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.

When nonsequential double ionization is treated using the strong-field approximation and the saddle-point (SP) method, the transition amplitude can be expressed as a coherent sum of the partial amplitudes corresponding to different SP solutions. For the case of the recollision excitation with subsequent ionization (RESI) mechanism of the nonsequential double ionization, we examine the partial contributions of the SP solutions which correspond to the electron responsible for the excitation. For a monochromatic linearly polarized laser field, we find that, in addition to the pair of the SP solutions with the shortest travel time, other SP solutions may also make a significant contribution to the photoelectron yield. Moreover, the SP solutions appear in pairs and exhibit notable modifications in comparison to those observed in high-order above-threshold ionization. Furthermore, for a bichromatic linearly polarized driving field, we investigate the intensity range obtained using the simpleman’s model for which the RESI mechanism is dominant. We find that this range must be modified if the photoelectron yield corresponding to the SP solution for which the photoelectron has the highest energy upon return to the parent ion is small. This is particularly the case for the excitation channels involving loosely bound excited states.

Designing controllers that accomplish tasks while guaranteeing safety constraints remains a significant challenge. We often want an agent to perform well in a nominal task, such as environment exploration, while ensuring it can avoid unsafe states and return to a desired target by a specific time. In particular we are motivated by the setting of safe, efficient, hands-off training for reinforcement learning in the real world. By enabling a robot to safely and autonomously reset to a desired region (e.g., charging stations) without human intervention, we can enhance efficiency and facilitate training. Safety filters, such as those based on control barrier functions, decouple safety from nominal control objectives and rigorously guarantee safety. Despite their success, constructing these functions for general nonlinear systems with control constraints and system uncertainties remains an open problem. This paper introduces a safety filter obtained from the value function associated with the reach-avoid problem. The proposed safety filter minimally modifies the nominal controller while avoiding unsafe regions and guiding the system back to the desired target set. By preserving policy performance while allowing safe resetting, we enable efficient hands-off reinforcement learning and advance the feasibility of safe training for real world robots. We demonstrate our approach using a modified version of soft actor-critic to safely train a swing-up task on a modified cartpole stabilization problem.

This study examines the urgency of strengthening Indonesia's presidential institution to enhance governance and adapt to contemporary challenges. The research aims to assess the institution's capacity to ensure political stability, promote democratic values, and address corruption and centralization of power. Utilizing mixed methods, the study combines surveys, in-depth interviews, and direct observation, supported by thematic and statistical analysis. Key findings indicate that improving inter-institutional collaboration, adopting innovative decision-making strategies, and leveraging technology for transparency are crucial for addressing governance challenges. The study concludes that reforms in legal frameworks and accountability mechanisms are vital for enhancing public trust and institutional responsiveness. These findings provide actionable insights for policymakers to advance democratic governance and institutional resilience

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.

A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG). This study aimed to examine several aggregation operators using complex Diophantine interval-valued Pythagorean normal sets. We calculated the weighted average and geometric distance based on an aggregating model. We demonstrate that complex Diophantine interval-valued Pythagorean normal sets satisfy algebraic structures such as associative, distributive, idempotent, bounded, commutative and monotonic properties. In this study, we discuss the mathematical properties of the score and accuracy values. We provide an example of how enhanced score and accuracy values are used in the real world. Machine tool technology and computer science play essential roles in robots. To evaluate robotic systems, four factors must be considered such as tasks, precision, speed and completion of the work. Consequently, it is evident that the models are significantly influenced by the natural number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nabla$$\end{document}. To further demonstrate the effectiveness of the suggested approach, flowchart based multi-criteria decision-making is provided and applied to a numerical example. Additionally, a comparative study has been carried out to demonstrate the better results that the proposed approach provides when compared to current approaches.

