How to ‘find’ an error minimized genetic code: neutral emergence as an alternative to direct Darwinian selection for evolutionary optimization

Error minimization (EM) of the standard genetic code (SGC) refers to the assignment of amino acids to codons in such a way that the deleterious impact of mutations is reduced. The SGC is nearly optimal for the property of EM, compared to randomly generated codes, and prompts the question of how the property arose. Brute force searching of alternative genetic codes is unlikely to have occurred, given the high number of alternative codes. Therefore, a heuristic search of ‘code space’, the space of alternative codes, would have been necessary. Uncovering the nature of this heuristic search is key to understanding the evolution of the genetic code, and consequently the origin of life. Scenarios that rely on direct selection for the property of EM require codon reassignments to sample code space, but these are problematic mechanistically. Alternatively, it has been shown that EM may have emerged in a neutral fashion as a byproduct of the process of genetic code expansion. In this scenario, similar amino acids are added to similar codons via the gene duplication of tRNAs and aminoacyl-tRNA synthetases. Mimicking this process via simulation indeed produces high levels of EM in the resulting genetic codes. These observations imply that optimization has occurred by an alternative to direct selection, commonly viewed as the only form of evolutionary optimization followed in nature. I propose that the neutral emergence of EM produced by code expansion is a genetic algorithm but unlike direct selection, the local selection criterion (amino acid and codon similarity) is distant from the global fitness function (EM), leading to the emergent optimization of EM. By presenting this counter example I clarify how evolutionary optimization in biological systems is not restricted to direct selection, and emphasize that additional processes may lead to the production of beneficial traits, via ‘non-Darwinian optimization’.

     

Autonomous trucks: an affront to masculinity?

Autonomous (or self-driving) vehicle technology has become a commercial reality in a number of cars being driven on public roads around the globe. However, this technology is not only confined to cars. It is equally applicable to trucks and there is speculation that it will be autonomous trucks that will hit the roads first because they operate in ‘a less complicated traffic environment’ and are therefore ideal starting points for the coming automated vehicle market.¹1 https://www.theguardian.com/technology/2015/may/06/nevada-self-driving-trucks-public-roads-daimler-inspiration, last accessed 15 December 2016. For example, in May 2015, authorities granted a license to Daimler to test its self-driving trucks on public roads in the US State of Nevada.²2 https://www.theguardian.com/technology/2015/may/06/nevada-self-driving-trucks-public-roads-daimler-inspiration, last accessed 15 December 2016. These use a series of different technologies, including video cameras and radar, which, when applied in an incremental way, allow drivers to take breaks, although there must always be a qualified driver at the wheel.³3 M Taylor and P Maynard, “Self-driving cars” (2015) 21(5), CTLR 133, 134. It is clear to see the benefits of self-driving trucks to trucking companies, who could use them to transport goods across much longer distances and without all of the scheduled breaks than is presently possible with human truck drivers. But what about the impact on the image of the retained drivers themselves? Traditionally, truck drivers have been men and this representation is well-entrenched in a variety of media. Does the introduction of self-driving truck technology represent an attack on the masculinist truck driving culture as portrayed in TV shows such as ‘Ice Road Truckers’ or ‘Outback Truckers’. If so, is such a change to be encouraged or is the historical image (though objectionable to some) worthy of protection? Given that self-driving trucks could be available for purchase from the middle of the coming decade, the socio-legal aspects of self-driving truck technology will be reflected on and the degree to which this issue can be contemplated at law addressed.     

Collaboration in Multi-Robot Exploration: To Meet or not to Meet?

Work on coordinated multi-robot exploration often assumes that all areas to be explored are freely accessible. This common assumption does not always hold, especially not in search and rescue missions after a disaster. Doors may be closed or paths blocked detaining robots from continuing their exploration beyond these points and possibly requiring multiple robots to clear them. This paper addresses the issue how to coordinate a multi-robot system to clear blocked paths. We define local collaborations that require robots to collaboratively perform a physical action at a common position. A collaborating robot needs to interrupt its current exploration and move to a different location to collaboratively clear a blocked path. We raise the question when to collaborate and whom to collaborate with. We propose four strategies as to when to collaborate. Two obvious strategies are to collaborate immediately or to postpone any collaborations until only blocked paths are left. The other two strategies make use of heuristics based on building patterns. While no single strategy behaves optimal in all scenarios, we show that the heuristics decrease the time required to explore unknown environments considering blocked paths.     

