Physical Processes Research Articles

Effect of Sulfur Contents on Polycyclic Aromatic Compounds in Low-Rank Bituminous Coals

Different coal seams go through distinct biological, physical, and chemical processes. Polycyclic aromatic compounds (PACs) in coal may retain information about these processes, especially in low-rank bituminous coals. Three coal seams with different sulfur contents from the Ningwu Coalfield were studied to understand the relation of different sulfur contents with PAC formation in low-rank bituminous coals. Coal samples were extracted by solvent and separated using liquid chromatography. The collected aromatic hydrocarbon fractions were analyzed by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). A total of 27 sulfur-containing PACs (SPACs) were identified in the high-sulfur samples, whereas only 8 SPACs were found in the low-sulfur coal and middle-sulfur coal. The total SPACs to total PACs ratios (T-SPACs/T-PACs) are 1.15%, 2.17%, and 10.65% in the low-sulfur, middle-sulfur, and high-sulfur coal, respectively. The variations of SPAC species and their content ratios indicate that SPAC formation is controlled by the sulfur contents in the low-rank bituminous coals. A total of 18 oxygen-containing PACs (OPACs) were identified in the low-sulfur coal and middle-sulfur coal, whereas only 11 OPACs were found in the high-sulfur samples. The average ratios of OPACs to the identified aromatic compounds (T-OPACs/T-PACs) are 9.81%, 9.62%, and 6.91% in the low-, middle-, and high-sulfur coals, exhibiting a negative correlation with sulfur contents and indicating that OPACs were also influenced by sulfur contents in low-rank bituminous coals. The ratios of total contents of polycyclic aromatic hydrocarbons (PAHs) to total PACs (T-PAHs/T-PACs) are 89.1%, 88.2%, and 82.0% in the low-, middle-, and high-sulfur coals, respectively, indicating a decreasing trend from low- and middle-sulfur coal to high-sulfur coal. This variation could be caused by the reaction of PAHs and sulfur to form SPACs.

Cross-material battery capacity estimation using hybrid-model fusion transfer learning

Evaluating battery health involves navigating the intricate interplay of physical, chemical, and electrochemical processes across multiple scales—a task that becomes even more complex with the introduction of new battery materials. This necessitates substantial development, modeling, and recalibration of boundary conditions. Our study introduces a hybrid fusion model that combines convolutional neural networks (CNNs) with self-attention mechanisms to enhance battery health assessments. In total, three datasets are involved—covering 77 LFP, 20 NMC, and 18 NCA batteries—encompassing over 170,000 cycles across a broad spectrum of battery materials and operational conditions for pre-training the base model and for transfer learning. Our findings reveal that, when transferring aging knowledge from LFP to ternary batteries (NMC and NCA) under diverse chemistries, temperatures, and operational strategies, the model achieved root mean square errors (RMSEs) of 7.47 mAh and 12.4 mAh, mean absolute percentage errors (MAPEs) of 0.67 % and 1.14 %, and coefficients of determination (R2) of 0.922 and 0.918, respectively. These results demonstrate the effectiveness of our hybrid fusion model, which uses deep transfer learning and combines CNNs with self-attention mechanisms to accurately diagnose battery capacity across various types by analyzing short cycle sequences and integrating insights throughout the cell operational history.

Adolescents Perceptions of Factors Causing Anxiety

Adolescence is a transition period from childhood to adulthood, most of them will experience various changes. Changes that occur in adolescents can be physical, mental and social changes. Some factors that cause anxiety that have been studied include fear of change, thinking too much about something, not having friends to talk to, and many more. The purpose of this study is to determine the factors that cause anxiety based on their experiences. The exploratory qualitative research method was used in this study to reveal the experiences of adolescents who have excessive anxiety. The results of the study showed that adolescents have various perceptions about the factors that cause anxiety in themselves, including; 1) Loss, 2) Thinking too much about something, 3) Broken family, 4) Verbal bullying, 5) Trauma, 6) Failure to do something, 7) Economic problems in the family and 8) Too sensitive.

