This paper presents the results of an action research conducted in a kindergarten in Sarajevo Canton. The participants were four female kindergarten educators who collaborated with two university professors who took the role of research leaders and moderators of reflective meetings. The action research was conceived as a model of professional development for preschool teachers in the Reggio pedagogy field, aiming to develop the skill of documenting pedagogical observation and the competence of implementing reflective practice (RP below the text) based on the Reggio principles. Data were collected on two levels: the educators documented their educational practice (photos, transcripts, videos, etc.), which was the basic material for analysis at collaborative reflective meetings, and all of it was documented by the research leaders. The data were analyzed simultaneously during the research (to decide on further action) and finally at the end of the research. The results of the research indicate that the action research raised awareness of the elements of traditional educational practice and developed the skills of pedagogical documentation management and the skill of implementing RP. Considering the limited time period for the realization of the research (14 months), significant but not optimal results were achieved, and there is still room for further progress in terms of improving the skills of keeping records and the capacity of RP implementation. It is necessary to systematically provide support for the professional development of educators through the development of reflective learning communities in kindergartens instead of the one-off and lecture-based forms that are offered.

Sociology offers a valuable lens through which to examine the societal transformations taking place in the age of artificial intelligence. By analysing micro-, meso- and macro-social levels, sociology can shed light on how AI affects processes such as socialisation, education, training, employment, communication, leisure and work. Furthermore, the impact of AI on social sustainability is a critical concern. This paper proposes a reflexive analysis of the sociology of AI to explore its potential contributions to social sustainability in the digital age. It considers the challenges associated with accessing and promoting digital literacy for AI, both as consumers and producers. It also considers the implications for sociology as a scientific discipline, encompassing both research methodologies and the products of inquiry. Through this analysis, the paper seeks to provide insights into how the sociology of AI can contribute to a more sustainable society in the digital age, and to identify the obstacles that need to be overcome to achieve this goal.   Received: 22 May 2024 / Accepted: 22 December 2024 / Published: 11 January 2025

Two different European Reference Networks cover connective tissue diseases with pediatric onset (ERN ReCONNET and ERN RITA). The transition of care is a significant focus, with ReCONNET centers actively addressing this through updated programs. Despite these efforts, challenges persist. We aimed to inventory transitional care programs for rCTDs across Europe. In April 2023, the ERN ReCONNET Transition of Care Task Force, consisting of expert clinicians, patient advocates, and coordination team members, created a survey to assess transitional care practices. The survey was distributed to ERN ReCONNET and ERN RITA centers, and responses received by March 15, 2024, were analyzed. Sixty-seven responses from 59 centers across 20 European countries were collected. Pediatric rheumatologists typically initiated the transition process (49% of centers). Twenty centers had joint clinics. Despite positive self-assessments of transitional programs, significant limitations were noted. Transition policies varied, with only 40% of centers having a formal standardized policy and less than half of the centers adhering to available transition of care guidelines. Transfer readiness was evaluated using validated questionnaires in 13% of centers, while 29% transitioned patients based solely on age without any readiness assessments. Main challenges included finding adult-oriented centers and the lack of guidelines or engagement from adult centers. Adult healthcare providers also noted a lack of training in adolescent medicine. The survey highlighted diverse transition practices and resources across centers, with challenges in readiness evaluation and the use of guidelines. Despite these obstacles, respondents rated ongoing transition processes positively. Enhancing patient perspectives in the transition process is crucial to meet their needs during this critical phase.

BACKGROUND Atherosclerosis of the coronary arteries is a chronic, progressive condition characterized by the buildup of plaque within the arterial walls. Coronary artery disease (CAD), more specifically coronary atherosclerosis (CATS), is one of the leading causes of death worldwide. Computational modeling frameworks have been used for simulation of atherosclerotic plaque progression and with the advancement of agent-based modeling (ABM) the simulation results became more accurate. However, there is a need for optimization of resources for predictive modeling, hence surrogate models are being built to substitute lengthy computational models without compromising the results. OBJECTIVE This study explores the development of a surrogate model for atherosclerotic plaque progression using ABM simulation data. METHOD The dataset used for this study contains samples from latin-hypercube sampling based generated simulation parameters used in conjunction with 15 patient-specific geometries and corresponding plaque progression data. The developed surrogate model is based on deep learning using artificial neural networks (ANN). RESULTS The surrogate model achieved an accuracy of 95.4% in benchmarking with the ABM model it was built upon which indicates the robustness of the framework. CONCLUSION Adoption of surrogate models with high accuracy in practice opens an avenue for utilization of high-fidelity decision support systems for predicting atherosclerotic plaque progression in real-time.

