Dynamic Characterization Research Articles

Energetic and dynamic characterization of pollutant dispersion in varied building layouts through an augmented analysis procedure

This work presents a post-data analysis procedure, namely, proper orthogonal decomposition (POD)–dynamic mode decomposition (DMD)–discrete Fourier transform analysis, for evaluating the dominant features of the flow fields from both energetic and dynamic perspectives. The large-eddy simulation (LES) was first employed to reproduce the flow field surrounding three types of building layouts. Subsequently, both POD and DMD were conducted according to LES simulation results. The extracted modes were classified into three types based on the POD and DMD: Type-1 mode: energetically and dynamically significant mode, Type-2 mode: energetically significant and dynamically insignificant mode, and Type-3 mode: energetically insignificant and dynamically significant mode. The findings indicate that Type-1 mode governs the primary velocity field and the predominant vortex patterns observed at the rear of the building arrays, as the reduction of inter-building widths leads to a shorter flow separation region. Type-2 mode is characterized by the presence of small-scale vortices and the high turbulent kinetic energy region, which periodically triggers pollutant increase in the vicinity of structures. Type-3 mode demonstrates a minimal energetic influence on the flow field; nevertheless, it significantly contributes to the consistent build-up of pollutants within the far-wake region. The present study also investigates the predominant coherent structures of flow fields concerning various building layouts and highlights the influence of passage widths on the efficiency of pollutant removal. This comprehensive analysis enables a systematic exploration of flow patterns within various building layouts, offering potential solutions for pollutant dispersion challenges in metropolitan areas.

Real-time imaging of standing-wave patterns in microresonators

Real-time characterization of microresonator dynamics is important for many applications. In particular, it is critical for near-field sensing and understanding light-matter interactions. Here, we report camera-facilitated imaging and analysis of standing wave patterns in optical ring resonators. The standing wave pattern is generated through bidirectional pumping of a microresonator, and the scattered light from the microresonator is collected by a short-wave infrared (SWIR) camera. The recorded scattering patterns are wavelength dependent, and the scattered intensity exhibits a linear relation with the circulating power within the microresonator. By modulating the relative phase between the two pump waves, we can control the generated standing waves' movements and characterize the resonator with the SWIR camera. The visualized standing wave enables subwavelength distance measurements of scattering targets with nanometer-level accuracy. This work opens broad avenues for applications in on-chip near-field (bio)sensing, real-time characterization of photonic integrated circuits, and backscattering control in telecom systems.

Historical Dynamic Mapping of Eucalyptus Plantations in Guangxi during 1990–2019 Based on Sliding-Time-Window Change Detection Using Dense Landsat Time-Series Data

Eucalyptus plantations are expanding rapidly in southern China owing to their short rotation periods and high wood yields. Determining the plantation dynamics of eucalyptus plantations facilitates accurate operational planning, maximizes benefits, and allows the scientific management and sustainable development of eucalyptus plantations. This study proposes a sliding-time-window change detection (STWCD) approach for the holistic characterization and analysis of eucalyptus plantation dynamics between 1990 and 2019 through dense Landsat time-series data. To achieve this, pre-processing was first conducted to obtain high-quality reflectance data and the monthly composite maximum normalized-difference vegetation index (NDVI) time series was determined for each Landsat pixel. Second, a sliding time window was used to segment the time series and obtain the NDVI change characteristics of the subsequent segments, and a sliding time window-based LandTrendr change detection algorithm was applied to detect the crucial growth or harvesting phases of the eucalyptus plantations. Third, pattern-matching technology was adopted based on the change detection results to determine the characteristics of the eucalyptus planting dynamics. Finally, we identified the management history of the eucalyptus plantations, including planting times, generations, and rotation cycles. The overall accuracy of eucalyptus identification was 90.08%, and the planting years of the validation samples and the planting years estimated by our algorithm revealed an apparent correlation of R2 = 0.98. The results showed that successive generations were mainly first- and second-generations, accounting for 75.79% and 19.83% of the total eucalyptus area, respectively. The rotation cycles of the eucalyptus plantations were predominantly in the range of 4–8 years. This study provides an effective approach for identifying eucalyptus plantation dynamics that can be applied to other short-rotation plantations.

