Open Research Lines Research Articles

A step closer to sustainable CO2 conversion: Limonene carbonate production driven by ionic liquids

This work aims to advance the biocarbonate concept by developing the first process to produce limonene carbonate based on ionic liquids (ILs). Conventional petroleum-derived cyclic carbonates are recognized products partially composed of CO2 with the main drawback of the high energy consumption that imposes epoxide production. In contrast, natural epoxidable compounds, such as terpenes, stand out in the literature as a more sustainable open research line to enable CO2 conversion processes with better sustainable indicators. Limonene, an abundant natural compound, is identified as a key terpene in the aforementioned discussion. Ammonium-based ILs are experimentally selected and optimized, after covering massive anion and cation substituent tuning, achieving high selectivity and competitive yields to limonene carbonate. The reaction-extraction platform concept, which recovers the catalyst by liquid-liquid extraction, is envisioned and developed using a rational experimental-computational approach. The work concludes with a novel process to effectively produce limonene carbonate by using an IL catalyst and water as an extracting solvent. Ultimately, taking advance of the process simulation, a CO2 emissions assessment was conducted. Using renewable raw materials enhances the sustainability of CO2 conversion to cyclic carbonate, reducing global warming impact compared to fossil-based epoxides. However, limonene extraction and epoxidation have a tangible impact on the overall result of CO2 balance, turning efforts outside battery limits of the CO2 conversion process in the search of a limonene carbonate production line with negative neat CO2 emissions that may change the paradigm in the fixation of CO2 through cycloaddition reactions.

Structural and functional characterization of genes PYL-PP2C-SnRK2s in the ABA signalling pathway of Cucurbita pepo

BackgroundThe core regulation of the abscisic acid (ABA) signalling pathway comprises the multigenic families PYL, PP2C, and SnRK2. In this work, we conducted a genome-wide study of the components of these families in Cucurbita pepo.ResultsThe bioinformatic analysis of the C. pepo genome resulted in the identification of 19 CpPYL, 102 CpPP2C and 10 CpSnRK2 genes. The investigation of gene structure and protein motifs allowed to define 4 PYL, 13 PP2C and 3 SnRK2 subfamilies. RNA-seq analysis was used to determine the expression of these gene families in different plant organs, as well as to detect their differential gene expression during germination, and in response to ABA and cold stress in leaves. The specific tissue expression of some gene members indicated the relevant role of some ABA signalling genes in plant development. Moreover, their differential expression under ABA treatment or cold stress revealed those ABA signalling genes that responded to ABA, and those that were up- or down-regulated in response to cold stress. A reduced number of genes responded to both treatments. Specific PYL-PP2C-SnRK2 genes that had potential roles in germination were also detected, including those regulated early during the imbibition phase, those regulated later during the embryo extension and radicle emergence phase, and those induced or repressed during the whole germination process.ConclusionsThe outcomes of this research open new research lines for agriculture and for assessing gene function in future studies.

Immersive Virtual Reality to Improve Functional Capacities in People with Multiple Sclerosis: Study Protocol

Multiple sclerosis is an autoimmune, inflammatory, and chronic neurodegenerative disease caused by myelin loss in the central nervous system. One strategy that shows evidence of numerous benefits is therapeutic exercise, but these therapies, based on repetitive physical actions, can sometimes be unmotivating for patients. Our proposal suggests that an exergame programme with immersive virtual reality (IVR) is feasible for people with multiple sclerosis (pwMS) and will improve their physical function through more motivational sessions. We present a protocol for a single-blind randomised controlled trial to assess the feasibility and impact on functional capacities of an 8-week IVR programme (ExeRVIEM protocol) in pwMS. Balance, gait, risk of falling, functional mobility and lower limb strength, fatigue, handgrip strength, and reaction times will be evaluated. The control group will maintain the usual activities scheduled in the centre, and the experimental group will add the ExeRVIEM protocol (two sessions per week). Therapies based on the combination of exercise and IVR explored in this study may offer new treatment approaches and open new lines of research in this field by improving the functionality of pwMS, as well as motivating patients and encouraging their adherence to treatment.

