Search

This study investigates how capital and institutional quality are associated with bank stability using an aggregate dataset comprising 173 banking systems from 2002 to 2020. First, our study suggests that banks with higher capital tend to be more stable, supporting the moral hazard hypothesis. Second, institutional quality improves financial stability of banks, confirming the role of proper banking environment. We further examine how capital and institutional quality jointly affect banking stability, and find that better institutional quality allows capital to impose a more positive effect on bank stability. However, this relationship is more pronounced with banking systems having low capital, indicating that capital and institutional quality could substitute each other in enhancing bank stability when the former is strong enough. These results are robust to the use of alternative proxies for bank stability and capital. We provide several implications for relevant stakeholders to uphold bank stability.

Atypical teratoid rhabdoid tumors (ATRT) are rare and aggressive embryonal tumors of central nervous system that typically affect children younger than 3 years of age. Given the generally poor outcomes of patients with ATRT and the significant toxicities associated with conventional multi-modal therapies, there is an urgent need for more novel approaches to treat ATRT, one such approach being immunotherapy. The recent rise of large-scale, multicenter interdisciplinary studies has delineated several molecular and genetic characteristics unique to ATRT. This review aims to describe currently available data on the tumor immune microenvironment of ATRT and its specific subtypes and to summarize the emerging clinical and preclinical results of immunotherapy-based approaches. It will also highlight the evolving knowledge of epigenetics on immunomodulation in this epigenetically influenced tumor, which may help guide the development of effective immunotherapeutic approaches in the future.

ABSTRACTMost speech processing models begin with feature extraction and then pass the feature vector to the primary processing model. The solution's performance mainly depends on the quality of the feature representation and the model architecture. Much research focuses on designing robust deep network architecture and ignoring feature representation's important role during the deep neural network era. This work aims to exploit a new approach to design a speech signal representation in the time-frequency domain via Linear Chirplet Transform (LCT). The proposed method provides a feature vector sensitive to the frequency change inside human speech with a solid mathematical foundation. This is a potential direction for many applications. The experimental results show the improvement of the feature based on LCT compared to MFCC or Fourier Transform. In both speaker gender recognition, dialect recognition, and speech recognition, LCT significantly improved compared with MFCC and other features. This result also implies that the feature based on LCT is independent of language, so it can be used in various applications.

This study uses aggregate data from 133 developing and emerging markets from 2002 to 2020 and investigates how market concentration and capital are related to bank stability. We find that banks operating in more concentrated banking markets tend to be more stable than those operating in a less concentrated market, which supports the concentration–stability hypothesis. Furthermore, the research reveals that capital significantly influences banks’ financial stability in developing and emerging markets, highlighting the role of capital as a significant financing source in these countries. Importantly, evidence shows that market concentration might enhance the positive effect of capital on bank stability. The findings should be important for policymakers, bank managers, and fund providers for banks to uphold bank stability in the less developed financial markets. These findings are robust to regression models that include alternative bank stability and market concentration proxies.

There is an extensive amount of research and literature discussing the role of various nutrients throughout the wound healing process. Despite the importance of nutrition in wound healing, dietary protocols often remain absent from wound care standards. This may be due to a lack of comprehensive literature that summarises the complexities and considerations associated with nutrient deficiency and supplementation into an easily accessible and inclusive reference tool. The purpose of this review is to assess the nutrients with key roles in the wound healing process, and subsequently provide information that enables optimisation of nutrition in wound healing. The goal is to consolidate the complexities associated with this topic into a simple, easy-to-use reference tool. We have identified the most important nutrients required for optimal wound healing and condensed the findings into an inclusive chart to be utilised in a clinical setting. This reference tool will include patient populations at risk of deficiency, the stage of wound healing in which each nutrient is required, delivery method and recommended daily intake, outpatient recommendations for rich food sources of each nutrient, and considerations associated with each nutrient.

