between grinding duration and pigment dispersion, aiming to establish empirical equations for the grinding rate constant as a function of particle size distribution and feed rate. Through experimental validation, the developed kinetic model provides insights into the dynamics of pigment dispersion and offers predictive capabilities for optimizing dispersion processes. Understanding the underlying mechanisms of pigment dispersion through mathematical modeling contributes to enhancing the performance and quality of final products in diverse industrial applications. The development of a new kinetic model, effective mathematical model is proposed to accurately simulate the evolution was applicable for the particle size from 32.67 to 122.4 nm distribution of pigment during comminution processes. In addition, it was observed that the kinetic model was not applicable for the particle size from 166.2 to 190.1 nm and also confirmed that the grinding was completed within 40 min, which was possible for uniform particle size distribution.

Three-dimensional radiation dosimetry of carbon ion beams using surfactant hydrogels: Fundamental investigation.

In carbon ion radiotherapy, accurate measurement of the three-dimensional (3D) absorbed dose distribution is critical for effectively targeting tumors. Although micellar gel dosimeters exhibit considerable potential for measuring 3D absorbed dose distributions, few studies have focused on radiotherapy using carbon ion beams. This study investigated the applicability of the surfactant hydrogel dosimeter (SHD), a micellar gel dosimeter, to measuring a 3D dose absorbed through carbon ion beam irradiation. A cubic target region of 34mm per side was established at a depth of 46mm below the upper surface of an SHD specimen. Scanning irradiation was performed using a pencil beam of carbon ions at the Ion-beam Radiation Oncology Center in Kanagawa ("i-ROCK"), Japan, under irradiation conditions set by the treatment planning system ("Monaco for Carbon", Ver. 5.20, Elekta AB, Sweden) to create a spread-out Bragg peak within the target. The physical dose was set to 10Gy at the isocenter, situated at the center of the target. The SHD responsiveness was measured twice using optical computed tomography (CT) ("Vista 15", Modus Medical Devices, Canada) for three irradiated specimens, and six types of measured optical attenuation coefficient (OAC) were obtained. To assess whether the OAC represented the absorbed dose expected in the treatment plan, we compared the relative distribution of the OAC and that of the absorbed dose. Relative fraction (RF) was used to measure the difference between the relative value of the OAC and that of the absorbed dose. Moreover, the distribution of OH radical (•OH) concentration obtained by Monte Carlo simulation ("PHITS" ver. 3.24 JAEA, Japan) and that of the OAC were compared. In the direction of beam travel, the relative distribution of the OAC was lower than that of the absorbed dose. This discrepancy could be attributed to a decrease in the concentration of •OH produced by irradiation owing to the recombination reaction, which does not accurately reflect the absorbed dose. By contrast, the distributions in the plane perpendicular to the beam travel were consistent. The RF increased from±3% to±13% along the beam travel direction. The small RF in the plane perpendicular to the beam travel could be attributed to the constant distribution of linear energy transfer, regardless of the irradiation position, and the generation of radicals proportionally to the absorbed dose. The increase in RF along the beam travel direction was ascribed to ring artifacts in the irradiated region. The measurement of the absorbed dose distribution in the beam travel direction should be improved. The observed discrepancy is attributed to the reduced reactivity of the SHD due to a high liner energy transfer near the Bragg peak. However, the absorbed dose distribution can be effectively evaluated in the plane perpendicular to the direction of beam travel.

ANALYSIS OF THE RESULTS OF SIMULATIVE MODELLING OF THE INFORMATION SECURITY SYSTEM IN THE CORPORATE NETWORKS OF HIGHER EDUCATION INSTITUTIONS