Although the influence of infill masonry on horizontal load structure behavior is well-documented, current standards and regulations have yet to fully incorporate or explicitly define the load-bearing capacity of this complex system. Canadian and American standards present more comprehensive and specific methodologies for calculating the load-bearing capacity of infill masonry and frame systems. In contrast, European standards tend to focus on offering general guidelines for the design of these systems without delving into the detailed calculation procedures. However, extensive data and experimental studies on this topic are available in the literature. The primary aim of this paper was to compile a database of experiments involving frames with different types of infill masonry. Subsequently, the empirical results obtained through the application of analytical expressions from various standards are compared to the experimental data included in the compiled database. The obtained load-bearing values were compared to different standards and work conducted by various researchers found in the literature in order to assess their reliability. Based on the obtained results, important conclusions were drawn, specifically to the most accurate equivalent diagonal model used and the analytical expressions to be used in the assessment of the masonry-infilled steel frame behavior. The equivalent diagonal model, utilized in all analytical expressions, can provide highly accurate estimations of load-bearing capacities that closely align with the experimental results. Regardless of the type of infill element, the analytical expressions consistently overestimated the load-bearing capacity. In the presence of longitudinal force, analytical expressions tend to be conservative, providing significantly lower load-bearing values compared with experimental results, which ensures a safety margin. The database can be utilized to develop numerical models, which can subsequently serve as the foundation for probabilistic methods used in conducting reliability assessments.

Background/Objectives: Colorectal cancer (CRC) remains a significant health burden, and its delayed diagnosis at advanced stages leads to poor survival outcome. Detection of known and novel prognostic markers is essential. In this study, the status of likely prognostic markers—the apoptotic inducing factor (AIFM3), vestigial-like family member 4 (VGLL4), and WNT4—was evaluated. Methods: AIFM3, VGLL4, and WNT4 expression in CRC tissues across different stages (Dukes A–D) were analyzed using histological immunofluorescence staining and RNA sequencing analyses. Results: In advanced CRC stages, progressive loss of normal crypt architecture, reduction of goblet cells, and necrotic debris were detected along with differential expression patterns of AIFM3, VGLL4, and WNT4. AIFM3 exhibited high reactivity in the lamina propria of healthy tissue and Dukes A, but this was diminished in advanced CRC stages. VGLL4 expression, initially confined to the lamina propria, increased significantly in the epithelium of Dukes B and C, with a cytoplasmic localization pattern. WNT4 expression was elevated in the CRC epithelium across all stages, contrasting with a significant reduction in lamina propria reactivity. RNA sequencing corroborated these findings, showing significant downregulation of AIFM3 and WNT4 and upregulation of VGLL4 in CRC tissues compared to controls. Expression of AIFM3 and WNT4 showed no correlation with survival outcome, while low VGLL4 expression was correlated with better survival outcome. Conclusions: The results suggest distinct roles for AIFM3, VGLL4, and WNT4 in CRC progression, highlighting only VGLL4 as a potential prognostic marker. Further evaluation of VGLL4 and its specific role in CRC progression remains to be elucidated.

Embedded systems, particularly when integrated into the Internet of Things (IoT) landscape, are critical for projects requiring robust, energy-efficient interfaces to collect real-time data from the environment. As these systems become complex, the need for dynamic reconfiguration, improved availability, and stability becomes increasingly important. This paper presents the design of a framework architecture that supports dynamic reconfiguration and “on-the-fly” code execution in IoT-enabled embedded systems, including a virtual machine capable of hot reloads, ensuring system availability even during configuration updates. A “hardware-in-the-loop” workflow manages communication between the embedded components, while low-level coding constraints are accessible through an additional abstraction layer, with examples such as MicroPython or Lua. The study results demonstrate the VM’s ability to handle serialization and deserialization with minimal impact on system performance, even under high workloads, with serialization having a median time of 160 microseconds and deserialization having a median of 964 microseconds. Both processes were fast and resource-efficient under normal conditions, supporting real-time updates with occasional outliers, suggesting room for optimization and also highlighting the advantages of VM-based firmware update methods, which outperform traditional approaches like Serial and OTA (Over-the-Air, the ability to update or configure firmware, software, or devices via wireless connection) updates by achieving lower latency and greater consistency. With these promising results, however, challenges like occasional deserialization time outliers and the need for optimization in memory management and network protocols remain for future work. This study also provides a comparative analysis of currently available commercial solutions, highlighting their strengths and weaknesses.

