Biomass feedstock preprocessing and long‐distance transportation logistics

Biomass‐based biofuels have gained attention because they are renewable energy sources that could facilitate energy independence and improve rural economic development. As biomass supply and biofuel demand areas are generally not geographically contiguous, the design of an efficient and effective biomass supply chain from biomass provision to biofuel distribution is critical to facilitate large‐scale biofuel development. This study compared the costs of supplying biomass using three alternative biomass preprocessing and densification technologies (pelletizing, briquetting, and grinding) and two alternative transportation modes (trucking and rail) for the design of a four‐stage biomass–biofuel supply chain in which biomass produced in Illinois is used to meet biofuel demands in either California or Illinois. The BioScope optimization model was applied to evaluate a four‐stage biomass–biofuel supply chain that includes biomass supply, centralized storage and preprocessing (CSP), biorefinery, and ethanol distribution. We examined the cost of 15 scenarios that included a combination of three biomass preprocessing technologies and five supply chain configurations. The findings suggested that the transportation costs for biomass would generally follow the pattern of coal transportation. Converting biomass to ethanol locally and shipping ethanol over long distances is most economical, similar to the existing grain‐based biofuel system. For the Illinois–California supply chain, moving ethanol is Biomass‐based biofuels have gained attention because they are renewable energy sources that could facilitate energy independence and improve rural economic development. As biomass supply and biofuel demand areas are generally not geographically contiguous, the design of an efficient and effective biomass supply chain from biomass provision to biofuel distribution is critical to facilitate large‐scale biofuel development. This study compared the costs of supplying biomass using three alternative biomass preprocessing and densification technologies (pelletizing, briquetting, and grinding) and two alternative transportation modes (trucking and rail) for the design of a four‐stage biomass–biofuel supply chain in which biomass produced in Illinois is used to meet biofuel demands in either California or Illinois. The BioScope optimization model was applied to evaluate a four‐stage biomass–biofuel supply chain that includes biomass supply, centralized storage and preprocessing (CSP), biorefinery, and ethanol distribution. We examined the cost of 15 scenarios that included a combination of three biomass preprocessing technologies and five supply chain configurations. The findings suggested that the transportation costs for biomass would generally follow the pattern of coal transportation. Converting biomass to ethanol locally and shipping ethanol over long distances is most economical, similar to the existing grain‐based biofuel system. For the Illinois–California supply chain, moving ethanol is $0.24 gal^?1 less costly than moving biomass even in densified form over long distances. The use of biomass pellets leads to lower overall costs of biofuel production for long‐distance transportation but to higher costs if used for short‐distance movement due to its high capital and processing costs. Supported by the supply chain optimization modeling, the cellulosic‐ethanol production and distribution costs of using Illinois feedstock to meet California demand are $0.08 gal^?1 higher than that for meeting local Illinois demand.     

A New Tradeoff Model for Fuzzy Supply Chain Network Design and Optimization

This article proposes a novel mixed integer linear programming model for solving a fuzzy supply chain network (SCN) design problem. This problem includes fuzzy parameters, choosing suppliers according to their quality of raw materials, and the supplier's engagement contracts. There is a tradeoff between raw material quality, and its purchasing and reprocessing costs. If a decision-maker (DM) wishes to work with a supplier that supplies a low-quality raw material, this raw material may be in need of reprocessing. To avoid the reprocessing costs, a supplier that provides a high-quality raw material can be chosen, but in this case the DM faces a high purchasing cost. An integrated fuzzy SCN system that consists of multiple suppliers, manufacturers, distribution centers, and retailers is considered in order to address problems under the aforementioned tradeoffs. Finally, concluding remarks and suggestions for future work are presented.     

