Dynamic Information Research Articles

Insights into the fluid dynamics of bioaerosol formation in a model respiratory tract

Bioaerosols produced within the respiratory system play an important role in respiratory disease transmission. These include infectious diseases such as common cold, influenza, tuberculosis, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among several others. It is, therefore, of immense interest to understand how bioaerosols are produced within the respiratory system. This has not been extensively investigated. The present study computationally investigates how bioaerosols are produced in a model respiratory tract due to hydrodynamic interactions between breathed air and a thin mucus layer, which lines the inner surface of the tract. It is observed that Kelvin–Helmholtz instability is established in the thin mucus layer due to associated fluid dynamics. This induces interfacial surface waves which fragment forming bioaerosols under certain conditions. A regime map is created—based on pertinent dimensionless parameters—to enable identification of such conditions. Analysis indicates that bioaerosols may be produced even under normal breathing conditions, contrary to expectations, depending on mucus rheology and thickness of the mucus layer. This is possible during medical conditions as well as during some treatment protocols. However, such bioaerosols are observed to be larger (∼O(100)μm) and are produced in less numbers (∼100), as compared to those produced under coughing conditions. Treatment protocols and therapeutic strategies may be suitably devised based on these findings.

Carbon Storage Dynamics in Lower Shimentan Formation of the Qiantang Sag, East China Sea Shelf Basin: Stratigraphy, Reservoir – Cap Analysis, and Source – Sink Compatibility

Carbon Storage Dynamics in Lower Shimentan Formation of the Qiantang Sag, East China Sea Shelf Basin: Stratigraphy, Reservoir – Cap Analysis, and Source – Sink Compatibility

Co-evolving networks for opinion and social dynamics in agent-based models.

The rise of digital social media has strengthened the coevolution of public opinions and social interactions that shape social structures and collective outcomes in increasingly complex ways. The existing literature often explores this interplay as a one-directional influence, focusing on how opinions determine social ties within adaptive networks. However, this perspective overlooks the intrinsic dynamics driving social interactions, which can significantly influence how opinions form and evolve. In this work, we address this gap, by introducing the co-evolving opinion and social dynamics using stochastic agent-based models. Agents' mobility in a social space is governed by both their social and opinion similarity with others. Similarly, the dynamics of opinion formation is driven by the opinions of agents in their social vicinity. We analyze the underlying social and opinion interaction networks and explore the mechanisms influencing the appearance of emerging phenomena, such as echo chambers and opinion consensus. To illustrate the model's potential for real-world analysis, we apply it to General Social Survey data on political identity and public opinion regarding governmental issues. Our findings highlight the model's strength in capturing the coevolution of social connections and individual opinions over time.

An automatic method for extracting sand dunes based on slope cost distance from digital elevation models

Sand dunes significantly impact climate, water resources, and human infrastructure, reflecting sand sources and wind conditions. However, their complex and heterogeneous terrain leads to fragmented and poorly continuous dune extraction results. Focusing on the Badain Jaran Desert, this study developed a sand dune extraction method using slope cost distance analysis with FABDEM data. First, positive and negative terrains were segmented using 30 m resolution digital elevation data. Next, slope patches were classified based on specific criteria: slope less than 1.5°, patch area greater than 0.01 km2, and patches entirely within negative terrains. The filtered patches served as source data, and slope raster data were used to calculate slope cost distance. Sand dunes and interdune areas were delineated based on a predefined slope cost threshold. Post-processing, such as smoothing and vector conversion, yielded the final extraction results. The method effectively extracted compound transverse megadunes and pyramid megadunes, addressing misclassification issues and accurately defining interdune areas. It demonstrated faster processing speeds compared to traditional methods, with high precision (89.38 % & 90.37 %), accuracy (96.5 % & 92.89 %), and recall (94.77 % & 98.63 %). The results are more complete and less fragmented, aiding in the extraction of micro-scale dune features and revealing macro-scale spatial patterns, which are beneficial for studying dune formation, development, and wind dynamics.

Dynamic Formation of Robot Movement Route in Nondeterministic Environment with Bypassing Stationary and Nonstationary Obstacles

Dynamic Formation of Robot Movement Route in Nondeterministic Environment with Bypassing Stationary and Nonstationary Obstacles

Structure and spin of the low- and high-spin states of Fe2+(phen)3 studied by x-ray scattering and emission spectroscopy.