Group Actions on Twisted Sums of Banach Spaces

We study bounded actions of groups and semigroups G on exact sequences of Banach spaces from the point of view of (generalized) quasilinear maps, characterize the actions on the twisted sum space by commutator estimates and introduce the associated notions of G-centralizer and G-equivariant map. We will show that when (A) G is an amenable group and (U) the target space is complemented in its bidual by a G-equivariant projection, then uniformly bounded compatible families of operators generate bounded actions on the twisted sum space; that compatible quasilinear maps are linear perturbations of G-centralizers; and that, under (A) and (U), G-centralizers are bounded perturbations of G-equivariant maps. The previous results are optimal. Several examples and counterexamples are presented involving the action of the isometry group of L_p(0,1), pne 2 on the Kalton–Peck space Z_p, certain non-unitarizable triangular representations of the free group {mathbb {F}}_infty on the Hilbert space, the compatibility of complex structures on twisted sums, or bounded actions on the interpolation scale of L_p-spaces. In the penultimate section we consider the category of G-Banach spaces and study its exact sequences, showing that, under (A) and (U), G-splitting and usual splitting coincide. The purpose of the final section is to present some applications, showing that several previous result are optimal and to suggest further open lines of research.

Development of a new Ni voltammetric sensor for hardened concrete conditions estimate

Developing efficient monitoring systems to control reinforced concrete structures (RCS) is still an open research line in the building sector. Thus, in this work was proposed the novelty use of Ni voltammetric sensor to control the concrete conditions by means of PCA model. The efficiency of voltammetric sensors are verified in other sectors like food or wastewater treatment, where the sensors are used in liquid media, in the study was intended verify the high potential use of this sensors in porous materials such as concrete. With this purpouse the sensor response was characterized in three different concretes (w/c = 0.6, w/c = 0.5 and w/c = 0.4) and three different concrete conditions (water satured conditions, presence of chlorides and concrete carbonation). Then, was developed a PCA model, where was verified the capability of the sensor to classify the concrete state. The validation of the model pointed an acceptance range between 78.3% and 95.4% (with a 95% confidence index).

Optimal Floquet Stationkeeping under the Relative Dynamics of the Three-Body Problem

Deep space missions, and particularly cislunar endeavors, are becoming a major field of interest for the space industry, including for the astrodynamics research community. While near-Earth missions may be completely covered by perturbed Keplerian dynamics, deep space missions require a different modeling approach, where multi-body gravitational interactions play a major role. To this end, the Restricted Three-Body Problem stands out as an insightful first modeling strategy for early mission design purposes, retaining major dynamical transport structures while still being relatively simple. Dynamical Systems Theory and classical Hamiltonian Mechanics have proven themselves as remarkable tools to analyze deep-space missions within this context, with applications ranging from ballistic capture trajectory design to stationkeeping. In this work, based on this premise, a Hamiltonian derivation of the Restricted Three-Body Problem co-orbital dynamics between two spacecraft is introduced in detail. Thanks to the analytical and numerical models derived, connections between the relative and classical Keplerian and CR3BP problems are shown to exist, including first-order linear solutions and an inherited Hamiltonian normal form. The analytical linear and higher-order models derived allow the theoretical finding and unveiling of natural co-orbital phase space structures, including relative periodic and quasi-periodic orbital families, which are further exploited for general proximity operation applications. In particular, a novel reduced-order, optimal low-thrust stationkeeping controller is derived in the relative Floquet phase space, hybridizing the classical State Dependent Ricatti Equation (SDRE) with Koopman control techniques for efficient unstable manifold regulation. The proposed algorithm is demonstrated and validated within several end-to-end low-cost stationkeeping missions, and comparison against classical continuous stationkeeping algorithms presented in the literature is also addressed to reveal its enhanced performance. Finally, conclusions and open lines of research are discussed.