Pollution and Cost in the Coke-Making Supply Chain in Shanxi Province, China

An integrated system trade-off model has been developed to assess costs and pollution associated with transportation in the coke-making supply chain in Shanxi Province, China. A transportation-flow, cost-minimization solver is combined with models for calculating coke-making plant costs, estimating transportation costs from a geographic information system road and rail database, and aggregating coke-making capacity among plants. Model outputs of economic cost, nitrogen oxides (NO_x) emissions, and transport distributions are visualized using an Internet-based graphic user interface. Data for the model were collected on survey trips to Shanxi Province as well as from secondary references and proxies. The modularity and extensibility of the system trade-off model facilitate introduction of new data sets in order to examine various planning scenarios.
Scenarios of coke-making plant aggregation, rail infrastructure improvement, and technology transfer were evaluated using the model. Costs and pollution emissions can be reduced by enlarging coke-making plants near the rail stations and closing down other plants. Preferential minimization of transportation costs gives a lower total cost than simply minimizing plant costs. Therefore, policy makers should consider transportation costs when planning the reallocation of coke-making capacity in Shanxi Province. Increasing rail-transport capacity is less effective than aggregating plant capacity. On the other hand, transfer of low-pollution truck technology results in a large emission reduction, however, reflecting the importance of truck transportation in the Shanxi Province coke-making industry.     

Informing Packaging Design Decisions at Toyota Motor Sales Using Life Cycle Assessment and Costing

Throughout their life cycle stages—material production, package manufacture, distribution, end-of-life management—packaging systems consume natural resources and energy, generate waste, and emit pollutants. Each of these stages also carries a financial cost. Motivated by a desire to decrease environmental burdens while reducing financial costs associated with the packaging of accessory and service parts, Toyota Motor Sales (TMS) partnered with the Donald Bren School of Environmental Science & Management to build a life cycle assessment and costing tool to support packaging design decisions. The resulting Environmental Packaging Impact Calculator (EPIC) provides comprehensive life cycle assessment (LCA) and life cycle costing (LCC). It allows packaging designers to identify environmentally and economically preferable packaging systems in daily decision-making. EPIC's parameterized process flow model allows users to assess many different packaging systems using a single model. Its input/output interface is designed for users without preexisting knowledge of LCA theory or practice and calculates results based on relatively few input data. The main motivation behind this environmental design tool is to provide relevant information to those individuals who are in the best position to reduce life cycle impacts and costs from TMS's packaging and distribution systems.     

Perturbation analysis analyzed—mathematical modeling of intact and perturbed gene regulatory circuits for animal development

Gene regulatory networks for animal development are the underlying mechanisms controlling cell fate specification and differentiation. The architecture of gene regulatory circuits determines their information processing properties and their developmental function. It is a major task to derive realistic network models from exceedingly advanced high throughput experimental data. Here we use mathematical modeling to study the dynamics of gene regulatory circuits to advance the ability to infer regulatory connections and logic function from experimental data. This study is guided by experimental methodologies that are commonly used to study gene regulatory networks that control cell fate specification. We study the effect of a perturbation of an input on the level of its downstream genes and compare between the cis-regulatory execution of OR and AND logics. Circuits that initiate gene activation and circuits that lock on the expression of genes are analyzed. The model improves our ability to analyze experimental data and construct from it the network topology. The model also illuminates information processing properties of gene regulatory circuits for animal development.     

刺旋花种群形态参数的通径分析与亚灌木个体生物量建模

对刺旋花４种形态参数的通径分析表明,冠幅（Ｃ）对种群生物量作用最大,其它依次为分枝数（ＢＮ）、基径（ＢＤ）和高度（Ｈ）．在此基础上,选取ＣＨ和常用变量Ｄ２Ｈ,就７种常规方程对生物量建模的效果进行比较,并同时建立营养器官和单株总生物量的预测方程．结果表明,选取变量ＣＨ较Ｄ２Ｈ合适,线性回归方程较其它方程准确直观,其中单株生物量择优预测方程为Ｙ＝１２．１０＋０．０１０５ＣＨ（Ｒ＝０．９８３,Ｐ＜０．０１）．     

Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations

We develop and analyze a mathematical model, in the form of a system of ordinary differential equations (ODEs), governing cancer growth on a cell population level with combination immune, vaccine and chemotherapy treatments. We characterize the ODE system dynamics by locating equilibrium points, determining stability properties, performing a bifurcation analysis, and identifying basins of attraction. These system characteristics are useful not only to gain a broad understanding of the specific system dynamics, but also to help guide the development of combination therapies. Numerical simulations of mixed chemo-immuno and vaccine therapy using both mouse and human parameters are presented. We illustrate situations for which neither chemotherapy nor immunotherapy alone are sufficient to control tumor growth, but in combination the therapies are able to eliminate the entire tumor.     

