Stopping rules for phase II studies

This paper, the second in a series of three papers concerned with the statistical aspects of interim analyses in clinical trials, is concerned with stopping rules in phase II clinical trials. Phase II trials are generally small-scale studies, and may include one or more experimental treatments with or without a control. A common feature is that the results primarily determine the course of further clinical evaluation of a treatment rather than providing definitive evidence of treatment efficacy. This means that there is more flexibility available in the design and analysis of such studies than in phase III trials. This has led to a range of different approaches being taken to the statistical design of stopping rules for such trials. This paper briefly describes and compares the different approaches. In most cases the stopping rules can be described and implemented easily without knowledge of the detailed statistical and computational methods used to obtain the rules.

Decision rules and information provision : monitoring vs manipulation

We analyze the contractual design problem of a principal who delegates decision-making and information provision. The principal faces two tasks: he has to decide the level of discretion to be granted to the decision-maker and to establish who is in charge of supplying the information. We show that these two choices are intrinsically related. When the decision-maker is granted high discretion, information provision is optimally delegated to the parties directly affected by the decision. Conversely, when the decision-maker enjoys little discretion, it is more desirable to rely on a third impartial agent. The paper helps rationalize some organizational arrangements that are commonly observed in the context of judicial and antitrust decision-making.

Design of boundary-scan testing in CMOS image sensors for industrial applications: internship repor

Tests on printed circuit boards and integrated circuits are widely used in industry,resulting in reduced design time and cost of a project. The functional and connectivity tests in this type of circuits soon began to be a concern for the manufacturers, leading to research for solutions that would allow a reliable, quick, cheap and universal solution. Initially, using test schemes were based on a set of needles that was connected to inputs and outputs of the integrated circuit board (bed-of-nails), to which signals were applied, in order to verify whether the circuit was according to the specifications and could be assembled in the production line. With the development of projects, circuit miniaturization, improvement of the production processes, improvement of the materials used, as well as the increase in the number of circuits, it was necessary to search for another solution. Thus Boundary-Scan Testing was developed which operates on the border of integrated circuits and allows testing the connectivity of the input and the output ports of a circuit. The Boundary-Scan Testing method was converted into a standard, in 1990, by the IEEE organization, being known as the IEEE 1149.1 Standard. Since then a large number of manufacturers have adopted this standard in their products. This master thesis has, as main objective: the design of Boundary-Scan Testing in an image sensor in CMOS technology, analyzing the standard requirements, the process used in the prototype production, developing the design and layout of Boundary-Scan and analyzing obtained results after production. Chapter 1 presents briefly the evolution of testing procedures used in industry, developments and applications of image sensors and the motivation for the use of architecture Boundary-Scan Testing. Chapter 2 explores the fundamentals of Boundary-Scan Testing and image sensors, starting with the Boundary-Scan architecture defined in the Standard, where functional blocks are analyzed. This understanding is necessary to implement the design on an image sensor. It also explains the architecture of image sensors currently used, focusing on sensors with a large number of inputs and outputs.Chapter 3 describes the design of the Boundary-Scan implemented and starts to analyse the design and functions of the prototype, the used software, the designs and simulations of the functional blocks of the Boundary-Scan implemented. Chapter 4 presents the layout process used based on the design developed on chapter 3, describing the software used for this purpose, the planning of the layout location (floorplan) and its dimensions, the layout of individual blocks, checks in terms of layout rules, the comparison with the final design and finally the simulation. Chapter 5 describes how the functional tests were performed to verify the design compliancy with the specifications of Standard IEEE 1149.1. These tests were focused on the application of signals to input and output ports of the produced prototype. Chapter 6 presents the conclusions that were taken throughout the execution of the work.

A method for plotting the complementary root locus using the root-locus (positive gain) rules

The root-locus method is a well-known and commonly used tool in control system analysis and design. It is an important topic in introductory undergraduate engineering control disciplines. Although complementary root locus (plant with negative gain) is not as common as root locus (plant with positive gain) and in many introductory textbooks for control systems is not presented, it has been shown a valuable tool in control system design. This paper shows that complementary root locus can be plotted using only the well-known construction rules to plot root locus. It can offer for the students a better comprehension on this subject. These results present a procedure to avoid problems that appear in root-locus plots for plants with the same number of poles and zeros.

Design of a simplified neuro-fuzzy system based on CMAC Architectures

This work presents the design of a fuzzy controller with simplified architecture that use an artificial neural network working as the aggregation operator for several active fuzzy rules. The simplified architecture of the fuzzy controller is used to minimize the time processing used in the closed loop system operation, the basic procedures of fuzzification are simplified to maximum while all the inference procedures are computed in a private way. As consequence, this simplified architecture allows a fast and easy configuration of the simplified fuzzy controller. The structuring of the fuzzy rules that define the control actions is previously computed using an artificial neural network based on CMAC Cerebellar Model Articulation Controller. The operational limits are standardized and all the control actions are previously calculated and stored in memory. For applications, results and conclusions several configurations of this fuzzy controller are considered.

