Neutral fitness landscapes in signalling networks

Biological and technological systems process information by means of cascades of signals. Be they interacting genes, spiking neurons or electronic transistors, information travels across these systems, producing, for each set of external conditions, an appropriate response. In technology, circuits performing specific complex tasks are designed by humans. In biology, however, design has to be ruled out, confronting us with the question of how these systems could have arisen by accumulation of small changes. The key factor is the genotype-phenotype map. With the exception of RNA folding, not much is known about the exact nature of this mapping. Here, we show that structure of the genotype-phenotype map of simple feed-forward circuits is very close to the ones found in RNA; they have a large degree of neutrality, by which a circuit can be completely rewired keeping its input-output function intact, and there is a relatively small neighbourhood of a given circuit containing almost all the phenotypes.     

Learning Read-Constant Polynomials of Constant Degree Modulo Composites

Boolean functions that have constant degree polynomial representation over a fixed finite ring form a natural and strict subclass of the complexity class ACC⁰. They are also precisely the functions computable efficiently by programs over fixed and finite nilpotent groups. This class is not known to be learnable in any reasonable learning model. In this paper, we provide a deterministic polynomial time algorithm for learning Boolean functions represented by polynomials of constant degree over arbitrary finite rings from membership queries, with the additional constraint that each variable in the target polynomial appears in a constant number of monomials. Our algorithm extends to superconstant but low degree polynomials and still runs in quasipolynomial time.     

Open Challenges in Relationship-Based Privacy Mechanisms for Social Network Services

Social networking services (SNSs) such as Facebook and Twitter have experienced explosive growth during the few past years. Millions of users have created their profiles on these services because they experience great benefits in terms of friendship. SNSs can help people to maintain their friendships, organize their social lives, start new friendships, and meet others who share their hobbies and interests. However, all these benefits can be eclipsed by the privacy hazards that affect people in SNSs. People expose intimate information about their lives on SNSs, and this information affects the way others think about them. It is crucial that users be able to control how their information is distributed through the SNSs and decide who can access it. This article presents a list of privacy threats that can affect SNS users and what requirements privacy mechanisms should fulfill to prevent this threats. Then the article reviews current approaches and analyzes to what extent they cover the requirements.     

Self-adaptive utility-based web session management

In the Internet, where millions of users are a click away from your site, being able to dynamically classify the workload in real time, and predict its short term behavior, is crucial for proper self-management and business efficiency. As workloads vary significantly according to current time of day, season, promotions and linking, it becomes impractical for some ecommerce sites to keep over-dimensioned infrastructures to accommodate the whole load. When server resources are exceeded, session-based admission control systems allow maintaining a high throughput in terms of properly finished sessions and QoS for a limited number of sessions; however, by denying access to excess users, the website looses potential customers.In the present study we describe the architecture of AUGURES, a system that learns to predict Web user’s intentions for visiting the site as well its resource usage. Predictions are made from information known at the time of their first request and later from navigational clicks. For this purpose we use machine learning techniques and Markov-chain models. The system uses these predictions to automatically shape QoS for the most profitable sessions, predict short-term resource needs, and dynamically provision servers according to the expected revenue and the cost to serve it. We test the AUGURES prototype on access logs from a high-traffic, online travel agency, obtaining promising results.     

Stability during storage of LC-PUFA-supplemented infant formula containing single cell oil or egg yolk

The medical community recommends that infant formulae should mimic human milk as far as possible, particularly in regards to long-chain polyunsaturated fatty acids (LC-PUFA). These include arachidonic acid (AA) and docosahexaenoic acid (DHA), both of which provide biochemical and functional benefits to neonates. However, LC-PUFAs are highly susceptible to oxidation and the composition of formulae must be carefully controlled. In this study, the stability of two types of LC-PUFA-supplemented milk-based powdered infant formula was evaluated over the course of 18 months storage at 25 °C and 40 °C. One contained egg yolk phospholipids (IF-EPL) and the other contained triacylglycerides (DHA and AA) synthesized by single cell oils (IF-SCO). The following parameters were monitored: peroxide values, volatile content (propanal, pentanal and hexanal), fatty acid profiles, and potential and free furfural content (5-hydroxymethyl-2-furaldehyde and 2-furaldehyde). In addition, these formulae were subjected to sensory evaluations by a panel of experts. The parameters studied revealed acceptable lipid stability in both types of formula, with better results for IF-EPL. At the end of the study period, significant deficits (p < 0.05) in linoleic acid were noted in both formulae. However, no significant decreases were observed in the other fatty acids, including AA and DHA. In regards to furfural content, both formulae exhibited a similar increase, indicative of the typical Maillard reaction characteristic of products stored for long periods.     

