Generalizing Agarwal's method for the interpretation of recovery tests under non-ideal conditions

Pumping tests are performed during aquifer characterization to gain conceptual understanding about the system through diagnostic plots and to estimate hydraulic properties. Recovery tests consist of measuring head response in observation and/or pumping wells after pumping termination. They are especially useful when the pumping rate cannot be accurately controlled. They have been traditionally interpreted using Theis' recovery method, which yields robust estimates of effective transmissivity but does not provide information about the conceptual model. Agarwal proposed a method that has become standard in the oil industry, to obtain both early and late time reservoir responses to pumping from recovery data. However, the validity of the method has only been tested to a limited extent. In this work, we analyze Agarwal's method in terms of both drawdowns and log derivatives for non-ideal conditions: leaky aquifer, presence of boundaries, and one-dimensional flow. Our results show that Agarwal's method provides excellent recovery plots (i.e., the drawdown curve that would be obtained during pumping) and parameter estimates for nearly all aquifer conditions, provided that a constant pumping rate is used and the log derivative at the end of pumping is constant, which is too limiting for groundwater hydrology practice, where observation wells are usually monitored. We generalize Agarwal's method by (1) deriving an improved equivalent time for time-dependent pumping rate and (2) proposing to recover drawdown curves by extrapolating the pumping phase drawdowns. These yield excellent diagnostic plots, thus facilitating the conceptual model analysis for a broad range of conditions.Peer ReviewedPostprint (published version

Construction Effects of the Karun 4 Dam, Iran, on the Groundwater in the Adjacent Karstic Aquifer

Water Resources Planning and Managemen

Photosensitiser-gold nanoparticle conjugates for photodynamic therapy of cancer

Gold nanoparticles (AuNPs) have been extensively studied within biomedicine due to their biocompatibil- ity and low toxicity. In particular, AuNPs have been widely used to deliver photosensitiser agents for photodynamic therapy (PDT) of cancer. Here we review the state-of-the-art for the functionalisation of the gold nanoparticle surface with both photosensitisers and targeting ligands for the active targeting of cancer cell surface receptors. From the initial use of the AuNPs as a simple carrier of the photosensitiser for PDT, the field has significantly advanced to include: the use of PEGylated modification to provide aqueous compatibility and stealth properties for in vivo use; gold metal-surface enhanced singlet oxygen generation; functionalisation of the AuNP surface with biological ligands to specifically target over- expressed receptors on the surface of cancer cells and; the creation of nanorods and nanostars to enable combined PDT and photothermal therapies. These versatile AuNPs have significantly enhanced the efficacy of traditional photosensitisers for both in vitro and in vivo cancer therapy. From this review it is apparent that AuNPs have an important future in the treatment of cancer

A robust solution to resource-constraint project scheduling problem

This paper aims to propose a solution to the resource-constraint project scheduling problem (RCPSP). RCPSP is a significant scheduling problem in project management. Currently, there are insufficient studies dealing with the robustness of RCPSP. This paper improves the robustness of RCPSP and develops a Robust RCPSP, namely RRCSP. RRCSP is structured with relaxing a fundamental assumption that is 'the tasks start on time as planned'. Relaxing this assumption makes the model more realistic. The proposed solution minimizes the makespan while maximizing the robustness. Maximizing the robustness requires maximizing floating time of activities (it is NP hard). This creates more stability in the project finishing time. RCPSP stands as the root cause of many other problems such as multi-mode resourceconstrained project scheduling problems (MRCPSP), multi-skill resource-constrained project scheduling problem (MSRCPSP), or similar problems and hence proposing a solution to this problem contributes to pave a new line for future research in other mentioned areas. The applicability of the proposed model is examined through a numerical example