The chemical composition and thickness of nails are obstacles for treatments of various nail diseases, such as onychomycosis. Topical medications are currently the preferred method of treatment because of reduced adverse systemic effects. However, penetration of the product from the nail plate into the nail bed continues to be an issue because of factors such as distance required to reach the target area, chemical barriers, and drug inactivation upon keratin binding. Beyond developing novel drugs, some studies have investigated mechanical and chemical methods to optimize drug delivery. The issue of nail diseases is still a challenge and requires multifactorial treatments.

Food resources face severe damages under extraordinary situations of catastrophes such as earthquakes, cyclones, and tsunamis. Under such scenarios, speedy assessment of food resources from agricultural land is critical as it supports aid activity in the disaster‐hit areas. In this article, a deep learning approach was presented for the detection and segmentation of coconut trees in aerial imagery provided through the AI competition organised by the World Bank in collaboration with OpenAerialMapand WeRobotics. Masked Region‐based Convolution Neural Network (Mask R‐CNN) approach was used for identification and segmentation of coconut trees. For the segmentation task, Mask R‐CNN model with ResNet50 and ResNet101 based architectures was used. Several experiments with different configuration parameters were performed and the best configuration for the detection of coconut trees with more than 90% confidence factor was reported. For the purpose of evaluation, Microsoft COCO dataset evaluation metric namely mean average precision (mAP) was used.An overall 91% mean average precision for coconut trees’ detection was achieved.

This study examines loan loss provision (LLP) behaviours of Vietnamese banks between 2006 and 2015. The findings show that earnings management is positively related to LLP regardless of the restructuring period, suggesting that LLPs can be used by Vietnamese banks as a mechanism for aggressive earnings management. There appears to be no capital management before the restructuring period. However, the findings indicate that Vietnamese banks use capital management with LLP during the restructuring period. Furthermore, the positive relation between LLP and future earnings during the restructuring period suggests that investors may view an abnormal increase in LLP as a signal of loan quality. The findings further demonstrate that LLP is positively associated with bank inefficiency, credit growth, bank size, and lending specialisation. State-owned commercial banks are found to reserve a greater level of provisions compared to privately owned commercial banks. Based on the research findings, we offer several implications for relevant stakeholders.

Tumour growth and invasiveness require extracellular matrix (ECM) degradation and are stimulated by the GALA pathway, which induces protein O-glycosylation in the endoplasmic reticulum (ER). ECM degradation requires metalloproteases, but whether other enzymes are required is unclear. Here, we show that GALA induces the glycosylation of the ER-resident calnexin (Cnx) in breast and liver cancer. Glycosylated Cnx and its partner ERp57 are trafficked to invadosomes, which are sites of ECM degradation. We find that disulfide bridges are abundant in connective and liver ECM. Cell surface Cnx–ERp57 complexes reduce these extracellular disulfide bonds and are essential for ECM degradation. In vivo, liver cancer cells but not hepatocytes display cell surface Cnx. Liver tumour growth and lung metastasis of breast and liver cancer cells are inhibited by anti-Cnx antibodies. These findings uncover a moonlighting function of Cnx–ERp57 at the cell surface that is essential for ECM breakdown and tumour development.

For the classification of sequential data, dynamic Bayesian networks and recurrent neural networks (RNNs) are the preferred models. While the former can explicitly model the temporal dependences between the variables, and the latter have the capability of learning representations. The recurrent temporal restricted Boltzmann machine (RTRBM) is a model that combines these two features. However, learning and inference in RTRBMs can be difficult because of the exponential nature of its gradient computations when maximizing log likelihoods. In this article, first, we address this intractability by optimizing a conditional rather than a joint probability distribution when performing sequence classification. This results in the “sequence classification restricted Boltzmann machine” (SCRBM). Second, we introduce gated SCRBMs (gSCRBMs), which use an information processing gate, as an integration of SCRBMs with long short-term memory (LSTM) models. In the experiments reported in this article, we evaluate the proposed models on optical character recognition, chunking, and multiresident activity recognition in smart homes. The experimental results show that gSCRBMs achieve the performance comparable to that of the state of the art in all three tasks. gSCRBMs require far fewer parameters in comparison with other recurrent networks with memory gates, in particular, LSTMs and gated recurrent units (GRUs).