Sleep, dietary intake and physical activity changes with onset of shift work in intern paramedics

Paramedic work is associated with high staff turn-over, insufficient sleep and adverse health outcomes. Our understanding of the relationship between paramedic work and the health behaviours that may precede adverse health outcomes is limited, as few longitudinal studies have examined health behaviours in workers before they commence on the road work. Such research is needed to inform evidence-based recommendations specifically for new paramedics. The current observational cohort study examined self-reported sleep, dietary intake and physical activity in 21 intern paramedics: 15 female and 6 male (median age: 23.0 years [interquartile range (IQR): 4.0]) from an Australian ambulance service. A subset of participants ( n = 16) provided fasting blood samples for cardiometabolic markers (cholesterol, triglycerides and fasting glucose). Data were collected quarterly (pre-shift work, 3 months, 6 months, 9 months and 12 months post commencement). Linear mixed models showed that the first 12 months of shift work were associated with poorer sleep quality ( p = .036), consumption of fewer kilojoules ( p = .026), reduced saturated fat consumption ( p = .005) and lower sodium ( p = .043) and sugar ( p = .038) intake. There were significant increases in leisure time physical activity ( p = .008). This study shows negative changes in sleep quality and improvements in diet and leisure time physical activity during the first 12 months of paramedic work. Individual differences observed in this study, and ongoing suboptimal dietary intake, highlight a need for larger studies with more participants and a focus on personalised strategies for new recruit paramedics.

Robust constraints on the physics of the MeV emission line in GRB 221009A from optical depth arguments

ABSTRACT The brightest-of-all-time gamma-ray burst (GRB), GRB 221009A, is the first GRB observed to have emission line (up to 37 MeV) in its prompt emission spectra. It is naturally explained as $e^-/e^+$ annihilation line that was Doppler boosted in the relativistic jet of the GRB. In this work, we repeatedly apply the simple optical depth argument to different physical processes necessary to produce an observable $e^-/e^+$ annihilation line. This approach results in robust constraints on the physics of the line: We conclude that in GRB 221009A, the $e^-/e^+$ pairs were produced at a radius greater than $4.3\times 10^{15}$ cm from the central engine, and annihilated in a region between $1.4\times 10^{16}$ and $4.3\times 10^{16}$ cm. From these constraints, we established a self-consistent picture of $e^-/e^+$ production, cooling, and annihilation. We also derived a criterion for pair production in the GRB prompt emission: $E_{\rm {iso}} \gtrsim 3.3\times 10^{53} E_{\rm {peak},100} (1+z) R^2_{\rm {prod},16}~\text{erg}$. Using this criterion, we find tens of candidate GRBs that could have produced $e^-/e^+$ in prompt emissions to annihilate. GRB 221009A is with the highest likelihood according to this criterion. We also predict the presence of a thermal radiation, with a time-evolving blackbody temperature, sweeping through soft X-ray during the prompt emission phase.

High Energy Density Radiative Transfer in the Diffusion Regime with Fourier Neural Operators

AbstractRadiative heat transfer is a fundamental process in high energy density physics and inertial fusion. Accurately predicting the behavior of Marshak waves across a wide range of material properties and drive conditions is crucial for design and analysis of these systems. Conventional numerical solvers and analytical approximations often face challenges in terms of accuracy and computational efficiency. In this work, we propose a novel approach to model Marshak waves using Fourier Neural Operators (FNO). We develop two FNO-based models: (1) a base model that learns the mapping between the drive condition and material properties to a solution approximation based on the widely used analytic model by Hammer & Rosen (2003), and (2) a model that corrects the inaccuracies of the analytic approximation by learning the mapping to a more accurate numerical solution. Our results demonstrate the strong generalization capabilities of the FNOs and show significant improvements in prediction accuracy compared to the base analytic model.