Mechanical and dynamic characterization of SiO2 nanofiller-based Luffa cylindrica fibre composites structures using finite element method

The present work mainly explored the fabrication of different weight percentages of SiO2 nano-filler-based Luffa cylindrica polymer composites (LCPC) and investigated their free vibration behaviour based on elastic properties acquired from a uniaxial tensile test. The elastic properties of fabricated polymer composites are obtained as per ISO 527-5 standards. The flexural responses of different nano-filler-based polymer composites are also analyzed using a three-point bending test in UTM. The completeness of the present polymer composite structure is verified by comparing it with the available published work and found to be in excellent agreement. The field emission scanning electron microscope (FESEM) helps to understand the interfacial bonds, fibre pullout, voids, internal cracks etc. between fibre and matrix by morphological images. The addition of SiO2 nano-filler into the polymer composites boosts mechanical properties such as tensile strength and flexural strength and also provides better compatibility between matrix and fibre due to the high surface area of SiO2 nano-filler. Later, the structural responses (free vibration) are investigated with respect to different parameters such as edge conditions, aspect ratio and side-to-thickness ratio.

Hexad robot: A 6-dof parallel PnP robot to accommodate antagonistic rotational capability and structural complexity

This paper proposed a new structure of full-mobility parallel robot, which combined the advantages of high-rotational capabilities and structural simplification, for high-speed operations of material handling. The proposed robot structure integrates lightweight and simple linkages with a relatively complex (i.e., compared to the single platform with limited rotational capability) articulated mechanism or gear train as wrist mechanism to amplify the end-effector rotations, but without significantly increased structural complexity of gearbox, compared to the existing designs. Parametric modeling are carried out for position analysis, workspace evaluation, singularity identification and dynamic characterization to qualify the proposed robot. Moreover, the structure of the proximal links are designed with topology optimization to ensure design requirements of stiffness and low inertia. The performance evaluation shows that the proposed robot can be of high potential application in the industrial production line.

AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles, and Binding Energetics of the SARS-CoV-2 Omicron BA.2.86 Spike Protein with ACE2 Host Receptor and Antibodies: Compensatory Functional Effects of Binding Hotspots in Modulating Mechanisms of Receptor Binding and Immune Escape.

The latest wave of SARS-CoV-2 Omicron variants displayed a growth advantage and increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with atomistic simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both the structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that the AlphaFold2-predicted structural ensemble of the BA.2.86 spike protein complex with ACE2 can accurately capture the main conformational states of the Omicron variant. Complementary to AlphaFold2 structural predictions, microsecond molecular dynamics simulations reveal the details of the conformational landscape and produced equilibrium ensembles of the BA.2.86 structures that are used to perform mutational scanning of spike residues and characterize structural stability and binding energy hotspots. The ensemble-based mutational profiling of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 revealed a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 convergent mutational hotspots R403K, F486P, and R493Q. To examine the immune evasion properties of BA.2.86 in atomistic detail, we performed structure-based mutational profiling of the spike protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against the BA.2.86 variant. The results revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have evolved to outcompete other Omicron subvariants by improving immune evasion while preserving binding affinity with ACE2 via through a compensatory effect of R493Q and F486P convergent mutational hotspots. This study demonstrated that an integrative approach combining AlphaFold2 predictions with complementary atomistic molecular dynamics simulations and robust ensemble-based mutational profiling of spike residues can enable accurate and comprehensive characterization of structure, dynamics, and binding mechanisms of newly emerging Omicron variants.

Are the Noah and Noah-MP land surface models accurate for frozen soil conditions?

