Teaching about Scientific Origins: Taking Account of Creationism

The purpose of this study was to develop a model for measuring experimental design ability based on functional magnetic resonance imaging (fMRI) during biological inquiry. More specifically, the researchers developed an experimental design task that measures experimental design ability. Using the developed experimental design task, they measured both the paper experimental design ability and the fMRI experimental design ability of subjects. Subjects’ paper experimental design ability was measured using the quotient equation of experimental design ability, and their fMRI experimental design ability using the brain connectivity coefficient. According to the fMRI results, differences in design ability existed among subjects in terms of brain connectivity coefficient level during the experimental design task. The experimental design ability brain connectivity coefficient level and quotient for each subject were analysed. Statistically significant correlations between subjects’ connectivity strength level among brain activation regions and quotient value guided the establishment of a measuring model. The model measured experimental design ability and could predict an individual’s experimental design ability quotient using his or her brain connectivity coefficient. Hence, the model developed for this study for measuring experimental design ability based on fMRI may serve as a practical measurement of students’ scientific experimental design ability. Furthermore, this study could serve as a founding theory for measuring models of other scientific processing abilities such as observation, question generation, classification, hypothesis generation and hypothesis evaluation.     

A unifying family of group sequential test designs

Currently, the design of group sequential clinical trials requires choosing among several distinct design categories, design scales, and strategies for determining stopping rules. This approach can limit the design selection process so that clinical issues are not fully addressed. This paper describes a family of designs that unifies previous approaches and allows continuous movement among the previous categories. This unified approach facilitates the process of tailoring the design to address important clinical issues. The unified family of designs is constructed from a generalization of a four-boundary group sequential design in which the shape and location of each boundary can be independently specified. Methods for implementing the design using error-spending functions are described. Examples illustrating the use of the design family are also presented.     

Quality-by-Design II: Application of Quantitative Risk Analysis to the Formulation of Ciprofloxacin Tablets

Qualitative risk assessment methods are often used as the first step to determining design space boundaries; however, quantitative assessments of risk with respect to the design space, i.e., calculating the probability of failure for a given severity, are needed to fully characterize design space boundaries. Quantitative risk assessment methods in design and operational spaces are a significant aid to evaluating proposed design space boundaries. The goal of this paper is to demonstrate a relatively simple strategy for design space definition using a simplified Bayesian Monte Carlo simulation. This paper builds on a previous paper that used failure mode and effects analysis (FMEA) qualitative risk assessment and Plackett-Burman design of experiments to identity the critical quality attributes. The results show that the sequential use of qualitative and quantitative risk assessments can focus the design of experiments on a reduced set of critical material and process parameters that determine a robust design space under conditions of limited laboratory experimentation. This approach provides a strategy by which the degree of risk associated with each known parameter can be calculated and allocates resources in a manner that manages risk to an acceptable level.     

景观设计思维的培养途径与教学探讨——从设计思维的特性谈起

作为一门以落地性为特征的应用型学科,对学生规划设计思维与能力的培养一直是风景园林专业教学的重要目标,如何通过教学有效地培养学生规划设计思维与能力也成为了风景园林专业教育关注的重要议题。本文从设计思维的特性出发,针对设计教学课程提出了一套控制方式和流程,并以同济大学本科三年级上学期的公园设计课程为例,对景观设计思维的培养途径和方法展开了教学尝试。     

Application of type synthesis theory to the redesign of a complex surgical instrument

Surgical instruments consist of basic mechanical components such as gears, links, pivots, sliders, etc., which are common in mechanical design. This paper describes the application of a method in the analysis and design of complex surgical instruments such as those employed in laparoscopic surgery. This is believed to be the first application of type synthesis theory to a complex medical instrument. Type synthesis is a methodology that can be applied during the conceptual phase of mechanical design. A handle assembly from a patented laparoscopic surgical stapler is used to illustrate the application of the design method developed. Type synthesis is applied on specific subsystems of the mechanism within the handle assembly where alternative design concepts are generated. Chosen concepts are then combined to form a new conceptual design for the handle assembly. The new handle assembly is improved because it has fewer number of parts, is a simpler design and is easier to assemble. Surgical instrument designers may use the methodology presented here to analyze the mechanical subsystems within complex instruments and to create new options that may offer improvements to the original design.     