Eco-friendly additive construction: Analysis of the printability of earthen-based matrices stabilized with potato starch gel and sisal fibers

• A prototype 3D printing system for construction ecofriendly composites was developed. • A printable composite made with soil, starch gel, and fibers was designed. • The inclusion of starch gel positively affects properties in fresh and hardened state. • The incorporation of sisal fibers allow controlling shrinkage cracking in printed filaments. 3D printing for construction purposes is a disruptive technology with the potential for rapid and massive applications making it a feasible alternative for social housing, temporary shelters after disasters, and, recently, for extraterrestrial habitats. However, most of the matrices used for construction by 3D printing are based on hydraulic cement as the main constituent, which is not easily available in remote locations and is an important greenhouse gases generator. Therefore, a good understanding to formulate and evaluate alternative matrices using soil and organic materials with the required fresh and hardened-state properties compatible with this emerging technology is needed. This article studies the printable capabilities of eco-friendly earthen-based matrices which uses potato starch as a natural stabilizer for raw soil mortars aiming to obtain 3D printed filaments with adequate fresh and hardened-states properties. The aqueous starch gel was combined with sisal fibers in the printing mixture to control shrinkage cracking problems during hardening. The optimization of the dosage of the stabilizer was carried out considering different tests in fresh and hardened printed filaments namely, pumpability and extrudability, stacking, shear vane, shrinkage cracking, Vicat needle, compression strength, and capillarity absorption tests. The results indicate that printable earthen-based matrices reinforced with 1 % of sisal fibers by weight of soil and stabilized with aqueous starch gels with concentrations up to 5 % (w/w) showed improved workability and minor cracking and can be used for 3D printing. These promising results in the field of material science combined with novel 3D printing technology that is also presented in the article open new lines of research for eco-friendly alternatives for the construction industry.

Optimizing Transport Logistics under Uncertainty with Simheuristics: Concepts, Review and Trends

Background: Uncertainty conditions have been increasingly considered in optimization problems arising in real-life transportation and logistics activities. Generally, the analysis of complex systems in these non-deterministic environments is approached with simulation techniques. However, simulation is not an optimization tool. Hence, it must be combined with optimization methods when our goal is to: (i) minimize operating costs while guaranteeing a given quality of service; or (ii) maximize system performance using limited resources. When solving NP-hard optimization problems, the use of metaheuristics allows us to deal with large-scale instances in reasonable computation times. By adding a simulation layer to the metaheuristics, the methodology becomes a simheuristic, which allows the optimization element to solve scenarios under uncertainty. Methods: This paper reviews the indexed documents in Elsevier Scopus database of both initial as well as recent applications of simheuristics in the logistics and transportation field. The paper also discusses open research lines in this knowledge area. Results: The simheuristics approaches to solving NP-hard and large-scale combinatorial optimization problems under uncertainty scenarios are discussed, as they frequently appear in real-life applications in logistics and transportation activities. Conclusions: The way in which the different simheuristic components interact puts a special emphasis in the different stages that can contribute to make the approach more efficient from a computational perspective. There are several lines of research that are still open in the field of simheuristics.

Reality-Virtuality Technologies in the Field of Materials Science and Engineering

The increasing use of reality-virtuality technologies (RVTs, which encompass virtual, augmented, and mixed reality) in different fields over the last decade is a phenomenon for which materials science and engineering (MSE) is no exception. To obtain an overview of the implementation of RVTs in MSE, this team conducted a systematic search of the scientific literature published since 2010 addressing the use of RVTs in MSE. Forty-one relevant papers were selected and analyzed in depth to reach several conclusions, including: (i) most of the works (67.3%) are focused on the MSE area of materials structure, processing, and properties, which implies that there are great possibilities for research in other MSE areas; (ii) most of the works (86.8%) are aimed exclusively at education or research, which means that there are many fields outside of the university in which the use of RVT tools has not been developed and evaluated; (iii) the most used technology is virtual reality (85.1%), which means that there are many research possibilities focused on augmented and mixed reality. Researchers can find in the present work examples of the use of RVTs in MSE as well as other relevant information useful to open new lines of research and ideas that can contribute to their current and future work.