Dynamic modeling of complex biological systems: a link between metabolic and macroscopic description

In this study, a class of dynamic models based on metabolic reaction pathways is analyzed, showing that systems with complex intracellular reaction networks can be represented by macroscopic reactions relating extracellular components only. Based on rigorous assumptions, the model reduction procedure is systematic and allows an equivalent 'input-output' representation of the system to be derived. The procedure is illustrated with a few examples.     

Exploring the emergence of a biojet fuel supply chain in Brazil: An agent‐based modeling approach

The aviation industry accounts for more than 2% of global CO₂ emissions. Biojet fuel is expected to make an essential contribution to the decarbonization of the aviation sector. Brazil is seen as a key player in developing sustainable aviation biofuels owing to its long‐standing experience with biofuels. Nevertheless, a clear understanding of what policies may be conducive to the emergence of a biojet fuel supply chain is lacking. We extended a spatially explicit agent‐based model to explore the emergence of a biojet fuel supply chain from the existing sugarcane–ethanol supply chain. The model accounts for new policies (feed‐in tariff and capital investment subsidy) and new considerations into the decision making about production and investment in processing capacity. We found that in a tax‐free gasoline regime, a feed‐in tariff above 3 R$/L stimulates the production of biojet fuel. At higher levels of gasoline taxation (i.e., 2.46 R$/L), however, any feed‐in tariff is insufficient to ensure the production of biojet fuel. Thus, at these levels of gasoline taxation, it is needed to introduce regulations on the production of biojet fuel to ensure its production. Given the current debate about the future direction of the biofuel policy in Brazil, we recommend further research into the effect of market mechanisms based on greenhouse gas emissions on the emergence of a Brazilian biojet fuel supply chain.     

Scalar modeling and analysis of a 3D biochemical reaction model

For many systems it is advantageous if analysis and modeling can be accomplished from a scalar time series because this greatly facilitates the experimental setup. Moreover, in real-life systems it is hardly true that all the state variables are available for analysis and modeling. Since the late 1980s, techniques have been put forward for building mathematical models from a scalar time series. One of the objectives of this paper is to verify if it is possible to obtain global non-linear models (non-linear differential equations) from scalar time series. Such data are obtained using a model of biochemical reaction with aperiodic (chaotic) oscillations as recently observed in the case of a glycolytic reaction (Nielsen, K., Sorensen, P.G., Hynne, F., 1997. Chaos in glycolysis. J Theor. Biol. 186, 303-306.). The main objective, however, is to investigate which state variable is more convenient for the task in practice. It is shown that observability indices seem to quantify quite well which variable should be preferred as the observable. The validity of the results are established performing rigorous topological analysis on the original system and the obtained models. The influence of noise, always present in experimental time series, on the dynamics underlying such a system is also investigated.     

Design,Construction, and Operation of a Fast Pyrolysis Plant for Biomass

A continuous fluidized‐bed plant (PDU‐scale) for fast pyrolysis of lingnocellulosic biomass gives rise to bio‐oil yields of 65 wt.‐%. The average reactor gas residence time was 1.2 s only. The gas and charcoal yields were 15–20 wt.‐%, respectively. The bio oils were chemically characterized. The main monomeric products of the thermal degradation of carbohydrates are acetic acid, hydroxyacetaldehyde, hydroxypropanone, and levoglucosan. The process described in this paper can also be used for disposal of inorganic‐, metal‐organic‐, and chlorine‐organic contaminated waste‐wood. Inorganic compounds of wood preservatives are concentrated in the charcoal fraction and can be separated easily. Chlorine‐organic wood preservatives are mostly degraded. The process has been positively tested as a technique for disposal, recycling, and exploitation of industrial biomass waste (wood waste, grinding grit, fibre sludge, cocoa shell and modern composites like HPL). Bio oil from fast pyrolysis can be used for the production of energy and chemical feedstock. Research for these purposes is ongoing.     