Comparison of Rosetta flexible-backbone computational protein design methods on binding interactions

Computational design of binding sites in proteins remains difficult, in part due to limitations in our current ability to sample backbone conformations that enable precise and accurate geometric positioning of side chains during sequence design. Here we present a benchmark framework for comparison between flexible-backbone design methods applied to binding interactions. We quantify the ability of different flexible backbone design methods in the widely used protein design software Rosetta to recapitulate observed protein sequence profiles assumed to represent functional protein/protein and protein/small molecule binding interactions. The CoupledMoves method, which combines backbone flexibility and sequence exploration into a single acceptance step during the sampling trajectory, better recapitulates observed sequence profiles than the BackrubEnsemble and FastDesign methods, which separate backbone flexibility and sequence design into separate acceptance steps during the sampling trajectory. Flexible-backbone design with the CoupledMoves method is a powerful strategy for reducing sequence space to generate targeted libraries for experimental screening and selection.     

Design and analysis of a robust genetic Muller C-element

This paper presents results on the design and analysis of a robust genetic Muller C-element. The Muller C-element is a standard logic gate commonly used to synchronize independent processes in most asynchronous electronic circuits. Synthetic biological logic gates have been previously demonstrated, but there remain many open issues in the design of sequential (state-holding) logic operations. Three designs are considered for the genetic Muller C-element: a majority gate, a toggle switch, and a speed-independent implementation. While the three designs are logically equivalent, each design requires different assumptions to operate correctly. The majority gate design requires the most timing assumptions, the speed-independent design requires the least, and the toggle switch design is a compromise between the two. This paper examines the robustness of these designs as well as the effects of parameter variation using stochastic simulation. The results show that robustness to timing assumptions does not necessarily increase reliability, suggesting that modifications to existing logic design tools are going to be necessary for synthetic biology. Parameter variation simulations yield further insights into the design principles necessary for building robust genetic gates. The results suggest that high gene count, cooperativity of at least two, tight repression, and balanced decay rates are necessary for robust gates. Finally, this paper presents a potential application of the genetic Muller C-element as a quorum-mediated trigger.     

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.     

A Brief History of De Novo Protein Design: Minimal,Rational, and Computational

Protein design has come of age, but how will it mature? In the 1980s and the 1990s, the primary motivation for de novo protein design was to test our understanding of the informational aspect of the protein-folding problem; i.e., how does protein sequence determine protein structure and function? This necessitated minimal and rational design approaches whereby the placement of each residue in a design was reasoned using chemical principles and/or biochemical knowledge. At that time, though with some notable exceptions, the use of computers to aid design was not widespread. Over the past two decades, the tables have turned and computational protein design is firmly established. Here, I illustrate this progress through a timeline of de novo protein structures that have been solved to atomic resolution and deposited in the Protein Data Bank. From this, it is clear that the impact of rational and computational design has been considerable: More-complex and more-sophisticated designs are being targeted with many being resolved to atomic resolution. Furthermore, our ability to generate and manipulate synthetic proteins has advanced to a point where they are providing realistic alternatives to natural protein functions for applications both in vitro and in cells. Also, and increasingly, computational protein design is becoming accessible to non-specialists. This all begs the questions: Is there still a place for minimal and rational design approaches? And, what challenges lie ahead for the burgeoning field of de novo protein design as a whole?     

