Dynamic Characterization Research Articles

Sodium dodecyl sulphate-treated nanohydroxyapatite as an efficient shale stabilizer for water-based drilling fluids

Drilling water-sensitive shale formations often leads to wellbore instability, resulting in drilling problems because of the clay's high-water affinity. To solve this problem, different nanoparticles (NPs), such as nanosilica, have been used to formulate water-based muds with potassium chloride (KCl-WBM). Nevertheless, the unmatched pore size of shale pores when using nanosilica fails to completely prevent shale swelling and dispersion. This study discusses the effects of KCl-WBM with sodium dodecyl sulphate-treated nanohydroxyapatite (nHAp/SDS) on shale swelling inhibition through various laboratory techniques. These techniques encompass the linear swell meter (LSM), the dynamic linear swell meter (DLSM), hot-rolling dispersion, suspension stability, and pore structure characterization of shale. The rheological and filtration characteristics of nHAp/SDS and compatibility tests were also studied, and the results were compared with those of nanosilica and KCl-WBM. At all concentrations, the performance of the nHAp/SDS test fluids surpassed that of nanosilica. When compared with KCl-WBM system at 10 cP and 25 °C, the nHAp/SDS and nanosilica concentrations increased the plastic viscosity by 20–90 % and 10–70 %, respectively. The inhibitory effect of nHAp/SDS surpasses that of conventional KCl-WBM and inorganic nanosilica. By adding 2.0 wt% nHAp/SDS to KCl-WBM, the shale swelling decreased from 10.1 to 4.7 % (a 53.4 % reduction). Nanosilica also reduced the swelling to 6.1 % (a 39.6 % reduction) during the LSM test at 25 °C. Under the DLSM test conditions, the shale swelling increased due to the activation of the clay platelet site at an increased temperature of 80 °C. For instance, between 25 and 80 °C, the DLSM test revealed that the shale plug height expanded from 6.1 to 9.8 % for 2.0 wt% nanosilica, 4.7–7.6 % for 2.0 wt% nHAp/SDS, and 10.1–18.8 % for KCl-WBM. Furthermore, the recovery rate of hot-rolled shale plugs with KCl-WBM increased from 89.8 to 96.2 % for nHAp/SDS and 76.6 to 88.8 % for nanosilica from the initial rates of 52.1–63.3 % between 65 and 120 °C. The contact angle results showed that nHAp/SDS is hydrophobic, reducing shale-water attraction. Moreover, the 12 nm nanosilica matches nanopore sizes to partially block shale pores. This research found that nHAp/SDS has the potential to improve wellbore stability.

Data-driven excavation trajectory planning for unmanned mining excavator

In autonomous mining scenarios, excavation trajectory planning plays a significant role since it considerably influences the working performance of the unmanned mining excavator (UME). Aiming at the limited dynamical characterization of traditional theoretical methods that yield unsatisfactory performance in trajectory planning, herein we propose a data-driven excavation trajectory planning framework based on deep learning for improving the operation performance in autonomous excavation scenarios. First, the actual sensing data is collected, and a temporal convolutional recurrent neural network (TCRNN) combining stacked dilated convolutions with an attention-based sequence to sequence (Seq2Seq) module is proposed to predict the digging force accurately. Then, the surrounding material profile is perceived based on Lidar, and a polynomial response surface is performed to point cloud reconstruction. Considering mining efficiency, energy consumption and stability in the excavation process, a multi-objective function is constructed, and a data-driven excavation trajectory planning framework based on TCRNN is established. To obtain the accurate solution of the planning framework, a discretization strategy based on Radau pseudospectral method is developed to model solving to ensure the working performance in autonomous mining. An actual unmanned prototype experiment is performed to investigate the performance of the proposed framework. The results demonstrate the effectiveness and superiority of the proposed framework.

Rupture of thin nematic walls between isotropic droplets of the same mesogenic material

ABSTRACT We prepared isotropic droplets surrounded by nematic fringes in smectic A freely suspended films. During their coalescence, a thin nematic film is formed that acts as a barrier and separates the isotropic cores of these droplets. This film ruptures in the course of the droplet merging process. The observation of the film dynamics provides an exceptional opportunity to study the rupture of a thin liquid barrier embedded in a surrounding viscous liquid. A detailed dynamic characterisation of the nematic walls is performed. Qualitatively similar observations have been reported in 3D for oil drops coalescing in water and vice versa, where the rupture of an intermediate thin fluid film retards the merging process. The peculiarity of the system reported here is that the material of the droplets and the membrane is identical.