The analysis shows that the insufficient level of information security in service networks is the main cause of huge losses for enterprises. Despite the appearance of a number of works to solve this problem, there is currently no unified system for assessing information security. This shows that this problem has not yet been sufficiently studied and relevant. This work is one of the steps towards creating a system for assessing information security in service networks. The purpose of the work is to develop an algorithm and simulation model, analyze the results of the simulation model to determine the main characteristics of the information security system (ISS), providing the ability to completely close all possible channels of threats by controlling all unauthorized access (UA) requests through the protection mechanism (PM). To solve the problem, a simulation method was applied using the principles of queuing systems (QS). This method makes it possible to obtain the main characteristics of the ISS from the UA with an unlimited amount of buffer memory (BM). Models, an algorithm and a methodology for the development of ISS from UA are proposed, which is considered as a single-phase multi-channel QS with an unlimited volume of BM. The process of obtaining simulation results was implemented in the GPSS World modeling system and comparative analyzes of the main characteristics of the ISS were carried out for various laws of distribution of output parameters. At the same time, UA requests were the simplest flows, and the service time was subject to exponential, constant and Erlang distribution laws. Conducted experiments based on the proposed models and algorithm for analyzing the characteristics of the ISS from the UA as a single-phase multi-channel QS with unlimited waiting time for requests in the queue confirmed the expected results. The results obtained can be used to build new or modify existing ISS in corporate networks for servicing objects for various purposes. This work is one of the approaches to generalizing the problems under consideration for systems with an unlimited volume of BM. Prospects for further research include research and development of the principles of hardware and software implementation of ISS in service networks.

Limitations of the rate-distribution formalism in describing luminescence quenching in the presence of diffusion.

When encountering complex fluorescence decays that deviate from exponentiality, a very appealing approach is to use lifetime or rate constant distributions. These are related by Laplace transform to the sum of exponential functions, stretched exponentials, Becquerel's decay function, and others. However, the limitations of this approach have not been sufficiently discussed in the literature. In particular, the time-independent probability distributions of the rate constants or decay times are occasionally used to describe bimolecular quenching. We show that in such a case, this mathematical formalism has a clear physical interpretation only when the fluorophore and quencher molecules are immobile, as in the solid state. However, such an interpretation is no longer possible once we consider the motion of fluorophores with respect to quenchers. Therefore, for systems in which the relative motion of fluorophores and quenchers cannot be neglected, it is not appropriate to use the time-independent rate or decay time distributions to describe, fit, or rationalize experimental results on fluorescence decay.

Ramping cells in the rodent medial prefrontal cortex encode time to past and future events via real Laplace transform

In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings from the rodent medial prefrontal cortex [J. Henke et al., eLife10, e71612 (2021)] during an interval reproduction task and identified two cell groups by modeling their temporal receptive fields using hierarchical Bayesian models. The firing in the "past cells" group peaked at the start of the interval and relaxed exponentially back to baseline. The firing in the "future cells" group increased exponentially and peaked right before the planned action at the end of the interval. Contrary to the previous assumption that timing information in the brain has one or two time scales for a given interval, we found strong evidence for a continuous distribution of the exponential rate constants for both past and future cell populations. The real Laplace transformation of time predicts exponential firing with a continuous distribution of rate constants across the population. Therefore, the firing pattern of the past cells can be identified with the Laplace transform of time since the past event while the firing pattern of the future cells can be identified with the Laplace transform of time until the planned future event.

Purcell gain equalized zero-mode waveguide

We refresh the design of zero-mode waveguides (ZMWs) by introducing metamaterials that makes the zeroth order resonant mode existence. Of particular importance, the resulting electromagnetic field exhibits nearly constant distribution but not a trivial solution of Maxwell’s equation, showing great advantage to equalize the excitation rate of molecules throughout the waveguides. A closed form expression for the wave impedance is derived which is verified by the finite-difference time-domain simulations. Benefitted from the cavity Purcell effect which is lacking in existing ZMWs, fluorescence amplification and lifetime reduction are simultaneously enhanced. A practical design where the excitation volume reduced down to sub-zeptoliter and the fluorescence lifetime shortened to picosecond scale is illustrated. This result makes single molecule real time (SMRT) sensing of biochemical reactions at biophysically relevant concentrations (~ μM) possible, combining off-the-shelf ultrafast lasers.

Variable leading-edge cone method for waverider design

The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) method to address these limitations. In the vLEC method, the waverider is directly designed from the preassigned leading edge and the variable shock angle distribution based on the Leading-Edge Cone (LEC) concept. Since the vLEC method is an approximate method, two test waveriders are designed and evaluated using numerical simulations to validate the shock design accuracy and the effectiveness of the vLEC method. The results show that the shocks of the test waveriders coincide well with the preassigned positions. Furthermore, four specifically designed application cases are conducted to analyze the performance benefits of the vLEC waveriders. The results of these cases indicate that, due to their variable shock angle distributions, the vLEC waveriders exhibit higher lift-to-drag ratios and better longitudinal static stability than conventional waveriders. Additionally, the vLEC waveriders demonstrate superior volumetric capacities near the symmetry plane, albeit with a minor decrease in volumetric efficiency.