In the Croatian apple germplasm, there are, presumably, unique genotypes that have not yet been documented in reference molecular databases. Due to similarities between accessions, incorrect names are often used, which creates a problem in the identification of accessions. Overall, 169 apple accessions and 11 reference cultivars from the largest ex situ apple collection in the Republic of Croatia were investigated within this study. The examined accessions have been genotyped using SSR markers. In order to assess the advantage of a high-resolution marker system, such as SNPs, compared to low-resolution markers, such as SSRs, a subset of 23 unique apple accessions and eight reference cultivars were genotyped using the 480K Affymetrix Axiom SNP array. Results obtained through the use of two marker systems revealed 26 synonyms, 40 duplicates, 13 mislabeling accessions, 45 accessions with confirmed identity (known cultivars), and 45 unique accessions, as well as the true identity of a large number of accessions, currently maintained at the Croatian National Apple Germplasm Bank. In order to investigate the pomological variability of unique apples, a three-year study was carried out on eleven pomological traits. The researched germplasm shows an exceptional diversity of pomological properties. Many of the accessions can be considered unique, and the results of the pomological characterization indicated that this germplasm contains valuable traits of interest for future breeding programs.

In this study, the effect of ammunition on soil quality (physical and chemical indicators) at shooting ranges was investigated at four sites in Croatia. The sites differ in soil type (fluvisols, leptosols and terra rossa) and climatic conditions (Mediterranean and continental). The intensity of shooting range use (calculated from the age of the lane and the average number of targets used per year) and the distance from the shooting range (−40 m to +240 m) were examined in relation to soil chemical composition and soil quality. High contents of Pb and Sb at 100 m from the shooting position were observed in fluvisol and terra rossa soils, and the contamination factors (CFs) ranged from 6 up to 97. The study found high natural soil Cr and Ni content in leptosols and terra rossa due to paedogenic reasons (CFs < 1.3) and soil acidification (a decrease in soil pHKCl) due to ammunition/target use. Long-term measures for sustainable soil management and environment protection must be taken at shooting ranges to minimise the potential risks to ecosystems, wildlife and human health (an EU strategy).

<p><strong>Aim</strong> Lung ultrasound (LUS) can be used for an assessment of volume overload in patients with end-stage kidney disease (ESKD) and those undergoing dialysis. The aim of this study was to analyse whether the initial use of LUS in evaluating volume status could benefit patients by optimizing haemodialysis treatment and improving their clinical status.<br /><strong>Methods</strong> The study included 50 haemodialysis patients in stage V of ESKD with the diagnosis of ischaemic heart failure with reduced (HFrEF) or midrange ejection fraction (HFmrEF). The assessment of volume status was verified solely by LUS (along with the analysis of B lines as measures of volume status). The specified laboratory parameters were performed initially, after three, and after six months.<br /><strong>Results</strong> The number of B-lines on LUS were decreased during the six-month follow-up compared to baseline, indicating a reduction in volume overload due to the LUS-guided protocol. Statistically significant differences were observed in the average creatinine (p=0.001) and parathormone (PTH) (p=0.003) levels over the six-month monitoring period. Significant differences were also noted in triglyceride (p=0.000) and potassium (p=0.02) levels. No significant differences were found in the values of other monitored parameters.&nbsp;<br /><strong>Conclusion</strong> In haemodialysis patients diagnosed with heart failure, LUS can aid the achievement of a more efficient volume reduction by decreasing B-lines, which are indicative of congestion. Our study also demonstrated beneficial effects of LUS on potassium and parathormone levels.</p>