Differential activation of neuronal populations can improve the efficacy of clinical devices such as sensory or cortical prostheses. Improving stimulus specificity will facilitate targeted neuronal activation to convey biologically realistic percepts. In order to deliver more complex stimuli to a neuronal population, stimulus optimization techniques must be developed that will enable a single electrode to activate subpopulations of neurons. However, determining the stimulus needed to evoke targeted neuronal activity is challenging. To find the most selective waveform for a particular population, we apply an optimization-based search routine, Powell’s conjugate direction method, to systematically search the stimulus waveform space. This routine utilizes a 1-D sigmoid activation model and a 2-D strength⁻duration curve to measure neuronal activation throughout the stimulus waveform space. We implement our search routine in both an experimental study and a simulation study to characterize... [more]

Tuberculosis (TB) is one of the most common infectious diseases worldwide. It is estimated that one-third of the world’s population is infected with TB. Most have the latent stage of the disease that can later transition to active TB disease. TB is spread by aerosol droplets containing Mycobacterium tuberculosis (Mtb). Mtb bacteria enter through the respiratory system and are attacked by the immune system in the lungs. The bacteria are clustered and contained by macrophages into cellular aggregates called granulomas. These granulomas can hold the bacteria dormant for long periods of time in latent TB. The bacteria can be perturbed from latency to active TB disease in a process called granuloma activation when the granulomas are compromised by other immune response events in a host, such as HIV, cancer, or aging. Dysregulation of matrix metalloproteinase 1 (MMP-1) has been recently implicated in granuloma activation through experimental studies, but the mechanism is not well understood.... [more]

Calculation of evaporation requires accurate thermophysical properties of the liquid. Such data are well-known for conventional fossil fuels. In contrast, e.g., thermal conductivity or dynamic viscosity of the fuel vapor are rarely available for modern liquid fuels. To overcome this problem, molecular models can be used. Currently, the measurement-based properties of n-heptane and diesel oil are compared with estimated values, using the state-of-the-art molecular models to derive the temperature-dependent material properties. Then their effect on droplet evaporation was evaluated. The critical parameters were liquid density, latent heat of vaporization, boiling temperature, and vapor thermal conductivity where the estimation affected the evaporation time notably. Besides a general sensitivity analysis, evaporation modeling in a practical burner ended up with similar results. By calculating droplet motion, the evaporation number, the evaporation-to-residence time ratio can be derived. A... [more]

The pennate diatom Phaeodactylum tricornutum is a model organism able to synthesize industrially-relevant molecules. Commercial-scale cultivation currently requires large monocultures, prone to bio-contamination. However, little is known about the identity of the invading organisms. To reduce the complexity of natural systems, we systematically investigated the microbiome of non-axenic P. tricornutum cultures from a culture collection in reproducible experiments. The results revealed a dynamic bacterial community that developed differently in “complete” and “minimal” media conditions. In complete media, we observed an accelerated “culture crash”, indicating a more stable culture in minimal media. The identification of only four bacterial families as major players within the microbiome suggests specific roles depending on environmental conditions. From our results we propose a network of putative interactions between P. tricornutum and these main bacterial factions. We demonstrate that,... [more]

The moisture content of biomass affects its processing for applications such as electricity or steam. In this study, the effects of variation in moisture content of banagrass and energycane was evaluated using techno-economic analysis and life-cycle assessments. A 25% loss of moisture was assumed as a variation that was achieved by field drying the biomass. Techno-economic analysis revealed that high moisture in the biomass was not economically feasible. Comparing banagrass with energycane, the latter was more economically feasible; thanks to the low moisture and ash content in energycane. About 32 GWh/year of electricity was produced by field drying 60,000 dry MT/year energycane. The investment for different scenarios ranged between $17 million and $22 million. Field-dried energycane was the only economically viable option that recovered the investment after 11 years of operation. This scenario was also more environmentally friendly, releasing 16-gCO₂ equivalent/MJ of electricity prod... [more]

The systematic design of an advanced and efficient control strategy for controlling critical quality attributes of the tablet compaction operation is necessary to increase the robustness of a continuous pharmaceutical manufacturing process and for real time release. A process model plays a very important role to design, evaluate and tune the control system. However, much less attention has been made to develop a validated control relevant model for tablet compaction process that can be systematically applied for design, evaluation, tuning and thereby implementation of the control system. In this work, a dynamic tablet compaction model capable of predicting linear and nonlinear process responses has been successfully developed and validated. The nonlinear model is based on a series of transfer functions and static polynomial models. The model has been applied for control system design, tuning and evaluation and thereby facilitate the control system implementation into the pilot-plant wi... [more]