Bichromatic tetraphasic full-field optical coherence microscopy.

Full-field optical coherence microscopy (FF-OCM) is a prevalent technique for backscattering and phase imaging with epi-detection. Traditional methods have two limitations: suboptimal utilization of functional information about the sample and complicated optical design with several moving parts for phase contrast. We report an OCM setup capable of generating dynamic intensity, phase, and pseudo-spectroscopic contrast with single-shot full-field video-rate imaging called bichromatic tetraphasic (BiTe) full-field OCM with no moving parts. BiTe OCM resourcefully uses the phase-shifting properties of anti-reflection (AR) coatings outside the rated bandwidths to create four unique phase shifts, which are detected with two emission filters for spectroscopic contrast. BiTe OCM overcomes the disadvantages of previous FF-OCM setup techniques by capturing both the intensity and phase profiles without any artifacts or speckle noise for imaging scattering samples in three-dimensional (3D). BiTe OCM also utilizes the raw data effectively to generate three complementary contrasts: intensity, phase, and color. We demonstrate BiTe OCM to observe cellular dynamics, image live, and moving micro-animals in 3D, capture the spectroscopic hemodynamics of scattering tissues along with dynamic intensity and phase profiles, and image the microstructure of fall foliage with two different colors. BiTe OCM can maximize the information efficiency of FF-OCM while maintaining overall simplicity in design for quantitative, dynamic, and spectroscopic characterization of biological samples.

Crocin-Phospholipid Complex: Molecular Docking, Molecular Dynamics Simulation, Preparation, Characterization, and Antioxidant Activity.

Crocin is a water-soluble carotenoid compound present in saffron (Crocus sativus L.), known for its wide range of pharmacological activities, including cardioprotective, hepatoprotective, anti-tumorigenic, anti-atherosclerosis, and anti-inflammatory effects. The instability of crocin, its low miscibility with oils, and poor bioavailability pose challenges for its pharmaceutical applications. This study aimed to design and prepare a crocin-phospholipid complex (CPC) and assess its physicochemical properties. The study investigated the formation of the complex and its binding affinity through molecular docking. Molecular dynamics (MD) simulations were conducted to find the optimal molar ratio of crocin to phospholipid for the complex's preparation. The CPC was produced using the solvent evaporation method. Techniques such as X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FE-SEM), nuclear magnetic resonance (NMR), and solubility studies were utilized to characterize and confirm the formation of CPC. Additionally, the in vitro antioxidant activity of crocin and CPC was evaluated. Molecular dynamic simulations explored molar ratios of 1: 1, 1: 1.5, and 1: 2 for crocin to phospholipid. The ratio of 1: 2 was found to be the most stable, exhibiting the highest probability of hydrogen bond formation. Molecular docking, FTIR, and NMR studies indicated hydrogen bond interactions between crocin and phospholipid, confirming CPC's formation. XRD and FE-SEM analyses showed a decrease in crocin's crystallinity within the phospholipid complex. Furthermore, the solubility of crocin in n-octanol was enhanced post-complexation, indicating an increase in crocin's lipophilic nature. Phospholipid complexation emerges as a promising technique for enhancing the physicochemical characteristics of crocin.

Characterization of dynamics and heat transfer in electro-spray at elevated flow rates

The advancement of semiconductor and microelectronics technologies has underscored the increasing importance of efficient heat management in electronic devices. To overcome the shortcoming of low flow rates of electro-spray, the present study is motivated by using visualization and heat transfer performance experiments to reveal the morphology evolution and heat transfer characteristics of electro-sprays with high flow rates. The results indicate that the morphology of electro-sprays is closely related to the electric field intensity and the flow rate, and can be classified into six modes: dripping mode, spindle mode, cone jet mode, multi-cone jet mode, simple jet mode, and oscillating jet mode. Furthermore, the formation mechanisms and transition rules of these modes are discussed in detail. In addition, the effects of the flow rate, voltage, and spray morphology on the heat transfer performance of electro-sprays was investigated, and strategies for enhancing heat transfer were subsequently proposes. At a flow rate is 800 ml/h and an applied voltage is 6 KV, the critical heat flux (CHF) can reach 100.8 W/cm2, and the maximum heat transfer coefficient (hmax) can reach 14416.55 W/m2K. This study not only enhances the comprehension of high flow rate electro-spray technology, but serves as a vital reference for the design and application of electro-spray cooling devices.

