Interaction Coefficients Research Articles

Quantification of Cytokine-Induced Cell Death in Human Colonic Organoids Using Live Fluorescence Microscopy.

Intestinal epithelial cell (IEC) death is increased in patients with inflammatory bowel diseases (IBD) such as ulcerative colitis (UC) and Crohn's disease (CD). This can contribute to defects in intestinal barrier function, exacerbation of inflammation, and disease immunopathogenesis. Cytokines and death receptor ligands are partially responsible for this increase in IEC death. IBD-relevant cytokines, such as TNF-α and IFN-γ, are cytotoxic to IECs both independently and in combination. This protocol describes a simple and practical assay to quantify cytokine-induced cytotoxicity in CD patient-derived colonic organoids using a fluorescent cell death dye (SYTOX Green Nucleic Acid Stain), live fluorescence microscopy, and open-source image analysis software. We also demonstrate how to use the Bliss independence mathematical model to calculate a coefficient of perturbagen interaction (CPI) based on organoid cytotoxicity. The CPI can be used to determine if interactions between cytokine combinations or other types of perturbagens are antagonistic, additive, or synergistic. This protocol can be implemented to investigate the cytotoxic activity of cytokines and other perturbagens using patient-derived colonic organoids.

Effect of triazolium-based ionic liquid (1, 4-dimethyl- 4H-1, 2, 4-triazolium iodide) on volumetric and ultrasonic properties of binary aqueous solutions of benzamide/benzylamine: experimental and computational study

ABSTRACT In the current investigation, effect of triazolium-based ionic liquid 1, 4-Dimethyl- 4 H-1,2,4-triazolium iodide (DMTI) on volumetric and ultrasonic properties of binary aqueous solutions of benzamide/benzylamine is analysed at four equidistant temperatures and atmospheric pressure. Molecular interactions of DMTI in binary aqueous solutions of benzylamine/benzamide are also interpreted using density (ρ) and speed of sound (u) data along with FT-IR measurements. Different volumetric and ultrasonic parameters were also computed by employing the experimental values of density (ρ) and speed of sound (u), and are further used to elucidate various kinds of interactions in the ternary system. Volumetric and acoustic transfer parameters were further used for the computation of interaction coefficients (pair and triplet). To analyse the outcomes of the estimated parameters, spectroscopic and density-functional theory (DFT) investigations have also been carried out.

The SIT model parameters for interactions of carbonate compounds with sodium and potassium ions accounting for association

The current study is devoted to the determination of the SIT coefficients at 298.15 K for interactions, involving CO2(aq), HCO3−, and CO32‐, with mostly Na+ and K+ ions. The SIT model is a simple yet physically sound model for activity coefficients in aqueous solutions, that has just one parameter for each cation-anion or a dissolved gas – electrolyte interaction. Among the issues that were met for carbonate systems are the side reactions of hydrolysis and disproportionation in the carbonate solutions, that complicate the analysis of data and lead to unusually large difference, up to 9%, in the values of activity coefficients, determined in different authoritative laboratories. For Na2CO3 and K2CO3 solutions, it was necessary to take into account the reaction of formation of the ionic pair M++CO32‐=MCO3−, with the equilibrium constants β1o equal to log10β1o= 0.75 ± 0.08 for M+=Na+ and to log10β1o= 0.67 ± 0.11 for M+=K+. In all, there are values for more than 20 binary SIT interaction coefficients. All results are valid at 298.15 K, 0.1 MPa.

Study on the mechanism of freeze-thaw cycles on the shear strength of geogrid-sand interface

The geogrid-soil interface characteristic is a critical factor influencing the behavior of reinforced soil structures. In seasonal frozen regions, the shear strength of the geogrid-soil interface fluctuates periodically with temperature, necessitating consideration of freeze-thaw cycle effects during engineering design. In this study, a series of large-scale direct shear tests were conducted to investigate the geogrid-sand interface behavior under different freeze-thaw cycles. The mechanism of the evolution and variation of the geogrid-sand interaction was discussed based on test results and the associated mesoscopic analysis. The results indicate that freezing enhances the shear strength of the geogrid-sand interface, whereas freeze-thaw cycles reduce the geogrid-sand interface shear stress. The cohesion and friction angle of the geogrid-sand interface decreased as the number of freeze-thaw cycles increased, but tended to stabilize after several freeze-thaw cycles. The influence of freeze-thaw cycles on the tensile strength and elongation of the geogrid was insignificant. Internal changes in sand during freeze-thaw cycles were considered as the key issue that led to the deterioration of the geogrid-sand interface. Furthermore, considering the interface cohesion and normal stress, the influence of freeze-thaw cycles on the interaction coefficient k between geogrid and soil was analyzed, which is referable for the design and application of reinforced soil engineering in cold regions under similar conditions.