Recently, low input agriculture has been encouraged because of its sustainability and environmentally friendly vision. Conversion of biomass into control‐released materials is one of the approaches to upcycle biomass and nutrients. This study aims at examining the dynamics of K release from Si‐rich biochars formed from various pyrolysis strategies with the findings expected to be applicable to develop new refinery strategies for biomass nutrients. A Si‐rich fern species [Dicranopteris linearis(Burm.f.) Underw.] was selected to prepare biochars under various pyrolysis conditions (e.g., temperature, N2supported). It was found that K was re‐located during pyrolysis and occurred as free K+ions, associated with organic matter and occluded in silica structure. Pyrolysis can be strategically applied to alter either the organic phase or the silica phase in the biochars in term of porosity and chemical reactivities, whereby controlling K release kinetics. The maximum level of released K was at 600 °C (5.4 g kg−1) which was about one order of magnitude higher than the minimum level of released K at 200 °C (0.55 g kg−1). This discrepancy in the release rates of K suggests that adjusting pyrolysis temperature can be a strategical practice to control K release and to develop biochar‐based K fertilizers.

Objective:The gold standard for offloading neuropathic forefoot and midfoot wounds is the total contact cast (TCC). However, in practice TCC is rarely used and is contraindicated in patients with fluctuating oedema, poor perfusion, lack of adequate tissue oxygenation and morbid obesity. It can also be too restrictive for patients, inevitably resulting in treatment rejection and delayed healing. This paper examines the role of shoe-based offloading devices as an alternative in reducing plantar pressure and optimising the healing of neuropathic ulcers.Method:Healthy subjects were recruited and fitted for two types of pixelated insoles: PegAssist (PA) insole system (Darco International, US) and FORS-15 (FORS) offloading insole (Saluber, Italy). An area of discreet, elevated high pressure was created by adding a 1/4-inch-thick felt pad to the plantar skin under the first metatarsal head. Subjects walked barefoot in surgical shoes with standard insoles (Condition 1), barefoot in pixelated insoles (Condition 2), barefoot with pixels removed (Condition 3). Dynamic plantar pressures were measured using F-Scan and the results were analysed to determine plantar pressure changes in each condition.Results:Using PA, the percentage reduction of plantar pressure (kPa) under the first metatarsal between Condition 1 and Condition 2 was 10.54±15.81% (p=0.022), between Condition 2 and Condition 3 was 40.13±11.11% (p<0.001), and between Condition 1 and Condition 3 was 46.67±12.95 % (p<0.001). Using FORS, the percentage reduction between Condition 1 and Condition 2 was 24.25±23.33% (p=0.0029), between Condition 2 and Condition 3 was 23.61±19.45% (p<0.001), and between Condition 1 and Condition 3 was 43.39±18.70% (p<0.001). A notable difference in the findings between the two insoles was the presence of a significant edge effect associated with PA, indicating that the offloading was not entirely successful. No edge effect was detected with FORS.Conclusion:Our current analysis shows that pixelated insoles exhibit potential for supplemental offloading in surgical shoes. These devices could provide an alternative way for physicians to offload plantar wounds and expedite closure for patients that cannot tolerate a TCC or other restrictive devices.