Thermal and dynamic characterization of a multi-jet system with different geometry diffusers

This paper proposed to use the impinging jets mixing process to improve the quality of residential heating and air conditioning. The main objective is to meet the requirements of occupants in terms of thermal comfort and air quality by proposing an optimal solution for the thermal homogenization improvement in the rooms by changing of the diffusers geometry and their arrangement in the ventilation and air-conditioning devices in blowing systems. This study involves both experimental and numerical studies of a three diffusers configurations composed of four peripheral jet with similar geometries and a central jet with a different geometry. All the configurations consist of four equidistant peripheral swirling jets, only the central jet that makes the difference between them. The configuration 1 includes a swirling central jet, on the other hand a circular central jet for the configuration 2 and finally a lobed central jet for configuration 3. The velocity and temperature distributions of the three configurations are investigated experimentally and numerically. Experimentally, the multifunction thermo-anemometer have been used to measure flow temperature and velocity. The dynamic and temperature features are more radially spread and get better homogeneity in configuration 3 and this is due to the energy distribution on the radial plane, which is relatively better than configuration 1 and configuration 2. The second part deals with numerical predictions of the dynamics and thermal fields of the three configurations considered. The study was realized using a RANS-based turbulence model. The numerical results are in reasonable agreement with our experiments for the three configurations. With this study, detailed information on the structure of the resulting flow is very useful to deepen the understanding of the physics of jet interaction and to validate turbulence models. The turbulence simulation is realized by the k-ω-SST model. This model gives a satisfactorily predicts the axial drop in velocity and temperature over the entire study range, demonstrating its ability to handle the interaction between swirling and lobe jets. Our results show that the geometry of the central diffuser is essential. This allows the axial velocity to decrease faster than configurations 1 and 2. This increases lateral diffusion, resulting in better homogenization.

Starfysh integrates spatial transcriptomic and histologic data to reveal heterogeneous tumor-immune hubs.

Spatially resolved gene expression profiling provides insight into tissue organization and cell-cell crosstalk; however, sequencing-based spatial transcriptomics (ST) lacks single-cell resolution. Current ST analysis methods require single-cell RNA sequencing data as a reference for rigorous interpretation of cell states, mostly do not use associated histology images and are not capable of inferring shared neighborhoods across multiple tissues. Here we present Starfysh, a computational toolbox using a deep generative model that incorporates archetypal analysis and any known cell type markers to characterize known or new tissue-specific cell states without a single-cell reference. Starfysh improves the characterization of spatial dynamics in complex tissues using histology images and enables the comparison of niches as spatial hubs across tissues. Integrative analysis of primary estrogen receptor (ER)-positive breast cancer, triple-negative breast cancer (TNBC) and metaplastic breast cancer (MBC) tissues led to the identification of spatial hubs with patient- and disease-specific cell type compositions and revealed metabolic reprogramming shaping immunosuppressive hubs in aggressive MBC.

Unveiling dynamics changes: Singular spectrum analysis-based method for detecting concept drift in industrial data streams

Industrial data streams frequently experience concept drifts. Current drift detection methods, focusing on prediction performance or data distribution, often neglect temporal dependencies and require prior distribution assumptions. These limitations have catalyzed the development of dynamic theory-based approaches that identify drifts by discerning variations in data dynamics. However, the majority of these exhibit high complexity in dynamics characterization and still underperform in industrial drift detection. To overcome these challenges, we propose a singular spectrum analysis-based drift detection method for industry data streams, comprising three modules: common dynamics extraction, noise-robust drift detection, and threshold adaptation. Our approach uses singular spectrum analysis (SSA) as the dynamics representation method instead of traditional high-dimensional phase space embedding and Fourier transform. SSA allows for the efficient description of principal dynamics by intelligently mixing the Fourier basis functions according to given data. The first two modules are specifically engineered to address the common dynamics and stochastic noise inherent in industrial data streams through a well-designed online common dynamics extraction algorithm and a noise-robust detection index respectively. Threshold adaptation module provides a more reasonable way of updating the drift threshold based on the extreme value theory, ensuring global consistency for parameter estimation of extreme value distribution. Our proposed method was tested on simulated examples and a real-world sintering process, exhibiting enhanced drift detection performance.

Unraveling the rapid ion migration in perovskite solar cells by circuit-switched transient photoelectric technique.