The role of product market competition and analyst attention in modulating the link between equity pledges and classification shifting

This study investigates the association between equity pledges and classification shifting earnings management in Chinese listed firms, spanning the period from 2016 to 2022. Additionally, it explores the moderating influence of product market competition (PMC) and analyst attention on this relationship. By analyzing a sample comprising 12,583 firm-year observations, several notable findings are observed. The regression results reveal a positive and statistically significant relationship between equity pledges and classification shifting earnings management (coefficient = 0.00234, p < 0.01). Moreover, this positive impact is further magnified when specifically considering downward classification shifting (coefficient = 0.00368, p < 0.01). Regarding the moderating factors, the results demonstrate a positive moderating effect of PMC on the relationship between equity pledges and classification shifting, with an interaction coefficient of 0.0165 (p < 0.01). This moderating effect is particularly pronounced in the context of downward classification shifting, with an interaction coefficient of 0.0142 (p < 0.01). Similarly, analyst attention also positively moderates the relationship, as indicated by an interaction coefficient of 0.00144 (p < 0.05), with a stronger effect observed in the case of downward classification shifting, with an interaction coefficient of 0.00329 (p < 0.01). Furthermore, additional tests reveal that leverage strengthens the aforementioned moderating effects. The three-way interaction involving debt, PMC, and equity pledges significantly influences classification shifting, with a coefficient of 0.0415 (p < 0.05). Specifically, debt exacerbates the moderating impact of competition on highly leveraged firms that engage in downward classification shifting, as evidenced by a coefficient of 0.0599 (p < 0.05). Similarly, debt reinforces the moderating role of analyst attention (coefficient = 0.00820, p < 0.05), especially for downward classification shifting (coefficient = 0.00902, p < 0.1). Propensity score matching and robustness tests validate the findings. Therefore, this research contributes to the understanding of the economic implications of equity pledge by focusing on earnings manipulation through classification shifting. It also examines this relationship within different competitive environments and external regulatory frameworks, aiming to promote the long-term viability of companies.

From Attitude to Behavior: The Effect of Residents' Food Waste Attitudes on Their Food Waste Behaviors in Shanghai.

Preventing food waste is important. Analyzing the effects of food waste attitudes on urban residents' waste production behaviors is necessary to reduce food waste. As Shanghai is a mega-city with a population of 24 million people, once food is adequately supplied, more attention is paid to the safety of food in terms of quantity, quality, and nutrition. COVID-19 gave a shock to the food supply in Shanghai, which in turn resulted in food waste behavior. The moderating effect of pandemic during the COVID-19 is one that has rarely been mentioned in previous studies. An investigation of urban residents was conducted in Shanghai. A total of 1030 valid questionnaires were collected in October 2020. This study examined the influence of food waste attitudes on food waste behavior under the moderating effects of pandemic expectations, quantity safety, quality safety, and price stability using a multivariate ordered probit model. The results show that food waste attitudes had a significant negative effect on food waste behavior at a p < 0.01 level of significance, which means that the more people feel shame about food waste, the less food waste they will have. The interaction coefficient between food waste attitudes and pandemic expectations was positive at a p < 0.1 level of significance. This paper concludes with strategies for dealing with food waste in the future.

A Divalent Metal Cation-Metabolite Interaction Model Reveals Cation Buffering and Speciation.

I present the perspective that the divalent metalome and the metabolome can be modeled as a network of chelating interactions instead of separate entities. I review progress in understanding the complex cellular environment, in particular recent contributions to modeling metabolite-Mg2+ interactions. I then demonstrate a simple extension of these strategies based approximately on intracellular Escherichia coli concentrations. This model is composed of four divalent metal cations with a range of cellular concentrations and physical properties (Mg2+, Ca2+, Mn2+, and Zn2+), eight representative metabolites, and interaction constants. I applied this model to predict the speciation of divalent metal cations between free and metabolite-chelated species. This approach reveals potentially beneficial properties, including maintenance of free divalent metal cations at biologically relevant concentrations, buffering of free divalent metal cations, and enrichment of functional metabolite-chelated species. While currently limited by available interaction coefficients, this modeling strategy can be generalized to more complex systems. In summary, biochemists should consider the potential of cellular metabolites to form chelating interactions with divalent metal cations.

