University of Limerick

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such ‘multilayer’ features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize ‘traditional’ network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other and provide a thorough discussion that compares, contrasts and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

The metaverse has the potential to extend the physical world using augmented and virtual reality technologies allowing users to seamlessly interact within real and simulated environments using avatars and holograms. Virtual environments and immersive games (such as, Second Life, Fortnite, Roblox and VRChat) have been described as antecedents of the metaverse and offer some insight to the potential socio-economic impact of a fully functional persistent cross platform metaverse. Separating the hype and “meta…” rebranding from current reality is difficult, as “big tech” paints a picture of the transformative nature of the metaverse and how it will positively impact people in their work, leisure, and social interaction. The potential impact on the way we conduct business, interact with brands and others, and develop shared experiences is likely to be transformational as the distinct lines between physical and digital are likely to be somewhat blurred from current perceptions. However, although the technology and infrastructure does not yet exist to allow the development of new immersive virtual worlds at scale - one that our avatars could transcend across platforms, researchers are increasingly examining the transformative impact of the metaverse. Impacted sectors include marketing, education, healthcare as well as societal effects relating to social interaction factors from widespread adoption, and issues relating to trust, privacy, bias, disinformation, application of law as well as psychological aspects linked to addiction and impact on vulnerable people. This study examines these topics in detail by combining the informed narrative and multi-perspective approach from experts with varied disciplinary backgrounds on many aspects of the metaverse and its transformational impact. The paper concludes by proposing a future research agenda that is valuable for researchers, professionals and policy makers alike.

A qualitative description design is particularly relevant where information is required directly from those experiencing the phenomenon under investigation and where time and resources are limited. Nurses and midwives often have clinical questions suitable to a qualitative approach but little time to develop an exhaustive comprehension of qualitative methodological approaches. Qualitative description research is sometimes considered a less sophisticated approach for epistemological reasons. Another challenge when considering qualitative description design is differentiating qualitative description from other qualitative approaches. This article provides a systematic and robust journey through the philosophical, ontological, and epistemological perspectives, which evidences the purpose of qualitative description research. Methods and rigor issues underpinning qualitative description research are also appraised to provide the researcher with a systematic approach to conduct research utilizing this approach. The key attributes and value of qualitative description research in the health care professions will be highlighted with the aim of extending its usage.

Additive manufacturing (AM) is fundamentally different from traditional formative or subtractive manufacturing in that it is the closest to the 'bottom up' manufacturing where a structure can be built into its designed shape using a 'layer-by-layer' approach rather than casting or forming by technologies such as forging or machining. AM is versatile, flexible, highly customizable and, as such, can suite most sectors of industrial production. Materials to make these parts/objects can be of a widely varying type. These include metallic, ceramic and polymeric materials along with combinations in the form of composites, hybrid, or functionally graded materials (FGMs). The challenge remains, however, to transfer this 'making' shapes and structures into obtaining objects that are functional. A great deal of work is needed in AM in addressing the challenges related to its two key enabling technologies namely 'materials' and 'metrology' to achieve this functionality in a predictive and reproductive ways. The good news is that there is a significant interest in industry for taking up AM as one of the main production engineering route. Additive Manufacturing, in our opinion, is definitely at the cross-road from where this new, much-hyped but somewhat unproven manufacturing process must move towards a technology that can demonstrate the ability to produce real, innovative, complex and robust products.

The trade-off between physical adsorption capacity and selectivity of porous materials is a major barrier for efficient gas separation and purification through physisorption. We report control over pore chemistry and size in metal coordination networks with hexafluorosilicate and organic linkers for the purpose of preferential binding and orderly assembly of acetylene molecules through cooperative host-guest and/or guest-guest interactions. The specific binding sites for acetylene are validated by modeling and neutron powder diffraction studies. The energies associated with these binding interactions afford high adsorption capacity (2.1 millimoles per gram at 0.025 bar) and selectivity (39.7 to 44.8) for acetylene at ambient conditions. Their efficiency for the separation of acetylene/ethylene mixtures is demonstrated by experimental breakthrough curves (0.73 millimoles per gram from a 1/99 mixture).

