Using agent based simulation to empirically examine complexity in carbon footprint business process

Through the critical analysis of the extant literature, it is observed that Simulation is widely used as a research method in Natural Sciences, Engineering and Social Sciences, in addition to argumentation and formalisation as the third way of carrying out research. Simulation is not so widely used in Business and Management research as it ought to have been, though this is changing for the better with the technological advances in computers and their computational power. These technological advances enhance the capability of theoretical research models, in defining a problem and their use in empirically examining a solution to the problem in simulated reality, like never before. Management journal searches for “Simulation and Complexity Theory” returned nil or zero returns, which explain that this combination is not popular in management research, though they are used individually more often. The major objective of this paper is to analyse some of the conceptual (or theoretical) and methodological (or empirical) contributions that Agent Based Simulation and Complexity Theory can make to the business and management community in their business process related research In view of this, some basic ideas are discussed of using Agent Based Simulation as a method in Business and Management Studies research and how an Agent Based Model can be applied to a business process as complex as Carbon Footprint. It is in this context that the use of Complexity as the base theory to empirically examine a business process is discussed. Throughout this article, our research on complex adaptive systems (e.g., Accounting Information System) in continuously changing organisations managing complex business processes (e.g., Carbon Footprint business process) is considered as the basis for illustrating some of the concepts. Through this article, avenues for further management research using these tools and methodology are suggested

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the dopamine D-2 receptor occupancy of olanzapine in rats

A mechanism-based PK-PD model was developed to predict the time course of dopamine D-2 receptor occupancy (D2RO) in rat striatum following administration of olanzapine, an atypical antipsychotic drug. A population approach was utilized to quantify both the pharmacokinetics and pharmacodynamics of olanzapine in rats using the exposure (plasma and brain concentration) and D2RO profile obtained experimentally at various doses (0.01-40 mg/kg) administered by different routes. A two-compartment pharmacokinetic model was used to describe the plasma pharmacokinetic profile. A hybrid physiology- and mechanism-based model was developed to characterize the D-2 receptor binding in the striatum and was fitted sequentially to the data. The parameters were estimated using nonlinear mixed-effects modeling . Plasma, brain concentration profiles and time course of D2RO were well described by the model; validity of the proposed model is supported by good agreement between estimated association and dissociation rate constants and in vitro values from literature. This model includes both receptor binding kinetics and pharmacokinetics as the basis for the prediction of the D2RO in rats. Moreover, this modeling framework can be applied to scale the in vitro and preclinical information to clinical receptor occupancy

Information storing by biomagnetites

Since the discovery of the presence of biogenic magnetites in living organisms, there have been speculations on the role that these biomagnetites play in cellular processes. It seems that the formation of biomagnetite crystals is a universal phenomenon and not an exception in living cells. Many experimental facts show that features of organic and inorganic processes could be indistinguishable at nanoscale levels. Living cells are quantum "devices" rather than simple electronic devices utilizing only the charge of conduction electrons. In our opinion, due to their unusual biophysical properties, special biomagnetites must have a biological function in living cells in general and in the brain in particular. In this paper we advance a hypothesis that while biomagnetites are developed jointly with organic molecules and cellular electromagnetic fields in cells, they can record information about the Earth's magnetic vector potential of the entire flight in migratory birds.Comment: 17 pages, 3 figure

Pharmacokinetic-Pharmacodynamic Modeling of the D2 and 5-HT2A Receptor Occupancy of Risperidone and Paliperidone in Rats

A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to describe the time course of brain concentration and dopamine D-2 and serotonin 5-HT2A receptor occupancy (RO) of the atypical antipsychotic drugs risperidone and paliperidone in rats. A population approach was utilized to describe the PK-PD of risperidone and paliperidone using plasma and brain concentrations and D-2 and 5-HT2A RO data. A previously published physiology- and mechanism-based (PBPKPD) model describing brain concentrations and D-2 receptor binding in the striatum was expanded to include metabolite kinetics, active efflux from brain, and binding to 5-HT2A receptors in the frontal cortex. A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone. The expanded PBPKPD model described brain concentrations and D-2 and 5-HT2A RO well. Inclusion of binding to 5-HT2A receptors was necessary to describe observed brain-to-plasma ratios accurately. Simulations showed that receptor affinity strongly influences brain-to-plasma ratio pattern. Binding to both D-2 and 5-HT2A receptors influences brain distribution of risperidone and paliperidone. This may stem from their high affinity for D-2 and 5-HT2A receptors. Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs

A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands

10.1371/journal.pone.0039076PLoS ONE76

Myocardial tagging by Cardiovascular Magnetic Resonance: evolution of techniques--pulse sequences, analysis algorithms, and applications

Cardiovascular magnetic resonance (CMR) tagging has been established as an essential technique for measuring regional myocardial function. It allows quantification of local intramyocardial motion measures, e.g. strain and strain rate. The invention of CMR tagging came in the late eighties, where the technique allowed for the first time for visualizing transmural myocardial movement without having to implant physical markers. This new idea opened the door for a series of developments and improvements that continue up to the present time. Different tagging techniques are currently available that are more extensive, improved, and sophisticated than they were twenty years ago. Each of these techniques has different versions for improved resolution, signal-to-noise ratio (SNR), scan time, anatomical coverage, three-dimensional capability, and image quality. The tagging techniques covered in this article can be broadly divided into two main categories: 1) Basic techniques, which include magnetization saturation, spatial modulation of magnetization (SPAMM), delay alternating with nutations for tailored excitation (DANTE), and complementary SPAMM (CSPAMM); and 2) Advanced techniques, which include harmonic phase (HARP), displacement encoding with stimulated echoes (DENSE), and strain encoding (SENC). Although most of these techniques were developed by separate groups and evolved from different backgrounds, they are in fact closely related to each other, and they can be interpreted from more than one perspective. Some of these techniques even followed parallel paths of developments, as illustrated in the article. As each technique has its own advantages, some efforts have been made to combine different techniques together for improved image quality or composite information acquisition. In this review, different developments in pulse sequences and related image processing techniques are described along with the necessities that led to their invention, which makes this article easy to read and the covered techniques easy to follow. Major studies that applied CMR tagging for studying myocardial mechanics are also summarized. Finally, the current article includes a plethora of ideas and techniques with over 300 references that motivate the reader to think about the future of CMR tagging