Background: There are limited therapeutic options in cases of failed reperfusion (modified thrombolysis in cerebral infarction [mTICI] score < 2b) after stent-retriever and/or aspiration based endovascular treatment (EVT) for acute ischemic stroke. Despite the absence of data supporting its use, rescue therapy (balloon angioplasty and/or stent implantation) is often utilized in such cases. Studies are limited to large vessel occlusions, while the outcomes and complications after rescue therapy in medium/distal vessel occlusions (MDVOs) have not been reported. This study aims to report the outcomes of rescue therapy in MDVO stroke patients. Methods: We performed an analysis of the “Blood pressure and Antiplatelet medication management after reScue angioplasty after failed Endovascular treatment in Large and distal vessel occlusions with probable IntraCranial Atherosclerotic Disease” (BASEL ICAD) retrospective registry. All MDVO stroke patients were included in the analysis. Results: Out of the 718 registry patients, 87 (12.1%) presented with an MDVO. Fifty-six patients (64.4%) showed an occlusion of the M2 segment of the middle cerebral artery. Rescue stenting was performed in 78 patients (89.7%) while balloon angioplasty alone was performed in 9 patients (10.3%). Successful reperfusion (mTICI score ⩾ 2b) was achieved in 73 (83.9%) patients after rescue therapy. Symptomatic intracranial hemorrhage (sICH) occurred in 8 patients (9.2%) and post-treatment stent occlusion in 12 patients (13.8%). Ninety days mortality was 20.7%. Twenty-eight patients (32.2%) achieved functional independence at 90 days (modified Rankin Scale 0–2). Conclusion: Rescue therapy with stenting and/or balloon angioplasty in patients undergoing EVT for isolated MDVO with suspected underlying intracranial atherosclerotic disease is an effective reperfusion strategy but is associated with complications and poor functional outcomes. Graphical abstract

The natural progression of bioprosthetic valve degeneration over time requires further interventions for those experiencing symptomatic prosthesis dysfunction. Transcatheter aortic valve replacement (TAVR) emerges as a promising therapeutic option to alleviate symptoms in such patients. The valve-in-valve (ViV) technique eliminates the necessity for repetitive open-heart surgical procedures, offering particular advantages for individuals with higher surgical risks. In this report, we describe the case of a 78-year-old female patient presenting with severe symptomatic aortic restenosis of a biological aortic valve implanted 5 years prior. Given the patient’s high surgical risk, a transcatheter ViV implantation was chosen as the treatment approach. Utilizing a balloon-expandable valve, the intervention resulted in the successful implantation of a functional TAVR, resulting in symptom relief and enabling a fast discharge from the hospital.

This study evaluated Maltodextrin (MD), Gum Arabic (GA), and Carboxymethylcellulose (CMC) in different ratios as coating materials to encapsulate citrus pomace phenolic compounds. Citrus encapsulates were obtained by ultrasound-assisted extraction followed by the freeze-drying process and were characterized regarding the microencapsulation efficiency, physical, and chemical properties. Carrier material choice reflected a significant effect on encapsulation efficiency, phenolic compounds retention, and reconstitution properties of encapsulated extract. The encapsulation efficiency of prepared encapsulates ranked from 50.909% to 84.000%, and it was strongly dependent upon CMC addition. A wide range of reconstitution parameters (water absorption index-WAI and water solubility index-WSI) suggested possible release mechanism modifications. HPLC analysis revealed the presence of three main phenolic compounds, namely Hesperidin, Naringin, and Rutin. A wall material mixture of MD, GA, and CMC in the same proportions was optimal for freeze-drying. This combination resulted in encapsulates with a low moisture content (1.936 ± 0.012%) and a low water activity (0.110 ± 0.001), indicating prolonged stability. Based on the obtained results, freeze-drying as an encapsulation technique should be considered as a promising solution to recover compounds from industry byproducts and protect them from environmental and gastrointestinal circumstances.