Ion migration activated by illumination is a critical factor responsible for the performance decline and stability degradation of perovskite solar cells (PSCs). While ion migration has been widely believed to be much slower than charge transport, recent research suggests that, despite the lack of understanding of the mechanism, it may also be involved in a series of rapid photoelectric responses of PSCs. Here, we report an improved circuit-switched transient photoelectric technique with nanosecond temporal resolution, which enables quantitative characterization of ion migration dynamics in PSCs across a fairly broad time window. Specifically, ion migration occurring within microseconds after illumination (corresponding to a diffusion length of ∼10-7cm) is unambiguously identified. In conjunction with the composition engineering protocol, we justify that it arises from the short-range migration of halide anions and organic cations around the contact/perovskite interface. The rapid ion migration kinetics revealed in this work strongly complement the well-established ion migration model, which offers new insights into the mechanism of ion-carrier interaction in PSC devices.

Dynamic Mechanical and Biological Characterization of New 3D-Printed Polymeric Dental Materials: A Preliminary Study

The literature shows evidence of the mechanical investigation of numerous polymeric dental biomaterials using a static approach. A more representative mechanical analysis of such materials must take into account the dynamic masticatory load of the oral cavity. The aim of this work is to study the dynamic mechanical proprieties and provide an in vitro characterization of 11 3D-printed new dental biomaterials to understand their clinical applications under physiological conditions. The analysis included Dynamical Mechanical Analysis (DMA) and an MTT cytotoxicity assay. The mechanical results at low frequencies (1–11 Hz) show high uncertainty, less fragility, and less strength. The biological results show a significant reduction in cell viability (p < 0.01) at both the 3 and 24 h timepoints, with a degree of recovery observed at 24 h. To assess the clinical potential of dental biomaterials, it is necessary to determine whether there are good dynamic mechanical properties and reduced adverse biological effects on oral cells. This may allow for the facile fabrication via 3D printing of prosthetic devices that can support masticatory loads over long periods of time. Further investigations of the presented polymeric materials are needed, exploring biological assessments for longer than 24 h.

Framing Morals: A Study of Moral Values in Netflix Teen Movie Finding Ohana (2021)

In an era when Netflix is the go-to source of entertainment, many families are particular about choosing the best entertainment for them, especially for their children, that serves both entertainment and educational purposes. Movies are frequently infused with moral messages. Movies also depict and suspect morally virtuous behavior through their exploration of overarching themes, the attribution of specific traits to heroic and villainous characters, and the resolution of pivotal moral dilemmas. This study utilizes a descriptive qualitative approach of moral values found in the attribution of theme and characterization of Netflix’s teen movie Finding ‘Ohana (2021) We argue the attribution of themes and dynamic characterization of the main characters in Finding ‘Ohana (2021) that serves as a learning opportunity for young viewers to discover moral values lessons. As a result, the portrayal of moral values in Finding ‘Ohana includes truthfulness, respect, tolerance and cooperation, hard work and functionalism, respect for human life and dignity of persons, and value of the present. We propose that utilizing movies as tools for moral education, treating them as case studies of moral dilemmas, and stimulating imaginative thinking about ethical situations through open and egalitarian discussions between adults and teenagers could enhance the effectiveness of moral education for teenagers.
 Keywords: moral values, film, finding ‘Ohana, identity, children and YA literatures

The role of intermediaries in derivatives markets: Evidence from VIX options

Consistent with models of intermediaries who absorb demand pressure from end-users and respond by changing prices, net option demand is positively related to option prices in the market for VIX puts and calls. VIX and SPX option markets are integrated: market-makers absorb end-users’ net long volatility positions and net demand affects prices across markets. Net demand changes in the most liquid markets result in spillover effects between the VIX and SPX markets. A dynamic characterization of prices and net demand suggests that VIX option markets and the SPX put market are integrated, while the SPX call market is more segregated.

