Vertical Gradient Research Articles

Inferring intrahalo light from stellar kinematics. A deep learning approach

In the context of structure formation, disentangling the central galaxy stellar population from the stellar intrahalo light can help us shed light on the formation history of the halo as a whole, as the properties of the stellar components are expected to retain traces of the formation history. Many approaches are adopted to assess the task, depending on different physical assumptions (e.g. the light profile, chemical composition, and kinematical differences) and depending on whether the full six-dimensional phase-space information is known (much like in simulations) or whether one analyses projected quantities (i.e. observations). This paper paves the way for a new approach to bridge the gap between observational and simulation methods. We propose the use of projected kinematical information from stars in simulations in combination with deep learning to create a robust method for identifying intrahalo light in observational data to enhance understanding and consistency in studying the process of galaxy formation. Using deep learning techniques, particularly a convolutional neural network called U-Net, we developed a methodology for predicting these contributions in simulated galaxy cluster images. We created a sample of mock images from hydrodynamical simulations (including masking of the interlopers) to train, validate and test the network. Reinforced training (Attention U-Net) was used to improve the first results, as the innermost central regions of the mock images consistently overestimate the stellar intrahalo contribution. Our work shows that adequate training over a representative sample of mock images can lead to good predictions of the intrahalo light distribution. The model is mildly dependent on the training size and its predictions are less accurate when applied to mock images from different simulations. However, the main features (spatial scales and gradients of the stellar fractions) are recovered for all tests. While the method presented here should be considered as a proof of concept, future work (e.g. generating more realistic mock observations) is required to enable the application of the proposed model to observational data.

Negative Anomalies in the Atmospheric Electric Field near the Earth's Surface in Seismically Active Regions

The paper examines poorly-studied negative bay-like anomalies in the near-earth atmospheric electric field in seismically active regions at fair weather suitable for atmospheric electric observations. Observation data analysis revealed characteristic features of anomalies formation that allow us to conclude that the anomalies are associated with the deformation of near-surface rocks at tectonoseismic process. On the basis of the concept of atmospheric electricity, the source of anomalies in the electric field is a local negative space charge of small ions in the near-earth air emerged at a negative vertical gradient of electrical conductivity. It was revealed that the charge and produced negative anomalies in the electric field have deformation and emanation processes in their origin. We propose a scheme of anomalies formation and consider the role of radon and thoron in their emergence. It was found that thoron plays a more important role in some cases.

Generation Mechanisms of SST Anomalies Associated with the Canonical El Niño Focusing on Vertical Mixing

Abstract The mean vertical advection of anomalous vertical temperature gradient is considered the dominant generation mechanism of positive sea surface temperature (SST) anomalies associated with the canonical El Niño. However, most past studies had a residual term in their heat budget analysis and/or did not quantify the role of vertical mixing even though active vertical turbulent mixing in the upper ocean is observed in the eastern equatorial Pacific. To quantitatively assess the importance of vertical mixing, a mixed layer heat budget analysis is performed using a hindcast simulation forced by daily mean atmospheric reanalysis data. It is found that when the mixed layer depth is defined as the depth at which potential density increases by 0.125 kg m−3 from the sea surface, the development of positive SST anomalies is predominantly governed by reductions in the cooling by vertical mixing, and their magnitude is much larger than those by vertical advection. The anomalous warming by vertical mixing may be partly explained by an anomalous deepening of the thermocline that leads to a decrease in the vertical temperature gradient, giving rise to suppression of the climatological cooling by vertical mixing. Also, an anomalously thick mixed layer reduces sensitivity to cooling by the mean vertical mixing and contributes to the anomalous SST warming. On the other hand, the dominant negative feedbacks are attributed to both anomalous surface heat loss and anomalous deepening of the mixed layer that weakens warming by the mean surface heat flux.