Perfect vortex beams generation based on reflective geometric phase metasurfaces

Perfect vortex beam (PVB) is a propagating light field with radial intensity distribution independent of topological charge and carrying orbital angular momentum (OAM). PVBs can be generated through the Fourier transformation of a Bessel-Gaussian (BG) beam, which traditionally requires a precisely aligned optical setup consisting of a spiral phase plate, a conical lens, and a Fourier lens. However, such traditional schemes are usually bulky and unstable. Here, we have utilized a method that differs from conventional approaches, employing metasurfaces designed as planar Pancharatnam-Berry (PB) phase elements to substitute for all the required components. Unlike traditional methods based on reflective or refractive elements, metasurface elements can significantly reduce the system's footprint. Because the use of metallic metasurfaces allows for a more flattened design plane, in this paper, we have demonstrated the generation of PVB within the 8 GHz microwave frequency band based on a single-layer metallic metasurface. The metasurface is composed of a square ring metal structure, which can serve as a half wave plate to provide the required geometric phase distribution for incident circularly polarized light to generate PVB. By rigorously optimizing the parameters of the square-ring structures, we have generated vortex beams carrying OAM with different topological charges. These vortex beams exhibit a constant radial intensity distribution, which validates their "perfect" characteristics. In addition, we also extracted the mode purity of different vortex beams, so that the mode states of different vortex beams can be distinguished. These results provide broader value for the application of perfect vortex beams in communication.

Novel approach to detect encasement failures in the anchorage system of guyed transmission towers by distribution of relaxation times

Anchor rods of guyed transmission towers encapsulated in Portland cement pastes and mortar are usually affected by corrosion processes when buried in soils with chemical aggressiveness. Encasement failures, such as cracks and leaks, cause preferential points of degradation of the inner metal bar, affecting its mechanical integrity over the years and causing, in many cases, the collapse of the transmission tower. However, the nondestructive testing (NDT) used for diagnosis has not shown conclusive results. In this study, a methodology to detect failures in the cement paste encasement was developed using electrochemical impedance spectroscopy (EIS) by evaluating the distribution of relaxation time constants (DRT) to identify different time constants of water in the pore structure of cement paste. These parameters were typically determined by the nuclear magnetic resonance (NMR) relaxometry technique, which was not correctly applied to the field tests. From the results, it was possible to detect the presence of cement paste in soils with electrical resistivities varying from 4.0 to 200.0 Ω.m by identifying their time constant at 0.10 ms, which was attributed to the water present in the hydrated calcium silicate gel (C-S-H) interlayers.

Immobilised artificial membrane liquid chromatography vs liposome electrokinetic capillary chromatography: Suitability in drug/bio membrane partitioning studies and effectiveness in the assessment of the passage of drugs through the respiratory mucosa

This study pioneers a comparison of the application of biomimetic techniques, immobilised artificial membrane liquid chromatography (IAM LC) and liposome electrokinetic capillary chromatography (LEKC), for the prediction of pulmonary drug permeability. The pulmonary absorption profiles of 26 structurally unrelated drug-like molecules were evaluated using their IAM hydrophobicity index (CHI IAM) measured in IAM LC, and the logarithm of distribution constants (log KLEKC) derived from the LEKC experiments. Lipophilicity (phospholipids) parameters obtained from IAM LC and most LEKC analyses were linearly related to the n-octanol/water partitioning coefficients of the neutral forms (i.e., log Po/w values) to a moderate extent. However, the relationship with distribution coefficients at the experimental pH (7.4) (i.e., log D7.4) were weaker overall for IAM LC data and sigmoidal for some liposome compositions (phosphatidyl choline (PC): phosphatidyl inositol (PI) 85:15 mol% and 90:10 mol%) and concentrations (4 mM) in LEKC. This suggests that phospholipid partitioning supports both hydrophobic and electrostatic interactions occurring between ionised drugs and charged phospholipid moieties. The latter interactions are original when compared to those taking place in the more established n-octanol/water partitioning systems.A stronger correlation (R2 > 0.65) was identified between the LEKC retention parameters, and the experimental apparent lung permeability (i.e., log Papp values) as opposed to the values obtained by IAM LC. Therefore, LEKC offers unprecedented advantages over IAM LC in simulating cell membrane partitioning processes in the pulmonary delivery of drugs. Although LEKC has the advantage of more effectively simulating the electrostatic and hydrophobic forces in drug/pulmonary membrane interactions in vitro, the technique is unsuitable for analysing highly hydrophilic neutral or anionic compounds at the experimental pH. Conversely, IAM LC is useful for analysing compounds spanning a wider range of lipophilicity. Its simpler and more robust implementation, and propensity for high-throughput automation make it a favourable choice for researchers in drug development and pharmacological studies.

