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The effects of adding different amounts (0.1%–0.5%) of arabic gum (AG) or guar gum (GG), natural polysaccharides with similar molecular mass but different viscosity, on the emulsifying properties of myofibrillar protein (MP) were investigated. The results showed that both AG and GG could significantly improve the emulsifying properties of MP, and AG was more effective in improving the emulsifying activity, while GG was more conducive to the emulsion stability. Both emulsifying activity index (EAI) and emulsion stability index (ESI) initially increased and then decreased with increasing the amount of added polysaccharides, reaching maximum values when 0.3% AG or 0.2% GG was added. Both polysaccharides, especially GG, resulted in a marked reduction of the interfacial protein content. The droplet size of emulsions gradually decreased with increasing the amount of added polysaccharides, and the droplet size distribution became more uniform. When more than 0.3% GG was added, slight flocculation occurred in the emulsions. At the same concentration, GG reduced the droplet size of the emulsions compared to AG. Rheological analysis confirmed that all emulsions were pseudoplastic fluids, exhibiting weak gel properties. AG at low levels (≤ 0.3%) caused a decrease in the viscosity of the emulsions while remarkably increasing the storage modulus. In contrast, the addition of GG significantly increased the apparent viscosity and storage modulus of the emulsions. Compared with AG, the emulsion prepared with GG, with higher viscosity, exhibited greater apparent viscosity and storage modulus, which was more favorable to the emulsion stability.

Delivery riders are more vulnerable than other traffic participants, especially in vehicle-involved delivery crashes. This study aims at identifying the unobserved heterogeneities in different factors, based on 4251 vehicle-scooter-style electric bicycle (SSEB) crashes. First, some potential factors are selected from seven perspectives, and the spatiotemporal characteristics are analysed. Second, a latent class clustering method is proposed to clarify the optimal number of clusters by maximizing the heterogeneities across clusters. Third, partial proportional odds (PPO) models for the whole dataset and sub-datasets are developed to explore the heterogeneities across various clusters. Besides, marginal effects are implemented to quantify the heterogeneities. The results evidence that there are remarkable heterogeneities across different clusters, especially in riding behaviours and road conditions. Several factors only significantly affect particular clusters but not the whole dataset. The PPO models for the sub-datasets perform better in identifying the underlying heterogeneities. The results also highlight the greater roles of riding behaviours and road conditions in delivery SSEB-vehicle crashes. The top five influencing factors are running red light, using cell phones, vehicle type, reverse riding and bike lane (their maximum marginal effects exceeding +35%). The findings could support to mitigate the related crash losses. [ABSTRACT FROM AUTHOR]

Understanding detection range is a key factor for the use of acoustic telemetry in fisheries research. Lakes have strong seasonal changes in thermal stratification, as well as short-term changes due to internal seiches. These thermal gradients in lakes imply strong sound-speed gradients that can refract and diverge acoustic signals, leading to acoustic attenuation and smaller detection range. Using field-based range testing and the Bellhop acoustic model, we investigated how changes in stratification lead to changes in detection range within Hamilton Harbour, Ontario, Canada. During the summer stratified period, the detection range was less than 350 m, whereas in the isothermal fall, range was up to 500 m. Range test data from three separate field observations showed a good correlation with Bellhop predictions. Owing to the intense internal seiches in Hamilton Harbour, the stratification in the shallower littoral regions essentially switched between stratified and isothermal conditions over short timescales, which is predicted to lead to high temporal variability in detection range that must be accounted for during the analysis and interpretation of telemetry-derived data. La comprehension de la portee de detection est un aspect cle de l'utilisation de la telemetrie acoustique dans la recherche sur les peches. Les lacs presentent de fortes variations saisonnieres de leur stratification thermique, ainsi que des variations a court terme decoulant de seiches internes. Ces gradients thermiques dans les lacs sous-entendent d'importants gradients de la vitesse du son qui peuvent entrainer une refraction et une divergence des signaux acoustiques, produisant une attenuation acoustique et une reduction de la portee de detection. Nous avons examine, en utilisant des essais de portee sur le terrain et le modele acoustique Bellhop, les modifications de la portee de detection decoulant des variations de la stratification dans le port de Hamilton (Ontario, Canada). Durant la periode de stratification estivale, la portee de detection est inferieure a 350 m, alors que durant la periode d'isothermie automnale, elle peut atteindre 500 m. Les donnees d'essais de portee issues de trois observations distinctes sur le terrain montrent une bonne correlation avec les predictions du modele Bellhop. En raison des intenses seiches internes dans le port de Hamilton, la stratification dans les secteurs littoraux moins profonds alterne entre des conditions stratifiees et des conditions isothermiques sur de courtes periodes, ce qui, selon les predictions, devrait produire une grande variabilite dans le temps de la portee de detection, dont l'analyse et l'interpretation de donnees issues de la telemetrie doivent tenir compte. [Traduit par la Redaction], Introduction Acoustic telemetry is an important tool that is being used to advance and improve conservation and management of fishes in lakes and coastal regions. Acoustic telemetry enables ecologists to [...]