Comparison of photon interaction coefficients for tumor compositions and healthy tissues simulated by Monte Carlo

This study compares interaction coefficients of photons (namely, mass attenuation, energy absorption and energy transfer coefficients) for some tumor tissues with simlar healthy tissues. Monte Carlo calculations were performed for adenoidcystic carcinoma, melanoma, rectal adenocarcinoma, sarcoma and squamous cell lung carcinoma. The simulation model involved a monoenergetic point source producing a pencil beam. Depending on the parameter under study, average flux, energy flux, or dose deposition from photons that travels in an absorber were scored in the range of 10 keV–20 MeV energy using MCNP6.1. The same model was used to compute the interaction coefficients of health tissues (namely, gastrointestinal tract-small intestine wall, lungs-parenchyma, salivary glands, skin, soft tissue (female+male)) for comparison purposes. The results showed that, depending on the contents of the tumor samples, photon interaction coefficients of a tumor may differ from those of a similar healthy tissue. This behavior was distinct, especially for energies up to 100 keV, and was attributed to the presence of relatively higher atomic number elements in the absorber.

Influence of fibre direction on the mechanical properties and artificial intelligence-based performance prediction of hybrid abaca-jute amino composites

In this study, the Hot-press method was used to create hybrid laminates using an equal amount of jute and abaca fibers with various fiber orientations [0/0/0/0/0/0, 0/45/0/0/45/0, 0/90/0/0/90/0, and +45/−45/+45/+45/−45/+45] embedded in amino resin. To assess the impact of fiber orientation on natural fiber hybrid eco-fiber composites, as per ASTM standard the tensile, flexural, impact, and ILSS tests were carried out. Additionally, conducting an in-depth statistical examination through the utilization of Machine Learning techniques like Artificial Neural Networks (ANN) to make predictions. The experimental results revealed that the voids and defects have a significant impact on composite density. (0/45/0/0/45/0)The fiber-oriented composite (Composite B) had a higher experimental density and void content than the other composites. The Composite A (0/0/0/0/0/0) outperformed other composites in terms of tensile strength, flexural load-bearing capacity, and impact strength by 5% to 29%. When compared to other composites, the Composite A fiber-oriented composite had the highest ILSS value (3.35 MPa). SEM analysis revealed a good interface between abaca-jute ecofibers and amino resin in the composite. ANN effectively predicts strengths with high R2 scores of 1, 0.98, and 0.99 for tensile, flexural, and impact strengths. The model’s interaction coefficients are close to 1, indicating strong correlative and predictive value.

Impact of NPK and Cytokinin on Growth Characteristics and Chemical Composition of Ficus Nitida Plants

Abstract The research was conducted in a greenhouse at the Department of Horticulture and Garden Engineering, College of Agriculture, University of Anbar, Ramadi City, to study the impact of NPK supplementation and CPPU cytokinin spraying on the vegetative and root growth characteristics of Ficus nitida L. The study encompassed two primary factors. The first factor comprises the NPK chemical fertilizer in four distinct concentrations: F0 (no addition), F1 (1g urea, 3g DAB, 2g potassium sulfate), F2 (2g urea, 6g DAB, 4g potassium sulfate), and F3 (3g urea, 9g DAB, 4g potassium sulfate). The second factor involves the cytokine CPPU at three concentrations: C0 (no addition), C1 (3 mg L-1), and C2 (6 mg/liter). The study was designed using a randomized complete block design (RCBD) consisting of three replications, with three pots allocated to each experimental unit. Each replicate consisted of 36 treatments, meaning the experiment contained 108 experimental units in all blocks. The results indicated a significant increase in the interaction coefficients between the study factors in plant height, leaf area, nitrogen percentage in the leaf, total chlorophyll content, root surface area, and root length.. Specifically, these parameters were measured at 21.333 cm, 30.837 cm2, 2.666%, 1.384 g, 55.223 cm2, and 13.947 cm, respectively.

