Antibiotic-loaded bone cement is associated with a reduction of the risk of revision of total knee arthroplasty: Analysis of the Catalan Arthroplasty Register.

Purpose: The purpose of this study was to analyse the impact on peri-prosthetic joint infection (PJI) rate and prosthetic survival using antibiotic-loaded bone cement (ALBC) versus plain cement during total knee arthroplasty (TKA).

Methods: A retrospective cohort study was conducted. The main data source was the Catalan Arthroplasty Register (RACat).

Manual versus deep learning measurements to evaluate cumulus expansion of bovine oocytes and its relationship with embryo development in vitro.

Cumulus expansion is an important indicator of oocyte maturation and has been suggested to be indicative of greater oocyte developmental capacity. Although multiple methods have been described to assess cumulus expansion, none of them is considered a gold standard. Additionally, these methods are subjective and time-consuming.

Child-Robot Interactions Using Educational Robots: An Ethical and Inclusive Perspective.

The Qui-Bot HO project involves developing four educational sustainable robots and their associated software. Robots are equipped with HRI features such as voice recognition and color sensing, and they possess a humanoid appearance. The project highlights the social and ethical aspects of robotics applied to chemistry and industry 4.

Modeling three sources of uncertainty in assisted reproductive technologies with probabilistic graphical models.

Embryo selection is a critical step in assisted reproduction: good selection criteria are expected to increase the probability of inducing a pregnancy. Machine learning techniques have been applied for implantation prediction or embryo quality assessment, which embryologists can use to make a decision about embryo selection. However, this is a highly uncertain real-world problem, and current proposals do not model always all the sources of uncertainty.

A Population-Based Iterated Greedy Algorithm for Maximizing Sensor Network Lifetime.

Finding dominating sets in graphs is very important in the context of numerous real-world applications, especially in the area of wireless sensor networks. This is because network lifetime in wireless sensor networks can be prolonged by assigning sensors to disjoint dominating node sets. The nodes of these sets are then used by a sleep-wake cycling mechanism in a sequential way; that is, at any moment in time, only the nodes from exactly one of these sets are switched on while the others are switched off.

A Robust Solution to Variational Importance Sampling of Minimum Variance.

Importance sampling is a Monte Carlo method where samples are obtained from an alternative proposal distribution. This can be used to focus the sampling process in the relevant parts of space, thus reducing the variance. Selecting the proposal that leads to the minimum variance can be formulated as an optimization problem and solved, for instance, by the use of a variational approach.

Syntactic characterizations of classes of first-order structures in mathematical fuzzy logic.

This paper is a contribution to graded model theory, in the context of mathematical fuzzy logic. We study characterizations of classes of graded structures in terms of the syntactic form of their first-order axiomatization. We focus on classes given by universal and universal-existential sentences.

Off-line synthesis of evolutionarily stable normative systems.

Within the area of multi-agent systems, normative systems are a widely used framework for the coordination of interdependent activities. A crucial problem associated with normative systems is that of synthesising norms that will effectively accomplish a coordination task and that the agents will comply with. Many works in the literature focus on the on-line synthesis of a single, (convention) whose compliance forms a rational choice for the agents and that effectively coordinates them in particular coordination situation that needs to be identified and modelled as a game in advance.

Individual prognosis of diabetes long-term risks: a CBR approach.

We present DIRAS, an application to support physicians in determining the risk of complications for individual diabetic patients. The risk pattern of each diabetic patient is obtained using a Case-based Reasoning method called LID. Case-based Reasoning is an Artificial Intelligence technique based on solving new situations according to past experiences.