To ensure food security amid dwindling natural resources, alternative proteins (APs) have been suggested as a sustainable solution. Yet, the adoption and consumption of APs remain limited. This review aims to delve into the latest progress (following PRISMA guidelines) concerning the utilization of proteins from alternative sources, particularly focusing on their effective incorporation into food products. Our findings reveal that insect proteins can improve amino acid profiles in bakery products. However, consumer acceptance remains low due to cultural biases, with optimal sensory results being achieved at lower substitution levels (5–10%). Mushroom proteins, when incorporated into meat analogs and bakery items, enhance nutritional value and offer favorable sensory properties, making them viable replacements in meat products. Plant-based proteins, such as pea and soy proteins, increase fiber and antioxidants and improve texture in meat alternatives, although formulation adjustments are necessary to meet consumer expectations for taste and overall experience. Microalgae offer unique benefits for bakery, confectionery, and dairy products by boosting protein, fatty acids, and probiotic growth while maintaining sensory acceptability. In conclusion, this study highlights that the effective incorporation of APs into food products can help in the development of healthier, more sustainable diets. That said, the success of AP acceptance will depend on continued innovations in formulation and consumer education.

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).

Importance Rapid digitalization of health care and a dearth of digital health education for medical students and junior physicians worldwide means there is an imperative for more training in this dynamic and evolving field. Objective To develop an evidence-informed, consensus-guided, adaptable digital health competencies framework for the design and development of digital health curricula in medical institutions globally. Evidence Review A core group was assembled to oversee the development of the Digital Health Competencies in Medical Education (DECODE) framework. First, an initial list was created based on findings from a scoping review and expert consultations. A multidisciplinary and geographically diverse panel of 211 experts from 79 countries and territories was convened for a 2-round, modified Delphi survey conducted between December 2022 and July 2023, with an a priori consensus level of 70%. The framework structure, wordings, and learning outcomes with marginal percentage of agreement were discussed and determined in a consensus meeting organized on September 8, 2023, and subsequent postmeeting qualitative feedback. In total, 211 experts participated in round 1, 149 participated in round 2, 12 participated in the consensus meeting, and 58 participated in postmeeting feedback. Findings The DECODE framework uses 3 main terminologies: domain, competency, and learning outcome. Competencies were grouped into 4 domains: professionalism in digital health, patient and population digital health, health information systems, and health data science. Each competency is accompanied by a set of learning outcomes that are either mandatory or discretionary. The final framework comprises 4 domains, 19 competencies, and 33 mandatory and 145 discretionary learning outcomes, with descriptions for each domain and competency. Six highlighted areas of considerations for medical educators are the variations in nomenclature, the distinctiveness of digital health, the concept of digital health literacy, curriculum space and implementation, the inclusion of discretionary learning outcomes, and socioeconomic inequities in digital health education. Conclusions and Relevance This evidence-informed and consensus-guided framework will play an important role in enabling medical institutions to better prepare future physicians for the ongoing digital transformation in health care. Medical schools are encouraged to adopt and adapt this framework to align with their needs, resources, and circumstances.

Environmental negotiations are complex, and conveying the interaction between science and policy in traditional teaching methods is challenging. To address this issue, innovative educational approaches like serious gaming and role-playing games have emerged. These methods allow students to actively explore the roles of different stakeholders in environmental decision-making and weigh for instance between sometimes conflicting UN Sustainable Development Goals or other dilemmas. In this work the phosphorus negotiation game (P-Game) is for the first time introduced. We present the initial quantitative and qualitative findings derived from engaging 788 students at various academic levels (Bachelor, Master, PhD, and Postdoc) across three continents and spanning 22 different countries. Quantitative results indicate that female participants and MSc students benefitted the most significantly from the P-Game, with their self-reported knowledge about phosphorus science and negotiation science/practice increasing by 71–93% (overall), 86–100% (females), and 73–106% (MSc students in general). Qualitative findings reveal that the P-Game can be smoothly conducted with students from diverse educational and cultural backgrounds. Moreover, students highly value their participation in the P-Game, which can be completed in just 2–3 h. This game not only encourages active engagement among participants but also provides valuable insights into the complex environmental issues associated with global phosphorus production. We strongly believe that the underlying methodology described here could also be used for other topics.