A numerical study of the effect of graphene nanoparticle size on brownian displacement, thermophoresis, and thermal performance of graphene/water nanofluid by molecular dynamics simulation

Brownian motion, often known as BM, is an inherent characteristic of minute particles suspended in a fluid. It plays an important role in several physical and chemical processes. Thermophoresis refers to the process where particles in a fluid are carried along with a gradient in temperature (Temp). This feature has significant importance in several applications, including microfluidics, thermal control, and energy conversion. Through the examination of the thermophoresis phenomenon in water/graphene nanofluid (NF), researchers might get valuable knowledge on the potential uses of these materials. The current study examined the effect of various sizes of graphene nanoparticles (NPs) (5, 6, 9, and 10 Å) on the thermal behavior (TB), BM, and thermophoresis of water/graphene NF using molecular dynamics (MD) simulation. This study reported the changes in heat flux (HF), thermal conductivity (TC), average Brownian displacement (BD), and thermophoresis. It is concluded that by increasing the size of graphene NPs from 5 to 10 Å, the average BD and thermophoresis increased from 3.06 Å and 23.88 Å to 4.16 Å and 31.46 Å, respectively. Due to their higher kinetic energy (KE) and momentum, larger graphene NPs experienced more BM, enabling them to withstand random thermal fluctuations more effectively than smaller particles. In addition, as the size of graphene NPs increased, the HF and TC values ​​increased from 39.54 W/m2 and 0.36 W/(m.K) to 47.19 W/m2 and 0.51 W/(m.K) after 10 ns. Therefore, the size-dependent changes in BD and thermophoretic effects led to a simultaneous increase in HF and TC of the NF, which was attributed to the larger heat transfer (HT) surface area, improved HT properties, and synergistic effects of larger graphene NPs. The maximum (Max) temperature increases from 1415 K to 1504 K. These findings were useful in a variety of industries, particularly for improving TB in different NFs.

Marsh topography reveals the signature of storm-surge-driven sedimentation

Salt marshes are valuable tidal landforms threatened by drowning due to increasing sea levels. Marsh accretion supported by sediment settling during repeated flooding potentially offsets the relative elevation loss. Although tidal flooding is commonly depicted as the main mechanism delivering the sediment to marshes, storm surges and waves may deeply affect tidal flow conditions and sediment reworking in shallow tidal systems, thus raising questions on the relative contribution of these processes to salt-marsh accretion. Here we show that storm surges substantially sustain the marsh sediment budget, locally contributing up to 90% of sedimentation, and critically influence depositional patterns by analyzing a 3-yr-long measurement record of sedimentation on the marshes in the Venice Lagoon (Italy). Surge-enhanced water levels promote wind-wave-driven sediment fluxes directly across the tidal flat-marsh transition, altering tidal sedimentation patterns and, thus, affecting marsh topographic elevation and morphology. By comparing sedimentation patterns and topographic profiles, we show that the signature of storm-surge sedimentation can be found in marsh topography, which we suggest therefore as an easily detectable indicator of the relative contribution of the different physical processes driving marsh vertical evolution. The comparison with other marshes worldwide, characterized by different tidal ranges and wave exposure, consistently supports the link between the salt-marsh topographic profile and the physical processes controlling marsh evolution.

Physical processes behind the emergence of fringes in superposition effects

Physical processes behind the emergence of fringes in superposition effects

Analog reservoir computing via ferroelectric mixed phase boundary transistors

Analog reservoir computing (ARC) systems have attracted attention owing to their efficiency in processing temporal information. However, the distinct functionalities of the system components pose challenges for hardware implementation. Herein, we report a fully integrated ARC system that leverages material versatility of the ferroelectric-to-mixed phase boundary (MPB) hafnium zirconium oxides integrated onto indium–gallium–zinc oxide thin-film transistors (TFTs). MPB-based TFTs (MPBTFTs) with nonlinear short-term memory characteristics are utilized for physical reservoirs and artificial neuron, while nonvolatile ferroelectric TFTs mimic synaptic behavior for readout networks. Furthermore, double-gate configuration of MPBTFTs enhances reservoir state differentiation and state expansion for physical reservoir and processes both excitatory and inhibitory pulses for neuronal functionality with minimal hardware burden. The seamless integration of ARC components on a single wafer executes complex real-world time-series predictions with a low normalized root mean squared error of 0.28. The material-device co-optimization proposed in this study paves the way for the development of area- and energy-efficient ARC systems.