Modern data, such as occurring in chemical engineering, typically entail large collections of samples with numerous dimensional components (or attributes). Visualizing the samples in relation of these components can bring valuable insight. For example, one may be able to see how a certain chemical property is expressed in the samples taken. This could reveal if there are clusters and outliers that have specific distinguishing properties. Current multivariate visualization methods lack the ability to reveal these types of information at a sufficient degree of fidelity since they are not optimized to simultaneously present the relations of the samples as well as the relations of the samples to their attributes. We propose a display that is designed to reveal these multiple relations. Our scheme is based on the concept of RadViz, but enhances the layout with three stages of iterative refinement. These refinements reduce the layout error in terms of three essential relationships—sample to... [more]

Microbial Fuel Cells (MFCs) represent a still relatively new technology for liquid organic waste treatment and simultaneous recovery of energy and resources. Although the technology is quite appealing due its potential benefits, its practical application is still hampered by several drawbacks, such as systems instability (especially when attempting to scale-up reactors from laboratory prototypes), internally competing microbial reactions, and limited power generation. This paper is an attempt to address some of the issues related to MFC application in wastewater treatment with a simulation model. Reactor configuration, operational schemes, electrochemical and microbiological characterization, optimization methods and modelling strategies were reviewed and have been included in a mathematical simulation model written with a multidisciplinary, multi-perspective approach, considering the possibility of feeding real substrates to an MFC system while dealing with a complex microbiological p... [more]

Various distance metrics and their induced norms are employed in the quantitative modeling of evolutionary dynamics. Minimization of these distance metrics, when applied to evolutionary optimization, are hypothesized to result in different outcomes. Here, we apply the different distance metrics to the evolutionary trait dynamics brought about by the interaction between two competing species infected by parasites (exploiters). We present deterministic cases showing the distinctive selection outcomes under the Manhattan, Euclidean, and Chebyshev norms. Specifically, we show how they differ in the time of convergence to the desired optima (e.g., no disease), and in the egalitarian sharing of carrying capacity between the competing species. However, when randomness is introduced to the population dynamics of parasites and to the trait dynamics of the competing species, the distinctive characteristics of the outcomes under the three norms become indistinguishable. Our results provide theore... [more]

The development of molecularly imprinted polymers (MIPs) to target polyphenols present in vegetable extracts was here addressed. Polydatin was selected as a template polyphenol due to its relatively high size and amphiphilic character. Different MIPs were synthesized to explore preferential interactions between the functional monomers and the template molecule. The effect of solvent polarity on the molecular imprinting efficiency, namely owing to hydrophobic interactions, was also assessed. Precipitation and suspension polymerization were examined as a possible way to change MIPs morphology and performance. Solid phase extraction and batch/continuous sorption processes were used to evaluate the polyphenols uptake/release in individual/competitive assays. Among the prepared MIPs, a suspension polymerization synthesized material, with 4-vinylpyridine as the functional monomer and water/methanol as solvent, showed a superior performance. The underlying cause of such a significant outcome... [more]

Clinical trial planning of candidate drugs is an important task for pharmaceutical companies. In this paper, we propose two new multistage stochastic programming formulations (CM1 and CM2) to determine the optimal clinical trial plan under uncertainty. Decisions of a clinical trial plan include which clinical trials to start and their start times. Its objective is to maximize expected net present value of the entire clinical trial plan. Outcome of a clinical trial is uncertain, i.e., whether a potential drug successfully completes a clinical trial is not known until the clinical trial is completed. This uncertainty is modeled using an endogenous uncertain parameter in CM1 and CM2. The main difference between CM1 and CM2 is an additional binary variable, which tracks both start and end time points of clinical trials in CM2. We compare the sizes and solution times of CM1 and CM2 with each other and with a previously developed formulation (CM3) using different instances of clinical trial... [more]

We present a generalized state-space model formulation particularly motivated by an online scheduling perspective, which allows modeling (1) task-delays and unit breakdowns; (2) fractional delays and unit downtimes, when using discrete-time grid; (3) variable batch-sizes; (4) robust scheduling through the use of conservative yield estimates and processing times; (5) feedback on task-yield estimates before the task finishes; (6) task termination during its execution; (7) post-production storage of material in unit; and (8) unit capacity degradation and maintenance. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings. Finally, we demonstrate the effectiveness of this model on a case study from the field of bio-manufacturin... [more]

Mesoporous alumina and magnesia were prepared using various polymers, poly(ethylene glycol) (PEG), poly(vinyl alcohol) (PVA), poly(N-(2-hydroxypropyl) methacrylamide) (PHPMA), and poly(dimethylacrylamide) (PDMAAm), as porogenic structure matrices. Mesoporous alumina exhibits large Brunauer⁻Emmett⁻Teller (BET) surface areas up to 365 m² g−1, while mesoporous magnesium oxide possesses BET surface areas around 111 m² g−1. Variation of the polymers has little impact on the structural properties of the products. The calcination of the polymer/metal oxide composite materials benefits from the fact that the polymer decomposition is catalyzed by the freshly formed metal oxide.

