Joanneum Research

This study examines Zimbabwe's public sector's serious cybersecurity issues in light of the country's fast digitisation and increasing reliance on e-governance tools. Adoption of digital services exposes governmental institutions to cyber risks that they are ill-prepared to handle, even if it also offers prospects for efficiency and transparency. Based on contextual analysis and international best practices, this conceptual paper suggests a paradigm for digital resilience that is specific to Zimbabwe. The framework combines awarenessraising, infrastructure modernisation, capacity-building, and policy reform into a cohesive strategy to strengthen public institutions against cyber threats. Examined as major barriers to cybersecurity maturity include institutional inertia, financial limitations, and regulatory fragmentation. In order to move Zimbabwe from reactive to proactive cybersecurity measures, the study urges immediate multi-stakeholder coordination.

Realtime human action recognition from video streams is becoming increasingly essential for applications that require immediate interpretation of human behavior. This includes scenarios such as interactive virtual environments and responsive healthcare systems. This paper presents HumAct, a novel algorithm developed for live human action recognition. It reliably detects a broad range of human actions, even within diverse and challenging video content. The algorithm achieves realtime performance, identifying actions for multiple persons in the scene with a delay of only two seconds from their occurrence in a video live stream. We demonstrate the practical effectiveness of the HumAct algorithm through two applications: enhancing intuitive interaction in VR/XR environments and delivering timely alerts for falling elderly persons in an ambient assisted living setting. Together, these examples highlight the flexibility and strong potential of our proposed live human action recognition algorithm for real-world deployment.

Polymeric based materials such as polyether ether ketone (PEEK) or polyethylene terephthalate (PET) are one of the most important thermoplastic synthetic materials in industry with a wide range of mechanical, tribological and thermal applications. In the unlubricated state, unfilled materials suffer from a relatively high friction coefficient with a COF >0.8. Deposition strategies were investigated to obtain low friction and wear-resistant coatings on PEEK and PET surfaces via atmospheric pressure plasma deposition (APPD). Several composite coatings based on molybdenum disulphide (MoS 2 ), graphite (C) and zinc (Zn) were developed to achieve good adhesion and low-friction properties. Given that the MoS 2 -C-Zn composite coating system is affected by humidity under ambient conditions, a polymeric based dry lubricant coating was intensively conceptualised to prevent this issue. The designed polymeric lubricant is based on a polyamide 12 (PA12) and a polyethylene terephthalate (PTFE) feedstock fraction. The strategy is to embed high quantities of PTFE inside the PA12 matrix with excellent anchoring properties within the plasma deposition process by generating a humidity independent low friction coating. Therefore, the PA12 feedstock with a relatively low melting temperature (i.e. 180 °C) was ideal to transfer the solid particles into liquid droplets for inserting the PTFE fraction as solid (i.e. with a significant higher melting point of 327 °C) during the coating process. The final PA12-PTFE coatings on PEEK demonstrated a stable COF <0.1 over 10,000 rotational cycles (i.e. 324 m) with no humidity impact during the ball-on-disc measurements under ambient conditions. The specific wear rates of the metallic (9.4 × 10 −4 mm 3 N −1 m −1 ) and polymeric (9.1 × 10 −5 mm 3 N −1 m −1 ) based coatings were also investigated. • Embedding of PTFE particles in PA12 by an atmospheric pressure plasma jet • Cohesion properties between PA12 and PTFE are tunable by the plasma process. • PA12-PTFE films with a COF <0.1 generated on unfilled PEEK. • MoS 2 -C-Zn films exhibit a COF 0.2 when the relative humidity level is <10 %.

Abstract High-accuracy GNSS (Global Navigation Satellite System) positioning requires the receiver to use correction data. This data is typically delivered via 4G mobile internet. In this paper, we present a novel method to deliver the data via C-ITS (Cooperative Intelligent Transport Systems and Service). We compare its performance against using 4G and analyze the impact on the accuracy during data gaps, all using data collected in test drives from a real deployment in a small segment of a motorway. The results show that with C-ITS, a comparable performance can be achieved. The observed 2D position errors in our tests were below 3.1 cm for 95% and below 10 cm for more than 99% of the time.

Digital twins are living digital surrogates of objects and processes from the world around us and serve many purposes in situations where a physical model cannot be used. Digital twins can be considered to still be in their nascent phase, be it in the variety of application domains or in the science of creating and manipulating them. The DIDYMOS-XR project uses digital twins to create large-scale (city-wide) and long-term eXtended Reality (XR) applications. In this paper, we propose three use cases—city planning, city maintenance, and city tourism—along with an industrial use case for manufacturing environments, demonstrated through evaluation sites in Germany and Spain. The paper introduces cutting-edge solutions in the creation, simulation, and manipulation of DTs, including advancements in 3D scene reconstruction, data enhancement, data compression, sensor fusion, localization, rendering, and scene understanding. Additionally, we address the ethical and privacy challenges of digital twin systems and propose strategies for mitigating these issues. This work offers a comprehensive framework for creating semantically rich, scalable, and interactive digital twins, providing valuable insights for diverse applications in urban planning, maintenance, tourism, and industrial optimization.