Nonreciprocal collective dynamics in a mixture of phoretic Janus colloids

A multicomponent mixture of Janus colloids with distinct catalytic coats and phoretic mobilities is a promising theoretical system to explore the collective behavior arising from nonreciprocal interactions. An active colloid produces (or consumes) chemicals, self-propels, drifts along chemical gradients, and rotates its intrinsic polarity to align with a gradient. As a result the connection from microscopics to continuum theories through coarse-graining couples densities and polarization fields in unique ways. Focusing on a binary mixture, we show that these couplings render the unpatterned reference state unstable to small perturbations through a variety of instabilities including oscillatory ones which arise on crossing an exceptional point or through a Hopf bifurcation. For fast relaxation of the polar fields, they can be eliminated in favor of the density fields to obtain a microscopic realization of the Nonreciprocal Cahn–Hilliard model for two conserved species with two distinct sources of non-reciprocity, one in the interaction coefficient and the other in the interfacial tension. Our work establishes Janus colloids as a versatile model for a bottom-up approach to both scalar and polar active mixtures.

Physics-driven deep neural networks for damage identification using guided wave damage interaction coefficients

In this paper, recent advancements in the development of a guided wave-based damage identification approach using wave damage interaction coefficients (WDICs) and deep neural networks (DNNs) are presented. These WDICs uniquely describe the complex scattering of guided waves around possible damages and depend on the properties of the damage itself. Hence, they are utilized as physics-based and highly sensitive damage features herein. It is demonstrated, that DNNs can effectively learn intricate relationships between damage characteristics and complex-shaped WDIC patterns from a compact sized training dataset. In this study, two training datasets are created by numerical finite element simulations and experimental scanning laser Doppler vibrometer measurements using a pseudo-damage approach. Therefore, the orientation and thickness of surface-bonded artificial damages are varied to generate the training data of 12 selected damage scenarios. The generalization capabilities of the fully trained DNNs allow to accurately predict WDICs even for damage scenarios unseen during training. The presented damage identification method leverages this powerful ability to characterize properties of unknown damages. Once trained, the accurate DNN predictions become available promptly and can be compared with measured WDICs from an unknown damage for selected sensor positions. The performance of both simulation-based and experiment-based structural health monitoring approaches are assessed, while also addressing current limitations and possible enhancements. For example, the great potential of incorporating the phase information of the complex-valued WDICs in the identification procedure is discussed. Hence, this study highlights the latest advancements in the development of the presented damage identification method with promising results and provides valuable insights in the application of WDICs as physics-based features for DNNs.

Middle Managerial Capability, Teamwork Dan Performance: Studi Peran Leader Gender

The Republic of Indonesia Police considers the existence of women and children important, which is demonstrated by the formation of the Directorate of Women and Children Services (PPA). Empirically, female leadership in all its processes has a positive impact on organizational performance. For this reason, the concern in this research is women's leadership as an answer to the complexity of the work of the East Java Regional Police PPA. Research is urgent to be carried out, considering the high number of PPA cases for the East Java Regional Police as an effort to test the role of middle manager capability in shaping performance through teamwork, with a gender leader mechanism. The results of testing the interaction of leader gender as a moderator variable are shown by an interaction coefficient value of -0.189, with a p-value of 0.003 &lt; 0.05, thus it can be said that leader gender influences the magnitude of the influence of middle manager capability (MMC) on teamwork (TMW). It can be said that the smaller the leader's gender (female leader), the stronger the influence of middle manager capability on teamwork.

Thermodynamic parameters of L-carnosine dissolution and solvation in binary aqueous-organic mixtures at T = 298.15 K.

Isothermal calorimetry was used to measure the enthalpies of L-carnosine digestion in aqueous solutions of acetonitrile (AN) 1,4-dioxane (DO), acetone (AC), dimethyl sulfoxide (DMSO), ethanol EtOH), 1-propanol (1-PrOH), and 2-propanol (2-PrOH). The values of ΔsolH° obtained were combined with the standard enthalpies of L-carnosine sublimation to obtain the corresponding enthalpies of solvation ΔsolvH°. In addition, the enthalpic coefficients of pairwise interactions (hxy) of L-carnosine with organic solvent molecules and the enthalpy of transfer (ΔtrH°) from water in their mixture with the latter were calculated. It is established that the solvation of L-carnosine is weakened in a series of (H2O + EtOH) > (H2O + 1-PrOH) > (H2O + 2-PrOH). This may be due to an increase in the hydrophobicity of alcohols of the same order as well as the presence of CH3-groups within the alcohol molecule. The weakening of the solvation energy of L-carnosine by co-solvent molecules in a series of mixed solvents: (H2O + AN) < (H2O + AC) < (H2O + DO) < (H2O + DMSO) is associated both with an increase in the hydration energy of co-solvents in the same order and with their physicochemical properties. The enthalpic coefficients of water-organic solvent pairwise interactions were discovered to be linearly related to the corresponding coefficients of L-carnosine-organic solvent interactions. An increase in the polarity and acidity of an organic solvent increases the energy of pairwise interactions between L-carnosine and the organic solvent. Increasing the cohesion energy density, molar volume, and basicity of the organic solvent reduces the energy of the pairwise interactions between L-carnosine and the organic solvent.