Multi-object tracking in traffic environments: A systematic literature review

The use of computer vision techniques to detect objects in images has grown in recent years. These techniques are especially useful to automatically extract and analyze information from an image or a sequence of them. One of the problems addressed by computer vision is multi-object tracking over frames sequences. To know the path and direction of objects can be crucial for some areas like traffic control and supervision; by doing that the system can be able to reduce traffic jams or redirect vehicles over less condensed areas. These algorithms include several aspects to have in mind in order to start a new development or research in this area, for instance, is important to review the current state-of-the art techniques, the hardware requirements, the main evaluation metrics, the commonly used datasets, among others. Therefore, the objective of this research is to present a systematic literature review which analyzes the recent works developed in the area of multi-object tracking in traffic environments. This paper reviews the techniques, hardware, datasets, metrics, and open lines of research in this area.

Dark Matter Searches Using NaI(Tl) at the Canfranc Underground Laboratory: Past, Present and Future

Sodium Iodide Thallium doped (NaI(Tl)) scintillation detectors have been applied to the direct searches for dark matter since the 1980s and have produced one of the most challenging results in the field—the observation by the DAMA/LIBRA collaboration of an annual modulation in the detection rate for more than twenty cycles. This result is very difficult to reconcile with negative results derived from other experiments using a large variety of target materials and detection techniques. However, it has been neither confirmed nor refuted in a model independent way up to the present. Such a model independent test of the DAMA/LIBRA result is the goal of the ANAIS-112 experiment, presently in the data taking phase at the Canfranc Underground Laboratory in Spain. ANAIS-112 design and operation leans on the expertise acquired at the University of Zaragoza in direct searches for Dark Matter particles using different targets and techniques and in particular using NaI(Tl) scintillation detectors for about thirty years, which are reviewed in the first section of this manuscript. In addition to presenting the status and more recent results of the ANAIS-112 experiment, open research lines, continuing this effort, will be presented.

Security in the Internet of Things Application Layer: Requirements, Threats, and Solutions

Communication systems and networks are evolving as an integral part of not only of our everyday life but also as a part of the industry, fundamental infrastructures, companies, etc. Current directions and concepts, such as the Internet of Things (IoT), promise enhanced quality of life, greater business opportunities, cost-effective manufacturing, and efficient operation management through ubiquitous connectivity and deployment of smart physical objects. IoT networks are able to collect, pre-process, and transmit a huge amount of data. A considerable portion of this data is security- and privacy-critical data, which makes IoT networks a tempting option for attackers. Given that these networks deal with the actual aspects of our lives and fundamental infrastructures (e.g. smart grids), cybersecurity in such networks is crucial. The large scale of these networks and their unique characteristics and complexity bring further vulnerabilities. In this study we give an introduction to IoT, focusing on the IoT application layer, security requirements, threats, and countermeasures in this layer, and some of the open issues and future research lines.

Identification of the interactome of the DP1 receptor for Prostaglandin D2: Regulation of DP1 receptor signaling and trafficking by IQGAP1