La presente investigación tuvo como objetivo analizar y comparar el impacto psicológico por la contingencia por COVID-19 en un grupo de mujeres de Colombia y México. La muestra estuvo conformada por un total de 193 mujeres con edades comprendidas entre los 18 y los 62 años residentes en Colombia (100) y México (93), seleccionados por medio de un muestreo por conveniencia, dentro de los criterios de inclusión se consideró el sexo (sólo mujeres), el rango de edad (que fueran mayor de edad) y el país de residencia, (Colombia y México), que se encontraran alfabetizadas. Para dar respuestas a los objetivos planteados, se hizo la administración de una encuesta sociodemográfica y la aplicación de la escala SCL-90R a través de un enlace de participación (formulario de Google) de forma individual. Se observó elevados puntajes en los patrones sintomatológicos de las dimensiones primarias y los síntomas positivos evaluados en la escala SCL90-R

Enzymes are versatile catalysts in the laboratory and on an industrial scale. To broaden their applicability in the laboratory and to ensure their (re)use in manufacturing the stability of enzymes can often require improvement. Immobilisation can address the issue of enzymatic instability. Immobilisation can also help to enable the employment of enzymes in different solvents, at extremes of pH and temperature and exceptionally high substrate concentrations. At the same time substrate-specificity, enantioselectivity and reactivity can be modified. However, most often the molecular and physical-chemical bases of these phenomena have not been elucidated yet. This tutorial review focuses on the understanding of enzyme immobilisation.

The label 'chronic fatigue syndrome' (CFS) has persisted for many years because of the lack of knowledge of the aetiological agents and the disease process. In view of more recent research and clinical experience that strongly point to widespread inflammation and multisystemic neuropathology, it is more appropriate and correct to use the term 'myalgic encephalomyelitis' (ME) because it indicates an underlying pathophysiology. It is also consistent with the neurological classification of ME in the World Health Organization's International Classification of Diseases (ICD G93.3). Consequently, an International Consensus Panel consisting of clinicians, researchers, teaching faculty and an independent patient advocate was formed with the purpose of developing criteria based on current knowledge. Thirteen countries and a wide range of specialties were represented. Collectively, members have approximately 400 years of both clinical and teaching experience, authored hundreds of peer-reviewed publications, diagnosed or treated approximately 50 000 patients with ME, and several members coauthored previous criteria. The expertise and experience of the panel members as well as PubMed and other medical sources were utilized in a progression of suggestions/drafts/reviews/revisions. The authors, free of any sponsoring organization, achieved 100% consensus through a Delphi-type process. The scope of this paper is limited to criteria of ME and their application. Accordingly, the criteria reflect the complex symptomatology. Operational notes enhance clarity and specificity by providing guidance in the expression and interpretation of symptoms. Clinical and research application guidelines promote optimal recognition of ME by primary physicians and other healthcare providers, improve the consistency of diagnoses in adult and paediatric patients internationally and facilitate clearer identification of patients for research studies.

Background: The accurate prediction of where faults are likely to occur in code can help direct test effort, reduce costs, and improve the quality of software. Objective: We investigate how the context of models, the independent variables used, and the modeling techniques applied influence the performance of fault prediction models. Method: We used a systematic literature review to identify 208 fault prediction studies published from January 2000 to December 2010. We synthesize the quantitative and qualitative results of 36 studies which report sufficient contextual and methodological information according to the criteria we develop and apply. Results: The models that perform well tend to be based on simple modeling techniques such as Naive Bayes or Logistic Regression. Combinations of independent variables have been used by models that perform well. Feature selection has been applied to these combinations when models are performing particularly well. Conclusion: The methodology used to build models seems to be influential to predictive performance. Although there are a set of fault prediction studies in which confidence is possible, more studies are needed that use a reliable methodology and which report their context, methodology, and performance comprehensively.

