Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours

Rideshare platforms, when assigning requests to drivers, tend to maximize profit for the system and/or minimize waiting time for riders. Such platforms can exacerbate biases that drivers may have over certain types of requests. We consider the case of peak hours when the demand for rides is more than the supply of drivers. Drivers are well aware of their advantage during the peak hours and can choose to be selective about which rides to accept. Moreover, if in such a scenario, the assignment of requests to drivers (by the platform) is made only to maximize profit and/or minimize wait time for riders, requests of a certain type (e.g. from a non-popular pickup location, or to a non-popular drop-off location) might never be assigned to a driver. Such a system can be highly unfair to riders. However, increasing fairness might come at a cost of the overall profit made by the rideshare platform. To balance these conflicting goals, we present a flexible, non-adaptive algorithm, \lpalg, that allows the platform designer to control the profit and fairness of the system via parameters $\alpha$ and $\beta$ respectively. We model the matching problem as an online bipartite matching where the set of drivers is offline and requests arrive online. Upon the arrival of a request, we use \lpalg to assign it to a driver (the driver might then choose to accept or reject it) or reject the request. We formalize the measures of profit and fairness in our setting and show that by using \lpalg, the competitive ratios for profit and fairness measures would be no worse than $\alpha/e$ and $\beta/e$ respectively. Extensive experimental results on both real-world and synthetic datasets confirm the validity of our theoretical lower bounds. Additionally, they show that \lpalg under some choice of $(\alpha, \beta)$ can beat two natural heuristics, Greedy and Uniform, on \emph{both} fairness and profit

Housing markets and independence in old age: expanding the opportunities

This report highlights the benefits of specialised private retirement accommodation and recommends a number of simple policy changes at no cost to the public purse to help increase its supply and address the challenges of housing an ageing population

A review of research on microseisms

This paper reviews the various problems of research on microseisms, and also the method of obtaining seismograms. Direction finding techniques are outlined, and possible origins of microseisms are suggested. The surf and wind theory of microseisms are compared. Mention is also made of some recent theories of microseisms. The paper shows how the subject of microseisms is closely connected with that of swell and storm prediction, a problem of interest to Defence Scientists and Meteorologists

Impact of heavy metals on the rhizosphere microflora of Jatropha multifida and their effective remediation

The impact of heavy metals (arsenic, chromium, copper and magnesium) in the rhizosphere microflora of Jatropha multifida used for phytoremediation was studied. The pot culture experiment of J. multifida dealt with the biochemical characteristics of heavy metals contaminated soil amended with waste water biosludge and biofertilizer (Azotobacter vinelandii). Plant growth promoting rhizobacteria such as Pseudomonas, Azotobacter and Rhizobium were isolated, characterized and screened for their heavy metal tolerance. Pseudomonas was found to be the most tolerant followed by Azotobacter and Rhizobium. Amongst heavy metals, As was most toxic followed by Cr, Mg and Cu. Amongst different soil treatments, T4 (garden soil with heavy metal, biosludge, and biofertilizer) served the best treatment for plants and microbial endurance under metal contamination. The results advocate that the toxicity of heavy metals in soil can be restored with concomitant amendment of organic sludge and appropriate biofertilizer.Key words: Heavy metals, rhizosphere, biosludge, biofertilizer, bioremediation

Surface excitonic emission and quenching effects in ZnO nanowire/nanowall systems: limiting effects on device potential.

We report ZnO nanowire/nanowall growth using a two-step vapour phase transport method on a-plane sapphire. X-ray diffraction and scanning electron microscopy data establish that the nanostructures are vertically well-aligned with c-axis normal to the substrate, and have a very low rocking curve width. Photoluminescence data at low temperatures demonstrate the exceptionally high optical quality of these structures, with intense emission and narrow bound exciton linewidths. We observe a high energy excitonic emission at low temperatures close to the band-edge which we assign to the surface exciton in ZnO at ~ 3.366 eV, the first time this feature has been reported in ZnO nanorod systems. This assignment is consistent with the large surface to volume ratio of the nanowire systems and indicates that this large ratio has a significant effect on the luminescence even at low temperatures. The band-edge intensity decays rapidly with increasing temperature compared to bulk single crystal material, indicating a strong temperature-activated non-radiative mechanism peculiar to the nanostructures. No evidence is seen of the free exciton emission due to exciton delocalisation in the nanostructures with increased temperature, unlike the behaviour in bulk material. The use of such nanostructures in room temperature optoelectronic devices appears to be dependent on the control or elimination of such surface effects

A Powerful and Computationally Efficient Algorithm for Transmission Loss Calculation

This paper deals with the formulation of transmission loss PL of a power system through a set of new coefficients (A coefficients) which are extremely efficient, exact and robust and suitable for real time application. Results on a few IEEE test systems are exciting and encouraging. They demonstrate that these A coefficients faithfully represent the system loss, are extremely robust and need not be re-evaluated for changes in the system loading conditions either for evaluation of system loss or cost of generation for economic load dispatch

Determining the direct mailing frequency with dynamic stochastic programming

Both in business to business and in consumer markets direct mailings are an important means of communication with individual customers. This paper studies the mailing frequency problem that addresses the issue of how often to send a mailing to an individual customer in order to establish a profitable long-term relationship rather than targeting profitable groups of customers at every new mailing instance. The mailing frequency is optimized using long-term objectives but restricts the decisions to the number of mailings to send to the individual over consecutive finite planning periods. A stochastic dynamic programming model that is formulated for this problem is easy to solved for many applications in direct mailing. A particular implementation of the model will provide the direct mailer with controls to stimulate desired response behavior of their customers. The model is calibrated for a large non-profit organization and shows that very large improvements can be achieved by approaching the mailing strategy with the mailing frequency problem, both in the number of mailing to send and in the profits resulting from the responses

Procedure for improving wildfire simulations using observations

This report suggests a variational update method for improving wildfire simulations using observations as feedback to update information. We first assume a onedimensional fire model for simplicity and present numerical simulations obtained in this case. As possible alternative approaches, we also discuss two other update methods: a particle filter method and an optimal control method