BackgroundMechanisms governing localization, trafficking and signaling of G protein-coupled receptors (GPCRs) are critical in cell function. Protein-protein interactions are determinant in these processes. However, there are very little interacting proteins known to date for the DP1 receptor for prostaglandin D2. MethodsWe performed LC-MS/MS analyses of the DP1 receptor interactome in HEK293 cells. To functionally validate our LC-MS/MS data, we studied the implications of the interaction with the IQGAP1 scaffold protein in the trafficking and signaling of DP1. ResultsIn addition to expected interacting proteins such as heterotrimeric G protein subunits, we identified proteins involved in signaling, trafficking, and folding localized in various cell compartments. Endogenous DP1-IQGAP1 co-immunoprecipitation was observed in colon cancer HT-29 cells. The interaction was augmented by DP1 agonist activation in HEK293 cells and GST-pulldown assays showed that IQGAP1 binds to intracellular loops 2 and 3 of DP1. Co-localization of the two proteins was observed by confocal microscopy at the cell periphery and in intracellular vesicles in the basal state. PGD2 treatment resulted in the redistribution of the DP1-IQGAP1 co-localization in the perinuclear vicinity. DP1 receptor internalization was promoted by overexpression of IQGAP1, while it was diminished by IQGAP1 knockdown with DsiRNAs. DP1-mediated ERK1/2 activation was augmented and sustained overtime by overexpression of IQGAP1 when compared to DP1 expressed alone. IQGAP1 knockdown decreased ERK1/2 activation by DP1 stimulation. Interestingly, ERK1/2 signaling by DP1 was increased when IQGAP2 was silenced, while it was impaired by IQGAP3 knockdown. ConclusionsOur findings define the putative DP1 interactome, a patho-physiologically important receptor, and validated the interaction with IQGAP1 in DP1 function. Our data also reveal that IQGAP proteins may differentially regulate GPCR signaling. General significanceThe identified putative DP1-interacting proteins open multiple lines of research in DP1 and GPCR biology in various cell compartments.

Dispositional Mindfulness and Injury Time Loss in Soccer

Soccer injuries have a low prevalence, albeit prompting detrimental effects for individuals and teams, particularly with prolonged convalescence periods. Age and injury severity appear as the most robust correlates with recovery duration. The role of dispositional mindfulness remains unknown, however, despite considerable evidence that highlights positive effects of mindfulness on injury rehabilitation. This study sought to examine whether dispositional mindfulness explained additional variability in injury time loss in an elite sample of soccer players (N = 207). A series of moderated regression analyses examined whether dispositional mindfulness interacted with either age or injury severity in explaining the length of recovery from an injury. The main findings suggest that dispositional mindfulness was unrelated with length of recovery. In contrast, age and injury severity related robustly with the length of lesion recovery, which was even longer for the older players with very severe injuries. The current findings constitute a novelty in the study of injuries in soccer and open new research lines to determine whether mindfulness interventions are likely to contribute to shorten objective rehabilitation length for a more sustainable approach to sports injury

Conceiving Socioscientific Issues in STEM Lessons from Science Education Research and Practice

This paper aims to elicit the different conceptions of Socioscientific Issues (SSI) in formal, non-tertiary STEM lessons. An examination of recent publications in the field of science education was conducted to elicit the most common conceptions of SSI as per the components of STEM lessons, namely: purpose, contents, teaching and learning strategies and assessment. As for purpose, the conceptions elicited have been organized in terms of contributing to citizenship goals, or to scientific competence. As for contents, it was found that SSI are related both to knowledge of science and knowledge about science and linked to skills such as argumentation. In terms of teaching and learning strategies, SSI are mainly associated with Inquiry-Based Learning; and with student engagement techniques such as dilemmas and group discussions. Lastly, performance assessment of student learning processes and results is typical when SSI are conceived as a method of assessment of STEM lessons. This conception sets up strong foundations for the design and evaluation of innovative SSI teaching. It shall also help to open new lines of research establishing connections among applications of SSI in different subjects, cultural contexts and educational systems.

The Phylogenetics and Biogeography of the Central Asian Hawkmoths, Hyles hippophaes and H. chamyla: Can Mitogenomics and Machine Learning Bring Clarity?