The accurate prediction of frozen soil conditions is a critical component of dynamic terrain characterization for engineering operations in cold regions. Currently the trusted resource for dynamic terrain within the US military uses gridded global soil conditions (i.e., temperature and moisture) generated by the Land Information System (LIS) architecture. LIS combines static terrain data with trusted surface weather information into the Noah land surface model to generate a continuous representation of the global surface conditions. Both the input weather data and the model output land surface state are adjusted to match the observed state using an advanced ensemble Kalman filter data assimilation technique to incorporate in situ and remote sensing observations. While this product has been robustly evaluated under unfrozen conditions only sporadic studies have investigated its ability to accurately simulate freeze/thaw cycles, and soil temperature and moisture under frozen conditions. Here, we present a broad comparison and evaluation of the simulated soil state against an in situ network of soil temperature and moisture distributed across the Continental United States that focuses on the winter season. This comparison includes both the Noah and the newer Noah with multi-parameterization (Noah-MP) land surface models. A comparison of the two models reveals substantial differences in simulated soil moisture, frozen content, and frozen soil strength. In general, Noah predicts colder soils with deeper frost depths, and frozen soils that are slightly stronger than Noah-MP. Initial results evaluating Noah and Noah-MP against in situ observations show that both models have significantly degraded model performance for frozen soil conditions compared to their performance for unfrozen soil. In particular, Noah has a significant and persistent cold bias of approximately −3 K when the soil temperature is below freezing. This cold bias is not present in Noah-MP and further analysis shows that this improvement was almost entirely caused by a better representation of thermal conduction through snow in Noah-MP. Specifically, we find that the bulk effective thermal conductivity of a snowpack is 2× greater in Noah, which allows for greater surface heat loss during the winter and, consequently, lower soil temperatures. This analysis reveals that the more advanced multi-layer snow model in Noah-MP substantially improves the representation of soil temperature during the cold season.

Assessment of thermographic tools for the validation of physics-based models of an induction sealing process

Measure of temperature dynamics in induction sealing processes is of paramount importance for the validation of physics-based models. In this work, commonly used commercial tools for temperature measurements, such as thermocouples, pyrometers and thermal cameras, are benchmarked for the characterization of the temperature dynamics occurring in multilayer aluminum foil-based packaging material undergoing relatively fast (i.e., ×100 ms) induction heating transients.

Cyclodextrins: Establishing building blocks for AI-driven drug design by determining affinity constants in silico

Cyclodextrins (CDs) are cyclic carbohydrate polymers that hold significant promise for drug delivery and industrial applications. Their effectiveness depends on their ability to encapsulate target molecules with strong affinity and specificity, but quantifying affinities in these systems accurately is challenging for a variety of reasons. Computational methods represent an exceptional complement to in vitro assays because they can be employed for existing and hypothetical molecules, providing high resolution structures in addition to a mechanistic, dynamic, kinetic, and thermodynamic characterization. Here, we employ potential of mean force (PMF) calculations obtained from guided metadynamics simulations to characterize the 1:1 inclusion complexes between four different modified βCDs, with different type, number, and location of substitutions, and two sterol molecules (cholesterol and 7-ketocholesterol). Our methods, validated for reproducibility through four independent repeated simulations per system and different post processing techniques, offer new insights into the formation and stability of CD-sterol inclusion complexes. A systematic distinct orientation preference where the sterol tail projects from the CD's larger face and significant impacts of CD substitutions on binding are observed. Notably, sampling only the CD cavity's wide face during simulations yielded comparable binding energies to full-cavity sampling, but in less time and with reduced statistical uncertainty, suggesting a more efficient approach. Bridging computational methods with complex molecular interactions, our research enables predictive CD designs for diverse applications. Moreover, the high reproducibility, sensitivity, and cost-effectiveness of the studied methods pave the way for extensive studies of massive CD-ligand combinations, enabling AI algorithm training and automated molecular design.

Quantifying the Properties of Nonproductive Attempts at Thermally Activated Energy-Barrier Crossing through Direct Observation

Thermally activated energy-barrier crossing is ubiquitous in physical, chemical, and biological processes. Most barrier-crossing attempts have insufficient energy to overcome the barrier; hence, productive transition paths that successfully cross the barrier are very rare compared to nonproductive fluctuations that enter the barrier region but return without crossing it. Recent experimental advances have yielded important insights into transition paths, but nonproductive attempts remain little studied experimentally or theoretically, even though they can reveal information about parts of the reaction energy landscape not visited during transition paths. Observing the diffusive dynamics of a bead hopping between bistable optical traps as a model system, we measured the duration, maximum position along the reaction coordinate, and occupancy statistics of unsuccessful crossing attempts. Experimental results agreed quantitatively with expectations of an analytical framework we derived from committor theory. Applying these analyses to a more complex example, DNA hairpin folding under tension, we found that some properties differed from those of transition paths, such as the asymmetric occupancies for folding and unfolding attempts, whereas others were similar, such as the diffusion coefficient reflecting landscape roughness. These results show how nonproductive crossing attempts can be detected and analyzed rigorously, enabling characterization of the full dynamics within the transition region. Published by the American Physical Society 2024