Polyether ether ketone (PEEK) is gaining recognition as a highly promising polymer for orthopedic implants, attributed to its exceptional biocompatibility, ease of processing, and radiation resistance. However, its long‐term in vivo application faces challenges, primarily due to suboptimal osseointegration from postimplantation inflammation and immune reactions. Consequently, biofunctionalization of PEEK implant surfaces emerges as a strategic approach to enhance osseointegration and increase the overall success rates of these implants. In our research, we engineered a multifaceted PEEK implant through the in situ integration of chitosan‐coated zinc‐doped bioactive glass nanoparticles (Zn‐BGNs). This novel fabrication imbues the implant with immunomodulatory capabilities while bolstering its osseointegration potential. The biofunctionalized PEEK composite elicited several advantageous responses; it facilitated M2 macrophage polarization, curtailed the production of inflammatory mediators, and augmented the osteogenic differentiation of bone marrow mesenchymal stem cells. The experimental findings underscore the vital and intricate role of biofunctionalized PEEK implants in preserving normal bone immunity and metabolism. This study posits that utilizing chitosan‐BGNs represents a direct and effective method for creating multifunctional implants. These implants are designed to facilitate biomineralization and immunomodulation, making them especially apt for orthopedic applications. [ABSTRACT FROM AUTHOR]

The second-order mean field games system (MFGS) in a bounded domain with the lateral Cauchy data are considered. This means that both Dirichlet and Neumann boundary data for the solution of the MFGS are given. Two Hölder stability estimates for two slightly different cases are derived. These estimates indicate how stable the solution of the MFGS is with respect to the possible noise in the lateral Cauchy data. Our stability estimates imply uniqueness. The key mathematical apparatus is the apparatus of two new Carleman estimates. [ABSTRACT FROM AUTHOR]

Pansharpening is a fundamental and crucial image processing task for many remote sensing applications, which generates a high-resolution multispectral image by fusing a low-resolution multispectral image and a high-resolution panchromatic image. Recently, vision transformers have been introduced into the pansharpening task for utilizing global contextual information. However, long-range and local dependencies modeling and multiscale feature learning are all essential to the pansharpening task. Learning and exploiting these various information raises a big challenge and limits the performance and efficiency of existing pansharpening methods. To solve this issue, we propose a pansharpening network based on multiscale embedding and dual attention transformers (MDPNet). Specifically, a multiscale embedding block is proposed to embed multiscale information of the images into vectors. Thus, transformers only need to process a multispectral embedding sequence and a panchromatic embedding sequence to efficiently use multiscale information. Furthermore, an additive hybrid attention transformer is proposed to fuse the embedding sequences in an additive injection manner. Finally, a channel self-attention transformer is proposed to utilize channel correlations for high-quality detail generation. Experiments over QuickBird and WorldView-3 datasets demonstrate the proposed MDPNet outperforms state-of-the-art methods visually and quantitatively with low running time. Ablation studies further verify the effectiveness of the proposed multiscale embedding and transformers in pansharpening. [ABSTRACT FROM AUTHOR]

This paper concentrates on a priori error estimates of two monolithic schemes for Biot's consolidation model based on the three‐field formulation introduced by Oyarzúa et al. (SIAM J Numer Anal, 2016). The spatial discretizations are based on the Taylor–Hood finite elements combined with Lagrange elements for the three primary variables. We employ two different schemes to discretize the time domain. One uses the backward Euler method, and the other applies the combination of the backward Euler and Crank‐Nicolson methods. A priori error estimates show that both schemes are unconditionally convergent with optimal error orders. Detailed numerical experiments are presented to validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

We are concerned with the mathematical study of the mean field games system (MFGS). In the conventional setup, the MFGS is a system of two coupled nonlinear parabolic partial differential equation (PDE)s of the second order in a backward–forward manner, namely, one terminal and one initial condition are prescribed, respectively, for the value function and the population density. In this paper, we show that uniqueness of solutions to the MFGS can be guaranteed if, among all four possible terminal and initial conditions, either only two terminals or only two initial conditions are given. In both cases, Hölder stability estimates are proven. This means that the accuracies of the solutions are estimated in terms of the given data. Moreover, these estimates readily imply uniqueness of corresponding problems for the MFGS. The main mathematical apparatus to establish those results is two new Carleman estimates, which may find application in other contexts associated with coupled parabolic PDEs. [ABSTRACT FROM AUTHOR]