Five-point superluminality bounds

We investigate how the speed of propagation of physical excitations is encoded in the coefficients of five-point interactions. This leads to a superluminality bound on scalar five-point interactions, which we present here for the first time. To substantiate our result, we also consider the case of four-point interactions for which bounds from S-matrix sum rules exist and show that these are parametrically equivalent to the bounds obtained within our analysis. Finally, we extend the discussion to a class of higher-point interactions.

Effect of solvent depletion on electrokinetic energy conversion in viscoelastic fluids

We analyze the electrokinetic energy conversion from the pressure-driven flow of viscoelastic fluids akin to dilute polymer solutions. In contrast to the previously reported results, we account for the reduced differential capacitance over the interfacial layer and the solvent-mediated non-electrostatic interactions, cumulatively represented in an extended continuum framework. We attribute a physical basis of our consideration from the perspective of the formation of a polymer-depleted layer at the channel interface, where the explicit role of the solvent appears to dictate the electromechanics–hydrodynamics coupling over the interfacial scales. By adapting a “box-model” depicting the alterations in the solvent permittivity across the interfacial layer and accommodating a non-electrostatic interaction coefficient concomitantly, the interfacial electrokinetics are coupled with the bulk flow of the polymer-rich medium using the simplified Phan-Thien–Tanner (sPTT) constitutive model. A closed-form theory is obtained that includes only two fitting parameters, namely, the span of the interfacial layer and the strength of the non-electrostatic interactions. These parameters are estimated from comprehensive molecular simulation data. The results of the investigation are analytically tractable and enable rationalizing the “electrokinetic” implications of the polymer-depleted interfacial layer and the possibility that the electrokinetic parameters can be extracted from measurements obtained from experiments. This paves the way toward optimizing the induced streaming potential for the conversion of hydraulic energy to electrical power in polymeric solutions.

Video-Based Kinematic Analysis of Movement Quality in a Phase 3 Clinical Trial of Troriluzole in Adults with Spinocerebellar Ataxia: A Post Hoc Analysis.

Traditional methods for assessing movement quality rely on subjective standardized scales and clinical expertise. This limitation creates challenges for assessing patients with spinocerebellar ataxia (SCA), in whom changes in mobility can be subtle and varied. We hypothesized that a machine learning analytic system might complement traditional clinician-rated measures of gait. Our objective was to use a video-based assessment of gait dispersion to compare the effects of troriluzole with placebo on gait quality in adults with SCA. Participants with SCA underwent gait assessment in a phase 3, double-blind, placebo-controlled trial of troriluzole (NCT03701399). Videos were processed through a deep learning pose extraction algorithm, followed by the estimation of a novel gait stability measure, the Pose Dispersion Index, quantifying the frame-by-frame symmetry, balance, and stability during natural and tandem walk tasks. The effects of troriluzole treatment were assessed in mixed linear models, participant-level grouping, and treatment group-by-visit week interaction adjusted for age, sex, baseline modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA), and time since diagnosis. From 218 randomized participants, 67 and 56 participants had interpretable videos of a tandem and natural walk attempt, respectively. At Week 48, individuals assigned to troriluzole exhibited significant (p=0.010) improvement in tandem walk Pose Dispersion Index versus placebo {adjusted interaction coefficient: 0.584 [95% confidence interval (CI) 0.137 to 1.031]}. A similar, nonsignificant trend was observed in the natural walk assessment [coefficient: 1.198 (95% CI-1.067 to 3.462)]. Further, lower baseline Pose Dispersion Index during the natural walk was significantly (p=0.041) associated with a higher risk of subsequent falls [adjusted Poisson coefficient:-0.356 [95% CI-0.697 to-0.014)]. Using this novel approach, troriluzole-treated subjects demonstrated improvement in gait as compared to placebo for the tandem walk. Machine learning applied to video-captured gait parameters can complement clinician-reported motor assessment in adults with SCA. The Pose Dispersion Index may enhance assessment in future research. TRIAL REGISTRATION-CLINICALTRIALS. NCT03701399.

