Multiscale modelling of fluid and solute transport in soft tissues and microvessels

This study focuses on the movement of particles and extracellular fluid in soft tissues and microvessels. It analyzes modeling applications in biological and physiological fluids at a range of different length scales: from between a few tens to several hundred nanometers, on the endothelial glycocalyx and its effects on interactions between blood and the vessel wall; to a few micrometers, on movement of blood cells in capillaries and transcapillary exchange; to a few millimetres and centimetres, on extracellular matrix deformation and interstitial fluid movement in soft tissues. Interactions between blood cells and capillary wall are discussed when the sizes of the two are of the same order of magnitude, with the glycocalyx on the endothelial and red cell membranes being considered. Exchange of fluid, solutes, and gases by microvessels are highlighted when capillaries have counter-current arrangements. This anatomical feature exists in a number of tissues and is the key in the renal medulla on the urinary concentrating mechanism. The paper also addresses an important phenomenon on the transport of macromolecules. Concentration polarization of hyaluronan on the synovial lining of joint cavities is presented to demonstrate how the mechanism works in principle and how model predictions agree to experimental observations quantitatively

Regional food self sufficiency: new visions for productive landscapes

Food is an important resource for the survival and development of civilization. Its potential is so huge that it affects physical and mental health in an individual sense, and it affects landscapes and even public relations in a social sense. For most people, having food is never a problem that the importance of food is overlooked. However, the right to food is not equal. There are still a considerable number of people have low food access, which means…, and they may also be forced to be in an unbalanced diet leading to health problems such as obesity. A large amount of food and the resources used to produce food are wasted, and unsustainable production methods cause the deterioration of the production environment are problems that need to be solved urgently. I believe it’s time to reimagine the role of food in our daily lives in terms of new ways of people participating in productive landscapes. Those landscapes can have a primary function as food production as well as secondary and even tertiary functions for example being places for public activities and education. Productive landscapes have have way more possibilities as long as we can give full play to our creativity. In the thesis I’m going to explore the possibility of food self-sufficiency in order to shift people’s visions and engagements with productive landscapes using New Bedford region as the test ground. During the design process, there will be new transformations of land based on calculated data. Those types of land will be multi-functional combining food production, environmental justice and human engagement together

The Influence of Online Product Presentation and Seller Reputation on the Consumers’ Purchase Intention across Different Involvement Products

In online market, consumers tend to make use of other signals when assessing the product quality due to the aggravated information asymmetry. Taking the moderating effects of product involvement into account, this paper developed a research model to study the influence mechanism of product information presentation and seller reputation on consumers’ perceived product quality and purchase intension. A lab experiment was designed to prove the research model, in which 57 participants’ questionnaire data was collected and eye movement data was recorded by SMI Hi-speed eye tracker when they viewed the website. The results showed that perceived product information presentation and seller reputation positively influenced consumers’ perceived product quality which further more affected the willingness to buy, with the moderating effects of product involvement. More specifically, the impact of perceived product information presentation got weaker when seller reputation got higher for low-involvement product

Cursed yet Satisfied Agents

In real life auctions, a widely observed phenomenon is the winner's curse -- the winner's high bid implies that the winner often over-estimates the value of the good for sale, resulting in an incurred negative utility. The seminal work of Eyster and Rabin [Econometrica'05] introduced a behavioral model aimed to explain this observed anomaly. We term agents who display this bias "cursed agents". We adopt their model in the interdependent value setting, and aim to devise mechanisms that prevent the cursed agents from obtaining negative utility. We design mechanisms that are cursed ex-post IC, that is, incentivize agents to bid their true signal even though they are cursed, while ensuring that the outcome is individually rational -- the price the agents pay is no more than the agents' true value. Since the agents might over-estimate the good's value, such mechanisms might require the seller to make positive transfers to the agents to prevent agents from over-paying. For revenue maximization, we give the optimal deterministic and anonymous mechanism. For welfare maximization, we require ex-post budget balance (EPBB), as positive transfers might lead to negative revenue. We propose a masking operation that takes any deterministic mechanism, and imposes that the seller would not make positive transfers, enforcing EPBB. We show that in typical settings, EPBB implies that the mechanism cannot make any positive transfers, implying that applying the masking operation on the fully efficient mechanism results in a socially optimal EPBB mechanism. This further implies that if the valuation function is the maximum of agents' signals, the optimal EPBB mechanism obtains zero welfare. In contrast, we show that for sum-concave valuations, which include weighted-sum valuations and l_p-norms, the welfare optimal EPBB mechanism obtains half of the optimal welfare as the number of agents grows large

Traffic-Aware Transmission Mode Selection in D2D-enabled Cellular Networks with Token System

We consider a D2D-enabled cellular network where user equipments (UEs) owned by rational users are incentivized to form D2D pairs using tokens. They exchange tokens electronically to "buy" and "sell" D2D services. Meanwhile the devices have the ability to choose the transmission mode, i.e. receiving data via cellular links or D2D links. Thus taking the different benefits brought by diverse traffic types as a prior, the UEs can utilize their tokens more efficiently via transmission mode selection. In this paper, the optimal transmission mode selection strategy as well as token collection policy are investigated to maximize the long-term utility in the dynamic network environment. The optimal policy is proved to be a threshold strategy, and the thresholds have a monotonicity property. Numerical simulations verify our observations and the gain from transmission mode selection is observed.Comment: 7 pages, 6 figures. A shorter version is submitted to EUSIPC

Efficient Multi-View Inverse Rendering Using a Hybrid Differentiable Rendering Method

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently reconstruct the 3D geometry and reflectance of a scene from multi-view images captured by conventional hand-held cameras. Our method follows an analysis-by-synthesis approach and consists of two phases. In the initialization phase, we use traditional SfM and MVS methods to reconstruct a virtual scene roughly matching the real scene. Then in the optimization phase, we adopt a hybrid approach to refine the geometry and reflectance, where the geometry is first optimized using an approximate differentiable rendering method, and the reflectance is optimized afterward using a physically-based differentiable rendering method. Our hybrid approach combines the efficiency of approximate methods with the high-quality results of physically-based methods. Extensive experiments on synthetic and real data demonstrate that our method can produce reconstructions with similar or higher quality than state-of-the-art methods while being more efficient.Comment: IJCAI202