Low-dose radiographic inspection of welding by a novel aperiodic reverse stochastic resonance method

Abstract Low-dose radiographic inspection is a growing trend in industry to minimize radiation risks to humans and the environment. However, reduction in radiation dose often introduces significant noise, which affects image quality and hinders accurate identification of subtle defects. This study addresses this issue by introducing a novel phenomenon called aperiodic reverse stochastic resonance (ARSR), observed in nonlinear systems excited by aperiodic binary signals. ARSR enables simultaneous amplitude amplification and reversal of signals under specific noise conditions. Leveraging ARSR, we propose an image denoising framework for low-dose radiographic inspections. First, a set of projection data is obtained by using Radon transform to reduce the dimensionality of X-ray images from different angles. Then, the projection data is modulated based on the ARSR system. Finally, the image is reconstructed based on the inverse Radon transform. Simulations and experimental comparison results in welding applications validate the effectiveness of the framework, demonstrating significant improvements in image quality for low-dose radiographic defect detection. Unlike advanced methods such as Gaussian filtering, BM3D, and DnCNN, which operate at the pixel level, ARSR performs denoising at the projection data stage, reducing noise impact, preserving original information, and focusing on physical data processing during imaging. This approach enhances the detection of subtle defects, highlighting the potential of stochastic resonance in image processing.

The ameliorating effects of adipose-derived stromal vascular fraction cells on blue light-induced rat retinal injury via modulation of TLR4 signaling, apoptosis, and glial cell activity.

Blue light (BL)-induced retinal injury has become a very common problem due to over exposure to blue light-emitting sources. This study aimed to investigate the possible ameliorating impact of stromal vascular fraction cells (SVFCs) on BL-induced retinal injury. Forty male albino rats were randomly allocated into four groups. The control group rats were kept in 12-h light/12-h dark. Rats of SVFC-control as the control group, but rats were intravenously injected once by SVFCs. Rats of both the BL-group and BL-SVFC group were exposed to BL for 2 weeks; then rats of the BL-SVFC group were intravenously injected once by SVFCs. Following the BL exposure, rats were kept for 8 weeks. Physical and physiological studies were performed; then retinal tissues were collected for biochemical and histological studies. The BL-group showed physical and physiological changes indicating affection of the visual function. Biochemical marker assessment showed a significant increase in MDA, TLR4 and MYD88 tissue levels with a significant decrease in TAC levels. Histological and ultrastructural assessment showed disruption of the normal histological architecture with retinal pigment epithelium, photoreceptors, and ganglion cell deterioration. A significant increase in NF-κB, caspase-3, and GFAP immunoreactivity was also detected. BL-SVFC group showed a significant improvement in physical, physiological, and biochemical parameters. Retinal tissues revealed amelioration of retinal structural and ultrastructural deterioration and a significant decrease in NF-κB and caspase-3 immunoreactivity with a significant increase in GFAP immunoreaction. This study concluded that SVFCs could ameliorate the BL-induced retinal injury through TLR-4/MYD-88/NF-κB signaling inhibition, regenerative, anti-oxidative, and anti-apoptotic effects.

Body, image, and digital technology in adolescence and contemporary youth culture.