Spontaneous convective pattern formation in a dusty plasma

We report on experimental observations of self-sustaining convective patterns in a dusty plasma system. The experiments are carried out in a capacitively coupled radio frequency (RF) argon plasma discharge in which a dusty plasma is produced by introducing micrometer-sized melamine formaldehyde particles. A self-sustained pair of convective cells with opposite vorticities is seen to appear in a lateral view of the system, beyond some threshold values of the background gas pressure and RF power. Particle tracking velocimetry measurements reveal the existence of a dust temperature gradient that is responsible for the convective counter-rotating patterns. The origin of the kinetic temperature gradient in the absence of any external heat source is attributed to the larger ion flux induced heating of the bottom layer of the dust cloud. The velocity and vorticity of the particles in the convective cell increase with an increase in the vertical kinetic temperature gradient. The experimental results compare reasonably well with the findings of molecular dynamics simulations of the laboratory system.

The joint effects of local, climatic, and spatial variables determine soil oribatid mite community assembly along a temperate forest elevational gradient.

Numerous factors influence mountain biodiversity variation across elevational gradients and recognizing the relative importance is vital for understanding species distribution mechanisms. We examined oribatid mites at nine elevations (from 600 to 2200 m a.s.l) and four vegetation types from mixed coniferous and broad-leaved forests to alpine tundra on Changbai Mountain. We assessed the contribution of environmental factors (climatic and local factors) and spatial processes (geographic or elevation distances) to oribatid mite community assembly and identified 59 oribatid mite species from 38 families and 51 genera. With increasing elevation, species richness and the Shannon index declined significantly, whereas abundance followed a hump-shaped trend. Soil TP, NH4 +-N, MAT, MAP, and elevation were the critical variables shaping oribatid mite communities based on random forest analysis. Moreover, environmental and spatial factors, and oribatid mite communities were significantly correlated based on Mantel and partial Mantel tests. Local characteristics (3.9%), climatic factors (1.9%), and spatial filtering (8.8%) played crucial roles in determining oribatid mite communities across nine elevational bands (based on variation partitioning analyses of abundance data). Within the same vegetation types, spatial processes had relatively little effects, with local characteristics the dominant drivers of oribatid mite community variation. Environmental and spatial filters together shape oribatid mite community assembly and their relative roles varied with elevation and vegetation type. These findings are crucial for the conservation, restoration, and management of Changbai mountain ecosystems in the context of climate change, along with the prediction of future vertical biotic gradient pattern evolution.

Large-scale semi-organized rolls in a sheared convective turbulence: Mean-field simulations

Based on a mean-field theory of a non-rotating turbulent convection [T. Elperin et al., Phys. Rev. E 66, 066305, (2002)], we perform mean-field simulations (MFS) of sheared convection that takes into account an effect of modification of the turbulent heat flux by the non-uniform large-scale motions. This effect is caused by the production of additional essentially anisotropic velocity fluctuations generated by tangling of the mean-velocity gradients by small-scale turbulent motions due to the influence of the inertial forces during the lifetime of turbulent eddies. These anisotropic velocity fluctuations contribute to the turbulent heat flux. As the result of this effect, there is an excitation of large-scale convective-shear instability, which causes the formation of large-scale semi-organized structures in the form of rolls. The lifetimes and spatial scales of these structures are much larger compared to the turbulent scales. By means of MFS performed for stress-free and no-slip vertical boundary conditions, we determine the spatial and temporal characteristics of these structures. Our study demonstrates that the modification of the turbulent heat flux by non-uniform flows leads to a strong reduction of the critical effective Rayleigh number (based on the eddy viscosity and turbulent temperature diffusivity) required for the formation of the large-scale rolls. During the nonlinear stage of the convective-shear instability, there is a transition from a two-layer vertical structure with two rolls in the vertical direction before the system reaches steady-state to a one-layer vertical structure with one roll after the system reaches steady state. This effect is observed for all effective Rayleigh numbers. We find that inside the convective rolls, the spatial distribution of the mean potential temperature includes regions with a positive vertical gradient of the potential temperature caused by the mean heat flux of the convective rolls. This study might be useful for understanding the origin of large-scale rolls observed in atmospheric convective boundary layers, as well as in numerical simulations and laboratory experiments.