Design and analysis of multiple choice feeding preference data

Traditional analyses of feeding experiments that test consumer preference for an array of foods suffer from several defects. We have modified the experimental design to incorporate into a multivariate analysis the variance due to autogenic change in control replicates. Our design allows the multiple foods to be physically paired with their control counterparts. This physical proximity of the multiple food choices in control/experimental pairs ensures that the variance attributable to external environmental factors jointly affects all combinations within each replicate. Our variance term, therefore, is not a contrived estimate as is the case for the random pairing strategy proposed by previous studies. The statistical analysis then proceeds using standard multivariate statistical tests. We conducted a multiple choice feeding experiment using our experimental design and utilized a Monte Carlo analysis to compare our results with those obtained from an experimental design that employed the random pairing strategy. Our experimental design allowed detection of moderate differences among feeding means when the random design did not.     

Concept of Intelligent Mechanical Design for Autonomous Mobile Robots

The concept of Intelligent Mechanical Design (IMD) is presented to show how a mechanical structure can be designed to affect robot controllability, simplification and task performance. Exploring this concept produces landmarks in the territory of mechanical robot design in the form of seven design principles. The design principles, which we call the Mecha-Telligence Principles (MTP), provide guidance on how to design mechanics for autonomous mobile robots. These principles guide us to ask the right questions when investigating issues concerning self-controllable, reliable, feasible, and compatible mechanics for autonomous mobile robots. To show how MTP can be applied in the design process we propose a novel methodology, named as Mecha-Telligence Methodology (MTM). Mechanical design by the proposed methodology is based on preference classification of the robot specification described by interaction of the robot with its environment and the physical parameters of the robot mechatronics. After defining new terms, we investigate the feasibility of the proposed methodology to the mechanical design of an autonomous mobile sewer inspection robot. In this industrial project we show how a passive-active intelligent moving mechanism can be designed using the MTM and employed in the field.     

The use of windows of operation as a bioprocess design tool

Bioprocess design problems are frequently multivariate and complex. However, they may be visualised by a graphical representation of the design constraints and correlations governing both the process and system under consideration, namely windows of operation. Windows of operation exist at all stages of process design and find use both in the identification of key constraints from limited information, and also, with more detailed knowledge, the sensitivity of a process to design or operating changes. In this way windows of operation may be used to help understand and optimise a bioprocess design. In this paper the formulation, development and application of windows of operation is discussed for a range of biological processes including fermentation, protein recovery and biotransformation.UCL is the Biotechnology and Biological Sciences Research Council's Interdisciplinary Research Centre for Biochemical Engineering and the Council's support is gratefully acknowledged.     

Fractional factorial design optimization of the separation of pilocarpine and its degradation products by capillary electrophoresis

The separation of pilocarpine and its degradation products by micellar electrokinetic capillary chromatography (MECC) has been optimized by using fractional factorial design of the experiments. Critical parameters were identified in a screening design, and an optimization design was used to optimize the separation. The optimal separation method was based on a borate buffer with sodium dodecyl sulfate (SDS). It is concluded that by using fractional factorial design it is possible to improve the separation of pilocarpine, it trans epimer, isopilocarpine and their hydrolysis products, pilocarpic acid and isopilocarpic acid.     

An accurate binding interaction model in de novo computational protein design of interactions: If you build it,they will bind

Computational protein design efforts aim to create novel proteins and functions in an automated manner and, in the process, these efforts shed light on the factors shaping natural proteins. The focus of these efforts has progressed from the interior of proteins to their surface and the design of functions, such as binding or catalysis. Here we examine progress in the development of robust methods for the computational design of non-natural interactions between proteins and molecular targets such as other proteins or small molecules. This problem is referred to as the de novo computational design of interactions. Recent successful efforts in de novo enzyme design and the de novo design of protein–protein interactions open a path towards solving this problem. We examine the common themes in these efforts, and review recent studies aimed at understanding the nature of successes and failures in the de novo computational design of interactions. While several approaches culminated in success, the use of a well-defined structural model for a specific binding interaction in particular has emerged as a key strategy for a successful design, and is therefore reviewed with special consideration.     