Design of a fuzzy controller with simplified architecture

This work presents the design of a fuzzy controller with simplified architecture. This architecture tries to minimize the time processing used in? the several stages of hazy modeling of systems and processes. The basic procedures of fuzzification and defuzzification are simplified to the maximum while the inference procedures are computed in private way. Therefore, the simplified architecture allows a fast and easy configuration of the fuzzy controller.All rules that define the control actions are determined by inference procedures and the defuzzification is made automatically using a simplified algorithm. The fuzzy controller operation is standardized and the control actions are previously calculated For general-purpose application? ann results, the industrial systems of fluid pow cona ol will be considered.

Usabilidade de software: estudo de recomendações básicas para verificação do nível de conhecimento dos alunos dos cursos de Design Gráfico e Sistemas de Informação da UNESP/Bauru

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

On Modular Design of Field Robotic Systems

Robots are needed to perform important field tasks such as hazardous material clean-up, nuclear site inspection, and space exploration. Unfortunately their use is not widespread due to their long development times and high costs. To make them practical, a modular design approach is proposed. Prefabricated modules are rapidly assembled to give a low-cost system for a specific task. This paper described the modular design problem for field robots and the application of a hierarchical selection process to solve this problem. Theoretical analysis and an example case study are presented. The theoretical analysis of the modular design problem revealed the large size of the search space. It showed the advantages of approaching the design on various levels. The hierarchical selection process applies physical rules to reduce the search space to a computationally feasible size and a genetic algorithm performs the final search in a greatly reduced space. This process is based on the observation that simple physically based rules can eliminate large sections of the design space to greatly simplify the search. The design process is applied to a duct inspection task. Five candidate robots were developed. Two of these robots are evaluated using detailed physical simulation. It is shown that the more obvious solution is not able to complete the task, while the non-obvious asymmetric design develop by the process is successful.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Multicelled Behaviour in E. coli: Design and experimental characterization of an engineered library of hybrid promoters.

Synthetic biology has recently had a great development, many papers have been published and many applications have been presented, spanning from the production of biopharmacheuticals to the synthesis of bioenergetic substrates or industrial catalysts. But, despite these advances, most of the applications are quite simple and don’t fully exploit the potential of this discipline. This limitation in complexity has many causes, like the incomplete characterization of some components, or the intrinsic variability of the biological systems, but one of the most important reasons is the incapability of the cell to sustain the additional metabolic burden introduced by a complex circuit. The objective of the project, of which this work is part, is trying to solve this problem through the engineering of a multicellular behaviour in prokaryotic cells. This system will introduce a cooperative behaviour that will allow to implement complex functionalities, that can’t be obtained with a single cell. In particular the goal is to implement the Leader Election, this procedure has been firstly devised in the field of distributed computing, to identify the process that allow to identify a single process as organizer and coordinator of a series of tasks assigned to the whole population. The election of the Leader greatly simplifies the computation providing a centralized control. Further- more this system may even be useful to evolutionary studies that aims to explain how complex organisms evolved from unicellular systems. The work presented here describes, in particular, the design and the experimental characterization of a component of the circuit that solves the Leader Election problem. This module, composed of an hybrid promoter and a gene, is activated in the non-leader cells after receiving the signal that a leader is present in the colony. The most important element, in this case, is the hybrid promoter, it has been realized in different versions, applying the heuristic rules stated in [22], and their activity has been experimentally tested. The objective of the experimental characterization was to test the response of the genetic circuit to the introduction, in the cellular environment, of particular molecules, inducers, that can be considered inputs of the system. The desired behaviour is similar to the one of a logic AND gate in which the exit, represented by the luminous signal produced by a fluorescent protein, is one only in presence of both inducers. The robustness and the stability of this behaviour have been tested by changing the concentration of the input signals and building dose response curves. From these data it is possible to conclude that the analysed constructs have an AND-like behaviour over a wide range of inducers’ concentrations, even if it is possible to identify many differences in the expression profiles of the different constructs. This variability accounts for the fact that the input and the output signals are continuous, and so their binary representation isn’t able to capture the complexity of the behaviour. The module of the circuit that has been considered in this analysis has a fundamental role in the realization of the intercellular communication system that is necessary for the cooperative behaviour to take place. For this reason, the second phase of the characterization has been focused on the analysis of the signal transmission. In particular, the interaction between this element and the one that is responsible for emitting the chemical signal has been tested. The desired behaviour is still similar to a logic AND, since, even in this case, the exit signal is determined by the hybrid promoter activity. The experimental results have demonstrated that the systems behave correctly, even if there is still a substantial variability between them. The dose response curves highlighted that stricter constrains on the inducers concentrations need to be imposed in order to obtain a clear separation between the two levels of expression. In the conclusive chapter the DNA sequences of the hybrid promoters are analysed, trying to identify the regulatory elements that are most important for the determination of the gene expression. Given the available data it wasn’t possible to draw definitive conclusions. In the end, few considerations on promoter engineering and complex circuits realization are presented. This section aims to briefly recall some of the problems outlined in the introduction and provide a few possible solutions.