Drone-Borne Magnetic Gradiometry in Archaeological Applications.

The use of magnetometers arranged in a gradiometer configuration offers a practical and widely used solution, particularly in archaeological applications where the sources of interest are generally shallow. Since magnetic anomalies due to archaeological remains often have low amplitudes, highly sensitive magnetic sensors are kept very close to the ground to reveal buried structures. However, the deployment of Unmanned Aerial Vehicles (UAVs) is increasingly becoming a reliable and valuable tool for the acquisition of magnetic data, providing uniform coverage of large areas and access to even very steep terrain, saving time and reducing risks. However, the application of a vertical gradiometer for drone-borne measurements is still challenging due to the instability of the system drone magnetometer in flight and noise issues due to the magnetic interference of the mobile platform or related to the oscillation of the suspended sensors. We present the implementation of a magnetic vertical gradiometer UAV system and its use in an archaeological area of Southern Italy. To reduce the magnetic and electromagnetic noise caused by the aircraft, the magnetometer was suspended 3m below the drone using ropes. A Continuous Wavelet Transform analysis of data collected in controlled tests confirmed that several characteristic power spectrum peaks occur at frequencies compatible with the magnetometer oscillations. This noise was then eliminated with a properly designed low-pass filter. The resulting drone-borne vertical gradient data compare very well with ground-based magnetic measurements collected in the same area and taken as a control dataset.

Physiologic Doses of TGF-β Improve the Composition of Engineered Articular Cartilage.

Conventionally, for cartilage tissue engineering applications, TGF-β is administered at doses that are several orders of magnitude higher than those present during native cartilage development. While these doses accelerate extracellular matrix (ECM) biosynthesis, they may also contribute to features detrimental to hyaline cartilage function, including tissue swelling, type-I collagen (COL-I) deposition, cellular hypertrophy, and cellular hyperplasia. In contrast, during native cartilage development, chondrocytes are exposed to moderate TGF-β levels, which serve to promote strong biosynthetic enhancements while mitigating risks of pathology associated with TGF-β excesses. Here, we examine the hypothesis that physiologic doses of TGF-β can yield neocartilage with a more hyaline-cartilage-like composition and structure relative to conventionally-administered supraphysiologic doses. This hypothesis was examined on a model system of reduced-size constructs (Ø2×2mm or Ø3×2mm) comprised of bovine chondrocytes encapsulated in agarose, which exhibit mitigated TGF-β spatial gradients allowing for an evaluation of the intrinsic effect of TGF-β doses on tissue development. Reduced-size (Ø2×2mm or Ø3×2mm) and conventional-size constructs (Ø4-Ø6mm×2mm) were subjected to a range of physiologic (0.1, 0.3, 1ng/mL) and supraphysiologic (3, 10ng/mL) TGF-β doses. At day 56, the physiologic 0.3ng/mL dose yielded reduced-size constructs with native-cartilage-matched Young's modulus (EY) (630±58kPa) and sulfated GAG (sGAG) content (5.9±0.6%) while significantly increasing the sGAG-to-collagen ratio, leading to significantly reduced tissue swelling relative to constructs exposed to the supraphysiologic 10ng/mL TGF-β dose. Further, reduced-size constructs exposed to the 0.3ng/mL dose exhibited a significant reduction in fibrocartilage-associated COL-I and a 77% reduction in the fraction of chondrocytes present in a clustered morphology, relative to the supraphysiologic 10ng/mL dose (p<0.001). EY was significantly lower for conventional-size constructs exposed to physiologic doses due to TGF-β transport limitations in these larger tissues (p<0.001). Overall, physiologic TGF-β appears to achieve an important balance of promoting requisite ECM biosynthesis, while mitigating features detrimental to hyaline cartilage function. While reduced-size constructs are not suitable for the repair of clinical-size cartilage lesions, insights from this work can inform TGF-β dosing requirements for emerging scaffold-release or nutrient-channel delivery platforms capable of achieving uniform delivery of physiologic TGF-β doses to larger constructs required for clinical cartilage repair.