This paper discusses a problem connected with the production process of ductile iron castings made using the in-mold method. The study results are presented showing that this method compromises the quality of the cast machine parts and of the equipment itself. Specifics of the nodularization process using the in-mold method do not provide the proper conditions for removal of chemical reaction products to the slag, i.e., the products stay in the mold cavity and they also decrease the quality of the casting. In this work, corrosion-type defects were diagnosed mostly on the surface of the casting and some compounds in the near-surface layer—i.e., fayalite (Fe₂SiO₄) and forsterite (Mg₂SiO₄)—which cause discontinuities in the metal matrix. The results presented here were selected based on experimental melts of ductile iron. The elements of the mold used in this study, the shape of the mixing chamber, charge materials, method of melting, temperature of liquid metal, etc. were directly relate... [more]

Mineral calcination worldwide accounts for some 5⁻10% of all anthropogenic carbon dioxide (CO₂) emissions per year. Roughly half of the CO₂ released results from burning fossil fuels for heat generation, while the other half is a product of the calcination reaction itself. Traditionally, the fuel combustion process and the calcination reaction take place together to enhance heat transfer. Systems have been proposed that separate fuel combustion and calcination to allow for the sequestration of pure CO₂ from the calcination reaction for later storage/use and capture of the combustion gases. This work presents a new tube-in-tube helical system for the calcination of minerals that can use different heat transfer fluids (HTFs), employed or foreseen in concentrated solar power (CSP) plants. The system is labeled ‘flameless’ since the HTF can be heated by other means than burning fossil fuels. If CSP or high-temperature nuclear reactors are used, direct CO₂ emissions can be divided in half.... [more]

Ecological mechanisms influence relationships among microbial communities, which in turn impact biogeochemistry. In particular, microbial communities are assembled by deterministic (e.g., selection) and stochastic (e.g., dispersal) processes, and the relative balance of these two process types is hypothesized to alter the influence of microbial communities over biogeochemical function. We used an ecological simulation model to evaluate this hypothesis, defining biogeochemical function generically to represent any biogeochemical reaction of interest. We assembled receiving communities under different levels of dispersal from a source community that was assembled purely by selection. The dispersal scenarios ranged from no dispersal (i.e., selection-only) to dispersal rates high enough to overwhelm selection (i.e., homogenizing dispersal). We used an aggregate measure of community fitness to infer a given community’s biogeochemical function relative to other communities. We also used ecol... [more]

Big Data may introduce new opportunities, and for this reason it has become a mantra among most industries. This paper focuses on examining how to develop cost and sustainable reporting by utilizing Big Data that covers economic values, production volumes, and emission information. We assume strongly that this use supports cleaner production, while at the same time offers more information for revenue and profitability development. We argue that Big Data brings company-wide business benefits if data queries and interfaces are built to be interactive, intuitive, and user-friendly. The amount of information related to operations, costs, emissions, and the supply chain would increase enormously if Big Data was used in various manufacturing industries. It is essential to expose the relevant correlations between different attributes and data fields. Proper algorithm design and programming are key to making the most of Big Data. This paper introduces ideas on how to refine raw data into valua... [more]

The bottleneck in creating dynamic models of biological networks and processes often lies in estimating unknown kinetic model parameters from experimental data. In this regard, experimental conditions have a strong influence on parameter identifiability and should therefore be optimized to give the maximum information for parameter estimation. Existing model-based design of experiment (MBDOE) methods commonly rely on the Fisher information matrix (FIM) for defining a metric of data informativeness. When the model behavior is highly nonlinear, FIM-based criteria may lead to suboptimal designs, as the FIM only accounts for the linear variation in the model outputs with respect to the parameters. In this work, we developed a multi-objective optimization (MOO) MBDOE, for which the model nonlinearity was taken into consideration through the use of curvature. The proposed MOO MBDOE involved maximizing data informativeness using a FIM-based metric and at the same time minimizing the model cur... [more]

Carbon dioxide conversion and utilization is gaining significant attention worldwide, not only because carbon dioxide has an impact on global climate change, but also because it provides a source for potential fuels and chemicals. Methanol is an important fuel that can be obtained by the hydrogenation of carbon dioxide. In this research, the modeling of a reactor to produce methanol using carbon dioxide and hydrogen is carried out by way of an ANOVA and a central composite design. Reaction temperature, reaction pressure, H₂/CO₂ ratio, and recycling are the chosen factors, while the methanol production and the reactor volume are the studied responses. Results show that the interaction AC is common between the two responses and allows improvement of the productivity in reducing the volume. A mathematical model for methanol production and reactor volume is obtained with significant factors. A central composite design is used to optimize the process. Results show that a higher productivity... [more]

