ObjectiveTo evaluate the predictive value of LA strain parameters and LASI for AF recurrence following electrical CV, and to compare them to conventional echocardiographic, biochemical, and clinical markers.MethodsIn this prospective, observational pilot study, 31 patients with persistent AF underwent electrical CV and were followed for six months. Echocardiographic evaluation included LA reservoir, conduit, and contractile strain, left atrial stiffness index, left atrial volume index (LAVI), left atrial appendage (LAA) morphology, left ventricular ejection fraction (LVEF), right atrial (RA) area, and right ventricular systolic pressure (RVSP). AF recurrence was assessed at three and six months.ResultsAt three months post-CV, LA reservoir, conduit, and contractile strain values were significantly negatively associated with AF recurrence (p < 0.001), while LASI and E/E' ratios were positively associated (p < 0.001). At six months, only contractile strain retained prognostic significance (p = 0.008). LVEF showed a positive correlation with recurrence at six months (p = 0.003), potentially reflecting the role of diastolic dysfunction.ConclusionLA strain parameters and LASI are valuable tools for predicting AF recurrence after CV, particularly in the early post-procedural period. Contractile strain may serve as a more reliable long-term predictor, emphasizing the importance of longitudinal atrial function assessment in rhythm outcome prediction. However, given the small sample size and single-center design, these results should be considered hypothesis-generating, requiring validation in larger studies.

Aim: This manuscript summarizes the key scientific and practical outcomes of the #DHPSP2024 digital networking event, focusing on emerging trends in digital health technologies, innovations in patient safety, and their implications for improving healthcare delivery. Methods: The #DHPSP2024 event was held from June 18 to 20, 2024, on X (formerly Twitter) and LinkedIn, connecting professionals and stakeholders in digital health and patient safety from different sectors. Data from posts on X and LinkedIn were analyzed for geographical distribution, engagement metrics (impressions, likes, shares), top hashtags, and frequently used terms. A qualitative analysis of the central themes and key online messaging discussions of the network event was also conducted. Results: On X, 2,329 posts by 179 participants from 38 countries generated over 231,000 impressions, with the most activity in Austria, China, and India. LinkedIn engagement included 3,475 likes, 217 comments, and 2,030 shares. Both platforms highlighted core themes such as digital health, patient safety, treatment quality, research on natural compounds, and interdisciplinary collaboration. Online messaging discussions emphasized technologies like telemedicine and artificial intelligence as critical tools for enhancing care delivery and patient safety. Participants also promoted special issues of scientific journals and explored collaborative research opportunities. Conclusions: The #DHPSP2024 event underscored the pivotal role of digital technologies in transforming healthcare, particularly in improving the quality and safety of interventions. The findings demonstrate how digital networking events, grounded in open innovation, foster global research communities, accelerate knowledge exchange, and support the integration of clinically relevant digital solutions. The strong engagement reflects growing interest in leveraging digital platforms to advance health outcomes and professional development. Overall, the event contributed to greater visibility of ongoing research, encouraged interdisciplinary cooperation, and may positively influence both the adoption of innovations in healthcare practice and the dissemination of scientific knowledge.

Introduction Hepatitis E virus (HEV) is foodborne zoonotic pathogen widespread among European swine yet unstudied in Bosnia and Herzegovina (B&H). We estimated HEV seroprevalence in domestic pigs in Federation of B&H (FB&H) and assessed farm-level risk factors for exposure. Methods Cross-sectional survey sampled 437 pigs from 87 farms across seven cantons via two-stage random design. Serum anti-HEV IgG measured by commercial indirect ELISA; managers completed standardized biosecurity/management questionnaire. Apparent seroprevalence calculated with 95% CIs. Univariable screening (α = 0.10) informed multivariable logistic regression with farm-level clustering; collinearity checked (Phi), AIC-guided forward selection applied. Results Animal-level seroprevalence 77.1% (95% CI 73.0–81.0%); herd-level 95.4% (88.9–98.7%). Adults showed higher seropositivity than growers (91.0% vs. 71.7%; p < 0.001). Significant factors: wild-boar proximity (adjusted POR 3.11; p = 0.04), small farm size (18.35; p < 0.001), swill feeding (5.70; p = 0.03). Cleaning ≥5×/month strongly protective (0.01; p < 0.001). All surveyed cantons had positives; no equivocal ELISA results. Discussion Findings indicate widespread HEV in FB&H swine with environmental, food-safety, and occupational implications. Older-animal pattern reflects cumulative exposure; small-farm context and wildlife interface likely sustain transmission, whereas frequent cleaning reduces risk. Strengthened biosecurity, wildlife exclusion, feed oversight (including prohibition/monitoring of swill feeding), and improved hygiene, should form basis of One Health interventions to mitigate potential zoonotic transmission via the pork production chain.

