Simulation-based workforce assignment in a multi-organizational social network for alliance-based software development

The development of alliance-based software requires the collaboration of many stakeholders. These different stakeholders across multiple organizations form a complex social network. The goal of this paper is to develop a novel modeling framework, which will help task managers devise optimal workforce assignments considering both short-term and long-term aspects of the software development process. The proposed framework is composed of an assignment module and a prediction module. For a given task, the assignment module first selects a candidate workforce mix. Based on the candidate workforce mix, the prediction module then predicts the short-term performance (productivity) as well as the long-term performance (workforce training and robustness of the organization) of the organization. Then, the assignment module selects another candidate mix, and this iteration continues until an optimal workforce mix is found. The prediction module and the assignment module are based on an agent-based simulation method and a multi-objective optimization model, respectively. The proposed modeling framework is illustrated with a software enhancement request process in Kuali, an alliance-based open source software development project involving 12 organizations. The constructed framework is executed with varying parameters to demonstrate its use and benefit in the software enhancement process.     

Hybrid simulation and optimization-based design and operation of integrated photovoltaic generation,storage units,and grid

Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control extremely difficult and requires storage units as an additional concern. The goal of this research is to design and develop a flexible tool, which will allow us to obtain (1) an optimal capacity of an integrated photovoltaic (PV) system and storage units and (2) an optimal operational decision policy considering the current and future market prices of the electricity. The proposed tool is based on hybrid (system dynamics model and agent-based model) simulation and meta-heuristic optimization. In particular, this tool has been developed for three different scenarios (involving different geographical scales), where PV-based solar generators, storage units (compressed-air-energy-storage (CAES) and super-capacitors), and grid are used in an integrated manner to supply energy demands. Required data has been gathered from various sources, including NASA and TEP (utility company), US Energy Information Administration, National Renewable Energy Laboratory, commercial PV panel manufacturers, and publicly available reports. The constructed tool has been demonstrated to (1) test impacts of several factors (e.g. demand growth, efficiencies in PV panel and CAES system) on the total cost of the integrated generation and storage system and an optimal mixture of PV generation and storage capacity, and to (2) demonstrate an optimal operational policy.     

Simultaneous extraction of source and drain resistances in top contact organic thin film transistors from a single test structure

A method of extraction of source and drain resistances in linear mode of operation from a single transistor is described. The proposed method can also be used to measure source resistance over the entire operating range from linear to saturation mode of operation. The method uses two floating probes outside the channel, one adjacent to the source and the other to the drain to sense the voltage under these contacts. Using transmission line analysis, the source and drain resistances are directly extracted from these measurements. 2D numerical simulation results confirm the validity of the proposed technique and sensitivity analysis shows that the method is more accurate than the conventional gated four probe technique, especially, when the source resistance is much smaller than the channel resistance. Experimental results obtained with Pentacene top-contact transistors are used to illustrate the proposed technique. Analysis of two devices with very different source resistance is carried out to highlight the ability of the proposed technique to offer insight into the different contributing factors. Current crowding under the source contact and accurate estimation of mobility without the distorting effects of source resistance are also described.     

N ‐acetylcysteine–PLGA nano‐conjugate: effects on cellular toxicity and uptake of gadopentate dimeglumine

Gadolinium as a contrast agent in MRI technique combined with DTPA causes contrast induced nephropathy (CIN) and nephrogenic systemic fibrosis (NSF) which can reduce by usage of antioxidants such as N‐acetyl cysteine by increasing the membrane''s permeability leads to lower cytotoxicity. In this study, N ‐acetyl cysteine‐PLGA Nano‐conjugate was synthesized according to stoichiometric rules of molar ratios andafter assessment by FTIR, NMR spectroscopy and Atomic Force Microscopy (AFM) imaging was combined with Magnevist® (gadopentetate dimeglumine) and its effects on the renal cells were evaluated. MTT [3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐Diphenyltetrazolium Bromide] and cellular uptake assays have indicated relatively significant toxicity of magnevist (P  < 0.05) on three cell lines including HEK293, MCF7 and L929 compared to other synthesized ligands that shown no toxicity. Moreover, systemic evaluation has shown no notable changes of blood urea nitrogen (BUN) and creatinine in kidney of mice. In consequence, antioxidant effect was increased as well as the renal toxicity of the contrast agent reduced at the cell level. As a result, PLGA‐NAC nano‐conjugate can be a promising choice for decreasing the magnevist toxicity for treatment and prevention of CIN and will be able to open a new horizon to research on reduction of toxicity of contrast agents by using nanoparticles.Inspec keywords: blood, toxicology, nanofabrication, cellular biophysics, biomedical materials, nanoparticles, chromatography, cancer, biodegradable materials, biomedical MRI, kidney, pH, nanomedicine, patient treatment, diseases, atomic force microscopy, Fourier transform infrared spectraOther keywords: cellular toxicity, gadopentate dimeglumine, contrast agent, magnetic resonance imaging technique, diethylenetriamine pentaacetate, contrast‐induced nephropathy, nephrogenic systemic fibrosis, stoichiometric rules, molar ratios, dimethyl sulphoxide solution, chromatography techniques, nuclear magnetic resonance spectroscopy, atomic force microscopy imaging, Magnevist®, gadopentetate dimeglumine, renal cells, MTT cytotoxicity, human embryonic kidney‐293, L929 cell lines, in vitro conditions, cellular uptake assays, Magnevist uptake, antioxidant effect, renal toxicity, cell level, PLGA nanocarrier, acetylcysteine nanoconjugate, Magnevist toxicity, N‐acetylcysteine–PLGA nano‐conjugate, N‐acetyl cysteine‐poly‐lactic‐co‐glycolic acid nanoconjugate     