The western Palaearctic species of the hawkmoth genus Hyles (Lepidoptera: Sphingidae) have long been the subject of molecular phylogenetic research. However, much less attention has been paid to the taxa inhabiting the central and eastern Palaearctic, particularly Central Asia, where almost 50% of the species diversity of the genus occurs. Yet, many taxonomic conundrums hinder a proper assessment of the true diversity in these moths. One still unresolved group of species includes Hyles hippophaes and Hyles chamyla. Despite a largely overlapping morphology and ecology, a plethora of infraspecific taxa display some unique divergent characters over a wide geographical area. In this study, we undertook a taxonomic assessment of each population and resolved this species complex using an integrative approach. A combination of new computational techniques (DAISY-II) in comparative morphology and recent advances in DNA extraction methods and sequencing of museum specimens (WISC) alongside more traditional genetic approaches allowed testing of the three main phenotypes—bienerti, chamyla and apocyni—in terms of their morphological, mitochondrial and biogeographical integrity, and to elucidate their evolutionary relationships. Our results support the existence of two closely related species, Hyles chamyla and H. hippophaes, but the former species H. apocyni (here discussed as the ecological form apocyni of H. chamyla) is best regarded as a hybrid between H. chamyla and H. h. bienerti. The results indicate that the evolutionary relationship between H. chamyla and H. hippophaes is one of admixture in the context of ongoing ecological differentiation, which has led to shared morphological characters and a blurring of the species boundaries. These results clarify the evolutionary relationships of this species complex and open future research lines, including the analysis of nuclear markers and denser sampling, particularly of H. hippophaes and H. vespertilio in western Europe.

George Bereday Award for 2020

Previous articleNext article FreeAwardGeorge Bereday Award for 2020PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreEach year the George Bereday Award Committee selects the most outstanding Comparative Education Review (CER) article for the George Bereday Award. The selection committee includes scholars who are chosen for their breadth of methodological skills and intellectual rigor. This year’s committee was chaired by Jeremy Rappleye (Kyoto University, Japan), and included Inés Dussel (Centro de Investigación y de Estudios Avanzados, Mexico), Guorui Fan (East China Normal University, China), Padma Sarangapani (Tata Institute of Social Sciences, India), Miki Sugimura (Sophia University, Japan), and Stephen Carney (Roskilde University, Denmark). From 26 research articles published in volume 64 (2020) of CER (themselves selected from almost 200 annual submissions), the George Bereday Committee awarded the honor to Lisa Yiu for her article “Educational Injustice in a High-Stakes Testing Context: A Mixed Methods Study on Rural Migrant Children’s Academic Experiences in Shanghai Public Schools,” published in July. The committee reported the following: “The article utilized an impressive mixed methods approach to suggest that ‘successful’ teaching practices can only be understood within the diminished integrity of teaching in high-stakes testing contexts. It brings into rich focus the ways that the essentially moral act of teaching comes to be distorted under various national and global assessments, whilst artfully linking the teaching-learning experience to the larger social, political and economic landscape, including the hukou system and PISA. The committee noted the piece emerged from the author’s own experiences, multiyear relations with Shanghai teachers, and linguistic abilities, and felt the article had potential to open new lines of critical research.” The CER editors congratulate Lisa Yiu on this honor.The committee also noted the high quality of other articles and in particular offered an honorable mention to two articles: Manuel Enrique Cardoso, “Policy Evidence by Design: International Large-Scale Assessment and Grade Repetition,” published in November, and Nigel O. M. Brissett, “Teaching Like a Subaltern: Postcoloniality, Positionality, and Pedagogy in International Development and Education,” also published in November.George Zygmunt Fijalkowski Bereday, born in Warsaw in 1920, was both the founding editor of the CER and a cofounder of the Comparative Education Society, along with his close colleague William Brickman. A graduate of London and Oxford (while also serving in the British army during World War II), Professor Bereday subsequently arrived in the United States for PhD studies at Harvard’s Graduate School of Education. Later he received a JD from Columbia Law School, where he studied while teaching comparative education, sociology, and juvenile law at Columbia Teachers College from 1955 until his untimely death in 1983. William Brickman (writing in the fall of that year in Western European Education) called Bereday an extraordinarily talented and gifted personality: “A polyglot, he read, spoke, comprehended, and lectured in several Slavic, Germanic, and Romance languages … and he attained a practical ability in the use of Japanese. Brickman also enthused that “Professor Bereday represented a rare blend of the classical and the modern, of Eastern and Western European education and scholarship, and of the Occidental and Oriental cultures” and that he “exhibited endless evidence of humanism toward other cultures and humanitarianism toward persons of all ethnic, racial, and national backgrounds.” The composition of this year’s George Bereday Award Committee underscores that legacy. Previous articleNext article DetailsFiguresReferencesCited by Comparative Education Review Volume 65, Number 2May 2021 Sponsored by the Comparative and International Education Society Article DOIhttps://doi.org/10.1086/713788 © 2021 by the Comparative and International Education Society. All rights reserved.PDF download Crossref reports no articles citing this article.