The study aims to make an update on the distribution and ecology of sand flies in the Quang Ninh province, Northern Vietnam, where Leishmaniacases were reported in 2001. Seventeen sites were chosen in three districts of the province: Ha Long, Cam Pha, and Hoanh Bo. Phlebotomine sand flies were collected using 68 CDC light traps from May 30 to 3 June 2016. Captured specimens were transferred individually into Eppendorf tubes with 90% ethanol. The sand fly heads and genitalia were removed and were mounted in Euparal after successive different baths. Specimen identification was determined based on the morphology of the cibarium, pharynx, and/or male genitalia or female spermathecae. A total of 416 sand flies (125 females, 283 males) belonging to four genera were collected and 10 sand fly species were identified: Sergentomyia silvatica, Se. barraudi, Se. hivernus, Se. bailyi, Phlebotomus mascomai, Ph. stantoni, Ph. yunshengensis, Ph. betisi, Chinius junlianensis, Idiophlebotomus longiforceps. The Sergentomyiagenus prevailed (79.7% of the collected sand flies), followed by the Phlebotomusgenus (13.7%), the Chiniusgenus (6.1%), and the Idiophlebotomusgenus (0.8%). Besides these well-defined taxa, five specimens, named sp1, showed unknown morphological characteristics, requiring further study. The majority of sand flies were collected in rock caves suggesting the cavernicolous character of the species in the Quang Ninh province. However, specimens were also collected in intra and peridomiciliary sites in which Ph. stantoniand Se. hivernuswere found as the main species. It is worth noting that two Ph. stantoniwere found in the house of a patient affected by Leishmania.

In this research, the response surface methodology with a polynomial model was used to represent the experimental data of the combination of steaming, drying, and tempering process for extra-large cashew nuts. The desired values of pre-treatment conditions minimize the broken kernel percentage and maximize the shelling capacity to achieve cost effectiveness. In the this study, the steaming, drying, and tempering conditions were optimized for the minimization of the broken kernel percentage and the maximization of the shelling capacity of extra-large cashew nuts (bigger than 32 mm). The optimal conditions were steaming temperature at 100 ℃ for 38 min, then drying at 70 ℃ for 30 min, and finally tempering for 4 h. Under these conditions, the minimal broken kernel and maximal shelling capacity achieved were 2.45 ± 0.24% and 14.58 ± 0.35 kg/h, respectively.

•Two dump truck lifting mechanisms with opposite placements were compared on the kinetics and dynamics•MATLAB Simscape was used to access the kinetics and dynamic of two models•The analytical calculations to validate the simulation for both models give errors of less than 5%•The established model is extremely helpful in studying and designing hydraulic-mechanical systems

In this paper, a lifetime model for bond wire contacts of insulated gate bipolar transistors (IGBT) power modules is reported. This model is based on power cycling tests obtained under accelerated conditions, and a finite-element model taking into account the electrical, thermal, and mechanical coupling. It allows us to estimate the bond wire lifetime for a large scale of junction temperature swing amplitudes ( $ {\Delta }T_{j}$ ) and stress durations ( $t_{\mathrm{\scriptscriptstyle ON}}$ ). To build it, a numerical design of experiment was performed in both high and low stress values ( $\Delta T_{j}$ ). Then, a strain-life curve has been constructed where the average strain values on a defined volume around the contact areas between top-metallization and the most exposed bond wires to fatigue and lift-off have been used. As a result, it has been shown that the total strain is linearly dependent with $\Delta T_{j}$ and power law dependent with $t_{\mathrm{\scriptscriptstyle ON}}$ . The combination of the strain-life relation and the strain dependency with stress parameters leads to the lifetime relationship. The obtained lifetime model has been satisfactorily validated with some additional experimental points obtained from literature and with a large range of values for $t_{\mathrm{\scriptscriptstyle ON}}$ . This methodology can be easily replicated to other structures and is quite generic.

ABSTRACTVaccines are strongly recommended globally as an effective measure to prevent serious illness from and spread of COVID-19. Concerns about safety following vaccination continue to be the most common reason that people do not accept the vaccine. This retrospective study was carried out on 4341 people who received the first dose of ChAdOx1 nCoV-19, BBIBP-CorV, or mRNA-1273 vaccine at Jio Health Clinic in Ho Chi Minh City, Vietnam. Post-injection side effects were either reported by participants or actively collected by health care staff by means of telemedicine. Local side effects were reported by 35.5% of all individuals, with pain being the most common symptom (33.3%). Systemic side effects were reported by 44.2% of individuals, with fever (25.3%) and fatigue (21.4%) being the most common. Age ≤60 years, female gender, and ChAdOx1 nCoV-19 were significant independent risk factors for both local and systemic side effects, while a history of allergy was significant as a risk factor for local side effects. A total of 43 individuals (1.0%) reported concerning symptoms of rare severe complications, which were addressed and treated by physicians via Jio Health app.