A Generalized Method for Dynamic Fracture Characterization Using Two-Phase Rate Transient Analysis of Flowback and Production Data

Summary This study presents a comprehensive method for characterizing reservoir properties and hydraulic fracture (HF) closure dynamics using the rate transient analysis of flowback and production data. The proposed method includes straightline analysis (SLA), type-curve analysis (TCA), and model history matching (MHM), which are developed for scenarios of two-phase flow in fracture, stimulated reservoir volume (SRV), and nonstimulated reservoir volume (NSRV) domains. HF closure dynamics are characterized by two key parameters, which are pressure-dependent permeability and porosity controlled by fracture permeability modulus and compressibility. The above techniques are combined into a generalized workflow to estimate iteratively the five parameters (including four optional parameters and one fixed parameter) by reconciling data in different domains of time (single-phase water flow, two-phase flow, and hydrocarbon-dominated flow), analysis methods (SLA, TCA, and MHM), and phases (water and hydrocarbon phase). We used flowback and production data from a shale gas well in the US and a shale oil well in China to verify the practicability of the method. The analysis results of the field cases confirm the good performance of the newly developed comprehensive method and verify the accuracy in estimating the static fracture properties [initial fracture pore volume (PV) and permeability] and the HF dynamic parameters using the proposed generalized workflow. The accurate prediction of the decreasing fracture permeability and porosity, fracture permeability modulus, and compressibility demonstrates the applicability of the comprehensive method in quantifying HF dynamics. The field application results suggest a reduction of the fracture PV by 15% and 20%, and a reduction of the fracture permeability by 80% and 90% for shale gas and shale oil wells, respectively.

Research on the dynamic characterization and detection of refrigerant leakage in multi-connected air-conditioning system

Microleakage, frequently arising from aging or inadequate installation, significantly affects the performance and longevity of refrigeration systems. The presence of microleakages, while not precipitating an immediate system failure, results in the gradual deterioration of components and escalates the energy consumption within buildings. Nonetheless, identifying these microleakages through conventional methodologies poses significant challenges. This study introduced a dynamic model specifically designed for detecting microleakages in multi-connected air conditioning systems, particularly in variable refrigerant volume (VRV) systems. Experiments performed under standard operating conditions were integral to enhancing the model's accuracy and furthering its validation. The model integrates the structural and thermophysical attributes of various components, thereby addressing the issues related to data acquisition in standard VRV during instances of microleakage. The analysis of dynamic parameter shifts during system microleakage led to the generation of a comprehensive dataset, which proves invaluable for machine learning and fault detection tasks. A detection and alerting protocol is written in Python presented, chiefly anchored on pressure deviations, augmented by temperature shifts and refrigeration and heating capacities, all represented as virtual volumetric alterations. The findings indicate a delayed transmission of the leakage signal from the leakage point to the system's detection points, with the maximal delay occurring at the compressor inlet under refrigeration conditions, amounting to 239 s. Evaluation under prescribed conditions indicated variances in pressure, temperature, and refrigeration and heating capacities by up to 13.2 %, thereby validating the model's precision and reliability. The program, tested with the generated dataset, accurately identifies leakage states within an average time of 20 min. This model and detection strategy provide a new perspective on microleakage in refrigeration systems, suggesting a robust strategy for their sustained and secure operation.

Abstract B083: Single-cell and spatial transcriptomic characterization of treatment resistance and immune dynamics in high-grade serous ovarian cancer

Abstract B083: Single-cell and spatial transcriptomic characterization of treatment resistance and immune dynamics in high-grade serous ovarian cancer

Higher-order thin layer method as an efficient forward model for calculating dispersion curves of surface and Lamb waves in layered media

The thin layer method (TLM) is an effective semi-discrete numerical tool for analyzing wave motion in stratified media. The TLM can calculate the eigenvalues and eigenvectors for both propagating and decaying waves, which is essential to simulate waves near the source. The eigenvectors are particularly useful in various applications, such as estimating modal contributions, calculating synthetic seismograms, determining Green’s function, analyzing site response, and solving wave amplification problems in earthquake engineering, to name a few. In practice, most engineering applications use linear element-based TLM. However, the overall performance of TLM depends upon the type of element and the number of thin layers. The linear element TLM requires relatively thin sub-layers to obtain an accurate solution, making it computationally expensive and time-consuming. This study explores the potential of using non-linear higher-order TLM (HTLM) for forward modeling. The mathematical framework of TLM is used to formulate the generalized HTLM in determining the multimodal dispersion curve of Rayleigh, Love, and Lamb waves. The convergence and computational efficiency of different orders of HTLM have been investigated on a diverse set of published soil profiles and plate-like structures. Since non-linear interpolation functions better capture the change in displacement and stress between the layers, the findings reveal that the HTLM consistently outperforms the linear element TLM in terms of accuracy. Furthermore, the computational efficiency of different order HTLM is analyzed by comparing the total degrees of freedom and CPU time. Remarkably, higher-order HTLMs exhibit improved accuracy without increasing the computational burden, making them an attractive option for practical applications such as global search-based inversion and full spectrum inversions where fast and economical forward modeling is essential. Therefore, the HTLM will become helpful in seismic wavefield modeling, dynamic soil characterization, non-destructive evaluation methods, wave propagation analysis through waveguides, seismic site response analysis, etc.