An improved solar cell circuit model for organic solar cells

The validity of conventional circuit model for interpreting results obtained using organic solar cells is examined. It is shown that the central assumption in the model that photo-generated current remains constant from short-circuit to open-circuit condition may not hold for organic cells. An improved model based on the photovoltaic response of organic solar cells is proposed and a method of extracting the parameters of the model is presented.     

Properties of ultra-thin wafer-bonded silicon-on-insulator MOSFET's

Strong interface coupling effects on the subthreshold and transconductance characteristics have been experimentally observed and analytically modeled. For total depletion, the subthreshold swing reaches a nearly ideal value. The front channel subthreshold slope of ultrathin MOSFETs is very sensitive to the density of states at the buried Si-SiO₂ interface so that a thicker fully depleted film is preferable when the quality of this interface is poor. The transconductance reaches a maximum for total depletion. Simple theoretical models are proposed which explain the substantial variations of the transconductance and subthreshold slope as the opposite interface is scanned from inversion to total depletion and accumulation. These MOSFETs behave very well and demonstrate that high carrier mobilities and low densities of defects can be obtained at both interfaces even in ultrathin silicon-on-insulator (SOI) structures     

Hybrid agent-based simulation for policy evaluation of solar power generation systems

To encourage the adoption of solar power as well as new technological improvements in solar industry, state and federal governments have employed various kinds of incentives over the past decades, such as rebates, tax return opportunities, and Net Metering credits. At the same time, however, the governments concern regulations to avoid highly steep growth of solar energy without considering necessary supporting structure such as storage components, which will increase the electricity price and threaten the stability of existing transmission systems. The goal of this research is to develop a decision support tool to analyze the effectiveness of various policies (both incentives as well as regulations) on the proper growth rate of distributed photovoltaic (PV) systems avoiding the instability of the transition system or steep rising of the electricity price. To this end, we propose a hybrid two-level simulation modeling framework, which is significantly more detailed than the simplified structures commonly used in most policy evaluations. The lower-level model concerns the calculation of PV system payback period of individual household based on hourly electricity generation (PV) and consumptions, incentive levels, PV module price, and hourly electricity price (grid). The higher-level model, running on a weekly basis for 20 years, concerns the household adoption behaviors of the PV systems influenced by various factors, including payback period, household income, word-of-mouth effect and advertisement effect. Agent-based and system dynamics modeling techniques are leveraged in both levels. The proposed models have been developed for residential areas at two different regions in the US based on real data, which have been used to illustrate the impact of policies in different regions.     

Minimum-error discrimination between two sets of similarity-transformed quantum states

Using the equality form of the necessary and sufficient conditions introduced in Jafarizadeh (Phys Rev A 84:012102 (9 pp), 2011), minimum error discrimination between states of the two sets of equiprobable similarity transformed quantum qudit states is investigated. In the case that the unitary operators describing the similarity transformations are generating sets of two irreducible representations and the states fulfill a certain constraint, the optimal set of measurements and the corresponding maximum success probability of discrimination are determined in closed form. In the cases that they are generating sets of reducible representations, there exist no closed-form formula in general, but the procedure can be applied properly in each case provided that the states obey some constraints. Finally, we give the maximum success probability of discrimination and optimal measurement operators for some important examples of mixed quantum states, such as generalized Bloch sphere m-qubit states, qubit states and their three special cases.