The structure and spin of photoexcited Fe2+(phen)3 in water are examined by x-ray scattering and x-ray emission spectroscopy with 100 ps time resolution. Excitation of the low-spin (LS) ground state (GS) to the charge transfer state 1MLCT* leads to the formation of a high-spin (HS) state that returns to the GS in 725 ps. Density functional theory (DFT) predicts a Fe-N bond elongation in HS by 0.19 Å in agreement with the scattering data. The angle between the ligands increases by 5.4° in HS, which allows the solvent to get 0.33 Å closer to Fe in spite of the expansion of the molecule. The rise in solvent temperature from the return of photoproducts to the GS is dominated by the formation dynamics of HS, 1MLCT* → HS, which is followed by a smaller rise from the HS → GS transition. The latter agrees with the 0.61 eV energy gap E(HS)-E(LS) calculated by DFT. However, the temperature rise from the 1MLCT → HS transition is greater than expected, by a factor of 2.1, which is explained by the re-excitation of nascent HS* by the 1.2 ps pump pulse. This hypothesis is supported by optical spectroscopy measurements showing that the 1.2 ps long pump pulse activates the HS* → 5MLCT* channel, which is followed by the ultrafast return to HS* via intersystem crossing. Finally, the spins of the photoproducts are monitored by the Kβ emission and the spectra confirm that the spins of LS and HS states are 0 and 2, respectively.

Enhancing e-government in digital transformation: integrating archive management and digital solutions in Pekanbaru, Indonesia

Efficient and modern archive management is very important in this digital era, especially at the local government level. In this context, this study explores the urgency of archive management using the Integrated Dynamic Archival Information System (SRIKANDI) approach in the Pekanbaru City Government. The research method used is qualitative, with data sources from interviews, documentation, and observation and analysis using the NVivo 12 Plus software. The study's results identified challenges to SRIKANDI implementation, including inadequate technological infrastructure, the need for skilled human resources in information technology, attention to data security, changes in organizational culture, and ongoing technical support. Based on these findings, policy recommendations have been made, including investments in technology infrastructure, human resource training and development, strict data protection, and changes in organizational culture. This research has positive implications for archive management, increasing efficiency and accountability in Pekanbaru. This research provides insights for other city governments wishing to undertake similar digital transformations in electronic-based archives management

Analyst network centrality, forecast accuracy, and persistent influence

ABSTRACT This paper explores how analysts’ forecasting behaviour is related to their centrality within a dynamic information network. In this network, analysts who issued coverage reports on the same listed firms in clusters are connected. The social learning hypothesis and social capital theory suggest that financial analysts could learn from other analyst forecasts and obtain information from analyst reports. Employing a dynamic complex network methodology, we focus on analysts’ network centrality – degree, betweenness, and closeness – to represent their information access based on a sample of 819,539 analyst forecasts in the Chinese A-share market from 2018 to 2022. Our findings suggest that analysts with more central positions in the network produce more accurate earnings-per-share forecasts and have a longer persistent influence on other analysts. Our results support the perspective that the diffusion of information among analysts affects their forecasts and reporting behaviour.

Modelling of the effects of driving signal parameters on the droplet formation dynamics in piezoelectric inkjet

Piezoelectric inkjet technology has been widely adopted in various industrial applications due to its versatility and compatibility with a wide range of ink chemistries. The driving signal, pivotal in activating the piezoelectric element to expel droplets, significantly influences droplet formation dynamics. Parameters such as droplet size, velocity, breakup time, and the occurrence of satellite droplets are all influenced by the driving signal and ultimately affect the overall quality of the printing process. This paper introduces a model for drop-on-demand (DOD) droplet formation dynamics from a single nozzle employing a bipolar driving signal. The model establishes a quantitative correlation between the waveform of the driving signal and key parameters including average jetting velocity at the nozzle exit, droplet jetting frequency, and droplet volume. Furthermore, an experimental setup is developed for the calibration and validation of the proposed model. Results demonstrate a close alignment between the model predictions and experimental observations, affirming its efficacy in forecasting droplet formation behaviors based on driving signal parameters.

Heterostructure-induced enhanced persistent luminescence for low temperature applications

We report a strategy to enhance the low-temperature persistent luminescence (LT PersL) in perovskite oxides through the formation of a heterostructure, i.e. NaNbO3-LiNbO3 with Pr3+ dopants, via the defect engineering method. Prominent LT PersL was realized when the Na/Li ratio was 0.6/0.4, with the red emission still visible over 1 h after the cessation of charging at 253 K. The PersL-enhancement mechanism is elucidated with elaborate structural characterization and density functional theory calculations. The introduction of the heterostructure increased electron–hole recombination efficiency, generated long-distance photogenerated carriers, and created a pathway for successive shifts in the band structure between NaNbO3 and LiNbO3 to form shallow broad traps with broad distribution. The promising applications of these materials in dynamic information encryption and anti-counterfeiting fields at low temperatures are demonstrated.