More questions than answers: an examination of “To drill or not to drill: a synthesis of experts’ judgments”

The original paper by Nezhad and Baharlou (1991) employed the analytic hierarchy process to estimate the volume of recoverable oil available from a reservoir. The method has undoubted strengths, in particular the rapidity with which it may be employed and the limited resources required to perform the calculations. It is argued here that more information could have been obtained from the original calculation. In addition, it is suggested that modifying some factors in the procedure could affect the outcome. Simple approximate algorithms are presented that are helpful in interpreting the final results     

Botnets: To what extent are they a threat to information security?

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The purpose of this article is to examine to what extent botnets pose a threat to information security. In Chapter 1 the terms in the title are defined, and a comprehensive overview of botnets is provided in order to equip the reader with an understanding of the context for the remaining chapters. The motives for using botnets and the methods in which they are used are outlined. The methods of botnet attack are then analysed in terms of their potential impact on information security and a conclusion is drawn that botnets are indeed a threat to information security in general terms.Chapter 2 then goes on to examine the extent of the threat from the three different perspectives of governments, corporate and the general public. The threats from each perspective and their impacts are identified, and each threat type for each perspective is then categorised in terms of probability and potential impact. The extent of the threat of each botnet-related attack from each perspective is then assessed using a model recommended by ISO/IEC 27005:2008, and the conclusion is drawn that the extent of the threat that botnets pose to governments, corporates and the general public is High.In Chapter 3, we look at how law enforcement agencies investigate botnets and the criminals behind them, and establish the challenges they face in doing so. It is clear that law enforcement face an uphill struggle due to technical tricks employed by the botherders to remain untraceable, lack of resources with the necessary skillset, the legal complexity of working with multiple jurisdictions, and procedural delays working with foreign law enforcement agencies. The conclusion is drawn that botnets are here to stay and that for the time being the botherders will have the upper hand.     

To hear—to say: the mediating presence of the healing witness

Illness and trauma challenge self-narratives. Traumatized individuals, unable to speak about their experiences, suffer in isolation. In this paper, I explore Kristeva’s theories of the speaking subject and signification, with its symbolic and semiotic modalities, to understand how a person comes to speak the unspeakable. In discussing the origin of the speaking subject, Kristeva employs Plato’s chora (related to choreo, “to make room for”). The chora reflects the mother’s preparation of the child’s entry into language and forms an interior darkroom, the reservoir of lived experience, from which self-narratives issue. Unable to speak of their suffering, traumatized individuals need someone to help them make room for a time of remembrance, someone who is a willing and capable listener. I call such a person a healing witness. Through the mediating presence of the healing witness, fragmented memories of trauma are recreated and incorporated into self-narratives that are sharable with others. Unfortunately, opportunities for witnessing are vanishing. In the last section, I examine the failure of modern media and communication technologies to bear (“hold,” “carry,” “transport”) acts of witnessing. I argue that they perturb the semiotic. According to Kristeva, meaning arises from the dialectical tension between the semiotic (drives and affects) and the symbolic (logic and rules) and is threatened by arid discourse, psychosomatic illnesses, and outbreaks of violence when the semiotic is not represented. Unless we open technology to the imaginary, we risk losing the capacity to bear witness to one another and to create narratives and connections that are meaningful.     

Aqueous Computing: A Survey with an Invitation to Participate

The concept of aqueous computing is presented here,first infull generality,and afterward,using an implementation in a specific enzymatic technology.Aqueous computing arose in the context of biomoloecular (DNA) computing,but the concept is independent of the specifics of its biochemical origin.Alternate technologies for realizing aqueous computing are being considered for future implementation.A solution of an instance of the Boolean satisfiability problem,(SAT),is reported here that provides a new example of an aqueous computation that has been carried out successfully.This small instance of the SAT problem is sufficiently complex to allow our current enzymatic technology to be illustrated in detail.The reader is invited to participate in the rich interdisciplinary activity required by wet lab computing.A project is suggested to the reader for determining the three-colorings of a graph.The basic operations required for this project are exhibited in the solution of the SAT example reported here.     

Optimal Cache Memory Exploitation for Continuous Media: To Cache or to Prefetch?