Quantitative analysis on resistant forces at oil-surfactant-rock interfaces with dynamic wettability characterization

Adhesion of oil at rock surface plays an important role in the liberation of oil from micro-/nano-pores, especially for heavy oil that has extremely high viscosity. Although molecular dynamics simulation is widely used to study the interfacial interaction for some specific oil-water-rock systems, experimental measurements provide more realistic and reliable evidence. In this work, we propose a dynamic wettability characterization method to indirectly measure resistant forces at oil-surfactant-rock interfaces, including frictional force, wettability hysteresis force, and viscous force, which are parallel with the oil-solid interface. The adhesive force, which is normal to the oil-solid interface is calculated through measurement of work of adhesion. The results show that work of adhesion instead of contact angle can better describe the adhesion of oil at solid surface. The effect of surfactant concentration on work of adhesion is different for water-wet and oil-wet surfaces. Moreover, average viscous forces are calculated through force analysis on oil drops moving along solid surface in different surfactant environments. It is found that viscous force has a magnitude comparable to the frictional force during the movement, while the wettability hysteresis force is negligible. On the other hand, the adhesive force calculated from the work of adhesion is also comparable to the viscous force. Therefore, both the resistant forces parallel with and normal to the oil-solid interface should be minimized for the liberation of oil from rock surface. This work proposes a simple method to evaluate the wetting capability of different surfactants and measure the adhesive force between heavy oil and rock surfaces indirectly, which provides insight into the adhesion of heavy oil at rock surface and would be valuable for the development of surfactant-based oil recovery methods.

Signaling pathways and regulatory networks in quail skeletal muscle development: insights from whole transcriptome sequencing

Quail, as an advantageous avian model organism due to its compact size and short reproductive cycle, holds substantial potential for enhancing our understanding of skeletal muscle development. The quantity of skeletal muscle represents a vital economic trait in poultry production. Unraveling the molecular mechanisms governing quail skeletal muscle development is of paramount importance for optimizing meat and egg yield through selective breeding programs. However, a comprehensive characterization of the regulatory dynamics and molecular control underpinning quail skeletal muscle development remains elusive. In this study, through the application of HE staining on quail leg muscle sections, coupled with preceding fluorescence quantification PCR of markers indicative of skeletal muscle differentiation, we have delineated embryonic day 9 (E9) and embryonic day 14 (E14) as the start and ending points, respectively, of quail skeletal muscle differentiation. Then, we employed whole transcriptome sequencing to investigate the temporal expression profiles of leg muscles in quail embryos at the initiation of differentiation (E9) and upon completion of differentiation (E14). Our analysis revealed the expression patterns of 12,012 genes, 625 lncRNAs, 14,457 circRNAs, and 969 miRNAs in quail skeletal muscle samples. Differential expression analysis between the E14 and E9 groups uncovered 3,479 differentially expressed mRNAs, 124 lncRNAs, 292 circRNAs, and 154 miRNAs. Furthermore, enrichment analysis highlighted the heightened activity of signaling pathways related to skeletal muscle metabolism and intermuscular fat formation, such as the ECM-receptor interaction, focal adhesion, and PPAR signaling pathway during E14 skeletal muscle development. Conversely, the E9 stage exhibited a prevalence of pathways associated with myoblast proliferation, exemplified by cell cycle processes. Additionally, we constructed regulatory networks encompassing lncRNA‒mRNA, miRNA‒mRNA, lncRNA‒miRNA-mRNA, and circRNA-miRNA‒mRNA interactions, thus shedding light on their putative roles within quail skeletal muscle. Collectively, our findings illuminate the gene and non-coding RNA expression characteristics during quail skeletal muscle development, serving as a foundation for future investigations into the regulatory mechanisms governing non-coding RNA and quail skeletal muscle development in poultry production.

Abstract 1588 Structure, Conformational Dynamics, and Biochemical Characterization of Starch Excess4 from Zea mays

Abstract 1588 Structure, Conformational Dynamics, and Biochemical Characterization of Starch Excess4 from Zea mays