In recent years, Federated Learning (FL) has gained relevance in training collaborative models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the most common approach ...in the literature, where a central entity creates a global model. However, a centralized approach leads to increased latency due to bottlenecks, heightened vulnerability to system failures, and trustworthiness concerns affecting the entity responsible for the global model creation. Decentralized Federated Learning (DFL) emerged to address these concerns by promoting decentralized model aggregation and minimizing reliance on centralized architectures. However, despite the work done in DFL, the literature has not (i) studied the main aspects differentiating DFL and CFL; (ii) analyzed DFL frameworks to create and evaluate new solutions; and (iii) reviewed application scenarios using DFL. Thus, this article identifies and analyzes the main fundamentals of DFL in terms of federation architectures, topologies, communication mechanisms, security approaches, and key performance indicators. Additionally, the paper at hand explores existing mechanisms to optimize critical DFL fundamentals. Then, the most relevant features of the current DFL frameworks are reviewed and compared. After that, it analyzes the most used DFL application scenarios, identifying solutions based on the fundamentals and frameworks previously defined. Finally, the evolution of existing DFL solutions is studied to provide a list of trends, lessons learned, and open challenges.
•We review concepts related to the explainability of AI methods (XAI).•We comprehensive analyze the XAI literature organized in two taxonomies.•We identify future research directions of the XAI ...field.•We discuss potential implications of XAI and privacy in data fusion contexts.•We identify Responsible AI as a concept promoting XAI and other AI principles in practical settings.
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in Machine Learning, the entire community stands in front of the barrier of explainability, an inherent problem of the latest techniques brought by sub-symbolism (e.g. ensembles or Deep Neural Networks) that were not present in the last hype of AI (namely, expert systems and rule based models). Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models. The overview presented in this article examines the existing literature and contributions already done in the field of XAI, including a prospect toward what is yet to be reached. For this purpose we summarize previous efforts made to define explainability in Machine Learning, establishing a novel definition of explainable Machine Learning that covers such prior conceptual propositions with a major focus on the audience for which the explainability is sought. Departing from this definition, we propose and discuss about a taxonomy of recent contributions related to the explainability of different Machine Learning models, including those aimed at explaining Deep Learning methods for which a second dedicated taxonomy is built and examined in detail. This critical literature analysis serves as the motivating background for a series of challenges faced by XAI, such as the interesting crossroads of data fusion and explainability. Our prospects lead toward the concept of Responsible Artificial Intelligence, namely, a methodology for the large-scale implementation of AI methods in real organizations with fairness, model explainability and accountability at its core. Our ultimate goal is to provide newcomers to the field of XAI with a thorough taxonomy that can serve as reference material in order to stimulate future research advances, but also to encourage experts and professionals from other disciplines to embrace the benefits of AI in their activity sectors, without any prior bias for its lack of interpretability.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Low-frequency vibration modes of biological particles, such as proteins, viruses and bacteria, involve coherent collective vibrations at frequencies in the terahertz and gigahertz domains. These ...vibration modes carry information on their structure and mechanical properties, which are good indicators of their biological state. In this work, we harnessed a particular regime in the physics of coupled mechanical resonators to directly measure these low-frequency mechanical resonances of a single bacterium. We deposit the bacterium on the surface of an ultrahigh frequency optomechanical disk resonator in ambient conditions. The vibration modes of the disk and bacterium hybridize when their associated frequencies are similar. We developed a general theoretical framework to describe this coupling, which allows us to retrieve the eigenfrequencies and mechanical loss of the bacterium low-frequency vibration modes (quality factor). Additionally, we analysed the effect of hydration on these vibrational modes. This work demonstrates that ultrahigh frequency optomechanical resonators can be used for vibrational spectrometry with the unique capability to obtain information on single biological entities.