Network continuous-media applications are emerging with a great pace. Cache memories have long been recognized as a key resource (along with network bandwidth) whose intelligent exploitation can ensure high performance for such applications. Cache memories exist at the continuous-media servers and their proxy servers in the network. Within a server, cache memories exist in a hierarchy (at the host, the storage-devices, and at intermediate multi-device controllers). Our research is concerned with how to best exploit these resources in the context of continuous media servers and in particular, how to best exploit the available cache memories at the drive, the disk array controller, and the host levels. Our results determine under which circumstances and system configurations it is preferable to devote the available memory to traditional caching (a.k.a. data sharing) techniques as opposed to prefetching techniques. In addition, we show how to configure the available memory for optimal performance and optimal cost. Our results show that prefetching techniques are preferable for small-size caches (such as those expected at the drive level). For very large caches (such as those employed at the host level) caching techniques are preferable. For intermediate cache sizes (such as those at multi-device controllers) a combination of both strategies should be employed.     

Clinical application of antibody microarray in chronic kidney disease: How far to go?

Chronic kidney disease (CKD) that affects about 10% of the adult population has been shown as a worldwide public health problem in recent years. Both basic and clinical investigations have identified complex disease-associated protein networks involved in the pathophysiologic processes of CKD. The traditional single-assay approach and proteomic analysis of those related proteins have given birth to a steadily increasing panel of molecules that may have the potential to serve as biomarkers for CKD. However, both approaches suffered from some shortcomings from a technological point of view. Antibody microarray (AbM) is characterized by high sensitivity, specificity, and quantitative ability for a particular set of known proteins. However, its application in CKD has been very limited so far. The objective of this review, therefore, is to address the potential applications of AbM in studying of CKD. We will briefly discuss the proteins involved in the development of CKD, future directions in which AbM approaches would probably display its potential and also some key issues that need to be considered in application of this novel technique.     

To log,or not to log: using heuristics to identify mandatory log events – a controlled experiment

Context

User activity logs should capture evidence to help answer who, what, when, where, why, and how a security or privacy breach occurred. However, software engineers often implement logging mechanisms that inadequately record mandatory log events (MLEs), user activities that must be logged to enable forensics.

Goal

The objective of this study is to support security analysts in performing forensic analysis by evaluating the use of a heuristics-driven method for identifying mandatory log events.

Method

We conducted a controlled experiment with 103 computer science students enrolled in a graduate-level software security course. All subjects were first asked to identify MLEs described in a set of requirements statements during the pre-period task. In the post-period task, subjects were randomly assigned statements from one type of software artifact (traditional requirements, use-case-based requirements, or user manual), one readability score (simple or complex), and one method (standards-, resource-, or heuristics-driven). We evaluated subject performance using three metrics: statement classification correctness (values from 0 to 1), MLE identification correctness (values from 0 to 1), and response time (seconds). We test the effect of the three factors on the three metrics using generalized linear models.

Results

Classification correctness for statements that did not contain MLEs increased 0.31 from pre- to post-period task. MLE identification correctness was inconsistent across treatment groups. For simple user manual statements, MLE identification correctness decreased 0.17 and 0.12 for the standards- and heuristics-driven methods, respectively. For simple traditional requirements statements, MLE identification correctness increased 0.16 and 0.17 for the standards- and heuristics-driven methods, respectively. Average response time decreased 41.7 s from the pre- to post-period task.

Conclusion

We expected the performance of subjects using the heuristics-driven method to improve from pre- to post-task and to consistently demonstrate higher MLE identification correctness than the standards-driven and resource-driven methods across domains and readability levels. However, neither method consistently helped subjects more correctly identify MLEs at a statistically significant level. Our results indicate additional training and enforcement may be necessary to ensure subjects understand and consistently apply the assigned methods for identifying MLEs.

     

Determinants of students’ continuance intention to use blogs to learn: an empirical investigation

This study examines factors influencing students’ continuance intention to use blogs to learn in an undergraduate-level course. The research uses constructs from relevant theoretical frameworks, including the technology acceptance model, social cognitive theory, innovation diffusion theory, and expectation–confirmation model. A survey administered to 108 university students in a Canadian university was analysed using the partial least squares technique. The results show that perceived usefulness and perceived compatibility have positive effects on students’ attitudes towards blog use; perceived ease of use did not. Perceived compatibility, perceived self-efficacy, and perceived support for enhancing social ties with blogs have significant effects on the positive impacts of learning with such tools. Attitude and positive impacts of learning with blogs influence satisfaction with blog use. Both attitude and satisfaction are determinants of students’ continuance intention to use blogs to learn. Satisfaction with blog use is the main predictor of continued use intention.     

