Viscous Taylor droplets in axisymmetric and planar tubes: from Bretherton's theory to empirical models

The aim of this study is to derive accurate models for quantities characterizing the dynamics of droplets of non-vanishing viscosity in capillaries. In particular, we propose models for the uniform-film thickness separating the droplet from the tube walls, for the droplet front and rear curvatures and pressure jumps, and for the droplet velocity in a range of capillary numbers, $Ca$, from $10^{-4}$ to $1$ and inner-to-outer viscosity ratios, $\lambda$, from $0$, i.e. a bubble, to high viscosity droplets. Theoretical asymptotic results obtained in the limit of small capillary number are combined with accurate numerical simulations at larger $Ca$. With these models at hand, we can compute the pressure drop induced by the droplet. The film thickness at low capillary numbers ($Ca<10^{-3}$) agrees well with Bretherton's scaling for bubbles as long as $\lambda<1$. For larger viscosity ratios, the film thickness increases monotonically, before saturating for $\lambda>10^3$ to a value $2^{2/3}$ times larger than the film thickness of a bubble. At larger capillary numbers, the film thickness follows the rational function proposed by Aussillous \& Qu\'er\'e (2000) for bubbles, with a fitting coefficient which is viscosity-ratio dependent. This coefficient modifies the value to which the film thickness saturates at large capillary numbers. The velocity of the droplet is found to be strongly dependent on the capillary number and viscosity ratio. We also show that the normal viscous stresses at the front and rear caps of the droplets cannot be neglected when calculating the pressure drop for $Ca>10^{-3}$

Does technological progress magnify regional disparities?

We study how technological progress in manufacturing and transportation to-gether with migration costs interact to shape the space-economy. Rising labor productivity in the manufacturing sector fosters the agglomeration of activities, whereas falling transport costs associated with technological and organizational in-novations fosters their dispersion. Since these two forces have been at work for a long time, the final outcome must depend on how drops in the costs of producing and trading goods interact with the various costs borne by migrants. Finally, when labor is heterogeneous, the most efficient workers of the less productive region are the first to move to the more productive region

In vivo assessment of the mechanical properties of the child cortical bone using quantitative computed tomography

The mechanical properties of the rib cortical bone are extremely rare on children due to difficulties to obtain specimens to perform conventional tests. Some recent studies used cadaveric bones or bone tissues collected during surgery but are limited by the number of samples that could be collected. A non-invasive technique could be extremely valuable to overcome this limitation. It has been shown that a relationship exists between the mechanical properties (apparent Young’s modulus and ultimate strength) and the bone mineral density (assessed using Quantitative Computed Tomography, QCT), for the femur and recently by our group for the adult ribs ex vivo. Thus the aim of this study was to assess the mechanical properties of the child rib cortical bone using both QCT images in vivo and the previous relationship between bone mineral density and mechanical properties of the rib cortical bone. Twenty-eight children were included in this study. Seven age-groups have been considered (1, 1.5, 3, 6, 10, 15, 18 years old). The QCT images were prescribed for various thoracic pathologies at the pediatric hospital in Lyon. A calibration phantom was added to the clinical protocol without any modifications for the patient. The protocol was approved by the ethical committee. A 3D reconstruction of each thorax was performed using the QCT images. A custom software was then used to obtain cross-sections to the rib midline. The mean bone mineral density was then computed by averaging the Hounsfield Units in a specific cross-section and by converting the mean value (Hounsfield Units) in bone mineral density using the calibration phantom. This bone mineral density was assessed for the 6th rib of each subject. Our relationship between the bone mineral density and the mechanical properties of the rib cortical bone was used to derive the mechanical properties of the child ribs in vivo. The results give values for the apparent Young’s modulus and the ultimate strength. The mechanical properties increase along growth. As an example the apparent Young’s modulus in the lateral region ranges from 7 GPa +/-3 at 1 year old up to 13 GPa +/- 2 at 18 years old. These data are in agreement with the few previous values obtained from child tissues. This methodology opens the way to in vivo measurement of the mechanical properties of the child cortical bone based on calibrated QCT images