Oxidation mechanism of the Si-X (X=HfO2, Yb2O3 or HfO2+Yb2O3) composite systems in air and water vapor at 1300 ℃

The formation rate of SiO2 during oxidation of Si bond layer is a key issue to determine the lifetime of environmental barrier coatings. The oxidation kinetics and mechanism of Si and Si-X (X=HfO2, Yb2O3 or HfO2+Yb2O3) composite systems were investigated systematically. The thickness of the SiO2 layer was greatly reduced by the dynamic formation of silicates (HfSiO4, Yb2SiO5 and Yb2Si2O7) in air and water vapor, benefiting for long-term servicing. However, the addition of HfO2 promoted the oxidation of Si with an increased total SiO2 thickness, while that of Yb2O3 not. These results provide a guidance for the design of next generation bond layers.

Multi-stage experiments in Bronze Age spear combat: insights on wear formation, trauma, and combat contexts

This paper presents and discusses an experimental investigation of Bronze Age spear combat, with a focus on the impacts of bronze points against each other and other materials such as wooden shafts and shields, and animal tissues which act as a proxy for the human body.A replicable methodology comprising of a series of interconnected experiments gradually shifting the ratio between control and actualism is presented. The results offer fresh insights into prehistoric combat dynamics and the relationship between combat style, contact material, and the formation of wear traces. A comprehensive account of the morphology and formation dynamics of the damage inflicted on weapons, skin, and bone is provided, supported by detailed photographic documentation.The experimental design permitted to assess the frequency and type of collisions that would occur in actual spear combat. Furthermore, the development and modification of wear traces over time was also observed for the first time on spear points. The tests provided further insights into the level of training and skill required to execute specific movements with different combat objectives. Potential indicators for spear use in various combat contexts, such as fighting against multiple opponents versus more controlled encounters like duels, have been identified. The wear traces produced experimentally find convincing comparisons in the archaeological record.In conclusion, the results contribute to a more detailed understanding of Bronze Age armed encounters and provide robust guidance for interpreting combat marks on archaeological copper alloy weapons and on bones.

STHKT: Spatiotemporal Knowledge Tracing with Topological Hawkes Process

Knowledge Tracing (KT) is a method that seeks to forecast students’ future performance based on their historical interactions with intelligent tutoring systems. Various KT techniques have been developed from distinct perspectives, such as probability, logic, and deep learning, to scrutinize interaction sequences. However, most current methods predominantly concentrate on temporal or structural information, considering simple question sequences or interaction sequences, but fail to describe the topological dependencies between sequences, which can lead to changes in causal structures,as referred to as dynamic structural information in the paper. The dynamic information includes the clustering effect among concepts and questions, as well as the group effect among students and questions: Questions with the same knowledge concepts tend to present increasingly similar response patterns in the sequence, and concurrently, students who answer similar questions often exhibit closer knowledge states. We introduce the STHKT method, which employs a tripartite heterogeneous graph to capture relationships among concepts, questions, and students. By incorporating temporal information through a topological graph, we employ two Graph Convolution Networks (GCNs) to model the two effects separately. Following this, we apply the Hawkes Process to introduce a spatiotemporal attention mechanism that combines both effects. Through comparative experiments, ablation studies and case studies, we validate the efficacy of key components in the model. Experiment results indicate that the STHKT model can effectively model the two major effects, integrate dynamic structural information, and to some extent improve the accuracy of predicting students’ response probabilities. It is the first time that these two effects have been considered in the process of knowledge tracing, and it is adaptable to large-scale online education platforms.

Detecting Chirality-Induced Spin Selectivity in Randomly Oriented Radical Pairs Photogenerated by Hole Transfer.