Real-time study of spatio-temporal dynamics (4D) of physiological activities in alive biological specimens with different FOVs and resolutions simultaneously

This article reports the development of a microscopy imaging system that gives feasibility for studying spatio-temporal dynamics of physiological activities of alive biological specimens (over entire volume not only for a particular section, i.e., in 4D). The imaging technology facilitates to obtain two image frames of a section of the larger specimen (∼mm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim \ ext {mm}$$\\end{document}) with different FOVs at different resolutions or magnifications simultaneously in real-time (in addition to recovery of 3D (volume) information). Again, this imaging system addresses the longstanding challenges of housing multiple light sources (6 at the maximum till date) in microscopy (in general) and light sheet fluorescence microscopy (LSFM) (in particular), by using a tuneable pulsed laser source (with an operating wavelength in the range ∼420\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 420$$\\end{document}–670 nm) in contrast to the conventional CW laser source being adopted for inducing photo-excitation of tagged fluorophores. In the present study, we employ four wavelengths (∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} 488 nm, 585 nm, 590 nm, and 594 nm). Our study also demonstrates quantitative characterization of spatio-temporal dynamics (velocity—both amplitude and direction) of organelles (mitochondria) and their mutual correlationships. Mitochondria close to the nucleus (or in clustered cells) are observed to possess a lower degree of freedom in comparison to that at the cellular periphery (or isolated cells). In addition, the study demonstrates real-time observation and recording of the development and growth of all tracheal branches during the entire period (∼95\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 95$$\\end{document} min) of embryonic development (Drosophila). The experimental results—with experiments being conducted in various and diversified biological specimens (Drosophila melanogaster, mouse embryo, and HeLa cells)—demonstrate that the study is of great scientific impact both from the aspects of technology and biological sciences.

Parametric Amplification of Acoustically Actuated Micro Beams Using Fringing Electrostatic Fields.

We report on theoretical and experimental investigation of parametric amplification of acoustically excited vibrations in micromachined single-crystal silicon cantilevers electrostatically actuated by fringing fields. The device dynamics are analyzed using the Mathieu-Duffing equation, obtained using the Galerkin order reduction technique. Our experimental results show that omnidirectional acoustic pressure used as a noncontact source for linear harmonic driving is a convenient and versatile tool for the mechanical dynamic characterization of unpackaged, nonintegrated microstructures. The fringing field's electrostatic actuation allows for efficient parametric amplification of an acoustic signal. The suggested amplification approach may have applications in a wide variety of micromechanical devices, including resonant sensors, microphones and microphone arrays, and hearing aids. It can be used also for upward frequency tuning.

Characterization of the benthic biogeochemical dynamics after flood events in the Rhône River prodelta: a data–model approach

Abstract. At the land–sea interface, the benthic carbon cycle is strongly influenced by the export of terrigenous particulate material across the river–ocean continuum. Episodic flood events delivering massive sedimentary materials can occur, but their short-term impact on carbon cycling is poorly understood. In this paper, we use a coupled data–model approach to estimate the temporal variations in sediment–water fluxes, biogeochemical pathways and their reaction rates during these abrupt phenomena. We studied one episodic depositional event in the vicinity of the Rhône River mouth (NW Mediterranean Sea) during the fall–winter of 2021/22. The distributions of dissolved inorganic carbon (DIC), sulfate (SO42-) and methane (CH4) were measured in sediment porewaters collected every 2 weeks before and after the deposition of a 25 cm sediment layer during the main winter flood event. Significant changes in the distribution of DIC, SO42- and CH4 concentrations were observed in the sediment porewaters. The use of an early diagenetic model (FESDIA) to calculate biogeochemical reaction rates and fluxes revealed that this type of flood event can increase the total organic carbon mineralization rate in the sediment by 75 % a few days after deposition. In this period, sulfate reduction is the main process contributing to the increase in total mineralization relative to non-flood deposition. The model predicts a short-term decrease in the DIC flux out of the sediment from 100 to 55 mmolm-2d-1 after the deposition of the new sediment layer with a longer-term increase by 4 %, therefore implying an initial internal storage of DIC in the newly deposited layer and a slow release over relaxation of the system. Furthermore, examination of the stoichiometric ratios of DIC and SO42- as well as model output over this 5-month window shows a decoupling between the two modes of sulfate reduction following the deposition – organoclastic sulfate reduction (OSR) intensified in the newly deposited layer below the sediment surface, whereas anaerobic oxidation of methane (AOM) intensified at depth below the former buried surface. The bifurcation depth of sulfate reduction pathways, i.e., the sulfate–methane transition zone (SMTZ), is shifted deeper by 25 cm in the sediment column following the flood deposition. Our findings highlight the significance of short-term transient biogeochemical processes at the seafloor and provide new insights into the benthic carbon cycle in the coastal ocean.

