Search

An Aqueous Redox Flow Battery (ARFB) has emerged as a sustainable option for large-scale energy storage systems due to its relatively low cost and abundant raw materials. However, there exists a pressing need to enhance its power density and energy efficiency by addressing limitations such as low stability and poor solubility of redox-active species. In this study, we present a systematic analysis of an asymmetric viologen-based negolyte named MMV (1-methyl-4,4′-bipyridinium iodide) and its detailed comparative study with N,N′-dimethyl-4,4′-bipyridinium diiodide (dimethyl viologen (DMV)). Following extensive electrochemical characterization, we constructed an alkaline MMV battery paired with the potassium ferro/ferricyanide posolyte at a higher concentration (0.8 M), yielding a cell voltage of 1.25 V, nearly equivalent to those of vanadium RFBs. Remarkably, long-term cycling with 97% coulombic efficiency (CE) and 71% energy efficiency (EE) was achieved at a current density of 60 mA cm−2. Furthermore, we observed 99% capacity retention over 100 cycles and 75% capacity retention over 500 charge/discharge cycles. Additionally, we performed a detailed Density Functional Theory (DFT) analysis of MMV. This study underscores the importance of inhibiting dimer formation in viologen derivatives and positions MMV as a promising negolyte surpassing DMV. [ABSTRACT FROM AUTHOR]

We analyzed the planning problem for HIV screening, testing, and care. This problem consists of determining the optimal fraction of patients to be screened in every period as well as the optimum staffing level at each part of the healthcare system to maximize the total health benefits to the patients measured by quality-adjusted life-years (QALYs) gained. We modeled this problem as a nonlinear mixed integer programming program comprising disease progression (the transition of the patients across health states), system dynamics (the flow of patients in different health states across various parts of the healthcare delivery system), and budgetary and capacity constraints. We applied the model to the Greater Los Angeles (GLA) station in the Veterans Health Administration system. We found that a Centers for Disease Control and Prevention recommended routine screening policy in which all patients visiting the system are screened for HIV irrespective of risk factors may not be feasible because of budgetary constraints. Consequently, we used the model to develop and evaluate managerially relevant policies within existent capacity and budgetary constraints to improve upon the current risk based screening policy of screening only high risk patients. Our computational analysis showed that the GLA station can achieve substantial increase (20% to 300%) in the QALYs gained by using these policies over risk based screening. The GLA station has already adapted two of these policies that could yield better patient health outcomes over the next few years. In addition, our model insights have influenced the decision making process at this station.

We consider the Retail Planning Problem in which the retailer chooses suppliers, and determines the production, distribution and inventory planning for products with uncertain demand in order to minimize total expected costs. This problem is often faced by large retail chains that carry private label products. We formulate this problem as a convex mixed integer program and show that it is strongly NP-hard. We determine a lower bound by applying a Lagrangean relaxation and show that this bound out- performs the standard convex programming relaxation, while being computationally efficient. We also establish a worst-case error bound for the Lagrangean relaxation. We then develop heuristics to generate feasible solutions. Our computational results indicate that our convex programming heuristic yields feasible solutions that are close to optimal with an average suboptimality gap at 3.4%. We also develop managerial insights for practitioners who choose suppliers, and make production, distribution and inventory decisions in the supply chain.

We consider a competitive version of the traditional aggregate production planning model with capacity constraints. In the general case, multiple products are produced by a group of competing producers with limited capacities. Production quantities, prices and consequently profits depend on production and allocation decisions of each producer. In addition, there is competition for the raw material whose supplies are limited, and where prices reflect these limitations. Such situations have recently occurred in several process industry settings including the petro-refining and metal processing sectors, such as steel and copper. We use a successive “Bertrand-Cournot” framework to address this problem and to determine optimal production quantities, prices and profits at the producers and at the raw material supplier.

Kaushik Rajaram,1 Patricia Losada-Pérez,2,3 Veronique Vermeeren,1 Baharak Hosseinkhani,1 Patrick Wagner,2,4 Veerle Somers,1 Luc Michiels1 1Biomedical Research Institute (BIOMED), Hasselt University, Hasselt, 2Institute for Materials Research (IMO), Hasselt University, 3IMEC vzw, Division IMOMEC, Diepenbeek, 4Soft Matter and Biophysics Section, Department of Physics and Astronomy, KU Leuven, Leuven, Belgium Abstract: Over the last three decades, phage display technology has been used for the display of target-specific biomarkers, peptides, antibodies, etc. Phage display-based assays are mostly limited to the phage ELISA, which is notorious for its high background signal and laborious methodology. These problems have been recently overcome by designing a dual-display phage with two different end functionalities, namely, streptavidin (STV)-binding protein at one end and a rheumatoid arthritis-specific autoantigenic target at the other end. Using this dual-display phage, a much higher sensitivity in screening specificities of autoantibodies in complex serum sample has been detected compared to single-display phage system on phage ELISA. Herein, we aimed to develop a novel, rapid, and sensitive dual-display phage to detect autoantibodies presence in serum samples using quartz crystal microbalance with dissipation monitoring as a sensing platform. The vertical functionalization of the phage over the STV-modified surfaces resulted in clear frequency and dissipation shifts revealing a well-defined viscoelastic signature. Screening for autoantibodies using antihuman IgG-modified surfaces and the dual-display phage with STV magnetic bead complexes allowed to isolate the target entities from complex mixtures and to achieve a large response as compared to negative control samples. This novel dual-display strategy can be a potential alternative to the time consuming phage ELISA protocols for the qualitative analysis of serum autoantibodies and can be taken as a departure point to ultimately achieve a point of care diagnostic system. Keywords: dual-display phage, surface plasmon resonance, quartz crystal microbalance, dissipation monitoring, streptavidin-binding protein, rheumatoid arthritis