The Role of Advection in Storm Surge for Hurricane Michael (2018)

AbstractHurricane Michael (2018) made landfall near Mexico Beach, FL, as a Category 5 hurricane, with gauge‐measured water levels over 4 m. Wind and pressure fields were created by blending a parametric near‐field model with a gridded far‐field model. Winds and modeled water levels were well validated across Michael's large impact a‐ea. A detailed analysis of the coastal surge caused by Michael demonstrates that advection contributed significantly to Michael's highest water levels and the timing of the water level across a large portion of the Michael impact area. A momentum balance in a streamwise‐normal coordinate system demonstrates that the advection contributions due to spatial gradients in the flow are identified with streamwise convergence/expansion of the flow field (Bernoulli acceleration) and curvature in the flow field (centrifugal acceleration). These effects are created by the regional geometry and the storm's wind field and are most likely to affect back barrier water levels and along curved coastlines. These findings provide an improved understanding of the role of advection in determining storm surge and, thus, the importance of including it in storm surge models.

The primate cortical LFP exhibits multiple spectral and temporal gradients and widespread task dependence during visual short-term memory.

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3 and 80 Hz that differ between the two monkeys. The LFP power in each band, as well as the sample entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in cortical pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task-dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread, and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.NEW & NOTEWORTHY We recorded extracellular electrophysiological signals from roughly the breadth and depth of a cortical hemisphere in nonhuman primates (NHPs) performing a visual memory task. Analyses of the band-limited local field potential (LFP) power displayed widespread, frequency-dependent cortical gradients in spectral power. Using a machine learning classifier, these features allowed robust cortical area decoding. Further task dependence in LFP power were found to be widespread, indicating large-scale gradients of LFP activity, and task-related activity.

Response of the phytoplankton size fractions along environmental gradients from an oxygen minimum zone in the central Mexican Pacific

The marine phytoplankton community responds to latitudinal, longitudinal (coast to ocean), and vertical environmental gradients, an important subject in Oxygen minimum zones (OMZ). The phytoplankton structure and the effect of environmental gradients along the central Mexican Pacific, an area within an OMZ, were studied, especially the importance of size fractions and taxonomic groups. A combination of various methods and protocols, such as microscopic analysis, flow cytometer, and pigment analysis, were followed in this study. Oceanographic conditions included thermal gradients along the study area and unreported evidence of a weak upwelling in the southern zone (Acapulco). Vertical distribution of chlorophyll a showed subsurface maxima (SCM, 15-45 m depth) in all stations, and deeper chlorophyll-a maxima (DCM, 85-95 m depth) in more oceanic stations. Chain-forming diatoms dominated in the northern zone stations. Prochlorococcus, Synechococcus, and picoeukaryotes abundances ranged between 0.01 to 21.7 cells×104 mL-1, although most samples showed the highest contribution to biomass (47.95 μg C L-1) by picoeukaryotes. Expected tendencies of Prochlorococcus distribution were observed: highest densities coincided with the DCM and divinyl chlorophyll-a distribution at oceanic stations. Fucoxanthin had the highest concentrations, whereas fucoxanthin and zeaxanthin concentrations were higher at SCM depths. We documented the co-dominance of the pico- and microplankton: picoplankton was important at the DCM, related to oligotrophic and more stratified water column, whereas microplankton prevailed in coastal stations, with mixed water column, high nutrient concentrations, and diatoms as the dominant group. Picoeukaryotes abundances were related to the concentration of prasinoxanthin, which suggests an important mamiellophyte component not previously revealed.