Semantic Methods for Intelligent Distributed Design Environments

Continuous advancements in technology have led to increasingly comprehensive and distributed product development processes while in pursuit of improved products at reduced costs. Information associated with these products is ever changing, and structured frameworks have become integral to managing such fluid information. Ontologies and the Semantic Web have emerged as key alternatives for capturing product knowledge in both a human-readable and computable manner. The primary and conclusive focus of this research is to characterize relationships formed within methodically developed distributed design knowledge frameworks to ultimately provide a pervasive real-time awareness in distributed design processes. Utilizing formal logics in the form of the Semantic Web’s OWL and SWRL, causal relationships are expressed to guide and facilitate knowledge acquisition as well as identify contradictions between knowledge in a knowledge base. To improve the efficiency during both the development and operational phases of these “intelligent” frameworks, a semantic relatedness algorithm is designed specifically to identify and rank underlying relationships within product development processes. After reviewing several semantic relatedness measures, three techniques, including a novel meronomic technique, are combined to create AIERO, the Algorithm for Identifying Engineering Relationships in Ontologies. In determining its applicability and accuracy, AIERO was applied to three separate, independently developed ontologies. The results indicate AIERO is capable of consistently returning relatedness values one would intuitively expect. To assess the effectiveness of AIERO in exposing underlying causal relationships across product development platforms, a case study involving the development of an industry-inspired printed circuit board (PCB) is presented. After instantiating the PCB knowledge base and developing an initial set of rules, FIDOE, the Framework for Intelligent Distributed Ontologies in Engineering, was employed to identify additional causal relationships through extensional relatedness measurements. In a conclusive PCB redesign, the resulting “intelligent” framework demonstrates its ability to pass values between instances, identify inconsistencies amongst instantiated knowledge, and identify conflicting values within product development frameworks. The results highlight how the introduced semantic methods can enhance the current knowledge acquisition, knowledge management, and knowledge validation capabilities of traditional knowledge bases.

Essays on behavioral aspects of the design and disclosure of compensation contracts