On the Synergy between Virtual Reality and Multi-Agent Systems

Multi-agent systems integrate a great variety of artificial intelligence techniques from different fields, these systems have made it possible to create intelligent systems more efficiently. On the other hand, virtual reality applications are accepted as viable techniques in different areas such as visualization, simulation, design, and research. The combined use of these two technologies has led to the development of realistic and interactive applications. This work aims to do a Systematic Mapping Study (SMS) relying on the guidelines of Kitchenham and Petersen to analyze the state of the art of VR applications using multi-agent systems. Inclusion and exclusion criteria have been applied to identify relevant papers, 82 articles were selected and categorized according to the publication type, the research type, the asset type, and the purpose of the work. A complete review of the 82 selected articles was performed, based on the research questions that were established. This review made it possible to clarify the open lines of research that exist and to know where research in this field can be directed.

Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application

• Much is disclosed about the paradigm, theory, and development of PSO. • Relevant neighborhood topologies, fitness landscapes, and variants are addressed. • Various PSO-based complex optimization scenarios are discussed. • Key PSO practices are introduced to facilitate further future implementation. • A set of interesting open issues and potential future research lines are put forward. Over the ages, nature has constantly been a rich source of inspiration for science, with much still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial intelligence, was rendered to model the collective behavior of social swarms in nature. Ultimately, Particle Swarm Optimization algorithm (PSO) is arguably one of the most popular SI paradigms. Over the past two decades, PSO has been applied successfully, with good return as well, in a wide variety of fields of science and technology with a wider range of complex optimization problems, thereby occupying a prominent position in the optimization field. However, through in-depth studies, a number of problems with the algorithm have been detected and identified; e.g., issues regarding convergence, diversity, and stability. Consequently, since its birth in the mid-1990s, PSO has witnessed a myriad of enhancements, extensions, and variants in various aspects of the algorithm, specifically after the twentieth century, and the related research has therefore now reached an impressive state. In this paper, a rigorous yet systematic review is presented to organize and summarize the information on the PSO algorithm and the developments and trends of its most basic as well as of some of the very notable implementations that have been introduced recently, bearing in mind the coverage of paradigm, theory, hybridization, parallelization, complex optimization, and the diverse applications of the algorithm, making it more accessible. Ease for researchers to determine which PSO variant is currently best suited or to be invented for a given optimization problem or application. This up-to-date review also highlights the current pressing issues and intriguing open challenges haunting PSO, prompting scholars and researchers to conduct further research both on the theory and application of the algorithm in the forthcoming years.

Towards Automatic Construction of Multi-Network Models for Heterogeneous Multi-Task Learning

Multi-task learning, as it is understood nowadays, consists of using one single model to carry out several similar tasks. From classifying hand-written characters of different alphabets to figuring out how to play several Atari games using reinforcement learning, multi-task models have been able to widen their performance range across different tasks, although these tasks are usually of a similar nature. In this work, we attempt to expand this range even further, by including heterogeneous tasks in a single learning procedure. To do so, we firstly formally define a multi-network model, identifying the necessary components and characteristics to allow different adaptations of said model depending on the tasks it is required to fulfill. Secondly, employing the formal definition as a starting point, we develop an illustrative model example consisting of three different tasks (classification, regression, and data sampling). The performance of this illustrative model is then analyzed, showing its capabilities. Motivated by the results of the analysis, we enumerate a set of open challenges and future research lines over which the full potential of the proposed model definition can be exploited.