An Investigation of Interactions between Plants and Water, Energy and Carbon Budgets in the Soil-Plant-Atmosphere Continuum

Exchange of energy and substance (water, carbon dioxide, etc.) between land surface and atmosphere has a significant impact on climate. Considerable part of this exchange occurs through the soil-plant-atmosphere continuum (SPAC) where plants play an important role. Therefore functions of plants in water, energy and carbon cycles of the SPAC need to be extensively studied. When dry climatic conditions appear, plants can cope with the adverse circumstances by taking advantage of some biological or hydrological processes. In this study, the Three-Layer Variable Infiltration Capacity (VIC-3L) land surface model is extended to include some important biological or hydrological processes under water-limited climatic conditions: (1) movement of soil water from wet to dry regions through hydraulic redistribution (HR); (2) groundwater dynamics; (3) plant water storage; and (4) photosynthetic process. The extended VIC-3L model (referred to as VIC+ model) is evaluated with an analytical solution under simple conditions and with observed data at two AmeriFlux sites. Scenario simulations demonstrate that: (1) HR has significant impacts on water, energy and carbon budgets during the dry season; (2) Rise of groundwater table, increase of root depth, HR, and plant water storage can increase dry-season latent heat flux; (3) Plant water storage can weaken the intensity of upward HR; (4) Frozen soil can restrict downward HR in the wet winter and reduce the soil water reserves for the dry season. Groundwater can have significant impacts on the interactions between land surface and atmosphere by way of mechanisms such as influencing plant transpiration. The VIC+ model is used to conduct numerical experiments to study impacts of groundwater on transpiration. The relationship between transpiration and groundwater dynamics, and the related subsurface processes under various conditions are revealed and analyzed through results of numerical experiments. In order to predict interactions between land surface and atmosphere in the future, vegetation needs to be represented dynamically in modeling studies. To this end, the CASACNP biogeochemical model has been coupled with the VIC+ model. This coupled model is used to conduct scenario simulations to demonstrate impacts of vegetation on water and energy cycles when dynamic growth of vegetation is represented

Minimizing the Maximum Flow Time in the Online Food Delivery Problem

We study a common delivery problem encountered in nowadays online food-ordering platforms: Customers order dishes online, and the restaurant delivers the food after receiving the order. Specifically, we study a problem where k vehicles of capacity c are serving a set of requests ordering food from one restaurant. After a request arrives, it can be served by a vehicle moving from the restaurant to its delivery location. We are interested in serving all requests while minimizing the maximum flow-time, i.e., the maximum time length a customer waits to receive his/her food after submitting the order. We show that the problem is hard in both offline and online settings even when k = 1 and c = ?: There is a hardness of approximation of ?(n) for the offline problem, and a lower bound of ?(n) on the competitive ratio of any online algorithm, where n is number of points in the metric. We circumvent the strong negative results in two directions. Our main result is an O(1)-competitive online algorithm for the uncapacitated (i.e, c = ?) food delivery problem on tree metrics; we also have negative result showing that the condition c = ? is needed. Then we explore the speed-augmentation model where our online algorithm is allowed to use vehicles with faster speed. We show that a moderate speeding factor leads to a constant competitive ratio, and we prove a tight trade-off between the speeding factor and the competitive ratio

A Hierarchical Grouping Algorithm for the Multi-Vehicle Dial-a-Ride Problem

Ride-sharing is an essential aspect of modern urban mobility. In this paper, we consider a classical problem in ride-sharing - the Multi-Vehicle Dial-a-Ride Problem (Multi-Vehicle DaRP). Given a fleet of vehicles with a fixed capacity stationed at various locations and a set of ride requests specified by origins and destinations, the goal is to serve all requests such that no vehicle is assigned more passengers than its capacity at any point along its trip. We propose an algorithm HRA, which is the first non-trivial approximation algorithm for the Multi-Vehicle DaRP. The main technical contribution is to reduce the Multi-Vehicle DaRP to a certain capacitated partitioning problem, which we solve using a novel hierarchical grouping algorithm. Experimental results show that the vehicle routes produced by our algorithm not only exhibit less total travel distance compared to state-of-the-art baselines, but also enjoy a small in-transit latency, which crucially relates to riders' traveling times. This suggests that HRA enhances rider experience while being energy-efficient

From Bitcoin to Solana -- Innovating Blockchain towards Enterprise Applications

This survey presents a comprehensive study of recent advances in block-chain technologies, focusing on how issues that affecting the enterprise adoption were progressively addressed from the original Bitcoin system to Ethereum, to Solana etc. Key issues preventing the wide adoption are scala-bility and performance, while recent advances in Solana has clearly demon-strated that it is possible to significantly improve on those issues by innovat-ing on data structure, processes and algorithms by consolidating various time-consuming algorithms and security enforcements, and differentiate and balance users and their responsibilities and rights, while maintaining the re-quired security and integrity that blockchain systems inherently offer

Observation-based Model for BDI-Agents

We present a new computational model of BDI-agents, called the observation-based BDI-model. The key point of this BDI-model is to express agents' beliefs, desires and intentions as a set of runs (computing paths), which is exactly a system in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our BDI-model is computationally grounded in that we are able to associate the BDI-agent model with a computer program, and formulas, involving agents' beliefs, desires (goals) and intentions, can be understood as properties of program computations. We present a sound and complete proof system with respect to our BDI-model and explore how symbolic model checking techniques can be applied to model checking BDI-agents. In order to make our BDI-model more flexible and practically realistic, we generalize it so that agents can have multiple sources of beliefs, goals and intentions