Regular exercise improves health, modulating the immune system and impacting inflammatory status. Immunoglobulin G (IgG) N-glycosylation reflects changes in inflammatory status; thus, we investigated the impact of regular exercise on overall inflammatory status by monitoring IgG N-glycosylation in a previously inactive, middle-aged, overweight and obese population (50.30 ± 9.23 years, BMI 30.57 ± 4.81). Study participants (N = 397) underwent one of three different exercise programs lasting three months with blood samples collected at baseline and at the end of intervention. After chromatographically profiling IgG N-glycans, linear mixed models with age and sex adjustment were used to investigate exercise effects on IgG glycosylation. Exercise intervention induced significant changes in IgG N-glycome composition. We observed an increase in agalactosylated, monogalctosylated, asialylated and core-fucosylated N-glycans (padj = 1.00 × 10−4, 2.41 × 10−25, 1.51 × 10−21 and 3.38 × 10−30, respectively) and a decrease in digalactosylated, mono- and di-sialylated N-glycans (padj = 4.93 × 10−12, 7.61 × 10−9 and 1.09 × 10−28, respectively). We also observed a significant increase in GP9 (glycan structure FA2[3]G1, β = 0.126, padj = 2.05 × 10−16), previously reported to have a protective cardiovascular role in women, highlighting the importance of regular exercise for cardiovascular health. Other alterations in IgG N-glycosylation reflect an increased pro-inflammatory IgG potential, expected in a previously inactive and overweight population, where metabolic remodeling is in the early stages due to exercise introduction.

Glycans are an essential structural component of Immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation). We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in the in vitro IgG expression system. Up- and downregulation of three genes, EEF1A1, MANBA and TNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in this in vitro expression system.

Catalytic materials are the greatest challenge for the commercial application of water electrolysis (WEs) and fuel cells (FCs) as clean energy technologies. There is a need to find an alternative to expensive and unavailable platinum group metal (PGM) catalysts. This study aimed to reduce the cost of PGM materials by replacing Ru with RuO2 and lowering the amount of RuO2 by adding abundant and multifunctional ZnO. A ZnO@RuO2 composite in a 10:1 molar ratio was synthesized by microwave processing of a precipitate as a green, low-cost, and fast method, and then annealed at 300°C and 600°C to improve the catalytic properties. The physicochemical properties of the ZnO@RuO2 composites were investigated by X-ray powder diffraction (XRD), Raman and Fourier transform infrared (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM), UV-Vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) spectroscopy. The electrochemical activity of the samples was investigated by linear sweep voltammetry in acidic and alkaline electrolytes. We observed good bifunctional catalytic activity of the ZnO@RuO2 composites toward HER and OER in both electrolytes. The improved bifunctional catalytic activity of the ZnO@RuO2 composite by annealing was discussed and attributed to the reduced number of bulk oxygen vacancies and the increased number of established heterojunctions.

BACKGROUND: Critical care medicine is a young branch of medicine, of which the development was much faster in High Income Countries (HICs) than in Low Resources Settings (LRS). Slovenia, as one of the successor states of former Yugoslavia, passed the process of transition and joined the European Union successfully. On the contrary, Bosnia and Herzegovina (B&H) went through the extremely difficult process of transition (four years of civil war), which left a deep scar to the healthcare system, including critical care medicine. OBJECTIVE: To examine the impact of HICs on the development of critical care in LRS. METHOD: This review examined the process of growing up the first modern Medical Intensive Care Unit (MICU) in the Republic of Srpska. RESULTS: The five-year process of transferring critical care knowledge from Slovenia to the health care system of Republic of Srpska has contributed to the existence of modern and state of the art MICU with tremendous social effects. CONCLUSION: The model of using the impact of HICs for improving critical care in LRS can be extrapolated to other similar settings.

Museums are traditionally considered learning environments and are ordinarily used for non-formal education. Physical museums, while being irreplaceable, are limited to a physical space, requiring mobility and physical presence. In addition, traditional exhibitions are not designed for interaction and physical exploration of artefacts. With the focus being shifted from museum exhibits to visitors’ experience, utilization of emerging technologies and co-creation of virtual museums not only helps in preservation of cultural heritage, but enhances the dissemination, engagement, and experience, while addressing the mobility and the plurality of voices and perspectives represented. In this work, we designed and developed the School House Virtual Museum with tangible user interfaces based on participatory, interdisciplinary, and co-creative methods with students and a larger community of researchers, artists, and practitioners working on heritage and memory. In a user study with 62 participants, usability and user experience were explored and the potential contribution of such virtual museums to learning, based on critical, cross-disciplinary, and participatory dialogue, both in cultural and educational institutions/programs has been investigated. The results have confirmed that the system has been well designed and developed, and the user experience was largely positive. The responses from educators and students confirmed that the application holds potential as a learning and education tool in either museums, schools, or when used independently.

Smart traffic lights systems (STLSs) are a promising approach to improve traffic efficiency at intersections. They rely on the information sent by vehicles via C2X communication (like in cooperative awareness messages (CAMs)) at the managed intersection. While there exists a large body of work on privacy-enhancing technologies (PETs) for cooperative Intelligent Transport Systems (cITS) in general, such PETs like changing pseudonyms often impact the performance of cITS applications. This paper analyzes the extent to which different PETs affect the performance of two types of STLSs, a phase-based and a reservation-based STLS. These are implemented in SUMO and combined with four different PETs. Through extensive simulations we then investigate the impact of those PETs on STLS performance metrics like time loss, waiting time, fuel consumption, and average velocity. Our analysis shows that the impact of PETs on performance varies greatly depending on the type of STLS. Finally, we propose a hybrid STLS which is a combination of the two STLS types as a potential solution for limiting the negative impact of PETs on performance.