Theoretical analysis of intrinsic reaction kinetics and the behavior of immobilized enzymes system for steady-state conditions

Mathematical modeling of immobilized enzymes under different kinetics mechanism viz. simple Michaelis–Menten, uncompetitive substrate inhibition, total competitive product inhibition, total non-competitive product inhibition and reversible Michaelis–Menten reaction are discussed. These five kinetic models are based on reaction diffusion equations containing non-linear terms related to Michaelis–Menten kinetics of the enzymatic reaction. Modified Adomian decomposition method is employed to derive the general analytical expressions of substrate and product concentration for all these five mechanisms for all possible values of the parameters Φ_S (Thiele modulus for substrate), Φ_P (Thiele modulus for product) and α (dimensionless inhibition degree). Also we have presented the general analytical expressions for the mean integrated effectiveness factor for all values of parameters. Analytical results are compared with the numerical results and also with the limiting case results, which are found to be good in agreement.     

Combined effects of pH, yeast extract, carbohydrates and di-ammonium hydrogen citrate on the biomass production and acidifying ability of a probiotic Lactobacillus plantarum strain, isolated from table olives, in a batch system

A four variables-five levels Central Composite Design (CCD) was developed to model the individual and interactive effects of carbohydrates (lactose or maltose), yeast extract, di-ammonium hydrogen citrate and pH on the biomass production (Abs_600 nm), viable and cultivable cell number and acidifying ability of a probiotic strain of Lactobacillus plantarum, isolated from table olives “Bella di Cerignola”. pH values were modeled through a negative Gompertz equation, in order to obtain the parameter α (metabolic adaptation time). This value and the biomass were submitted to a stepwise procedure and second order polynomial equations were derived. The parameter α was affected by the initial pH and lactose; the effect of the maltose, however, was not significant. The biomass production increased with increasing of yeast extract, di-ammonium hydrogen citrate and maltose concentrations and was maximum at pH 6.0 and 20 g l⁻¹ of lactose.     

Pharmacophore modeling,comprehensive 3D-QSAR,and binding mode analysis of TGR5 agonists

Takeda G-protein-coupled receptor 5 (TGR5) is emerging as an important and promising target for the development of anti-diabetic drugs. Pharmacophore modeling and atom-based 3D-QSAR studies were carried out on a new series of 5-phenoxy-1,3-dimethyl-1H-pyrazole-4-carboxamides as highly potent agonists of TGR5. The generated best six featured pharmacophore model AAHHRR consists of two hydrogen bond acceptors (A): two hydrophobic groups (H) and two aromatic rings (R). The constructed 3D-QSAR model acquired excellent correlation coefficient value (R^2?=^?0.9018), exhibited good predictive power (Q^2?=^?0.8494) and high Fisher ratio (F?=?61.2). The pharmacophore model was validated through Guner–Henry (GH) scoring method. The GH value of 0.5743 indicated that the AAHHRR model was statistically valuable and reliable in the identification of TGR5 agonists. Furthermore, the combined approach of molecular docking and binding free energy calculations were carried out for the 5-phenoxy-1,3-dimethyl-1H-pyrazole-4-carboxamides to explore the binding mode and interaction pattern. The generated contour maps revealed the important structural insights for the activity of the compounds. The results obtained from this study could be helpful in the development of novel and more potent agonists of TGR5.     

Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling,docking, and membrane molecular dynamics simulation analysis approach

Chemokine receptor 5 (CCR5) is an integral membrane protein that is utilized during human immunodeficiency virus type-1 entry into host cells. CCR5 is a G-protein coupled receptor that contains seven transmembrane (TM) helices. However, the crystal structure of CCR5 has not been reported. A homology model of CCR5 was developed based on the recently reported CXCR4 structure as template. Automated docking of the most potent (14), medium potent (37), and least potent (25) CCR5 antagonists was performed using the CCR5 model. To characterize the mechanism responsible for the interactions between ligands (14, 25, and 37) and CCR5, membrane molecular dynamic (MD) simulations were performed. The position and orientation of ligands (14, 25, and 37) were found to be changed after MD simulations, which demonstrated the ability of this technique to identify binding modes. Furthermore, at the end of simulation, it was found that residues identified by docking were changed and some new residues were introduced in the proximity of ligands. Our results are in line with the majority of previous mutational reports. These results show that hydrophobicity is the determining factor of CCR5 antagonism. In addition, salt bridging and hydrogen bond contacts between ligands (14, 25, and 37) and CCR5 are also crucial for inhibitory activity. The residues newly identified by MD simulation are Ser160, Phe166, Ser180, His181, and Trp190, and so far no site-directed mutagenesis studies have been reported. To determine the contributions made by these residues, additional mutational studies are suggested. We propose a general binding mode for these derivatives based on the MD simulation results of higher (14), medium (37), and lower (25) potent inhibitors. Interestingly, we found some trend for these inhibitors such as, salt bridge interaction between basic nitrogen of ligand and acidic Glu283 seemed necessary for inhibitory activity. Also, two aromatic pockets (pocket I – TM1-3 and pocket II – TM3-6) were linked by the central polar region in TM7, and the simulated inhibitors show important interactions with the Trp86, Tyr89, Tyr108, Phe112, Ile198, Tyr251, Leu255, and Gln280 and Glu283 residues. These results shed light on the usage of MD simulation to identify more stable, optimal binding modes of the inhibitors.     