Developments in deep learning have seen the use of layerwise unsupervised learning combined with supervised learning for fine-tuning. With this layerwise approach, a deep network can be seen as a more modular system that lends itself well to learning representations. In this paper, we investigate whether such modularity can be useful to the insertion of background knowledge into deep networks, whether it can improve learning performance when it is available, and to the extraction of knowledge from trained deep networks, and whether it can offer a better understanding of the representations learned by such networks. To this end, we use a simple symbolic language—a set of logical rules that we call confidence rules—and show that it is suitable for the representation of quantitative reasoning in deep networks. We show by knowledge extraction that confidence rules can offer a low-cost representation for layerwise networks (or restricted Boltzmann machines). We also show that layerwise extraction can produce an improvement in the accuracy of deep belief networks. Furthermore, the proposed symbolic characterization of deep networks provides a novel method for the insertion of prior knowledge and training of deep networks. With the use of this method, a deep neural–symbolic system is proposed and evaluated, with the experimental results indicating that modularity through the use of confidence rules and knowledge insertion can be beneficial to network performance.

Purpose:To identify anatomic and hemodynamic changes associated with impending visceral chimney stent-graft occlusion after endovascular aneurysm repair (EVAR) with the chimney technique (chEVAR). Methods:A retrospective evaluation was performed of computed tomography scans from 41 patients who underwent juxtarenal chEVAR from 2008 to 2012 to identify stent-grafts demonstrating conformational changes following initial placement. Six subjects (mean age 74 years; 3 men) were selected for detailed reconstruction and computational hemodynamic analysis; 4 had at least 1 occluded chimney stent-graft. This subset of repairs was systematically analyzed to define the anatomic and hemodynamic impact of these changes and identify signature patterns associated with impending renovisceral stent-graft occlusion. Spatial and temporal analyses of cross-sectional area, centerline angle, intraluminal pressure, and wall shear stress (WSS) were performed within the superior mesenteric and renal artery chimney grafts used for repair. Results:Conformational changes in the chimney stent-grafts and associated perturbations, in both local WSS and pressure, were responsible for the 5 occlusions in the 13 stented branches. Anatomic and hemodynamic signatures leading to occlusion were identified within 1 month postoperatively, with a lumen area <14 mm2(p=0.04), systolic pressure gradient >25 Pa/mm (p=0.03), and systolic WSS >45 Pa (p=0.03) associated with future chimney stent-graft occlusion. Conclusion:Chimney stent-grafts at increased risk for occlusion demonstrated anatomic and hemodynamic signatures within 1 month of juxtarenal chEVAR. Analysis of these parameters in the early postoperative period may be useful for identifying and remediating these high-risk stent-grafts.

The AAAI‐17 workshop program included 17 workshops covering a wide range of topics in AI. Workshops were held Sunday and Monday, February 4– 5, 2017, at the Hilton San Francisco Union Square in San Francisco, California, USA.

In addition to synthetic and semisynthetic compounds, natural products have received much attention as prolific sources of lead compounds with therapeutic effects on various diseases. In the process of screening the bioactivities of potential candidates, an in vivo assay is very important for providing meaningful insight into the efficacy, adverse effects, and modes of action that are relevant to humans. Among the many experimental models, Caenorhabditis elegansis particularly efficient due to its advantages in morphology, behavior, and genetic aspects. This review summarizes some basic and useful techniques commonly used in screening the bioactivities of natural products. Recent studies of naturally occurring extracts as well as bioactive compounds in various areas, namely, anti-aging, anti-neurodegeneration, anti-obesity, anti-infection, and gut health, are reviewed as examples of the applicability of the C. elegansmodel. Technological developments that incorporate C. elegansin other fields, such as instrumental analysis and emerging methods, are also discussed in this paper.