This thesis consists of four essays on the design and disclosure of compensation contracts. Essays 1, 2 and 3 focus on behavioral aspects of mandatory compensation disclosure rules and of contract negotiations in agency relationships. The three experimental studies develop psychology- based theory and present results that deviate from standard economic predictions. Furthermore, the results of Essay 1 and 2 also have implications for firms’ discretion in how to communicate their top management’s incentives to the capital market. Essay 4 analyzes the role of fairness perceptions for the evaluation of executive compensation. For this purpose, two surveys targeting representative eligible voters as well as investment professionals were conducted. Essay 1 investigates the role of the detailed ‘Compensation Discussion and Analysis’, which is part of the Security and Exchange Commission’s 2006 regulation, on investors’ evaluations of executive performance. Compensation disclosure complying with this regulation clarifies the relationship between realized reported compensation and the underlying performance measures and their target achievement levels. The experimental findings suggest that the salient presentation of executives’ incentives inherent in the ‘Compensation Discussion and Analysis’ makes investors’ performance evaluations less outcome dependent. Therefore, investors’ judgment and investment decisions might be less affected by noisy environmental factors that drive financial performance. The results also suggest that fairness perceptions of compensation contracts are essential for investors’ performance evaluations in that more transparent disclosure increases the perceived fairness of compensation and the performance evaluation of managers who are not responsible for a bad financial performance. These results have important practical implications as firms might choose to communicate their top management’s incentive compensation more transparently in order to benefit from less volatile expectations about their future performance. Similar to the first experiment, the experiment described in Essay 2 addresses the question of more transparent compensation disclosure. However, other than the first experiment, the second experiment does not analyze the effect of a more salient presentation of contract information but the informational effect of contract information itself. For this purpose, the experiment tests two conditions in which the assessment of the compensation contracts’ incentive compatibility, which determines executive effort, is either possible or not. On the one hand, the results suggest that the quality of investors’ expectations about executive effort is improved, but on the other hand investors might over-adjust their prior expectations about executive effort if being confronted with an unexpected financial performance and under-adjust if the financial performance confirms their prior expectations. Therefore, in the experiment, more transparent compensation disclosure does not lead to more correct overall judgments of executive effort and to even lower processing quality of outcome information. These results add to the literature on disclosure which predominantly advocates more transparency. The findings of the experiment however, identify decreased information processing quality as a relevant disclosure cost category. Firms might therefore carefully evaluate the additional costs and benefits of more transparent compensation disclosure. Together with the results from the experiment in Essay 1, the two experiments on compensation disclosure imply that firms should rather focus on their discretion how to present their compensation disclosure to benefit from investors’ improved fairness perceptions and their spill-over on performance evaluation. Essay 3 studies the behavioral effects of contextual factors in recruitment processes that do not affect the employer’s or the applicant’s bargaining power from a standard economic perspective. In particular, the experiment studies two common characteristics of recruitment processes: Pre-contractual competition among job applicants and job applicants’ non-binding effort announcements as they might be made during job interviews. Despite the standard economic irrelevance of these factors, the experiment develops theory regarding the behavioral effects on employees’ subsequent effort provision and the employers’ contract design choices. The experimental findings largely support the predictions. More specifically, the results suggest that firms can benefit from increased effort and, therefore, may generate higher profits. Further, firms may seize a larger share of the employment relationship’s profit by highlighting the competitive aspects of the recruitment process and by requiring applicants to make announcements about their future effort. Finally, Essay 4 studies the role of fairness perceptions for the public evaluation of executive compensation. Although economic criteria for the design of incentive compensation generally do not make restrictive recommendations with regard to the amount of compensation, fairness perceptions might be relevant from the perspective of firms and standard setters. This is because behavioral theory has identified fairness as an important determinant of individuals’ judgment and decisions. However, although fairness concerns about executive compensation are often stated in the popular media and even in the literature, evidence on the meaning of fairness in the context of executive compensation is scarce and ambiguous. In order to inform practitioners and standard setters whether fairness concerns are exclusive to non-professionals or relevant for investment professionals as well, the two surveys presented in Essay 4 aim to find commonalities in the opinions of representative eligible voters and investments professionals. The results suggest that fairness is an important criterion for both groups. Especially, exposure to risk in the form of the variable compensation share is an important criterion shared by both groups. The higher the assumed variable share, the higher is the compensation amount to be perceived as fair. However, to a large extent, opinions on executive compensation depend on personality characteristics, and to some extent, investment professionals’ perceptions deviate systematically from those of non-professionals. The findings imply that firms might benefit from emphasizing the riskiness of their managers’ variable pay components and, therefore, the findings are also in line with those of Essay 1.

Dicto: A Unified DSL for Testing Architectural Rules

Software architecture consists of a set of design choices that can be partially expressed in form of rules that the implementation must conform to. Architectural rules are intended to ensure properties that fulfill fundamental non-functional requirements. Verifying architectural rules is often a non- trivial activity: available tools are often not very usable and support only a narrow subset of the rules that are commonly specified by practitioners. In this paper we present a new highly-readable declarative language for specifying architectural rules. With our approach, users can specify a wide variety of rules using a single uniform notation. Rules can get tested by third-party tools by conforming to pre-defined specification templates. Practitioners can take advantage of the capabilities of a growing number of testing tools without dealing with them directly.

An analysis of protocols and publications suggested that most discontinuations of clinical trials were not based on preplanned interim analyses or stopping rules.

OBJECTIVES To investigate the frequency of interim analyses, stopping rules, and data safety and monitoring boards (DSMBs) in protocols of randomized controlled trials (RCTs); to examine these features across different reasons for trial discontinuation; and to identify discrepancies in reporting between protocols and publications. STUDY DESIGN AND SETTING We used data from a cohort of RCT protocols approved between 2000 and 2003 by six research ethics committees in Switzerland, Germany, and Canada. RESULTS Of 894 RCT protocols, 289 prespecified interim analyses (32.3%), 153 stopping rules (17.1%), and 257 DSMBs (28.7%). Overall, 249 of 894 RCTs (27.9%) were prematurely discontinued; mostly due to reasons such as poor recruitment, administrative reasons, or unexpected harm. Forty-six of 249 RCTs (18.4%) were discontinued due to early benefit or futility; of those, 37 (80.4%) were stopped outside a formal interim analysis or stopping rule. Of 515 published RCTs, there were discrepancies between protocols and publications for interim analyses (21.1%), stopping rules (14.4%), and DSMBs (19.6%). CONCLUSION Two-thirds of RCT protocols did not consider interim analyses, stopping rules, or DSMBs. Most RCTs discontinued for early benefit or futility were stopped without a prespecified mechanism. When assessing trial manuscripts, journals should require access to the protocol.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.