The physical, psychological and social changes that occur during adolescence constitute a physiological crisis that is necessary for development and growth. The establishment of a suitable "self-image" is important for facilitating harmonious psychophysical development during this time. In the current era, digital technology (DT) serves as an extraordinary means of communication for young people, who make significant use of images as a mode of expression. Accordingly, there is growing interest in the relationship between physical development, self-image and use of DT. A review of the published literature on the topic was carried out in April 2024. Fourteen studies (n = 14) were inclused from search of electronic databases such as PubMed, CINAHL, PsycInfo, MedLine, and Cochrane Library. The aim of this study is to explore the influence of (DT) on cultural models of adolescent body image, and how this "social" culture can affect wellbeing and development. It was considered that the rise of DT and social media (SM) emphasized in young people the culture of appearance, adherence to ideal models (thinness ideal) and social comparison at an unprecedented level. It was estimated that the digital mechanism works on the adolescent's vulnerability and stimulates the desire for experimentation and amplifies cultural beliefs that expose the young to deviant or pathological behaviors on the body. The use of digital images emphasizes the perception of self by making it more real and alive but empty of content. Our framework highlights that the adolescent can defend himself if he leaves the homologation that the SM condition, regains his own experiences, fill with emotional content and real life the images and the representation of the body.

On the Nature of Nonthermal Broadening of Spectral Lines Observed by IRIS

The origin of nonthermal broadening in solar spectra is one of the long-standing questions in solar physics. Various processes have been invoked—including unresolved flows, waves, and turbulent processes—but definitive answers are lacking. To investigate the physical processes responsible for nonthermal broadening, we examine its relation with the angle between the magnetic field and the line of sight in three different closed-field regions above plage regions at different locations on the solar disk. We obtained the nonthermal width of transition-region Si iv 1403 Å spectra observed in active regions by the Interface Region Imaging Spectrograph, after subtraction of the thermal and instrumental line broadening. To investigate the dependence of the measured broadening on the viewing angle between the line of sight and magnetic field direction, we determined the magnetic field direction at transition-region heights using nonlinear force-free extrapolations based on the observed photospheric vector magnetic field taken by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. We found that the nonthermal broadening shows a correlation with downward motion (redshifts) and alignment between the magnetic field and the observer’s line-of-sight direction. Based on the observed correlations, we suggest that velocity gradients within plasma flowing down along the magnetic field may lead to a significant portion of the observed nonthermal broadening of transition-region spectral lines in closed fields above plage regions.

Orthogonality catastrophe beyond bosonization from post-selection

We show that the dynamics induced by post-selected measurements can serve as a controlled route to access physical processes beyond the boundaries of Luttinger liquid physics. We consider a one-dimensional fermionic wire whose dynamics results from a sequence of weak measurements of the fermionic density at a given site, interspersed with unitary hopping dynamics. This realizes a non-Hermitian variant of the celebrated instance of a local scatterer in a fermionic system and its ensuing orthogonality catastrophe. We observe a distinct crossover in the system's time evolution as a function of the fermion density. In the high-density regime, reminiscent of the Hermitian case, a bosonized version of the model properly describes the dynamics while, as we delve into the low-density regime, the validity of bosonization breaks down, giving rise to irreversible behavior. Notably, this crossover from reversible to irreversible dynamics is nonperturbative in the measurement rate and can manifest itself even with relatively shallow measurement rates, provided that the system's density remains below the crossover threshold. Our results render a conceptually transparent model for exploring nonperturbative effects beyond bosonization, which could be used as a stepping stone to explore novel routes for the control of nonlinear dynamics in low-dimensional quantum systems. Published by the American Physical Society 2024

Deciphering the Characteristics and Drivers of the Summer Monsoon Precipitation Extremes Over the Indian Himalayas