The application of Industry 4.0 (I4.0) in the field of logistics leads to the emergence and development of the concept of logistics 4.0. Many I4.0 technologies have been applied in the field of logistics. The goal of this research is to analyze the applicability of nine key I4.0 technologies in logistics centers (LC). For this purpose, an integrated MEREC (MEthod based on the Removal Effects of Criteria)—fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) model was developed. The applicability of nine I4.0 technologies was evaluated based on 15 subcriteria within three main groups of criteria, namely, technological, social and political, and economic and operative. Using the MEREC method, the weight values of the criteria and subcriteria were determined, while the technologies were ranked using the fuzzy MARCOS method. Based on the results obtained by applying this integrated MCDM (multicriteria decision-making) model, CC was identified as the best alternative, i.e., the technology that is most applicable in logistics centers, followed by IoT and big data. An analysis of the sensitivity of the obtained results to the change in the importance of the criteria was carried out, which shows certain changes in the ranking when the importance of the most important criterion changes.

This paper analyzes the linear and non-linear relationship between non-performing loans and bank profitability measured by the Net Interest Margin for a sample of 74 Middle Eastern and North African banks over the period of 2005–2020. We used the System Generalized Method of Moments (SGMM) as a linear approach and the Panel Smooth Transition Regression (PSTR) model as a non-linear approach. The empirical results of the SGMM approach indicated that the ratio of NPLs negatively affects bank profitability. The findings of the non-linear relationship based on the PSTR model confirmed the existence of a threshold effect. We found that below the threshold of 4.42%, the effect of NPLs is negative but not significant, while after surpassing this threshold, the effect becomes negative and significant. As for bank specifics, we revealed that bank size is positively and significantly associated with bank profitability. For industry factors, we found that more bank concentration decreases bank profitability. Regarding the financial environment, we concluded that the global financial crisis exerted a negative impact on bank profitability. Moreover, we revealed a positive and significant impact of GDP on bank profitability as well as a negative impact of inflation on bank profitability. This study has some limitations regarding the social, economic, and financial differences of the whole sample, which includes banks from the Middle East and others from North Africa. Hence, decomposing the whole sample into two sub-samples could improve the results of this paper.

With the advent of Artificial Intelligence for healthcare, data synthesis methods present crucial benefits in facilitating the fast development of AI models while protecting data subjects and bypassing the need to engage with the complexity of data sharing and processing agreements. Existing technologies focus on synthesising real-time physiological and physical records based on regular time intervals. Real health data are, however, characterised by irregularities and multimodal variables that are still hard to reproduce, preserving the correlation across time and different dimensions. This paper presents two novel techniques for synthetic data generation of real-time multimodal electronic health and physical records, (a) the Temporally Correlated Multimodal Generative Adversarial Network and (b) the Document Sequence Generator. The paper illustrates the need and use of these techniques through a real use case, the H2020 GATEKEEPER project of AI for healthcare. Furthermore, the paper presents the evaluation for both individual cases and a discussion about the comparability between techniques and their potential applications of synthetic data at the different stages of the software development life-cycle.

A search is presented for displaced production of Higgs bosons or $Z$ bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes $H\rightarrow \gamma\gamma$ and $Z\rightarrow ee$. The analysis uses the full Run 2 data set of proton$-$proton collisions delivered by the LHC at an energy of $\sqrt{s}=13$ TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb$^{-1}$. Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a $Z$ boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for higgsino pair production, up to a $\tilde\chi^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\tilde\chi^0_1$ to Higgs ($Z$) bosons for a $\tilde\chi^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.

In recent times the chiral semimetal cobalt monosilicide (CoSi) has emerged as a prototypical, nearly ideal topological conductor hosting giant, topologically protected Fermi arcs. Exotic topological quantum properties have already been identified in CoSi bulk single crystals. However, CoSi is also known for being prone to intrinsic disorder and inhomogeneities, which, despite topological protection, risk jeopardizing its topological transport features. Alternatively, topology may be stabilized by disorder, suggesting the tantalizing possibility of an amorphous variant of a topological metal, yet to be discovered. In this respect, understanding how microstructure and stoichiometry affect magnetotransport properties is of pivotal importance, particularly in case of low-dimensional CoSi thin films and devices. Here we comprehensively investigate the magnetotransport and magnetic properties of ≈25 nm Co1–xSix thin films grown on a MgO substrate with controlled film microstructure (amorphous vs textured) and chemical composition (0.40 < x < 0.60). The resistivity of Co1–xSix thin films is nearly insensitive to the film microstructure and displays a progressive evolution from metallic-like (dρxx/dT > 0) to semiconducting-like (dρxx/dT < 0) regimes of conduction upon increasing the silicon content. A variety of anomalies in the magnetotransport properties, comprising for instance signatures consistent with quantum localization and electron–electron interactions, anomalous Hall and Kondo effects, and the occurrence of magnetic exchange interactions, are attributable to the prominent influence of intrinsic structural and chemical disorder. Our systematic survey brings to attention the complexity and the challenges involved in the prospective exploitation of the topological chiral semimetal CoSi in nanoscale thin films and devices.