Improved energy bound accuracy enhances the efficiency of continuous protein design

Flexibility and dynamics are important for protein function and a protein's ability to accommodate amino acid substitutions. However, when computational protein design algorithms search over protein structures, the allowed flexibility is often reduced to a relatively small set of discrete side‐chain and backbone conformations. While simplifications in scoring functions and protein flexibility are currently necessary to computationally search the vast protein sequence and conformational space, a rigid representation of a protein causes the search to become brittle and miss low‐energy structures. Continuous rotamers more closely represent the allowed movement of a side chain within its torsional well and have been successfully incorporated into the protein design framework to design biomedically relevant protein systems. The use of continuous rotamers in protein design enables algorithms to search a larger conformational space than previously possible, but adds additional complexity to the design search. To design large, complex systems with continuous rotamers, new algorithms are needed to increase the efficiency of the search. We present two methods, PartCR and HOT, that greatly increase the speed and efficiency of protein design with continuous rotamers. These methods specifically target the large errors in energetic terms that are used to bound pairwise energies during the design search. By tightening the energy bounds, additional pruning of the conformation space can be achieved, and the number of conformations that must be enumerated to find the global minimum energy conformation is greatly reduced. Proteins 2015; 83:1151–1164. © 2015 Wiley Periodicals, Inc.     

Incorporating prior parameter uncertainty in the design of sampling schedules for pharmacokinetic parameter estimation experiments

An experiment design procedure is proposed for nonlinear parameter estimation studies that formally incorporates prior parameter uncertainty. The design criterion derives from information theory considerations and involves an asymptotic interpretation of the expected posterior information provided by an experiment. A pharmacokinetic sample schedule design problem is used to illustrate and evaluate this information theoretic design strategy. The model considered is commonly used to describe the plasma concentration of a drug following its oral administration. The limitations and advantages of the proposed design procedure are discussed in relation to other previously reported design techniques for incorporating parameter uncertainty.     

酶分子设计常用策略和进展

酶分子的生物学功能很大程度上是由其三维空间结构和所处溶剂环境共同决定的。因此,优化酶分子的结构性质以及探索其性质最优的溶剂环境是改善酶分子功能以及进行理性设计的一个可行途径。从实际应用的角度来看,分子设计方法可以为酶工程提供一种有效的解决方案。目前,酶分子设计有两个重要的研究方向,包括提高酶分子的催化活力和优化其稳定性。同时,对酶分子设计方法的研究也有助于对蛋白质生物学机理的探索。在近些年的学术界酶分子设计案例中,生物信息学方法得到广泛的应用。本文系统地总结基于生物信息学的酶分子设计方法的背景、策略和一些经典案例。     

Applications of NMR to structure-based drug design in structural genomics

Structural genomics is poised to have a tremendous impact on traditional structure-based drug design programs. As a result, there is a growing need to obtain rapid structural information in a reliable form that is amenable to rational drug design. In this manner, NMR has been expanding and evolving its role in aiding the design process. A variety of NMR methodologies that cover a range of inherent resolution are described in the context of structure-based drug design in the era of structural genomics.     

Optimization of ski jumper's posture considering lift-to-drag ratio and stability

An optimization analysis of a ski jumper's posture has been performed to improve the lift-to-drag ratio, and to examine aerodynamic stability to ensure flight control and safety. Three-dimensional Reynolds-averaged Navier-Stokes equations were discretized using finite volume approximations for the flow analysis, and the shear stress transport k-ω turbulence model was used for a turbulence closure. The Airfoil theory and principles of aircraft stability were used to examine the stability mechanism. Two ski jumper posture angles were chosen as design variables through a preliminary test, and the lift-to-drag ratio was used as an objective function for the optimization problem. Thirteen design points within design spaces are selected by Latin hypercube sampling. In order to predict the objective function values in the design space, the Kriging model was constructed using the numerical results on the design points. By the sequential quadratic programming, the optimal point was found from the constructed the Kriging model. The Kriging model predicted the objective function value at the optimum point with a 1.1% error compared to the value obtained by numerical analysis. The optimum design showed a considerable lift-to-drag ratio improvement compared to the reference design.