When droplets coalesce on a superhydrophobic nanostructured surface, the resulting droplet can jump from the surface due to the release of excess surface energy. If designed properly, these superhydrophobic nanostructured surfaces can not only allow for easy droplet removal at micrometric length scales during condensation but also promise to enhance heat transfer performance. However, the rationale for the design of an ideal nanostructured surface as well as heat transfer experiments demonstrating the advantage of this jumping behavior are lacking. Here, we show that silanized copper oxide surfaces created via a simple fabrication method can achieve highly efficient jumping-droplet condensation heat transfer. We experimentally demonstrated a 25% higher overall heat flux and 30% higher condensation heat transfer coefficient compared to state-of-the-art hydrophobic condensing surfaces at low supersaturations (<1.12). This work not only shows significant condensation heat transfer enhancement but also promises a low cost and scalable approach to increase efficiency for applications such as atmospheric water harvesting and dehumidification. Furthermore, the results offer insights and an avenue to achieve high flux superhydrophobic condensation.

BACKGROUND: The aim of this study is to review the literature on known barriers and solutions that face educators when developing and implementing online learning programs for medical students and postgraduate trainees. METHODS: An integrative review was conducted over a three-month period by an inter-institutional research team. The search included ScienceDirect, Scopus, BioMedical, PubMed, Medline (EBSCO & Ovid), ERIC, LISA, EBSCO, Google Scholar, ProQuest A&I, ProQuest UK & Ireland, UL Institutional Repository (IR), UCDIR and the All Aboard Report. Search terms included online learning, medical educators, development, barriers, solutions and digital literacy. The search was carried out by two reviewers. Titles and abstracts were screened independently and reviewed with inclusion/exclusion criteria. A consensus was drawn on which articles were included. Data appraisal was performed using the Critical Appraisal Skills Programme (CASP) Qualitative Research Checklist and NHMRC Appraisal Evidence Matrix. Data extraction was completed using the Cochrane Data Extraction Form and a modified extraction tool. RESULTS: Of the 3101 abstracts identified from the search, ten full-text papers met the inclusion criteria. Data extraction was completed on seven papers of high methodological quality and on three lower quality papers. Findings suggest that the key barriers which affect the development and implementation of online learning in medical education include time constraints, poor technical skills, inadequate infrastructure, absence of institutional strategies and support and negative attitudes of all involved. Solutions to these include improved educator skills, incentives and reward for the time involved with development and delivery of online content, improved institutional strategies and support and positive attitude amongst all those involved in the development and delivery of online content. CONCLUSION: This review has identified barriers and solutions amongst medical educators to the implementation of online learning in medical education. Results can be used to inform institutional and educator practice in the development of further online learning.

The aim of this review was to provide an overview of assistive exoskeletons that have specifically been developed for industrial purposes and to assess the potential effect of these exoskeletons on reduction of physical loading on the body. The search resulted in 40 papers describing 26 different industrial exoskeletons, of which 19 were active (actuated) and 7 were passive (non-actuated). For 13 exoskeletons, the effect on physical loading has been evaluated, mainly in terms of muscle activity. All passive exoskeletons retrieved were aimed to support the low back. Ten-forty per cent reductions in back muscle activity during dynamic lifting and static holding have been reported. Both lower body, trunk and upper body regions could benefit from active exoskeletons. Muscle activity reductions up to 80% have been reported as an effect of active exoskeletons. Exoskeletons have the potential to considerably reduce the underlying factors associated with work-related musculoskeletal injury. Practitioner Summary: Worldwide, a significant interest in industrial exoskeletons does exist, but a lack of specific safety standards and several technical issues hinder mainstay practical use of exoskeletons in industry. Specific issues include discomfort (for passive and active exoskeletons), weight of device, alignment with human anatomy and kinematics, and detection of human intention to enable smooth movement (for active exoskeletons).

We present grammatical evolution, an evolutionary algorithm that can evolve complete programs in an arbitrary language using a variable-length binary string. The binary genome determines which production rules in a Backus-Naur form grammar definition are used in a genotype-to-phenotype mapping process to a program. We demonstrate how expressions and programs of arbitrary complexity may be evolved and compare its performance to genetic programming.

Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

This study integrated concepts from upper echelons, group process and social cognition theories to investigate how demographic diversity and group processes influence strategic consensus within the top management team (TMT), where strategic consensus is defined as the degree to which individual mental models of strategy overlap. Data from 76 high-technology firms in the United States and Ireland were used to examine three alternative models. The results showed that while demographic diversity alone did have effects on strategic consensus the overall fit of the model was not strong. Adding two intervening group process variables, interpersonal conflict and agreement-seeking, to the model greatly improved the overall relationship with strategic consensus. For the most part, TMT diversity had negative effects on strategic consensus. The model with superior fit showed both direct and indirect effects of diversity on strategic consensus. Copyright © 1999 John Wiley & Sons, Ltd.

Cocrystals, a long known but understudied class of crystalline solids, have attracted interest from crystal engineers and pharmaceutical scientists in the past decade and are now an integral part of the preformulation stage of drug development. This is largely because cocrystals that contain a drug molecule, pharmaceutical cocrystals, can modify physicochemical properties without the need for covalent modification of the drug molecule. This review presents a brief history of cocrystals before addressing recent advances in design, discovery and development of pharmaceutical cocrystals that have occurred since an earlier review published in 2004. We address four aspects of cocrystals: nomenclature; design using hydrogen-bonded supramolecular synthons; methods of discovery and synthesis; development of pharmaceutical cocrystals as drug products. Cocrystals can be classified into molecular cocrystals (MCCs) that contain only neutral components (coformers) and ionic cocrystals (ICCs), which are comprised of at least one ionic coformer that is a salt. That cocrystals, especially ICCs, offer much greater diversity in terms of composition and properties than single component crystal forms and are amenable to design makes them of continuing interest. Seven recent case studies that illustrate how pharmaceutical cocrystals can improve physicochemical properties and clinical performance of drug substances, including a recently approved drug product based upon an ICC, are presented.

This review captures the synthesis, assembly, properties, and applications of copper chalcogenide NCs, which have achieved significant research interest in the last decade due to their compositional and structural versatility. The outstanding functional properties of these materials stems from the relationship between their band structure and defect concentration, including charge carrier concentration and electronic conductivity character, which consequently affects their optoelectronic, optical, and plasmonic properties. This, combined with several metastable crystal phases and stoichiometries and the low energy of formation of defects, makes the reproducible synthesis of these materials, with tunable parameters, remarkable. Further to this, the review captures the progress of the hierarchical assembly of these NCs, which bridges the link between their discrete and collective properties. Their ubiquitous application set has cross-cut energy conversion (photovoltaics, photocatalysis, thermoelectrics), energy storage (lithium-ion batteries, hydrogen generation), emissive materials (plasmonics, LEDs, biolabelling), sensors (electrochemical, biochemical), biomedical devices (magnetic resonance imaging, X-ray computer tomography), and medical therapies (photochemothermal therapies, immunotherapy, radiotherapy, and drug delivery). The confluence of advances in the synthesis, assembly, and application of these NCs in the past decade has the potential to significantly impact society, both economically and environmentally.

The literature suggests that gamified learning interventions may increase student engagement and enhance learning. We empirically investigate this by exploring the impact of intrinsic and extrinsic motivation on the participation and performance of over 100 undergraduate students in an online gamified learning intervention. The paper makes a number of contributions. First, by synthesizing the literature the central concepts required for a learning intervention to be considered gamified are mapped and the development of an online gamified learning intervention is described. Second, the effect of gamification on learning outcomes is examined using a pre- and post-intervention survey. We find that gamified learning interventions have a positive impact on student learning. Third, our results show that while generally positive, the impact of gamified intervention*ns on student participation varies depending on whether the student is motivated intrinsically or extrinsically. These findings will be of practical interest to teaching and learning practitioners working in a range of educational contexts, and at all levels of education, who wish to increase student engagement and enhance learning.