AbstractThis study investigates the physical processes behind extreme precipitation events (EPEs) in the Himalayas, notorious for causing frequent floods and significant loss of life and property. Due to the presence of complex terrain, understanding the driving factors of these EPEs is challenging. Here, we decipher the precipitation characteristics and their driving factors responsible for the occurrence of EPEs in the Western Himalayas (WH) for the period 1979–2020. EPEs are defined as events exceeding the 99th percentile threshold. The extreme precipitation in the WH is contributed by both large‐scale precipitation (accounting for 61%) and convective precipitation (39%). Moreover, 25.49% of EPEs in this region are directly associated with monsoon depressions. The presence of distinct upper‐tropospheric gyres flanking the WH, along with a prominent zonal wave pattern, promotes a southward extension of the trough. This intensifies the low‐level convergence of moisture‐laden winds from the adjoining seas, resulting in substantial moisture availability for the EPEs. An omega‐type blocking pattern emerges 4 days before EPEs, facilitating the intrusion of an extratropical cyclonic circulation. This circulation, characterized by its slow eastward and equatorward movement, leads to low‐level moisture flux convergence and ascending motions, which in turn trigger the EPEs. This highlights the crucial role of extratropical signals in driving EPEs and implies that tropical‐extratropical interactions play an important role in these EPEs. Furthermore, the shifting of the Intertropical Convergence Zone is strongly linked to the enhancement of the intensity of EPEs. Moreover, moisture budget analysis shows that EPEs over the WH are primarily driven by vertical advection, with the dynamic (thermodynamic) terms explaining 92% (8%) contribution. The intensified diabatic heating structure further enhances the convection, facilitating the development of deep convection which controls the local thermodynamics of these EREs. Lastly, our study demonstrated that most intensified and persistent EPEs over the Himalayas are found to be linked with Quasi‐Resonance Amplification, which is driven by baroclinic waves with 5 and 8 zonal wave numbers that contribute to these EPEs.

Optical turbulence simulations over the Tibetan Plateau based on a single-column model with high-order closure

Optical turbulence limits the maximum resolution of ground-based telescopes and leads to image degradation. The use of atmospheric numerical techniques to forecast optical turbulence is crucial for observation scheduling and optimization of adaptive optic systems. Current research methods for forecasting optical turbulence are primarily based on mesoscale models with turbulence closure techniques to parameterize the key terms required for C n 2 calculations under the assumption of atmospheric quasi-steady-state balance, and then the integrated astroclimatic parameters related to C n 2 profile can be obtained. In this study, we propose what we believe to be a novel approach to forecast C n 2 using a boundary layer parameterization based on higher-order turbulence closure in the single-column framework of the CLUBB model. Compared to mesoscale models, the CLUBB model serves as a single-column model, which simplifies modifications and reduces compilation time, and is more conducive to testing the performance of C n 2 parameterization scheme. In the design of C n 2 parameterization scheme, we consider a more complete physical process rather than omitting certain terms to obtain a steady-state solution. The performance of the model is evaluated using measurements obtained during a field campaign conducted at Da Qaidam site above the Tibetan Plateau. The results show that the model is able to capture typical features of the C n 2 profile evolution under convective conditions. Comparison of the model with contemporaneous sounding measurements and quantification of the model’s performance using statistical operators demonstrate the statistical agreement between simulations and measurements. In terms of atmospheric seeing, we can observe a bias of 0.01 and a root-mean-square error (RMSE) of 0.31 without any model calibration, which outperforms the results of previous mesoscale modeling studies. In addition, the new parameterization scheme is also compared with two representative C n 2 algorithms previously used in the mesoscale models, with some improvements observed. The potential demonstrated by this approach is expected to bring greater value and advancement to the research of three-dimensional forecasting of optical turbulence in the future by coupling with the mesoscale model.