Bubbly Jet Impingement in Different Liquids

The impingement of bubbly jets in distilled water and ethanol has been experimentally studied on ground. An experimental apparatus for the study of jet impingement on ground and in microgravity has been designed. The opposed-jet configuration with changeable orientation is used in order to study which is the better disposition to achieve an efficient mixing process. The impact angle between jets that can be changed from 0° (frontal collision) up to 90° (perpendicular collision). The impinging jets are introduced into a test tank full of liquid by means of two bubble injectors. The bubble generation method, insensitive to gravity level for low Bond numbers, is based on the creation of a slug flow inside a T-junction of capillary tubes of 0.7 mm of diameter. Bubble velocities at the injector outlet and generation frequencies can be controlled by changing gas and liquid flow rates. Individual bubble properties and coalescence events, as well as the whole jet structure are analyzed from the images recorded by a high speed camera. Bubble velocities are compared with the velocity field of a single-phase jet. Rate of coalescence between bubbles is found higher in ethanol than in water, creating a higher dispersion in bubble sizes.     

Self-centeredness and selflessness: A theory of self-based psychological functioning and its consequences for happiness.

The theoretical model presented in this paper emerged from several different disciplines. This model proposes that the attainment of happiness is linked to the self, and more particularly to the structure of the self. We support the idea that the perception of a structured self, which takes the form of a permanent, independent and solid entity leads to self-centered psychological functioning, and this seems to be a significant source of both affliction and fluctuating happiness. Contrary to this, a selfless psychological functioning emerges when perception of the self is flexible (i.e., a dynamic network of transitory relations), and this seems to be a source of authentic-durable happiness. In this paper, these two aspects of psychological functioning and their underlying processes will be presented. We will also explore the potential mechanisms that shape them. We will conclude with an examination of possible applications of our theory. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms

Scalability is a key requirement for any KDD and data mining algorithm, and one of the biggest research challenges is to develop methods that allow to use large amounts of data. One possible approach for dealing with huge amounts of data is to take a random sample and do data mining on it, since for many data mining applications approximate answers are acceptable. However, as argued by several researchers, random sampling is difficult to use due to the difficulty of determining an appropriate sample size. In this paper, we take a sequential sampling approach for solving this difficulty, and propose an adaptive sampling method that solves a general problem covering many actual problems arising in applications of discovery science. An algorithm following this method obtains examples sequentially in an on-line fashion, and it determines from the obtained examples whether it has already seen a large enough number of examples. Thus, sample size is not fixed a priori; instead, it adaptively depends on the situation. Due to this adaptiveness, if we are not in a worst case situation as fortunately happens in many practical applications, then we can solve the problem with a number of examples much smaller than required in the worst case. We prove the correctness of our method and estimates its efficiency theoretically. For illustrating its usefulness, we consider one concrete task requiring sampling, provide an algorithm based on our method, and show its efficiency experimentally.     

13C and 23Na n.m.r. studies of the interactions between cations and kryptofix (2,2) bound to soluble or gel polyacrylamide

Interactions between univalent cations (Li⁺, Na⁺, K⁺, Ag⁺) and bivalent cations (Ba²⁺, Ca²⁺) with kryptofix (2,2) substituted polyacrylamide have been investigated using ¹³C n.m.r. The tendency to form complexes involves the dimensions of both the hydrated ion and the cavity size macrocycle and for Ag⁺ the nature of the interaction site. The sensitivity of the ²³Na n.m.r. method for detecting complex formation in solution from macromolecular species has been applied to the determination of the conditional formation constants of Na⁺ and Ba²⁺ complexes.