Controlled spermatozoa-oocyte interaction improves embryo quality in sheep

The current protocols of in vitro fertilization and culture in sheep rely on paradigms established more than 25 years ago, where Metaphase II oocytes are co-incubated with capacitated spermatozoa overnight. While this approach maximizes the number of fertilized oocytes, on the other side it exposes them to high concentration of reactive oxygen species (ROS) generated by active and degenerating spermatozoa, and positively correlates with polyspermy. Here we set up to precisely define the time frame during which spermatozoa effectively penetrates and fertilizes the oocyte, in order to drastically reduce spermatozoa-oocyte interaction. To do that, in vitro matured sheep oocytes co-incubated with spermatozoa in IVF medium were sampled every 30 min (start of incubation time 0) to verify the presence of a fertilizing spermatozoon. Having defined the fertilization time frame (4 h, data from 105 oocytes), we next compared the standard IVF procedures overnight (about 16 h spermatozoa/oocyte exposure, group o/nIVF) with a short one (4 h, group shIVF). A lower polyspermic fertilization (> 2PN) was detected in shIVF (6.5%) compared to o/nIVF (17.8%), P < 0.05. The o/nIVF group resulted in a significantly lower 2-cell stage embryos, than shIVF [34.6% (81/234) vs 50.6% (122/241) respectively, P < 0.001]. Likewise, the development to blastocyst stage confirmed a better quality [29% (70/241) vs 23.5% (55/234), shIVF vs o/nIVF respectively] and an increased Total Cell Number (TCN) in shIVF embryos, compared with o/n ones. The data on ROS have confirmed that its generation is IVF time-dependent, with high levels in the o/nIVF group. Overall, the data suggest that a shorter oocyte-spermatozoa incubation results in an improved embryo production and a better embryo quality, very likely as a consequence of a shorter exposure to the free oxygen radicals and the ensuing oxidative stress imposed by overnight culture

Generating and Instantiating Abstract Workflows with QoS User Requirements

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Multi Agent System for Machine Learning Under Uncertainty in Cyber Physical Manufacturing System

Recent advancement in predictive machine learning has led to its application in various use cases in manufacturing. Most research focused on maximising predictive accuracy without addressing the uncertainty associated with it. While accuracy is important, focusing primarily on it poses an overfitting danger, exposing manufacturers to risk, ultimately hindering the adoption of these techniques. In this paper, we determine the sources of uncertainty in machine learning and establish the success criteria of a machine learning system to function well under uncertainty in a cyber-physical manufacturing system (CPMS) scenario. Then, we propose a multi-agent system architecture which leverages probabilistic machine learning as a means of achieving such criteria. We propose possible scenarios for which our architecture is useful and discuss future work. Experimentally, we implement Bayesian Neural Networks for multi-tasks classification on a public dataset for the real-time condition monitoring of a hydraulic system and demonstrate the usefulness of the system by evaluating the probability of a prediction being accurate given its uncertainty. We deploy these models using our proposed agent-based framework and integrate web visualisation to demonstrate its real-time feasibility

The four types of self-adaptive systems: A metamodel

The basic ideas of self-adaptive systems are not a novelty in computer science. There are plenty of systems that are able of monitoring their operative context to take run-time decisions. However, more recently a new research discipline is trying to provide a common framework for collecting theory, methods, middlewares, algorithms and tools for engineering such software systems. The aim is to collect and classify existing approaches, coming from many different research areas. The objective of this work is providing a unified metamodel for describing the various categories of adaptation

A possible approach to the development of robotic multi-agent systems

The design of a an agent system for robotics is a problem that involves aspects coming from many different disciplines (robotics, artificial intelligence, computer vision, software engineering). The most difficult part of it, often consists in producing and tuning the algorithms that incorporates the robot behavior (planning, obstacle avoidance,. . . ) and abilities (vision, manipulation, navigation,. . . ). Frequently, the reuse of these parts is left to a copy and paste procedure from previous applications to the new one. In so doing many problems could arise. We propose a comprehensive approach for multi-agent systems oriented to robotics applications that uses a complete design methodology supported by a specific design tools and a pattern repository that interacting each other and with the designer allow the production of a coherent design that easily incorporates patterns coming from previously experienced features and automatically produces a large part of the final code © 2003 IEEE

Patterns reuse in the PASSI methodology

Design patterns already proved successful in lowering the development time and number of errors of object-oriented software; now, they are, candidate to play a similar role in the MAS (multi-agent system) context. In this work we describe our experiences in the identification, production and application of patterns for agents. Some patterns are described together with the classification criteria and documentation approach we adopt. Upon them, we base a pattern reuse process that can be considered one of the distinguishing elements of the design methodology (PASSI) we use to develop MAS. Patterns can be applied to an existing agent or used to produce a new one with the support of a specific web based application that can read both the JAVA source code and XMI representation of the agent design documentation. After the successful application of the desired pattern(s), the source code and the design diagrams (usually a structural and dynamic diagram) of the agent can be exported. Some experimental results are reported in order to demonstrate the utility of this approach in automatically producing an interesting percentage of code lines

A goal-oriented approach for representing and using design patterns

Design patterns are known as proven solutions to recurring design problems. The role of pattern documentation format is to transfer experience thus making pattern employment a viable technique. This research line proposes a goal-oriented pattern documentation that highlights decision-relevant information. The contribution of this paper is twofold. First, it presents a semi-structural visual notation that visualizes context, forces, alternative solutions and consequences in a compact format. Second, it introduces a systematic reuse process, in which the use of goal-oriented patterns aids the practitioner in selecting and customizing design patterns. An empirical study has been conducted the results of which supports the hypothesis that the goal-oriented format provides benefits for the practitioner. The experiment revealed a trend in which solutions better address requirements when the subjects are equipped with the new pattern documentation