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Head and neck squamous cell carcinoma (HNSCC) clearly involves activation of the Akt mammalian target of rapamycin (mTOR) signalling pathway. However, the effectiveness of treatment with the mTOR ...inhibitor rapamycin is often limited by chemoresistance. Melatonin suppresses neoplastic growth via different mechanisms in a variety of tumours. In this study, we aimed to elucidate the effects of melatonin on rapamycin‐induced HNSCC cell death and to identify potential cross‐talk pathways. We analysed the dose‐dependent effects of melatonin in rapamycin‐treated HNSCC cell lines (Cal‐27 and SCC‐9). These cells were treated with 0.1, 0.5 or 1 mmol/L melatonin combined with 20 nM rapamycin. We further examined the potential synergistic effects of melatonin with rapamycin in Cal‐27 xenograft mice. Relationships between inhibition of the mTOR pathway, reactive oxygen species (ROS), and apoptosis and mitophagy reportedly increased the cytotoxic effects of rapamycin in HNSCC. Our results demonstrated that combined treatment with rapamycin and melatonin blocked the negative feedback loop from the specific downstream effector of mTOR activation S6K1 to Akt signalling, which decreased cell viability, proliferation and clonogenic capacity. Interestingly, combined treatment with rapamycin and melatonin‐induced changes in mitochondrial function, which were associated with increased ROS production, increasing apoptosis and mitophagy. This led to increase cell death and cellular differentiation. Our data further indicated that melatonin administration reduced rapamycin‐associated toxicity to healthy cells. Overall, our findings suggested that melatonin could be used as an adjuvant agent with rapamycin, improving effectiveness while minimizing its side effects.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Most scenarios emerging from the Industry 4.0 paradigm rely on the concept of cyber‐physical production systems (CPPS), which allow them to synergistically connect physical to digital setups so as to ...integrate them over all stages of product development. Unfortunately, endowing CPPS with AI‐based functionalities poses its own challenges: although advances in the performance of AI models keep blossoming in the community, their penetration in real‐world industrial solutions has not so far developed at the same pace. Currently, 90% of AI‐based models never reach production due to a manifold of assorted reasons not only related to complexity and performance: decisions issued by AI‐based systems must be explained, understood and trusted by their end users. This study elaborates on a novel tool designed to characterize, in a non‐supervised, human‐understandable fashion, the nominal performance of a factory in terms of production and energy consumption. The traceability and analysis of energy consumption data traces and the monitoring of the factory's production permit to detect anomalies and inefficiencies in the working regime of the overall factory. By virtue of the transparency of the detection process, the proposed approach elicits understandable information about the root cause from the perspective of the production line, process and/or machine that generates the identified inefficiency. This methodology allows for the identification of the machines and/or processes that cause energy inefficiencies in the manufacturing system, and enables significant energy consumption savings by acting on these elements. We assess the performance of our designed method over a real‐world case study from the automotive sector, comparing it to an extensive benchmark comprising state‐of‐the‐art unsupervised and semi‐supervised anomaly detection algorithms, from classical algorithms to modern generative neural counterparts. The superior quantitative results attained by our proposal complements its better interpretability with respect to the rest of algorithms in the comparison, which emphasizes the utmost relevance of considering the available domain knowledge and the target audience when design AI‐based industrial solutions of practical value. Finally, the work described in this paper has been successfully deployed on a large scale in several industrial factories with significant international projection.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
While social media has been proved as an exceptionally useful tool to interact with other people and massively and quickly spread helpful information, its great potential has been ill-intentionally ...leveraged as well to distort political elections and manipulate constituents. In this article at hand, we analyzed the presence and behavior of social bots on Twitter in the context of the November 2019 Spanish general election. Throughout our study, we classified involved users as social bots or humans, and examined their interactions from a quantitative (i.e., amount of traffic generated and existing relations) and qualitative (i.e., user's political affinity and sentiment towards the most important parties) perspectives. Results demonstrated that a non-negligible amount of those bots actively participated in the election, supporting each of the five principal political parties.
•Wind energy has become the world’s fastest growing energy source.•Power generated by wind turbines is erratic due to the stochastic nature of wind.•The problem addressed is minimizing the standard ...deviation and maximizing energy.•Different wind turbine models are selected using evolutionary algorithms.