The typical challenge encountered in developing heavy-oil reservoirs is inefficient wellbore lifting caused by complex multiphase flows. The literature on modeling of a hybrid artificial-lift (AL) system is relatively sparse and these works typically model the AL system on the basis of individual AL methods. This paper presents a case study of the design and optimization of a hybrid AL system to improve heavy-oil production. We systematically design and model a hybrid electrical-submersible-pump/gas-lift (ESP/GL) system to enhance wellbore lifting and production optimization. We found that the implementation of a hybrid ESP/GL system provides the flexibility to boost production and reduces production downtime. Results from the pilot test show that the production rate in hybrid mode are approximately 30% higher than in ESP-only mode. The power consumption of the hybrid mode is 3% lower in the ESP-only mode. Additionally, the average ESP service life exceeds 6 years which is better than expected in the field development plan. The pump-performance-curve model is built with corrections for density and viscosity owing to the increased water production. We observed a higher pressure drawdown with GL injection at fixed ESP frequency. The GL injection reduces the density of the fluid column above the ESP, resulting in less pressure loss across the pump, less power consumption, and potentially extended service life. The nodal analysis results suggest that the pump capacity can be considerably expanded by manipulating the GL rate instead of increasing the frequency.

Post-partum haemorrhage is a leading cause of global maternal morbidity and mortality. Misoprostol, a prostaglandin analogue with uterotonic activity, is an attractive option for treatment because it is stable, active orally, and inexpensive. We aimed to assess the effectiveness of misoprostol as an adjunct to standard uterotonics compared with standard uterotonics alone for treatment of post-partum haemorrhage.

Abstract: Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented.

Abstract: A new non-Delaunay-based approach is presented to reconstruct a curve, lying in 2- or 3-space, from a sampling of points. The underlying theory is based on bounding curvature to determine monotone pieces of the curve. Theoretical guarantees are established. The implemented algorithm, based heuristically on the theory, proceeds by iteratively partitioning the sample points using an octree data structure. The strengths of the approach are (a) simple implementation, (b) efficiency-experimental performance compares favorably with Delaunay-based algorithms, (c) robustness-curves with multiple components and sharp corners are reconstructed satisfactorily, and (d) potential extension to surface reconstruction.

Radiotherapy is common treatment for head-and-neck cancer, during which the salivary glands are often included within the radiation field. The most common side effect of this treatment is the development of oral dryness (xerostomia). This study considers the administration of epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF or FGF2) at physiological concentrations before and after irradiation in order to repair radiation-induced damage in salivary gland cells. As a preliminary examination of the efficacy of this approach we have characterized the effects of EGF and bFGF on the apoptotic response of 15-Gy irradiated rat salivary glands in vitro. Also, we have developed a controlled-release delivery system to effectively administer the growth factor to the gland since local delivery is essential to avoid unwanted protection of cancer cells. In vitro administration of bFGF prior to and immediately after irradiation partially protected (44%) the rat parotid gland. EGF did not show any significant radioprotective effect on parotid glands after a single 15-Gy irradiation dose. Encapsulation, storage and release of bFGF from biodegradable 50/50 PLGA microspheres did not affect the functionality of the growth factor in vitro.

In this study, an analytical technique was developed to estimate the dynamic, three-dimensional wall shear and tensile forces within the arterial circulation and applied to our established model of flow-mediated graft remodeling within the rabbit carotid system. Through selective unilateral distal ligation, vein grafts were exposed to distinct flow environments, characterized by a sixfold difference in mean flow rate. Implanted vein grafts were harvested at 1, 3, 7, 14, and 28 days to evaluate graft morphology. Hemodynamic and real-time imaging data, obtained at graft implantation and harvest, served as input for estimation of dynamic shear stress and wall tension. Marked differences in the remodeling process were observed in high vs. low flow grafts, with low flow grafts demonstrating accelerated intimal hyperplasia and reduced outward remodeling. The impact was a peak in the maximum and minimum shear stress at Day 7, with a delayed increase in lumen diameter leading to partial normalization of the wall shear by Day 28. Intramural wall tension reached a maximum at Day 3, with an increase in wall thickness leading to a significant reduction in these forces by Day 14. Despite the significant morphologic changes, no differences in the incremental moduli of elasticity were observed.