Abstract During the NASA Perseverance rover's exploration of the Jezero crater floor, coatings were commonly observed on rocks. These features may record past water‐rock‐atmosphere interactions on the crater floor, and understanding their origin is important for constraining the timing of potential water activity and habitability at Jezero. Here, we characterize the morphologic, chemical, and spectral properties of the crater floor rock coatings using color images, visible/near‐infrared reflectance spectra, and chemical data from the Mastcam‐Z and SuperCam instruments. We show that coatings are common and compositionally similar across the crater floor, and consistent with a mixture of dust, fine regolith, sulfates, and ferric oxides indurated as a result of one or more episodes of widespread surface alteration. All coatings exhibit a similar smooth homogenous surface with variable thickness, color, and spatial extent on rocks, likely reflecting variable oxidation and erosional expressions related to formation and/or exposure age. Coatings unconformably overlie eroded natural rock surfaces, suggesting relatively late deposition that may represent one of the last alteration episodes on the Jezero crater floor. While more common at Jezero, these coatings may be consistent with rock coatings previously observed in situ at other landing sites and may be related to duricrust formation, suggesting a global alteration process on Mars that is not unique to Jezero. The Perseverance rover likely sampled these rock coatings on the crater floor and the results from this study could provide important context for future investigations by the Mars Sample Return mission aimed at constraining the geologic and alteration history of Jezero crater.

BackgroundCognitive impairment and psychological complaints are among the most common consequences for patients suffering from Post-Covid-19 condition (PCC). As there are limited training options available, this study examined a longitudinal tablet-based training program addressing cognitive and psychological symptoms.MethodsForty individuals aged between 36 and 71 years (M = 49.85, SD = 8.63; 80% female) were randomly assigned to either an intervention group (n = 20) or a waitlist control group (n = 20). The intervention group received a three-month tablet-based training program involving cognitive exercises, relaxation techniques, and physiotherapy exercises. Additionally, both groups underwent a thorough neuropsychological assessment (attention, memory, executive functions, word fluency, subjective cognitive complaints, fatigue, depression, anxiety, and quality of life) before the training, after 3 months of training, and after 6 months in order to assess long-term effects.ResultsPre-post comparisons revealed that individuals assigned to the intervention group (n = 18 after dropout), as compared to the control group (n = 16 after dropout), showed a reduction in subjective cognitive complaints (p < 0.001) as well as in depressive symptoms (p < 0.001). Additionally, their MoCA Memory Index Score remained stable (p = 0.496), while it declined significantly in the wait-list control group (p = 0.008). However, the training had no effect on the other domains assessed and not all training-related effects were stable over time. Finally, a higher number of post-Covid symptoms was negatively correlated with attention and memory capabilities (all p < 0.05), with a longer disease duration further amplifying the negative impact of post-Covid symptoms on memory performance.ConclusionTablet-based training programs can help improve subjective complaints, depressive symptoms, and memory and may serve as an additional therapy option. Further studies are needed to investigate the stability of these effects.

The disadvantage of generating electricity from renewable sources is the need for its simultaneous consumption afterwards or distribution to other consumers over long distances, which is accompanied by significant energy losses in networks with increasing transportation distances. In addition, there is a discrepancy between the seasonal maximum volumes of electricity generation and consumption. Thus, imbalances arise between the demand and supply of electricity on the market. This problem can be solved by converting excess green electricity into hydrogen, which can be stored in a gaseous or liquid state, transported over any distance and converted back into electrical or thermal energy at any time when the need arises. Although this process is characterized by energy losses, it allows creating climate-neutral energy reserves. Accordingly, the main technologies for creating hydrogen, their economic significance for the formation of the renewable energy market and the possibility of implementation within the framework of the pan-European energy system are analyzed. It has been established that Ukraine has favorable conditions for generating cheap electricity for the purpose of producing hydrogen, which can be supplied to the EU through the development of intergovernmental cooperation between Ukraine and the EU countries. A forecast of hydrogen production in Ukraine has been made and the possibilities of its supply to the EU market have been assessed.

Glioblastoma exhibits a very poor prognosis and profound metabolic alterations associated to its aggressiveness. Examining tumor metabolic states is crucial for identifying potential therapeutic targets, enabling personalized medicine applications. However, direct access to the functional glioblastoma tumor microenvironment (TME) in vivo is highly challenging, particularly due to the tumor location and risk of blood-brain-barrier disruption. Here, we developed a novel research platform combining the innovative sampling technology cerebral open flow microperfusion (cOFM) and HILIC-HRMS-based metabolomics to comprehensively characterize the local metabolic phenotype of human glioblastoma in xenograft animal model. Interstitial fluid (ISF) collected directly from the functional inner TME without trauma generation using cOFM, plasma (PL) and cerebrospinal fluid (CSF) were analyzed. The proposed method enabled consistent measurements, detecting nearly 400 metabolites with adequate analytical quality in the study samples, of which 281 were found in brain ISF. ISF presented the highest number of discriminant metabolites, with over 30% of the metabolome found to be altered in tumors compared to controls (p<0.05). Fewer significant metabolic changes were assessed in CSF. Correlation analysis of ISF and PL indicated distinct metabolic fluxes through lipid metabolism in these two compartments. Pathway enrichment analysis indicated significant alterations in pathways related to mechanisms contributing to glioblastoma progression. Evaluation of ISF samples revealed that glioblastoma metabolic reprogramming may involve altered activity of ABC transporters, fatty acid oxidation, enhanced metabolism of central carbon, arginine, proline, and amino acid derivatives engaged in redox homeostasis. Evaluation of PL samples indicated a pronounced contribution of systemic lipid-mediated signaling. ISF presented metabolic features and pathway activities from functional unaffected tumor, portraying metabolic traits of human glioblastoma tissue and corroborating the translational potential of this method. The novel cOFM-HILIC-HRMS research platform for in vivo/in situ monitoring of TME in glioblastoma can offer a promising and standardized tool for neuro-oncological research in the field of drug resistance and therapy development.