Tailored laser beam shapes for welding of copper using green laser radiation

AbstractThe rapid development of laser beam sources and adapted welding technologies in recent years lead to an increased use of laser welding techniques in automated production nowadays. Especially its precision and local energy input are key features for joining applications in electric vehicle components, where joints have to meet both mechanical and electrical requirements as current-carrying connections. However, the copper materials used are difficult to weld due to their physical properties, making a stable process with fewest seam imperfections only feasible within a limited process window. Recently available beam sources emitting visible laser radiation have proven to overcome the low absorptivity at process start, but spattering is still a prone defect significantly affecting process efficiency and quality. Literature approaches for modifying the energy input point to laser beam shaping as a method for reducing process imperfections, which, however, has not been extensively researched in copper processing using green laser radiation.Thus, this study investigates the influence of a shaped intensity profile for visible laser radiation created with a reflective diffractive optical element in laser beam welding with laser powers up to 3 kW. A characterization of the process dynamics is performed by use of high-speed imaging, and metallographic analysis is used to elaborate benefits of the applied beam shapes. With beam shaping, an enlarged heat conduction welding regime and an advantageous seam shape are found. Furthermore, a decrease in spatter formation during deep penetration welding is detected for the elliptical beam profile, which correlates with an oscillation movement of the capillary.

Characterization of Market and Labor Dynamics of the Local Mango Industry in Island Garden City of Samal (IGaCoS), Davao del Norte, Philippines

Understanding the inherent characteristics of a local agricultural industry is imperative in designing policies that are responsive to the context, needs, and challenges of its stakeholders. Grounded in this premise, this study unpacked the complexities of the mango industry in the Island Garden City of Samal, an agricultural city in the southern Philippines. Specifically, it aims to understand its labor dynamics and market arrangements using a qualitative approach. This study presents an overview of the mango production cycle in the garden city, which includes the corresponding labor requirements and market of the local mango industry. In terms of labor, aside from the quantity and quality of labor needed, this paper also presents the roles of men and women that are inherent in local mango production. Likewise, the study also enumerates the different issues and challenges faced by the local mango producers. These issues and challenges were concerns related to erratic prices, labor needs, and high production costs. Moreover, the study offers explanations for the existing labor dynamics in the garden city. This includes the interplay between the material nature of the commodity and the gender dynamics in the labor force. In addition, a discussion on the varying quality standards of different target markers is also provided. Finally, this study also explained the rationale behind the prevailing contractual arrangements within the local mango industry. The results presented in this paper offer insights into designing context-based programs and policies, which could further support the local mango industry.

Advancing PetroChina’s Development Strategies for Low-Permeability Oil Reservoirs

Based on PetroChina’s status and situation of low-permeability oil reservoir development, this paper analyzes the key common issues in the production capacity construction of new oilfields, the stable production of old oilfields, and enhanced oil recovery, and, in connection with the progress made in major development technologies and the results of major development tests for low-permeability oil reservoirs in recent years, puts forward the technical countermeasures and development directions. For optimizing the development of low-grade reserves, a comprehensive life-cycle development plan is essential, alongside experimenting with gas injection and energy supplementation in new fields. Addressing challenges in reservoir classification, multidisciplinary sweet spot prediction, and displacement–imbibition processes can significantly boost well productivity. In fine water flooding reservoirs, the focus should shift to resolving key technological challenges like dynamic heterogeneity characterization, and functional and nano-intelligent water flooding. For EOR, accelerating the application of carbon capture, utilization, and storage (CCUS) advancements, along with air injection thermal miscible flooding, and middle-phase microemulsion flooding, is crucial. This approach aims to substantially enhance recovery and establish a new model of integrated secondary and tertiary recovery methods.