Role of fictive temperature distribution involved in CO2 laser polishing of fused silica and its optimization for achieving even heat-affected zones

CO2 laser polishing process is a highly effective way for enhancing the surface quality and laser-induced damage threshold of fused silica optics. Nevertheless, due to the thermal history and spatial gradient of the thermodynamic temperature, the heat-affected zones can be formed unevenly on the surface with an increased fictive temperature, which causes the material densification and residual stress. In this work, a 3D model of structural relaxation coupled with temperature and flow fields was innovatively established to explore the role of fictive temperature distribution involved in CO2 laser polishing of fused silica. The Raman spectrum was applied to verify this model. Subsequently, the impacts of laser beam power, scanning speed, track overlapping, substrate temperature on the fictive temperature were discussed. The results indicate that decreasing the scanning speed and increasing the substrate temperature can decrease the fictive temperature. Additionally, a higher track overlapping can reduce the height of the fictive temperature “tool mark”. Moreover, an optimization strategy based on laser beam scanning speed was proposed based on the uniform distribution of fictive temperature. The depth difference of the heat-affected zones was reduced from 164.26 μm to 31.74 μm. This work could be used to quantitatively predict the 3D fictive temperature distribution and proposed an optimization strategy based on scanning speed to suppress the non-uniformity of fictive temperature distribution, which can provide significant theoretical guidance for CO2 laser polishing technology of fused silica optics.

Reindeer grazing reduces climate‐driven vegetation changes and shifts trophic interactions in the Fennoscandian tundra

Herbivores drive shifts in plant species composition by interacting with vegetation through defoliation, trampling and nutrient addition: urine and faeces. As herbivore effects on vegetation accumulate over time, they might spillover to other trophic levels, but how and when this happens is poorly understood. Since it is methodologically demanding to measure biodiversity across spatial gradients, an alternative approach is to assess it through biodiversity indices of vascular plants. We employed the Index of biodiversity relevance developed for Swedish flora which provides an estimated number of organisms associated with a plant species, allowing the quantification of trophic community size. Values from this index were coupled with vegetation data from a network of 96 fenced and paired grazed plots across Fennoscandia. We analysed the role herbivory has on plant richness and diversity, and on the number of organisms that interact with the vegetation according to the index values. We also explored how herbivores influence the competitive effects of tall shrubs on other plants since the dominance of a vegetation type links directly to biodiversity. Plant diversity had no clear response to grazing. Overall vegetation and the vegetation subgroups herbs and non‐fruit shrubs had higher biodiversity index values in fenced plots, indicating a higher number of plant–host interactions. Herb cover was negatively related to shrubs in both treatments but with a faster decline in the absence of herbivores. This study highlights the importance of maintaining herbivore populations in the Arctic to conserve the vegetation structure and biodiversity of the tundra. This method of coupling biodiversity indexes with vegetation data provides complementary information to the plant diversity, especially when methodological or time constraints prevent complete field inventories.

Investigating enhanced thermal comfort and energy efficiency through strategized airflow in Micro-Zonal Occupant-Centric Control (MZOCC)

The potential of Micro-Zonal Occupant Centric Control (MZOCC) to save HVAC energy consumption in medium sized open-plan offices has been established in literature. This is done by virtually dividing a thermal zone into micro-zones and allowing independent diffuser-level control in each micro-zone when the micro-zone is occupied. In continuation, there is a need to ensure that thermal comfort is achieved within micro-zones under such localised control. This is important because several forms of discomfort such as draft, horizontal thermal asymmetry and vertical thermal gradients may arise in MZOCC. Further, the effect of MZOCC airflow control strategies, such as setback flow and setback temperature, which were proposed in previous studies on thermal comfort of occupants needs to be evaluated. In an attempt to address these research gaps, this study explores thermal comfort for different scenarios of diffuser arrangements, airflow control strategies and occupancy conditions and also explores the effect of varying supply velocities used in setback flow and setpoint temperatures used as setback temperatures on air distribution and thermal comfort.Results show that low PMV values, increased draft discomfort and heavy thermal gradients are observed for certain scenarios of MZOCC. Tuning airflow control by choosing appropriate setback flow or setback temperature helps in restoring thermal comfort. As different forms of discomfort are observed in different cases, it is important to plan micro-zones and control airflow, such that, MZOCC does not violate thermal comfort criteria while optimising energy efficiency. This study gives a framework for selecting appropriate airflow control strategies for a selected diffuser arrangement for a given occupancy condition. Comfort-based MZOCC that uses appropriate airflow control strategy saves about 60% energy when the zone is half occupied and about 85% energy when the zone is quarter occupied. Results also show that, improving the diffuser arrangement improves energy savings and increases the options of airflow control strategies that can be used. Also, different airflow control strategies behave differently for each diffuser arrangement and has to be chosen separately for given diffuser setting and occupancy condition.