Energy security is currently one of the most important topics worldwide. Maintaining a reliable energy supply is one of the biggest challenges in security science. Additionally, defending energy infrastructure from cyberattacks is an ongoing issue. Understanding the vulnerabilities of energy infrastructure, especially the Smart Grid, which relies on information technology and communications, is a significant advantage. Understanding which system vulnerabilities lead to specific cyber threats presents a significant opportunity, enhancing the defence of energy infrastructure. This paper uses a systematic literature review to identify the most common cyber threat and Smart Grid vulnerability mentioned and researched in the literature from 2018 to 2025. This paper also aims to map the vulnerabilities that allow for cyber threats to occur, with the idea that if we know what causes a weak spot, we can effectively prevent it. Identifying specific weaknesses that could lead to cyber threats allows us to mitigate these dangers by addressing and correcting those vulnerabilities.

In this study, ethanolic and petroleum ether extracts of commercial cloves were prepared and analyzed. Soxhlet extraction (SE) and ultrasonic extraction (UAE) were used to prepare the extracts. Phytochemicals from plant material were extracted for 2 hours, in the case of both extraction techniques. The content of total polyphenols and flavonoids, as well as their antioxidant and antibacterial activity, were analyzed in the extracts. The results show an extremely high content of total polyphenols, which was also confirmed by the high antioxidant capacity, confirmed by DPPH and FRAP methods. Antibacterial screening on reference bacterial strains from the WDCM collection shows high potency of clove extracts at the tested concentration. In terms of the efficiency of extraction of bioactive components, petroleum ether in combination with ultrasonic extraction is the most effective. These results may contribute to further research and optimization of the extraction of biologically active components from cloves and related plant materials.

Despite the global coverage of the early detection programs, cervical cancer is still one of the most common causes of death among women worldwide. The integration of Pap test in the healthcare systems worldwide has led to major advances in the diagnosis of premalignant changes in the cervix, although there are limitations regarding the sensitivity of the test. Due to the somewhat lower sensitivity and specificity of the Pap test, the Human Papillomavirus (HPV) (test has been adopted as the first-tier screening method. The further evaluation of the findings is followed by the various complementary techniques and methods to diagnose patients or quantify the risk of developing high-grade cervical intraepithelial lesions. These techniques are increasingly being investigated to provide specific and reliable final diagnosis and instruct the further treatment. This review summarizes the biological basis of p16 and Ki-67 expression, their correlation, and their diagnostic role in the triage of HPV-positive women. The analysis includes results from major clinical trials and meta-analyses, which demonstrate that dual immunostaining of p16/Ki-67 provides higher sensitivity for detecting CIN2+/CIN3+ compared to cytology alone, with an acceptable trade-off in specificity. In conclusion, dual staining represents a reliable complementary tool for the evaluation of abnormal cytological findings, improving early detection of cervical cancer and guiding the appropriate management and treatment of patients.

This paper proposes a battery emulator based on a bidirectional non-inverting buck-boost power electronics converter. With the capability of bidirectional operation, it can emulate both charging and discharging processes. The proposed emulator is controlled with the advanced I2 dual current-mode control (I2DCMC) algorithm, combined with a feedforward control, which ensures fast and accurate tracking of the voltage and current characteristics of the batteries. The emulator is universal in terms of the various mathematical models of the batteries, which can be implemented in real time. It has no limitations regarding different battery types. Detailed analysis and the design procedure of the proposed battery emulator are presented. The performances of the emulator are validated with simulation and experimental results for three battery types: polymer Li-ion, conventional Li-ion, and lead–acid battery. Both steady and transient states are analyzed, especially transitions between charging and discharging phases. The possibility of simple time scaling of charging/discharging processes is successfully achieved and demonstrated, which is very important in making tests faster, with preserved battery characteristics. Considering its low-cost and user-friendly operation, the proposed emulator can be a good alternative to the real batteries in experimental tests of different power electronics systems. The prototype, which is developed for the experimental verification of the emulator, is designed for and limited to the research of lower power ratings systems of up to 100 W. It is suitable in education to easily demonstrate the behavior of the batteries in multiple scenarios in controlled laboratory conditions.

The complete classification of the saddle-point solutions for high-order above-threshold ionization, presented in and for a linearly polarized laser field, is generalized to the case of an arbitrary bichromatic elliptically polarized field. We first present the classification of the saddle-point solutions for the case of a monochromatic elliptically polarized driving field, which is the simplest example of the field that has two components, i.e., that evolves in the plane. For a bichromatic laser field whose elliptically polarized components have the frequencies rω and sω (r and s are integers, s>r, and ω is the fundamental frequency), the system of the saddle-point equations has 8s2 solutions per optical cycle. One-half of these solutions are the so-called backward-scattering solutions for which the direction of the electron motion is significantly affected by the rescattering. The other half are the forward-scattering solutions for which the electron is only slightly deflected during the rescattering event. For some specific field configurations, the number of saddle-point solutions can be smaller. For example, for a bicircular field, which consists of two counterrotating circularly polarized components, there are 4s(r+s) solutions, while for the corotating configuration there are 4s2 solutions. As an application, we have shown that for a monochromatic elliptically polarized laser field, all four threshold anomalies appear in the spectra of the rescattered photoelectrons.