Designing efficient materials for high-performance of non-fullerene organic solar cells through side-chain engineering on DBT-4F derivatives by non-fused-ring electron acceptors.

For the advancement in fields of organic and perovskite solar cells, various techniques of structural alterations are being employed on previously reported chromophores. In this study, the end-capped engineering is carried out on DBT-4F (R) by modifying terminal acceptors to improve optoelectronic and photovoltaic attributes. Seven molecules (AD1-AD7) are modeled using different push-pull acceptors. DFT/B3LYP/6-31G along with its time-dependent approach (TD-DFT) are on a payroll to investigate ground state geometries, absorption maxima (λmax), energy gap (Eg), excitation energy (Ex), internal reorganization energy, light harvesting efficiency (LHE), dielectric constant, open circuit voltage (VOC), fill factor (FF), etc. of OSCs. AD1 displayed the lowest band gap (1.76eV), highest λmax (876nm), lowest Ex (1.41eV), and lowest binding energy (0.21eV). Among various calculated parameters, all of the sketched molecules demonstrated greater dielectric constant when compared to R. The highest dielectric constant was exhibited by AD3 (56.26). AD5 exhibited maximum LHE (0.9980). Lower reorganization energies demonstrated improved charge mobility. AD5 and AD7 (1.63 and 1.68eV) have higher values of VOC than R (1.51eV). All novel molecules having outperforming attributes will be better candidates to enhance the efficacy of OSCs for future use. Precisely, a DFT and TD-DFT analysis on all of the proposed organic molecules were conducted, using the functional MPW1PW91 at 6-31G (d,p) basis set to examine their optoelectronic aspects, additionally the solvent-state computations were studied with a TD-SCF simulation. For all these simulations, Guassian 09 and GuassView 5.0 were employed. Moreover, the Origin 6.0, Multiwfn 3.8, and PyMOlyze 1.1 software were utilized for the visual depiction of the graphs of absorption, TDM, and DOS, respectively of the studied molecules. A number of crucial aspects such as FMOs, bandgaps, light-harvesting efficiency, electrostatic potential, dipole moment, ionization potential, open-circuit voltage, fill factor, binding energy, interaction coefficient, chemical hardness-softness, and electrophilicity index were also investigated for the studied molecules.

Understanding of lactobionic acid in aqueous-glycol mixtures at different temperatures: Ultrasonic investigation and spectroscopic study

The proposed investigation focused on the study of liquid mixtures that contain polyethylene glycols (PEGs) such as polyethylene glycol-200 and polyethylene glycol-400, and lactobionic acid aqueous solutions. The study aimed to examine the density and ultrasonic speed of these mixtures at different temperatures (288.15 K, 298.15 K, 308.15 K, and 318.15 K) and concentrations (0.01, 0.02 and 0.03) mol.kg-1 of lactobionic acid in aqueous medium. The experimental data obtained were used to estimate various density and sound-speed characteristics, and to calculate the apparent molar, partial molar, and transfer properties of volume and isentropic compressions, including (Vϕ, Vϕ0, ΔVϕ0 and Kϕ,s,Kϕ,s0, ΔKϕ,s0). The interaction coefficients (VAB, VABB, KAB and KABB) were determined using the values of ΔVϕ0and ΔKϕ,s0. Additionally, the study computed the limiting apparent molar expansibilities, its derivative, and empirical parameters. The findings of the study were evaluated in terms of interactions among the solutes and solvents in the liquid mixtures. Moreover, the spectroscopic study of the binary mixture of lactobionic acid and water at different their concentrations was done to find the different stretching and bonds available in the mixture.

Junction formation rates, residence times, and the rate of plastic flow in FCC metals

During plastic flow in metals, dislocations from slip systems with different glide planes collide to form junctions. After being in-residence within the dislocation network for some period of time, these junctions then break, thereby liberating the attached dislocation lines. In this work we use random forest discrete dislocation dynamics simulations to quantify the junction formation rate and junction residence time as a function of stress for all junction types in face-centered cubic metals. We then relate these quantities to the dislocation link-length distribution, which is found to exhibit an exponential form. This enables us to quantify the mean junction strength and also the slip system interaction coefficients. Finally, using the link-length model we obtain a flow rule for our systems which is physics-based with all parameters determined from DDD simulations. The insights here provide a path forward for a dislocation network theory of plastic flow based on the link-length distribution.