Back‐End‐of‐Line Integration of Synaptic Weights using HfO2/ZrO2Nanolaminates

AbstractIn artificial neural networks, the “synaptic weights” connecting the neurons are adjusted during the training. Beyond silicon, functionalizing the back‐end‐of‐line (BEOL) of CMOS circuits with novel materials is a key enabler for deploying neural network accelerators. The hardware implementation of the synaptic weights requires linear and reprogrammable resistive elements. In ferroelectric tunnel junctions, the resistance is programmed by controlling the configuration of the ferroelectric domains with electrical pulses. From ferroelectric HfZrO4to HfO2–ZrO2nanolaminates (NL), the crystallization temperature lowers below the upper limit of 400 °C required for CMOS BEOL. The device footprint is reduced, and the maximum‐to‐minimum conductance ratio increases from 7 to 32. Operated with pulses in the ultra‐fast (20 ns) and biological (500 µs) timescales, the synaptic plasticity exhibits several regimes. Dynamic hysteresis mode characterization after up to 1011switching cycles indicates the coexistence of ferroelectric and non‐ferroelectric effects such as defect rearrangement. Temperature‐dependent transport measurements in the Ohmic (linear) regime support these conclusions. Multi‐level resistive switching is achieved in HfO2–ZrO2NL co‐integrated to CMOS in the BEOL. 1T‐1R operation is demonstrated, paving the way for hardware implementation of synaptic weights for in‐memory neuromorphic computing.

Characterization of spatio-temporal dynamics of the constrained network of the filamentous fungus Podospora anserina using a geomatics-based approach.

In their natural environment, fungi are subjected to a wide variety of environmental stresses which they must cope with by constantly adapting the architecture of their growing network. In this work, our objective was to finely characterize the thallus development of the filamentous fungus Podospora anserina subjected to different constraints that are simple to implement in vitro and that can be considered as relevant environmental stresses, such as a nutrient-poor environment or non-optimal temperatures. At the Petri dish scale, the observations showed that the fungal thallus is differentially affected (thallus diameter, mycelium aspect) according to the stresses but these observations remain qualitative. At the hyphal scale, we showed that the extraction of the usual quantities (i.e. apex, node, length) does not allow to distinguish the different thallus under stress, these quantities being globally affected by the application of a stress in comparison with a thallus having grown under optimal conditions. Thanks to an original geomatics-based approach based on the use of automatized Geographic Information System (GIS) tools, we were able to produce maps and metrics characterizing the growth dynamics of the networks and then to highlight some very different dynamics of network densification according to the applied stresses. The fungal thallus is then considered as a map and we are no longer interested in the quantity of material (hyphae) produced but in the empty spaces between the hyphae, the intra-thallus surfaces. This study contributes to a better understanding of how filamentous fungi adapt the growth and densification of their network to potentially adverse environmental changes.

Characterization of droplet impact dynamics onto a stationary solid torus

The impingement mechanism of a liquid droplet on a solid torus surface is demonstrated using numerical simulations and an analytical approach. A computational model employing the volume of fluid method is developed to conduct simulations for the present investigation. Several influencing parameters, namely, diameter ratio (Dt/Do), contact angle (θ), initial droplet velocity (described by Weber number, We), surface tension (specified by Bond number, Bo), and viscosity of liquid drop (described by Ohnesorge number, Oh) are employed to characterize the impacting dynamics of a water drop onto a stationary toroidal substrate. The pattern of temporal and maximum deformation factors is elaborated by considering various relevant influencing factors to describe the fluidic behavior of the drop impingement mechanism. The key findings indicate that the developed central film gets ruptured at the early stage when the value of Dt/Do is lower because a relatively thin film is developed. Concomitantly, the very tiny drops get pinched off at Dt/Do= 0.83, whereas the detached drops are relatively large-sized in the case of lower Dt/Do= 0.16 due to the higher drainage rate of liquid mass through the hole at lower Dt/Do. It is also revealed that the first pinch-off is found to be faster with the continual upsurge of We for a specific value of Dt/Do and θ. Aside from that, efforts are made to show a scattered regime map in order to differentiate the pattern of droplet configuration during impingement. We have also attempted to establish a correlation that effectively characterizes the maximum deformation factor, which closely matches with the numerical findings. The developed correlation exhibits a firm agreement with the numerical data within deviations of 8.5%. Finally, an analytical framework is formulated to predict the deformations factor, which closely agrees with the computational findings.

Kinetic characterization of biomolecular hydrogel dynamics

Kinetic characterization of biomolecular hydrogel dynamics