The development of flexible bioelectronics remains a complex, multidisciplinary process that demands specialized expertise and labor-intensive efforts, limiting scalability, adaptability and accessibility. Here, we introduce DeviceAgent, an autonomous multimodal AI agent that integrates large language models (LLMs), vision-language models (VLMs), and domain-specific computational tools into a unified framework for bioelectronics research. Leveraging the emergent reasoning abilities of LLMs and VLMs, DeviceAgent enables zero and few-shot generalization, contextual learning, and flexible task execution across modalities. A multimodal context memory system orchestrates these capabilities, providing end-to-end support across the experimental pipeline–from high-level design objectives to fabrication protocol generation, visual defect inspection, and electrophysiological signal analysis, while maintaining human oversight at critical decision points. We demonstrate its capabilities through the development of stretchable mesh electronics for interfacing with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), a representative application involving complex device architectures, heterogeneous material nanofabrication, and electrophysiology analysis. DeviceAgent autonomously (1) generates customized bioelectronic layouts; (2) creates comprehensive fabrication protocols tailored to specific materials and processes; (3) identifies microscopic defects using visual reasoning; and (4) analyzes cardiac electrophysiological recordings in an interpretable manner. By embedding LLMs and VLMs within a structured, tool-augmented architecture, DeviceAgent establishes a scalable and accessible paradigm for AI-scientist collaboration in nanofabrication and bioelectronics research.

Connected and automated vehicles rely on data from various entities to support safety-critical applications such as Cooperative Adaptive Cruise Control (CACC). However, unauthorized data manipulation through, for example, data injection attacks can compromise vehicle safety and lead to incidents. Existing vehicular security mechanisms, such as Misbehavior Detection System (MBD), have limitations in detecting and mitigating all types of threats on their own. To address these limitations, our prior work has proposed the concept of a Trust Assessment Framework (TAF), which assesses data trustworthiness by combining evidence from multiple security systems operating as trust sources. However, TAF as a concept has not been extensively evaluated in safety-critical Cooperative Driving (CD) applications. In this work, we refine the architecture of the TAF and implement a software prototype based on it. We integrate the TAF prototype with a CACC simulation environment and implement three types of data injection attacks. We demonstrate that by incorporating multiple security mechanisms as trust sources, the TAF significantly improves attack detection performance and reduces the number of crashes by 86% compared to using a single security mechanism, such as MBD.

Authors in this paper investigates the relationship between the business environment and the operating performance of the plastic products manufacturing sector intended for the construction industry in Bosnia and Herzegovina (BiH). The focus is placed on how regulatory and institutional conditions impact economic indicators such as sales revenue growth, profit, export earnings, total assets, and employment. Since empirical studies in this area are scarce, this research contributes to filling an important academic gap. The study relies on both secondary and primary data sources. First, the business environment of BiH is evaluated using reports. Second, financial and operational data were collected for the top 20 companies in the plastic products manufacturing sector for the construction industry in BiH. The analysis covers the period 2015–2024, using indicators of revenue, profit, exports, total assets, and number of employees. A trend analysis was conducted to identify growth patterns, while a qualitative assessment was applied to connect these trends with the conditions of the business environment. The analysis of company performance reveals a positive growth trend in all major economic categories. Sales revenue steadily increased between 2015 and 2024, reflecting growing demand in the markets. Profitability improved despite regulatory barriers, indicating a strong adaptive capacity of firms. Export earnings expanded, showing that plastic product manufacturers. Total assets of the companies grew significantly, suggesting reinvestment and capacity expansion. Employment levels also increased, underscoring the sector’s contribution to job creation. These results support the hypothesis of a significant impact of the plastic products manufacturing industry on economic performance indicators in BiH.

Wearable electrochemical biosensors offer a promising alternative to conventional invasive blood‐based methods for monitoring biomarkers in diagnostic or therapeutic applications. Microneedle (MN)‐based technology provides direct access to the skin's interstitial fluid (ISF), enabling real‐time monitoring of biomarkers. Nevertheless, current micro‐ and nanofabrication techniques do not adequately support the development of MN‐based wearable technology that can utilize soft hybrid conductive inks, limiting its use in transdermal biosensing. Herein, an MN‐based biosensing platform is developed by integrating 3D printing, soft lithography, and hybrid conductive ink technology, featuring a fenestrated MN shell (FMNS) that serves as a protective layer for the inner hybrid conductive ink coating and prevents delamination during skin application. This FMNS patch demonstrates a wide pH monitoring range, high selectivity and accurate detection of subtle ISF pH changes, safe integration of hybrid conductive inks, and reduced fabrication time and cost when compared to other microfabrication methods such as lithography and deep reactive ion etching. The biosensor excels in protecting the biosensing layer and demonstrates excellent analytical performance in monitoring changes in pH levels of the skin ISF. This micro‐ and nanofabrication approach has great potential in integrating hybrid conductive ink technology into transdermal wearable devices for health monitoring and diagnostics.