A model predictive control (MPC) framework, exploiting both feedforward and feedback control loops, is employed to minimize large disturbances that occur in military water networks. Military installations’ need for resilient and efficient water supplies is often challenged by large disturbances like fires, terrorist activity, troop training rotations, and large scale leaks. This work applies the effectiveness of MPC to provide predictive capability and compensate for vast geographical differences and varying phenomena time scales using computational software and actual system dimensions and parameters. The results show that large disturbances are rapidly minimized while maintaining chlorine concentration within legal limits at the point of demand and overall water usage is minimized. The control framework also ensures pumping is minimized during peak electricity hours, so costs are kept lower than simple proportional control. Thecontrol structure implemented in this work is able to sup... [more]

Enormous advances in genetics and metabolic engineering have made it possible, in principle, to create new plants and crops with improved yield through targeted molecular alterations. However, while the potential is beyond doubt, the actual implementation of envisioned new strains is often difficult, due to the diverse and complex nature of plants. Indeed, the intrinsic complexity of plants makes intuitive predictions difficult and often unreliable. The hope for overcoming this challenge is that methods of data mining and computational systems biology may become powerful enough that they could serve as beneficial tools for guiding future experimentation. In the first part of this article, we review the complexities of plants, as well as some of the mathematical and computational methods that have been used in the recent past to deepen our understanding of crops and their potential yield improvements. In the second part, we present a specific case study that indicates how robust models... [more]

The primary objective of this work was to investigate the thermal and rheological properties of crude tall oil (CTO), a low-cost by-product from the Kraft pulping process, as a potential feedstock for biodiesel production. Adequate knowledge of CTO properties is a prerequisite for the optimal design of a cost-effective biodiesel process and related processing equipment. The study revealed the correlation between the physicochemical properties, thermal, and rheological behavior of CTO. It was established that the trans/esterification temperature for CTO was greater than the temperature at which viscosity of CTO entered a steady-state. This information is useful in the selection of appropriate agitation conditions for optimal biodiesel production from CTO. The point of interception of storage modulus (G′) and loss modulus (G′′) determined the glass transition temperature (40 °C) of CTO that strongly correlated with its melting point (35.3 °C). The flow pattern of CTO was modeled as a non... [more]

This article describes the development of a reaction database with the objective to collect data for multiphase reactions involved in small molecule pharmaceutical processes with a search engine to retrieve necessary data in investigations of reaction-separation schemes, such as the role of organic solvents in reaction performance improvement. The focus of this reaction database is to provide a data rich environment with process information available to assist during the early stage synthesis of pharmaceutical products. The database is structured in terms of reaction classification of reaction types; compounds participating in the reaction; use of organic solvents and their function; information for single step and multistep reactions; target products; reaction conditions and reaction data. Information for reactor scale-up together with information for the separation and other relevant information for each reaction and reference are also available in the database. Additionally, the ret... [more]

In recent years gas⁻liquid flow in microchannels has drawn much attention in the research fields of analytics and applications, such as in oxidations or hydrogenations. Since surface forces are increasingly important on the small scale, bubble coalescence is detrimental and leads to Taylor bubble flow in microchannels with low surface-to-volume ratio. To overcome this limitation, we have investigated the gas⁻liquid flow through micronozzles and, specifically, the bubble breakup behind the nozzle. Two different regimes of bubble breakup are identified, laminar and turbulent. Turbulent bubble breakup is characterized by small daughter bubbles and narrow daughter bubble size distribution. Thus, high interfacial area is generated for increased mass and heat transfer. However, turbulent breakup mechanism is observed at high flow rates and increased pressure drops; hence, large energy input into the system is essential. In this work Design of Experiment assisted evaluation of turbulent bubbl... [more]

Data reconciliation is a model-based technique that reduces measurement errors by making use of redundancies in process data. It is largely applied in modern process industries, being commercially available in software tools. Based on industrial applications reported in the literature, we have identified and tested different configuration settings providing a numerical assessment on the performance of several important aspects involved in the solution of nonlinear steady-state data reconciliation that are generally overlooked. The discussed items are comprised of problem formulation, regarding the presence of estimated parameters in the objective function; solution approach when applying nonlinear programming solvers; methods for estimating objective function gradients; initial guess; and optimization algorithm. The study is based on simulations of a rigorous and validated model of a real offshore oil production system. The assessment includes evaluations of solution robustness, constr... [more]