Achievability of Efficient Satisfaction Equilibria in Self-Configuring Networks

International audienceIn this paper, a behavioral rule that allows radio devices to achieve an efficient satisfaction equilibrium (ESE) in fully decentralized self-configuring networks (DSCNs) is presented. The relevance of ESE in the context of DSCNs is that at such state, radio devices adopt a transmission/receive configuration such that they are able to simultaneously satisfy their individual quality-of-service (QoS) constraints. An ESE is also an efficient network configuration, i.e., individual QoS satisfaction is achieved by investing the lowest possible effort. Here, the notion of effort refers to a preference each radio device independently establishes among its own set of actions. In particular, the proposed behavioral rule requires less information than existing rules, as in the case of the classical best response dynamics and its variants. Sufficient conditions for convergence are presented in a general framework. Numerical results are provided in the context of a particular uplink power control scenario, and convergence from any initial action profile to an ESE is formally proved in this scenario. This property ensures the proposed rule to be robust to the dynamic arrival or departure of radio devices in the network

Is multidimensional poverty associated to dementia risk? The case of older adults in Pakistan

BACKGROUND AND OBJECTIVES: Multidimensional poverty is associated with dementia. We aimed at establishing this association in Pakistan. RESEARCH DESIGN AND METHODS: A cross-sectional study was conducted in Punjab and Sindh, Pakistan, between March 30, 2002, and August 22, 2022, among adults aged 50 and older. Multidimensional poverty measures were composed of 6 dimensions and 15 indicators. Poverty was compared between adults with and without dementia using the Rowland Universal Dementia Assessment Scale, adjusting for sex, age, marital status, and household size. Associations between dementia and poverty were investigated using a multivariate logistic regression model. RESULTS: We found that 594 (72.7%), 171 (20.9%), and 52 (6.4%) had no, mild, and moderate-to-severe dementia, respectively. More women than men had dementia (11.4% vs 2.9%). Approximately 40.4% of adults with dementia were found to be deprived in 4 or more dimensions compared to 8.9% without dementia, and the difference in multidimensional poverty between them was 348.6%. Education, health, living conditions, and psychological well-being were the main contributors to poverty. Poverty in 4 or more dimensions was strongly associated with dementia (odds ratio [OR], 5.02; 95% confidence interval [CI], 2.07-12.16) after adjusting for sex, marital status, age, and household size, with greater odds for older women (OR, 2.02; 95% CI, 1.41-2.90). DISCUSSION AND IMPLICATIONS: Our findings suggest that early improvement in social determinants of health through targeted structural policies may prevent dementia later in life. Improving access to free, quality education, health care including mental health care and basic living standards, and employment should reduce the collective risk of dementia

Hierarchical structuring of cathodes and anodes for lithium-ion batteries

Extensive technological progress is essential to meet the ambitious future requirements of energy storage devices. This is due to the necessity of achieving high energy and power density operations, accompanied by high safety standards and extended lifespans, while maintaining low production and material costs. Significant importance is placed on the research of high energy active materials. However, besides material optimization, there is substantial potential for optimization by introducing electrodes with high mass loading, advanced electrode architectures, and their transfer to production level. Achieving appropriate trade-offs between high energy and power density, process reliability, and economic considerations poses a challenge for current lithium-ion battery technology. For this purpose, the laser-assisted generation of three-dimensional (3D) electrode architectures is studied and evaluated. Advanced electrode design incorporates micro and sub-micron structures that can be designed in various ways. Significant improvements in battery lifespan and high-power operation capabilities can be achieved compared to traditional two-dimensional (2D) electrodes. Furthermore, the production of 3D electrodes with laser processing requires coordination with other established manufacturing steps in the battery production process. In particular, the calendering of electrodes holds great importance as it has a significant impact on the microstructural properties of the composite electrode, including porosity, material density, and film adhesion strength. This study investigated the impact of laser-induced hierarchical structuring, comprising micro-/nano-porosities and microtopography, on electrodes with varying mass loadings from 2 mAh/cm² to 6 mAh/cm². In this regard, cells comprising graphite anodes and lithium-nickel-manganese-cobalt oxide cathodes were prepared and subjected to electrochemical characterization techniques

Deep Markov Random Field for Image Modeling

Markov Random Fields (MRFs), a formulation widely used in generative image modeling, have long been plagued by the lack of expressive power. This issue is primarily due to the fact that conventional MRFs formulations tend to use simplistic factors to capture local patterns. In this paper, we move beyond such limitations, and propose a novel MRF model that uses fully-connected neurons to express the complex interactions among pixels. Through theoretical analysis, we reveal an inherent connection between this model and recurrent neural networks, and thereon derive an approximated feed-forward network that couples multiple RNNs along opposite directions. This formulation combines the expressive power of deep neural networks and the cyclic dependency structure of MRF in a unified model, bringing the modeling capability to a new level. The feed-forward approximation also allows it to be efficiently learned from data. Experimental results on a variety of low-level vision tasks show notable improvement over state-of-the-arts.Comment: Accepted at ECCV 201