FlgM anti-sigma factors: identification of novel members of the family, evolutionary analysis, homology modeling, and analysis of sequence-structure-function relationships

FlgM proteins, also known as Anti-sigma-28 factor (sigma28), are negative regulators of flagellin synthesis. Recently, a three-dimensional structure of the Aquifex aeolicus sigma28/FlgM complex (PDB code: 1rp3) was determined by X-ray crystallography at 2.3 A resolution. Furthermore, experimental data on bacterial FlgM, including site-directed mutagenesis and structural characterization by NMR are also available. However, an interpretation of the sequence-structure-function relationships combining X-ray and NMR data with the evolutionary information extracted from the increasing number of FlgM-related sequences annotated in databases is not available. In the present study, we combined database sequence searches and sequence-analysis tools to update the multiple sequence alignment of a previously characterized cluster of orthologs (COG2747) and the PFAM classification of protein domains (PF04316) for the FlgM family. A phylogenetic analysis of 77 protein sequences revealed the presence of at least three major sequence clades within the FlgM family. Besides, we predicted functional residues using a SequenceSpace method. We also generated homology models for Bacillus subtilis and Salmonella typhimurium FlgM proteins, for which sequence-structure-function relationship data are available, and used the docking program ClusPro to hypothesize about the dimer association between FlgM proteins. In conclusion, the analysis presented in this work will be useful in designing new experiments to understand better protein-protein interactions between FglM, sigma factors, and putative molecules from the flagellar export apparatus. Electronic Supplementary Material is available in the online version of this article at http://link.springer.de/     

Structure conservation in lipoxygenases: Structural analysis of soybean lipoxygenase-1 and modeling of human lipoxygenases

Lipoxygenases are a class of non-heme iron dioxygenases which catalyze the hydroperoxidation of fatty acids for the biosynthesis of leukotrienes and lipoxins. The structure of the 839-residue soybean lipoxygenase-1 was used as a template to model human 5-, 12-, and 15-lipoxygenases. A distance-based algorithm for placing side chains in a low homology environment (only the four iron ligands were fixed during side chain placement) was devised. Twenty-six of the 56 conserved lipoxygenase residues were grouped in four distinct regions of the enzyme. These regions were analyzed to discern whether the side chain interactions could be duplicated in the models or whether alternate conformers should be considered. The effects of site directed mutagenesis variants were rationalized using the models of the human lipoxygenases. In particular, variants which shifted positional specificity between 12- and 15-lipoxygenase activity were analyzed. Analysis of active site residues produced a model which accounts for observed lipoxygenase positional specificity and stereospecificity.     

Design,synthesis and molecular modeling of novel N-acylhydrazone derivatives as pyruvate dehydrogenase complex E1 inhibitors

As potential inhibitors of pyruvate dehydrogenase complex E1 (PDHc-E1), a series of 19 1-((4-amino-2-methylpyrimidin-5-yl)methyl)-5-methyl-N′-(substituent)benzylidene-1H-1,2,3-triazole-4-carbohydrazide 4 has been synthesized and tested for their PDHc-E1 inhibitory activity in vitro. Some of these compounds such as 4a, 4g, 4l, 4o, 4p, and 4q were demonstrated to be effective inhibitors by the bioassay of Escherichia coli PDHc-E1. SAR analysis indicated that the PDHc-E1 inhibitory activity could be further enhanced by optimizing the substituted groups in the parent compound. Molecular modeling study with compound 4o as a model was performed to evaluate docking. The results of modeling study suggested a probable inhibition mechanism.