Chirality-induced spin selectivity (CISS) has the potential to control the spin dynamics of chiral molecules for applications in quantum information science. Here we investigate the effect of CISS on the spin dynamics of radical pair formation following photodriven hole transfer in a pair of donor-chiral bridge-acceptor (D-Bχ-A) enantiomers, where D = 2,2,6,6-tetramethyl[1,3]-dioxolo[4,5-f][1,3]benzodioxole, Bχ = (R)- or (S)-2,2'-dimethoxy-4,4'-diphenyl-5,5',6,6',7,7',8,8'-octahydro-1,1'-binaphthalene, and A = naphthalene-(1,4:5,8)-bis(dicarboximide). The results are compared to those obtained on the corresponding achiral D-B-A reference molecule in which B = 2″,3',5',6″-tetramethyl-1,1':4',1″:4″,1‴-quaterphenyl. Photoexcitation of A in a randomly oriented sample of D-Bχ-A in glassy butyronitrile at 85 K results in subnanosecond two-step hole transfer from 1*A to D to form D•+-Bχ-A•-, which was characterized using time-resolved electron paramagnetic resonance (TREPR) spectroscopy at X (9.6 GHz), Q (34 GHz), and W (94 GHz) bands. The spectra show line shape changes that are characteristic of a ∼38% contribution of CISS to the spin dynamics of D•+-Bχ-A•- formation. The line shape changes resulting from CISS are particularly apparent in the TREPR spectra at X-band as predicted by recent theory. These results show that (1) CISS has a significant influence on radical pair dynamics initiated by photodriven hole transfer, which is complementary to our recent electron transfer results, and (2) CISS can be detected using TREPR on radical pairs that are randomly oriented relative to an external magnetic field.

Linking feed, biodiversity, and filtration performance in a Self-Forming Dynamic Membrane BioReactor (SFD MBR) treating canning wastewater

A bench-scale self-forming dynamic membrane bioreactor (SFD MBR) treating canning wastewater showed instable filtration performance, with a worsening in correspondence of a change in the influent quality. To unveil the possible reasons for such behaviour, a microbial investigation was carried out to complement conventional filterability and settleability tests. The microbial communities of the influent wastewater, the activated sludge, and the filtering sludge cake (dynamic membrane) were characterised through metagenomic and differential abundance analyses. In parallel, the production of exopolymers was measured. The outputs indicate that under the tested conditions the canning wastewater promoted the development of a very peculiar microbial ecosystem, with a strong selection of the genus Thiothrix (relative abundance above 90 %). The Shannon index values in activated sludge were below 2, indicating a very low bacterial diversity. This may have limited the ecosystem resilience towards changes of external conditions, causing instability in the process of the dynamic membrane formation. Furthermore, the diversity analysis showed that the bacterial compositions of the feed and the sludge resulted not significantly linked to each other, confirming the main role of the chemical composition of the influent wastewater on overall process performances. When treating agro-industrial streams, in-depth feed characterisation is recommended in order to prevent the factors that may generate instability in SFD MBR performance.

Photocatalytic Edge Growth of Conductive Gold Lines On Microstructured TiO2-ITO Substrates.

Titanium dioxide is well-known for its excellent photocatalytic properties. UV-controlled photodeposition of gold on TiO2 is achieved by photocatalytic reduction of precursor ions from a tetrachloroauric solution. During the growth process on the surface, clusters grow from nucleation centers and coalescence is observed for sufficiently long UV illumination times, resulting in gold structures with complex shapes. Here, we hypothesize and demonstrate that the growth process is altered by employing an ITO sublayer below the TiO2 layer. Photocatalytic gold growth experiments on a microstructured thin film stack of 6 nm ITO and 70 nm TiO2 lead to strongly localized gold growth along the edge of the patterned area. A conductive gold line with a height of 3.8 μm is achieved along the edge of the TiO2-coated region, while gold growth on the surface of TiO2 is effectively suppressed. For substrates coated only with ITO or TiO2, no edge growth is observed. Furthermore, for an 845 nm thick TiO2 layer, either with or without ITO sublayer, gold growth on the TiO2 surface is dominant. Thus, for the effective steering of electrons to the edge, both the ITO sublayer and a sufficiently thin TiO2 layer are necessary. This modified method of photocatalytic deposition─electrons photogeneration in a thin layer, collection in a dedicated conductive sublayer, and growth by reduction at a different position─opens opportunities for localized material deposition. We are in particular aiming at extending the toolbox of neuromorphic engineering by providing a technical implementation of stimulus-controlled dynamic formation of directional conductive interlinks.

Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy of Staphylococcus aureus Biofilms.