Variability of young stellar objects in the Orion nebula

The Orion Nebula is one of the best-studied star-forming regions in our Galaxy and provides an ideal laboratory to study the early stages of star formation. Understanding the variability of young stellar objects (YSOs) can provide valuable insights into the underlying physical processes that occur during this crucial phase of stellar evolution. In this context, we have conducted a photometric survey with high temporal resolution of a six-square-degree region centered on NGC\,1980. We used two filters ($R$ and $I$) between 2012 and 2015 with the 15\,cm twin telescope RoBoTT at the Universit\"atssternwarte Bochum in Chile. Our goal is to identify and characterize the variable objects in this sample using a unique observational setup that allows us to obtain high-quality light curves with time sampling on the order of minutes. This is the first time such an intensive ground-based photometric campaign has been conducted in the Orion Nebula. After careful quality control, more than 13000 light curves were produced in either $R$ or $I$; the total number of matched light curves is 11889. The corresponding stars were subsequently matched with the 2MASS point source catalog, resulting in 8197 stars with $I < 16.5$ mag and AAA quality flags. We employed three methods -- amplitude, standard deviation, and the Stetson J index -- to identify variable objects in our sample, successfully classifying 561 stars as variables (irregular, periodic, and quasi-periodic). These stars serve as the foundation for further analysis. We confirmed 456 of these as known pre-main-sequence stars through cross-referencing with existing YSO catalogs, supported by spectroscopic and photometric data. The youth of the remaining stars was established based on their optical and infrared color signatures. The period, $P$, could be determined for 147 sources and ranges from 0.2 days to several weeks. The frequency of very short periods ($ < 1$ day) is two to four times higher than reported in previous studies. A significant population (10<!PCT!>) comes primarily from weak-line T Tauri stars, which are characterized by rotation periods of less than 1 day. These results emphasize the advantages of observations with an exceptional time sampling strategy that allows the identification of variability on scales from hours to years.

A Search for Collisions and Planet–Disk Interactions in the Beta Pictoris Disk with 26 Years of High-precision HST/STIS Imaging

β Pictoris's well-studied debris disk and two known giant planets, in combination with the stability of the Hubble Space Telescope’s Space Telescope Imaging Spectrograph (HST/STIS) (and now also JWST), offers a unique opportunity to test planet–disk interaction models and to observe recent planetesimal collisions. We present HST/STIS coronagraphic imaging from two new epochs of data taken between 2021 and 2023, complementing earlier data taken in 1997 and 2012. This data set enables a temporal comparison with the longest baseline and highest precision of any debris disk to date, with sensitivity to variations in temporal surface brightness of sub-percent levels in the midplane of the disk. While no localized changes in surface brightness are detected, which would be indicative of a recent planetesimal collision, there is a tentative brightening of the southeast side of the disk over the past decade. We link the constraints on surface brightness variations to dynamical models of the planetary system’s evolution and to the collisional history of planetesimals. Using a coupled collisional model and injection/recovery framework, we estimate sensitivity to expanding collisional debris down to a Ceres mass per progenitor in the most sensitive regions of the disk midplane. These results demonstrate the capabilities of long-baseline, temporal studies with HST (and also soon with JWST) for constraining the physical processes occurring within debris disks.

Multi-scale analysis of nutrient and environmental dynamics in Hongfeng Lake Southwest China

Traditional linear correlation analysis may not fully capture the true relationship between these variables. Therefore, multi-scale running correlation analysis, such as time-dependent intrinsic correlation (TDIC) and continuous wavelet transform based on Hilbert–Huang transform (HHT), provides valuable insights into local correlations and the evolving relationship between nutrients and environmental factors over time. In this study, we investigated seven environmental factors and four water quality nutrient indicators in deep lakes on the Yungui Plateau in southwestern China. The results revealed that there may be strong correlations between environmental factors and nutrient levels during certain periods, while opposite trends may emerge at other times. These variations in correlation could be attributed to uncertain physical processes, spatial heterogeneity, or the impact of different climatic factors on local hydrological processes. Wavelet analysis indicated that changes in environmental factors lag behind those in nutrient levels, particularly on a cycle of about 12 months. This suggests that changes in environmental factors align with natural patterns after the water body has been polluted. These conclusions underscore the complexity and dynamic nature of the relationship between environmental factors and nutrient levels in water bodies, highlighting the importance of employing advanced analysis techniques to capture this complexity.