Predicting cycling flows in cities without cycling data

Cycling is a potential tool to mitigate many of the problems faced by urban populations today. Encouraging the use of bicycles as a legitimate mobility tool, however, demands adequate knowledge of current mobility patterns, such as locations of trip generation and attraction. Unfortunately, cities usually do not gather enough data to adequately understand cycling demand. We propose models based on spatial econometrics and gradient boosted regression trees which can be trained with data from cities with mature cycling cultures and then applied to cities still in their cycling infancy to supply city officials with a better estimate of potential future OD matrices. We perform a case study in the Boston Metropolitan Area and show results comparing both types of models.

Decoupled Hydroclimate of Central and Southwestern Iran Controlled by the Strength of Southerly‐Westerly Jets During Marine Isotope Stage 3

AbstractThe regional impact of abrupt glacial climate variability remains poorly constrained for arid southwestern Asia, particularly winter dynamics during Marine Isotope Stage 3, due to limited paleoarchives in the Middle East. Here, we present continuous speleothem records of δ18O and δ13C with robust chronologies for southwestern and central Iran, spanning ∼50–30 ka. Stable‐isotope signals in the two stalagmites are generally uncorrelated and do not exhibit a consistent response to Greenland stadials or interstadials; however, both show a positive δ18O excursion that coincides with Heinrich event 4. We explore the potential mechanisms for intermittent coupling of speleothem δ18O across Iran through isotope‐enabled atmospheric modeling outputs, from which we utilize the spatial δ18O gradient as a proxy for wintertime westerly versus southerly jet strength. Our results suggest that during Heinrich event 4 and several Greenland stadials, stronger westerly winds enhanced Mediterranean moisture contributions to both sites and reduced aridity in southern Iran.

Integrated Design for Discrete Sulfur@Polymer Nanoreactor with Tandem Connection as Lithium-Sulfur Battery Cathodes.

Apart from electrode material modification, architecture design and optimization are important approaches for improving lithium-sulfur battery performance. Herein, an integrated structure with tandem connection is constructed by confining nanosulfur (NS) in conductive poly(3,4-ethylenedioxythiophene) (PEDOT) reaction chambers, forming an interface of discrete independent nanoreactor units bonded onto carbon nanotubes (noted as CNT/NS@PEDOT). The unique spatial confinement and concentration gradients of sulfur@PEDOT nanoreactors (SP-NRs) can promote reaction kinetics while facilitating rapid polysulfide transformation and minimizing dissolution and diffusion losses. Meanwhile, overall ultrahigh energy input and output are achieved through tandem connection with carbon nanotubes, isolation with PEDOT coating, and synergistic multiplicative effects among SP-NRs. As a result, it delivers a high initial discharge capacity of 1246 mAh g-1 at 0.1 C and 918 mAh g-1 at 1 C, the low capacity decay rate per lap of 0.011 % is achieved at a current density of 1 C after 1000 cycles. This research emphasizes the innovative structural design to provide a fresh trajectory for the further advancement of high-performance energy storage devices.