Understanding the dynamics of biofilm formation and its elemental composition is crucial for developing effective strategies against biofilm-associated infections. In this study, we employed scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) to investigate the morphological changes and elemental compositions of Staphylococcus aureus biofilms. SEM images revealed distinct stages of biofilm development, from initial aggregation to the formation of mature and aged biofilms. EDS analysis consistently showed elevated levels of sodium (Na), oxygen (O), and phosphorus (P) in the biofilm matrix, indicating its high negative charge and the presence of anionic biopolymers. The incorporation of extracellular DNA (eDNA) into the biofilm matrix, leading to significant retention of sodium ions, underscored the importance of electrostatic interactions in biofilm formation and stability. Our findings highlight the potential of EDS analysis in quantifying elemental compositions and elucidating the role of anionic biopolymers in biofilm development.

Secure image communication based on two-layer dynamic feedback encryption and DWT information hiding.

In response to the vulnerability of image encryption techniques to chosen plaintext attacks, this paper proposes a secure image communication scheme based on two-layer dynamic feedback encryption and discrete wavelet transform (DWT) information hiding. The proposed scheme employs a plaintext correlation and intermediate ciphertext feedback mechanism, and combines chaotic systems, bit-level permutation, bilateral diffusion, and dynamic confusion to ensure the security and confidentiality of transmitted images. Firstly, a dynamically chaotic encryption sequence associated with a secure plaintext hash value is generated and utilized for the first round of bit-level permutation, bilateral diffusion, and dynamic confusion, resulting in an intermediate ciphertext image. Similarly, the characteristic values of the intermediate ciphertext image are used to generate dynamically chaotic encryption sequences associated with them. These sequences are then employed for the second round of bit-level permutation, bilateral diffusion, and dynamic confusion to gain the final ciphertext image. The ciphertext image hidden by DWT also provides efficient encryption, higher level of security and robustness to attacks. This technology offers indiscernible secret data insertion, rendering it challenging for assailants to spot or extract concealed information. By combining the proposed dynamic closed-loop feedback secure image encryption scheme based on the 2D-SLMM chaotic system with DWT-based hiding, a comprehensive and robust image encryption approach can be achieved. According to the results of theoretical research and experimental simulation, our encryption scheme has dynamic encryption effect and reliable security performance. The scheme is highly sensitive to key and plaintext, and can effectively resist various common encryption attacks and maintain good robustness. Therefore, our proposed encryption algorithm is an ideal digital image privacy protection technology, which has a wide range of practical application prospects.

Spatial-Temporal Contextual Aggregation Siamese Network for UAV Tracking

In recent years, many studies have used Siamese networks (SNs) for UAV tracking. However, there are two problems with SNs for UAV tracking. Firstly, the information sources of the SNs are the invariable template patch and the current search frame. The static template information lacks the perception of dynamic feature information flow, and the shallow feature extraction and linear sequential mapping severely limit the mining of feature expressiveness. This makes it difficult for many existing SNs to cope with the challenges of UAV tracking, such as scale variation and viewpoint change caused by the change in height and angle of the UAV, and the challenges of background clutter and occlusion caused by complex aviation backgrounds. Secondly, the SNs trackers for UAV tracking still struggle with extracting lightweight and effective features. A tracker with a heavy-weighted backbone is not welcome due to the limited computing power of the UAV platform. Therefore, we propose a lightweight spatial-temporal contextual Siamese tracking system for UAV tracking (SiamST). The proposed SiamST improves the UAV tracking performance by augmenting the horizontal spatial information and introducing vertical temporal information to the Siamese network. Specifically, a high-order multiscale spatial module is designed to extract multiscale remote high-order spatial information, and a temporal template transformer introduces temporal contextual information for dynamic template updating. The evaluation and contrast results of the proposed SiamST with many state-of-the-art trackers on three UAV benchmarks show that the proposed SiamST is efficient and lightweight.

Dynamics of metal formation upon radiation-chemical reduction of Cd2+ ions in aqueous solutions: Morphology of cadmium precipitate

The dynamics of metal formation upon radiation-chemical reduction of Cd2+ ions in aqueous solutions in the presence of НCOONa and morphology of cadmium precipitate were studied. The dynamics process and the morphology were characterized by dynamic light scattering, photon correlation spectroscopy, scanning electron microscopy, and turbidimetry. The formation of aqueous dispersions of the metal with the initial particle size of approximately 0.20 ± 0.05 μm was demonstrated. The metal particles undergo agglomeration with time; as a result, their size increases to 2–3 μm. The process completes with the formation of the precipitate. A feature of the sediment morphology is the developed structure of its surface and high porosity. The pores (from 0.5 μm to several microns) make up 80–90% of its volume. The aggregation is accelerated with an increase in the absorbed dose (amount of reduced metal) and in the concentration of salts in the solution.