To connect or promote?: An exploratory examination of Facebook pages dedicated to moms

Mothers are increasingly using Facebook for a variety of communication functions. As an initial step toward understanding how mothers use Facebook, this exploratory study examines the types of messages mothers receive from Facebook pages solely designated for them. Using a content analysis, twelve Facebook pages and 526 administrators’ posts were analyzed. The majority of pages identified purpose as conversational/ discussion starter, while the majority of administrators’ posts were coded as informational/promotional. The discrepancies between the pages’ and posts’ purpose are considered. Directions for extending the research examining mothers and social networking sites are also suggested.     

Computer exhibitions — an overloaded market?: How to ge the most from an event

Computer trade exhibitions are held worldwide. Poor organization though has caused a number to fail. In order to have a successful show both visitors and exhibitors should understand their markets and the aims of the event.     

Determinants of users’ intention to adopt m-commerce: an empirical analysis

The fast-growing penetration of mobile devices and recent advances in mobile technologies have led to the development of increasingly sophisticated services such as m-shopping for goods or services and m-payment. However, although the number of mobile subscribers is increasing, levels of actual m-commerce activities in many cases remain low. Determining what influences users’ intention to use m-commerce is therefore of growing importance. The purpose of this study was to investigate possible factors. To this aim, we developed a conceptual user adoption model based on technology acceptance model variables and on specific factors such as social influence, personal innovativeness, customization, and individual mobility. The empirical results show that social influence and customization significantly affect perceived usefulness; mobility, customization, and personal innovativeness significantly affect perceived ease of use; and perceived usefulness and perceived ease of use have a direct positive effect on behavioral intention.     

‘To play or not to play’: A cross-temporal investigation using hedonic and instrumental perspectives to explain user intentions to explore a technology

The present research extends prior work on the relationship between users and technology by examining users’ intention to explore a technology. Drawing on exploration and individual motivation theories, we developed and tested a model examining the effects of hedonic (i.e., personal innovativeness and cognitive absorption) and instrumental (i.e., performance expectancy and image enhancement) factors on individuals’ intentions to explore a technology over time. Based on a study of 94 users exposed to a new technology, with measurements taken at two points in time, we found that both instrumental and hedonic factors affect individuals’ intentions to explore, but their effects change over time such that as time goes by, the effect of personal innovativeness decreases and performance expectancy increases. In addition to our contributions and implications for research on technology acceptance, we present practical implications both for developers and managers, with a view toward helping the development and deployment of technologies that satisfy the evolution of users’ needs over time.     

HUC-Prune: an efficient candidate pruning technique to mine high utility patterns

Traditional frequent pattern mining methods consider an equal profit/weight for all items and only binary occurrences (0/1) of the items in transactions. High utility pattern mining becomes a very important research issue in data mining by considering the non-binary frequency values of items in transactions and different profit values for each item. However, most of the existing high utility pattern mining algorithms suffer in the level-wise candidate generation-and-test problem and generate too many candidate patterns. Moreover, they need several database scans which are directly dependent on the maximum candidate length. In this paper, we present a novel tree-based candidate pruning technique, called HUC-Prune (High Utility Candidates Prune), to solve these problems. Our technique uses a novel tree structure, called HUC-tree (High Utility Candidates tree), to capture important utility information of the candidate patterns. HUC-Prune avoids the level-wise candidate generation process by adopting a pattern growth approach. In contrast to the existing algorithms, its number of database scans is completely independent of the maximum candidate length. Extensive experimental results show that our algorithm is very efficient for high utility pattern mining and it outperforms the existing algorithms.     

Waiting for the rapture: What can we do with computers to (hopefully) witness the emergence of life?

Natural Computing - Hadn’t this question already been answered? We all know about computation-universal Turing Machines. And we know that any such machine can simulate a space–time...     

To index or not to index: Time–space trade-offs for positional ranking functions in search engines

Positional ranking functions, widely used in web search engines and related search systems, improve result quality by exploiting the positions of the query terms within documents. However, it is well known that positional indexes demand large amounts of extra space, typically about three times the space of a basic nonpositional index. Textual data, on the other hand, is needed to produce text snippets. In this paper, we study time–space trade-offs for search engines with positional ranking functions and text snippet generation. We consider both index-based and non-index based alternatives for positional data. We aim to answer the question of whether positional data should be indexed, and how.We show that there is a wide range of practical time–space trade-offs. Moreover, we show that using about 1.30 times the space of positional data, we can store everything needed for efficient query processing, with a minor increase in query time. This yields considerable space savings and outperforms, both in space and time, recent alternatives from literature. We also propose several efficient compressed text representations for snippet generation, which are able to use about half of the space of current state-of-the-art alternatives with little impact in query processing time.