Adhesion of leukocytes to substrate involves the coupling of disparate length and timescales between molecular mechanics and macroscopic transport, and existing models of cell adhesion do not use full cellular information. To address these challenges, a multiscale computational approach for studying the adhesion of a cell on a substrate is developed and assessed. The cellular level model consists of a continuum representation of the field equations and a moving boundary tracking capability to allow the cell to change its shape continuously. At the receptor-ligand level, a bond molecule is mechanically represented by a spring. Communication between the macro/micro- and nanoscale models is facilitated interactively during the computation. The computational model is assessed using an adherent cell, rolling and deforming along the vessel wall under imposed shear flows. Using this approach, we first confirm existing numerical and experimental results. In this study, the intracellular viscosity and interfacial tension are found to directly affect the rolling of a cell. Our results also show that the presence of a nucleus increases the bond lifetime, and decreases the cell rolling velocity. Furthermore, it is found that a cell with a larger diameter rolls faster, and decreases the bond lifetime. This study shows that cell rheological properties have significant effects on the adhesion process contrary to what has been hypothesized in most literature.

Many critical issues in biofluid dynamics occur at the boundaries between fluids, solids, or both. These issues can be very complex since in many cases the boundaries are deformable and moving. Furthermore, different characteristic times, lengths, and material properties are often present which make any computational task taxing. The present review focuses on computational modeling techniques for moving boundaries and multi-component systems with emphasis on micro-scale biofluid physics, including i) the dynamics of leukocyte (white blood cell) deformation, recovery, and adhesion; and ii) the thin-film dynamics involving tear–structure interaction in soft contact lens applications. In these problems, multiple length scales exist, and at least one of them is on the order of 10 μm or smaller. After presenting appropriate computational techniques for moving boundaries, recent research on leukocyte deformation, recovery, and adhesion is reviewed in the context of multi-component, multi-time-scale, and micro-macro interactions. The soft contact lens problem is discussed from the viewpoint of large disparities in length scales due to high aspect ratios. Depending on the nature of the problem and the goal of the computation, alternative computational techniques can successfully address the physical and numerical challenges. A major interest of this article is to stress how moving boundary techniques can be applied to provide new insights into the physico-chemical behavior of complex biological systems. To treat different time and length scales with due care in a moving boundary framework is a grand challenge in developing first-principle-based computational capabilities. There are 175 references in this review article.

The rheological properties of a leukocyte significantly affect its biological and mechanical characteristics. To date, existing physical models of leukocyte are not capable of quantitatively explaining the wide range of deformation and recovery behaviors observed in experiment. However, a compound drop model has gained some success. In the present work, we investigate the effect of nucleus size and position, and the relative rheological properties of cytoplasm and nucleus, on cell recovery dynamics. Two nucleus sizes corresponding to that of neutrophil and lymphocyte are considered. Direct comparison between numerical simulations and experimental observation is made. Results indicate that the time scale ratio between the nucleus and cytoplasm plays an important role in cell recovery characteristics. Comparable time scales between the two cell components yield favorable agreement in recovery rates between numerical and experimental observations; disparate time scales, on the other hand, result in recovery behavior and cell shapes inconsistent with experiments. Furthermore, it is found that the nucleus eccentricity exhibits minimum influence on all major aspects of the cell recovery characteristics. The present work offers additional evidence in support of the compound cell model for predicting the rheological behavior of leukocytes. © 1999 Biomedical Engineering Society. PAC99: 8717-d, 8719Tt