Integrated Design for Discrete Sulfur@Polymer Nanoreactor with Tandem Connection as Lithium–Sulfur Battery Cathodes

AbstractApart from electrode material modification, architecture design and optimization are important approaches for improving lithium–sulfur battery performance. Herein, an integrated structure with tandem connection is constructed by confining nanosulfur (NS) in conductive poly(3,4‐ethylenedioxythiophene) (PEDOT) reaction chambers, forming an interface of discrete independent nanoreactor units bonded onto carbon nanotubes (noted as CNT/NS@PEDOT). The unique spatial confinement and concentration gradients of sulfur@PEDOT nanoreactors (SP‐NRs) can promote reaction kinetics while facilitating rapid polysulfide transformation and minimizing dissolution and diffusion losses. Meanwhile, overall ultrahigh energy input and output are achieved through tandem connection with carbon nanotubes, isolation with PEDOT coating, and synergistic multiplicative effects among SP‐NRs. As a result, it delivers a high initial discharge capacity of 1246 mAh g−1 at 0.1 C and 918 mAh g−1 at 1 C, the low capacity decay rate per lap of 0.011 % is achieved at a current density of 1 C after 1000 cycles. This research emphasizes the innovative structural design to provide a fresh trajectory for the further advancement of high‐performance energy storage devices.

Variational temporal convolutional networks for I-FENN thermoelasticity

Machine learning (ML) has been used to solve multiphysics problems like thermoelasticity through multi-layer perceptron (MLP) networks. However, MLPs have high computational costs and need to be trained for each prediction instance. To overcome these limitations, we introduced an integrated finite element neural network (I-FENN) framework to solve transient thermoelasticity problems in Abueidda and Mobasher (2024). This approach used a physics-informed temporal convolutional network (PI-TCN) within a finite element scheme for solving transient thermoelasticity problems. In this paper, we introduce an I-FENN framework using a new variational TCN model trained to minimize the thermoelastic variational form rather than the strong form of the energy balance. We mathematically prove that the I-FENN setup based on minimizing the variational form of transient thermoelasticity still leads to the same solution as the strong form. Introducing the variational form to the ML model brings the advantages of lower requirement for the differentiability of the basis function and, thus, lower memory requirement and higher computational efficiency. Also, it automatically satisfies zero Neumann boundary conditions, thus reducing the complexity of the loss function. The formulation based on the variational form complies with thermodynamic requirements. The proposed loss function reduces the difference between predicted and target data while minimizing the variational form of thermoelasticity equations, combining the benefits of both data-driven and variational methods. In addition, this study uses finite element shape functions for spatial gradient calculations and compares their performance against automatic differentiation. Our results reveal that models leveraging shape functions exhibit higher accuracy in capturing the behavior of the thermoelasticity problem and faster convergence. Adding the variational term and using shape functions for gradient calculations ensure better adherence to the underlying physics. We demonstrate the capabilities of this I-FENN framework through multiple numerical examples. Additionally, we discuss the convergence of the proposed variational TCN model and the impact of hyperparameters on its performance. The proposed approach offers a well-founded and flexible platform for solving fully coupled thermoelasticity problems while retaining computational efficiency, where the efficiency scales proportional to the model size.

Implications of mitochondrial membrane potential gradients on signaling and ATP production analyzed by correlative multi-parameter microscopy

The complex architecture and biochemistry of the inner mitochondrial membrane generate ultra-structures with different phospholipid and protein compositions, shapes, characteristics, and functions. The crista junction (CJ) serves as an important barrier separating the cristae (CM) and inner boundary membranes (IBM). Thereby CJ regulates the movement of ions and ensures distinct electrical potentials across the cristae (ΔΨC) and inner boundary (ΔΨIBM) membranes. We have developed a robust and flexible approach to visualize the CJ permeability with super-resolution microscopy as a readout of local mitochondrial membrane potential (ΔΨmito) fluctuations. This method involves analyzing the distribution of TMRM fluorescence intensity in a model that is restricted to the mitochondrial geometry. We show that mitochondrial Ca2+ elevation hyperpolarizes the CM most likely caused by Ca2+ sensitive increase of mitochondrial tricarboxylic acid cycle (TCA) and subsequent oxidative phosphorylation (OXPHOS) activity in the cristae. Dynamic multi-parameter correlation measurements of spatial mitochondrial membrane potential gradients, ATP levels, and mitochondrial morphometrics revealed a CJ-based membrane potential overflow valve mechanism protecting the mitochondrial integrity during excessive cristae hyperpolarization.