A Convolutional Neural Network with Multifrequency and Structural Similarity Loss Functions for Electromagnetic Imaging.

In this paper, artificial intelligence (AI) technology is applied to the electromagnetic imaging of anisotropic objects. Advances in magnetic anomaly sensing systems and electromagnetic imaging use electromagnetic principles to detect and characterize subsurface or hidden objects. We use measured multifrequency scattered fields to calculate the initial dielectric constant distribution of anisotropic objects through the backpropagation scheme (BPS). Later, the estimated multifrequency permittivity distribution is input to a convolutional neural network (CNN) for the adaptive moment estimation (ADAM) method to reconstruct a more accurate image. In the meantime, we also improve the definition of loss function in the CNN. Numerical results show that the improved loss function unifying the structural similarity index measure (SSIM) and root mean square error (RMSE) can effectively enhance image quality. In our simulation environment, noise interference is considered for both TE (transverse electric) and TM (transverse magnetic) waves to reconstruct anisotropic scatterers. Lastly, we conclude that multifrequency reconstructions are more stable and precise than single-frequency reconstructions.

Vertical Thermal Emission from Optical Antennas on an Epsilon‐Near–Zero Substrate

AbstractThis work presents a novel approach to achieve directional and normal thermal emission from epsilon‐near–zero (ENZ) materials. ENZ materials exhibit near–zero permittivity at the ENZ point, resulting in some unique properties compared to conventional optical materials including infinite wavelength, constant phase distribution, and decoupling of spatial and temporal fields inside the ENZ material. These properties are used to engineer the far‐field thermal emission from optical antennas fabricated on ENZ film in the mid‐infrared. By coupling the antenna resonance mode with the Berreman mode of the ENZ material, highly directional and normal emission is demonstrated. This approach could have significant implications for thermal management, energy conversion, and sensing applications.

A model for the lattice thermal conductivity of nanocrystalline materials with arbitrary grain size distribution

Nanocrystalline materials are a popular metamaterial used to control heat transport in semiconductor industrial applications. An accurate and reliable theoretical model is urgently needed but challenging for elucidating detailed microscopic heat transfer phenomena. In this study, we develop a mathematical model to predict the lattice thermal conductivity of nanocrystalline materials with arbitrary grain size distribution. The model first obtains the effective scattering rate of grain boundaries in single-grain-size materials, and then integrates the Landauer’s system transmission concept and series transmission concept to become applicable to multiple grain sizes. It takes into account not only intrinsic and grain boundary scattering effects, but also the effects of finite system size and grain size distribution. Numerical samples of silicon nanocrystals with single grain size, dual size, constant grain size distribution, and logarithmic normal grain size distribution are constructed and full-spectrum Monte Carlo simulations are performed for comparison. The excellent agreement observed between model predictions and simulation results validates the accuracy of the proposed theoretical model. This model will be very helpful in designing micron-scale thermal manipulation systems using nanostructures.

Short-term load distribution model for cascade giant hydropower stations with complex hydraulic and electrical connections

The cascade giant hydropower station system (CGHSS) has been widely applied in countries with abundant water resources. However, the dense hydropower stations and power grids bring complex hydraulic and power connections, including the backwater effect, multiple hydroplants sharing one reservoir and one-reservoir multiple dispatch power grid, which leads to modelling difficulties and inefficient model solving. To address these challenges, a short-term load distribution (SLD) model considering complicated hydraulic and electricity constraints is developed. First, the discharge of each hydroplant and the downstream forebay water level are used as inputs to construct a multivariate nonlinear function, and the average tailwater levels are obtained. Second, a head constraint considering the shared water level is added to the model to calculate the head of each hydroplant, making the output more accurate. Finally, the nonlinear constraints are linearly reconstructed using the Big-M method, triangulation technique and special ordered sets to reduce the model solution time. The SLD model is applied to the Xiluodu-Xiangjiaba cascade hydropower system in the Jinsha River. The results show that the developed model reduces water consumption by 4.02 %, 4.70 %, 5.79 % and 5.28 % compared to the constant proportional distribution model and the real operation, generating a more executable SLD scheme.

Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong.

The serial interval distribution is used to approximate the generation time distribution, an essential parameter to infer the transmissibility (${R}_t$) of an epidemic. However, serial interval distributions may change as an epidemic progresses. We examined detailed contact tracing data on laboratory-confirmed cases of COVID-19 in Hong Kong during the five waves from January 2020 to July 2022. We reconstructed the transmission pairs and estimated time-varying effective serial interval distributions and factors associated with longer or shorter intervals. Finally, we assessed the biases in estimating transmissibility using constant serial interval distributions. We found clear temporal changes in mean serial interval estimates within each epidemic wave studied and across waves, with mean serial intervals ranged from 5.5 days (95% CrI: 4.4, 6.6) to 2.7 (95% CrI: 2.2, 3.2) days. The mean serial intervals shortened or lengthened over time, which were found to be closely associated with the temporal variation in COVID-19 case profiles and public health and social measures and could lead to the biases in predicting ${R}_t$. Accounting for the impact of these factors, the time-varying quantification of serial interval distributions could lead to improved estimation of ${R}_t$, and provide additional insights into the impact of public health measures on transmission.

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation: A case study from southern highlands region of Tanzania

The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash floods. This study examines rainfall data of four stations (Iringa, Mbeya, Rukwa, and Ruvuma) spanning 30 years (1991–2020) to investigate drivers of extreme rainfall and non-stationarity behavior. The Generalized Extreme Value (GEV) model, commonly used in hydrological studies, assumes constant distribution parameters, which may not be true due to climate variability, potentially leading to bias in extreme quantile estimation. Recent studies have introduced a technique for constructing non-stationary Intensity-Duration-Frequency (IDF) rainfall curves. The method incorporates trends in the parameters of the GEV distribution, only using time as a covariate. However, uncertainty exists about whether time is the most suitable covariate, highlighting the need to explore all potential covariates for modeling non-stationarity. The aim of this study is to assess the influence of other time-varying covariates on extreme daily rainfall events, considering seasonality and climate change in the rainfall data. Specifically, five processes (i.e., local temperature changes (LTC), urbanization, annual Global Temperature Anomaly (GTA), the Indian Ocean Dipole (IOD), and the El Niño-Southern Oscillation (ENSO) cycle) were studied as drivers of extreme rainfall events. Sixty two non-stationary GEV models are developed based on these covariates and their combinations, alongside two non-stationary GEV models using the time covariate to capture the seasonality of the unimodal rainfall in the region, and one stationary GEV model (S0). With the use of corrected Akaike Information Criterion (AICc), the best model for each duration (i.e., 1-, 3-, and 5-days) of rainfall series is chosen. Results indicate that local processes (i.e., LTC and urbanization) are the optimal covariates for 1 day-duration rainfall, while global processes (i.e, IOD, ENSO cycle, and GTA) are identified as the most suitable covariates for 3, and 5 day-duration rainfall across all stations. The identified best non-stationary model (with their best covariates) are then used to develop non-stationary rainfall IDF curves for all stations. According to the analysis of non-stationary extreme values, the return periods of extreme rainfall events concluded a notable decrease in comparison to the stationary approach. The study also revealed strong correlations between global climate indices (ENSO, IOD, GTA) and long-duration extreme rainfall in Tanzania’s Southern Highlands. Local factors like Urbanization and temperature changes also show significant associations with 1-day duration events. These findings emphasize the need for integrated climate forecasting to inform effective adaptation strategies. Finally, the study addresses associated uncertainties in our predictions of forthcoming extreme rainfall events through rigorous analysis. The study demonstrated that return levels for extreme rainfall events exhibit a rising trend with increasing return period, indicating heightened intensity over longer time spans, whereas, a relative uncertainty analysis illustrate escalating uncertainty with increasing return periods, emphasizing challenges in long-term prediction.