Wind energy has become the world’s fastest growing energy source. Although wind farm layout is a well known problem, its solution used to be heuristic, mainly based on the designer experience. A key in search trend is to increase power production capacity over time. Furthermore the production of wind energy often involves uncertainties due to the stochastic nature of wind speeds. The addressed problem contains a novel aspect with respect of other wind turbine selection problems in the context of wind farm design. The problem requires selecting two different wind turbine models (from a list of 26 items available) to minimize the standard deviation of the energy produced throughout the day while maximizing the total energy produced by the wind farm. The novelty of this new approach is based on the fact that wind farms are usually built using a single model of wind turbine. This paper describes the usage of multi-objective evolutionary algorithms (MOEAs) in the context of power energy production, selecting a combination of two different models of wind turbine along with wind speeds distributed over different time spans of the day. Several MOEAs variants belonging to the most renowned and widely used algorithms such as SPEA2 NSGAII, PESA and msPEA have been investigated, tested and compared based on the data gathered from Cancun (Mexico) throughout the year of 2008. We have demonstrated the powerful of MOEAs applied to wind turbine selection problem (WTS) and estimate the mean power and the associated standard deviation considering the wind speed and the dynamics of the power curve of the turbines. Among them, the performance of PESA algorithm looks a little bit superior than the other three algorithms. In conclusion, the use of MOEAs is technically feasible and opens new perspectives for assisting utility companies in developing wind farms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Head and neck cancer is the sixth leading cancer by incidence worldwide. Unfortunately, drug resistance and relapse are the principal limitations of clinical oncology for many patients, and the ...failure of conventional treatments is an extremely demoralizing experience. It is therefore crucial to find new therapeutic targets and drugs to enhance the cytotoxic effects of conventional treatments without potentiating or offsetting the adverse effects. Melatonin has oncostatic effects, although the mechanisms involved and doses required remain unclear. The purpose of this study is to determine the precise underlying mitochondrial mechanisms of melatonin, which increase the cytotoxicity of oncological treatments, and also to propose new melatonin treatments in order to alleviate and reverse radio- and chemoresistant processes. We analyzed the effects of melatonin on head and neck squamous cell carcinoma (HNSCC) cell lines (Cal-27 and SCC-9), which were treated with 0.1, 0.5, 1, and 1.5 mM melatonin combined with 8 Gy irradiation or 10 μM cisplatin. Clonogenic and MTT assays, as well as autophagy and apoptosis, involving flow cytometry and western blot, were performed in order to determine the cytotoxic effects of the treatments. Mitochondrial function was evaluated by measuring mitochondrial respiration, mtDNA content (RT-PCR), and mitochondrial mass (NAO). ROS production, antioxidant enzyme activity, and GSH/GSSG levels were analyzed using a fluorometric method. We show that high concentrations of melatonin potentiate the cytotoxic effects of radiotherapy and CDDP in HNSCC, which are associated with increased mitochondrial function in these cells. In HNSCC, melatonin induces intracellular ROS, whose accumulation plays an upstream role in mitochondria-mediated apoptosis and autophagy. Our findings indicate that melatonin, at high concentrations, combined with cisplatin and radiotherapy to improve its effectiveness, is a potential adjuvant agent.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Saponin Profile of Wild Asparagus Species Jaramillo‐Carmona, Sara; Rodriguez‐Arcos, Rocío; Jiménez‐Araujo, Ana ...
Journal of food science,
March 2017, Volume:
82, Issue:
3
Journal Article
Peer reviewed
Open access
The aim of this work was to study the saponin profiles from spears of different wild asparagus species in the context of its genetic diversity aside from geographical seed origin. They included ...Asparagus pseudoscaber Grecescu, Asparagus maritimus (L.) Mill., Asparagus brachiphyllus Turcz., Asparagus prostrates Dumort., and Asparagus officinalis L. The saponin analysis by LC‐MS has shown that saponin profile from wild asparagus is similar to that previously described for triguero asparagus from Huétor‐Tájar landrace (triguero HT), which had not ever been reported in the edible part of asparagus. All the samples, except A. officinalis, were characterized for having saponins distinct to protodioscin and the total saponin contents were 10‐fold higher than those described for commercial hybrids of green asparagus. In particular, A. maritimus from different origins were rich in saponins previously found in triguero HT. These findings supported previous suggestion, based on genetic analysis, about A. maritimus being the origin of triguero HT. Multivariate statistics including principal component analysis and hierarchical clustering analysis were used to define both similarities and differences among samples. The results showed that the greatest variance of the tested wild asparagus could be attributed to differences in the concentration of particular saponins and this knowledge could be a tool for identifying similar species.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The aim of this review was to summarize the process and results of the Region of Murcia's 2022 Report Card on Physical Activity for Children and Youth.
Indicators from the Global Matrix initiative ...(Overall Physical Activity, Organized Sport & Physical Activity, Physical Fitness, Active Play, Active Transport, Sedentary Behaviors, Family & Peers, School, Community & Environment, and Government) were evaluated based on the best available data in the Region of Murcia.
Active play was the indicator with the highest grade (B+), followed by Organized Sport & Physical Activity (B) and Active Play (B). School and Family and Peers indicators obtained a C+ and C grade, respectively. Both Community and Environment and Sedentary Behaviors indicators received a D+ grade. The grade for Overall Physical Activity and Government indicators was D. Physical Fitness was the indicator with the lowest grade of this Report Card (D−). None of the indicators received an incomplete grade (INC) because of a lack of available information.
The present Report Card offers evidence highlighting the low level of physical activity in Spanish children and adolescents living in the Region of Murcia. Further studies and surveillance efforts are urgently needed for most of the indicators analyzed, which should be addressed by researchers and the Region of Murcia's Government for this specific population. A strong commitment from the Government of the Region of Murcia is needed at all levels to promote a cultural change that will lead children and young people in this region to improve the current situation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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