Lung ultrasound (LUS) is a valuable, non-invasive tool for detecting pulmonary congestion in patients with acute heart failure (AHF), with a higher sensitivity relative to physical examination. However, the association between LUS-detected pulmonary congestion and cardiovascular outcomes in patients with ST-segment elevation (STEMI) is not well established. This systematic review and meta-analysis evaluated cardiovascular outcomes in patients with STEMI and congested (wet) or non-congested (dry) lungs by LUS. We searched PubMed, Embase, and Cochrane databases, and conference abstracts for clinical trials evaluating LUS-congestion (LUS+) versus non-LUS-congestion (LUS-) in patients with STEMI. Risk ratios (RRs) and hazard ratios (HR) with 95%CIs were pooled using R software under random-effects models. We also calculated LUS sensitivity, specificity, and area under the curves (AUCs) for the prediction of in-hospital mortality and cardiogenic shock. We included five studies with 1,454 patients. The mean age was 60 to 65 years; 1,066 (73.3%) were male, and 451 (31%) had congested lungs (LUS+). Patients with congestion on LUS had a significantly higher risk of the composite endpoint of death, heart failure, acute coronary syndrome, and cardiogenic shock (HR 4.00; 95%CI 2.12-7.54; p<0.01; Figure 1A). There was also a higher risk of in-hospital mortality (RR 5.09; 95%CI 2.25-11.49; p<0.001; Figure 1B) and cardiogenic shock (RR 5.01; 95%CI 2.47-10.17; p<0.001; Figure 1C) compared to patients with non-congested lungs. Reinfarction was similar between groups (p=0.08; Figure 1D). LUS had high diagnostic accuracy for in-hospital mortality (SROC-AUC: 0.82) and cardiogenic shock (SROC-AUC: 0.77); a high sensitivity (0.84; 95%CI 0.49-0.97; Figure 2A), and moderate specificity (0.78; 95%CI 0.67-0.87; Figure 2A) for in-hospital mortality; and moderate sensitivity (0.75; 95%CI 0.42-0.93; Figure 2B) and specificity (0.76; 95% CI 0.61-0.87; Figure 2B) for cardiogenic shock. Congested lungs on LUS are significantly associated with a higher risk of in-hospital mortality and cardiogenic shock in patients with STEMI. Moreover, LUS has a high AUC for identifying in-hospital mortality and cardiogenic shock in this patient population. Figure 1 Figure 2

Network emulators play an important role in testing network systems, applications, and protocols. Emulators bridge the gap between simulation setups that lack realism in results and real-world trials that are accurate but often expensive, non-reproducible, and uncontrollable. This article presents an extended model of the Quantum Key Distribution Network Simulation Module (QKDNetSim) with a model catalog of QKD components and functionalities. We explore emulations of point-to-point connections in QKD networks and the interaction of essential components within QKD nodes. The presented tool will undoubtedly spur future development and teaching, and it is critical for testing novel applications and protocols applied to QKD networks.

This paper explores the impact of performance expectancy (PE) and effort expectancy (EE) on the behavioral intention (BI) of managers to implement environmental, social, and governance (ESG) practices in small and medium-sized enterprises (SMEs) in Bosnia and Herzegovina. Us ing the Technology Acceptance Model (TAM), the study analyzes how these factors influence decision-makers’ engagement in sustainable business activities. A survey of 247 managers was conducted to assess their BI, PE, and EE for each ESG component. The collected data were ana lyzed using structural equation modeling (SEM) to construct a second-order latent model that measures the combined effects of these factors. The study fills a gap in the literature by examin ing sector-specific differences in the factors influencing ESG implementation. The results reveal that both PE and EE significantly affect an organization’s intention to adopt ESG practices, with varying impacts between the manufacturing and service industries. The findings highlight the different challenges and complexities each industry faces in implementing ESG practices. While focusing on PE and EE, it is acknowledged that other factors such as organizational culture, stakeholder pressure, and industry-specific dynamics also play roles in ESG adoption. The main contribution of this work is the use of a second-order latent construct within the TAM model for ESG practices, offering a unique perspective on understanding behavioral intention.

Introduction Renal angiomyolipomas (AMLs) are neoplasms that can rarely rupture, causing hemorrhagic shock as the most serious complication. This pathological condition, (referring to AML) is classified as a benign tumor arising from the proliferation of epithelioid cells, consisting of fat tissue, blood vessels, and smooth muscle. Wunderlich syndrome describes a spontaneous, nontraumatic bleeding into the subcapsular or perirenal space. Most individuals with renal AML exhibit no symptoms and are often diagnosed incidentally, however, some may experience life-threatening complications such as rupture, hemorrhage, and circumstantial hypovolemic shock. Case outline Description of the clinical presentation of AML with rupture in a female patient with a brief overview of other cases of AML in the literature. Female patient, 68 years old, admitted for examination due to sudden severe pain in the abdomen with propagation to the right lumbar region accompanied by nausea and fatigue. After a complete physical examination, an abdominal ultrasound, and a CT scan, surgery was performed during which the right kidney was removed alongside the hematoma and the kidney envelopes, which were sent for pathohistological analysis. The result of the histopathological analysis confirmed that it was AML. Conclusion AMLs are benign neoplasms with potentially serious complications. The most serious complication of AML is rupture, leading to retroperitoneal hemorrhage, with tumor size being a significant risk factor. Considering the clinical importance of this potential complication, it is important to establish a swift and accurate radiological diagnosis, with the aim of timely therapeutic intervention and reduction of potential additional complications.

Timely and accurate defect detection is essential in the leather industry, as the quality of raw leather directly impacts both the usability and value of finished products. This paper provides a systematic overview of state-of-the-art solutions and proposes a novel approach for automated detection of leather surface defects using deep neural networks based on the Inception-V3 architecture. Five defect categories are introduced, focusing on their impact on leather quality. In addition, two deep neural network architectures were analyzed and implemented for defect detection and classification: a single-channel model and a multi-channel model with arbitration. The evaluation was carried out using a combination of a custom-developed dataset and publicly available datasets, assessed with standard performance metrics. Moreover, an image annotation tool was developed to facilitate precise defect labeling and the creation of variable-size datasets. Both models demonstrated promising results on the custom dataset, achieving accuracy rates exceeding 93%. The suggested methodology enhances the research domain of leather inspection automation by creating an openly accessible image dataset, performing a comparative analysis of detection models and creating software tools for data preparation. These contributions lay the foundation for further research in leather defect detection and potential industrial implementation.

Je li umjetna inteligencija, koja je danas pobudila sveopći znanstveni i javni interes, prilika koja se može pokazati korisnom za demokraciju ili je ona prijetnja koja donosi korjenite promjene i oko koje se trebamo duboko zabrinuti? S jedne strane, umjetna inteligencija može biti prilika za poboljšanje demokratskoga procesa u smislu jednostavnijega uključivanja u demokratsku raspravu i samim time u poboljšanju procesa kreiranja politika. S druge strane, rizici za demokraciju koje može generirati umjetna inteligencija mogu biti lažne informacije koje mogu izazvati različite društvene sukoba te kreirati mišljenja koja ne predstavljaju mišljenje javnosti. U oba slučaja, i kao prilika i kao prijetnja, umjetna inteligencija promijenit će mnoge aspekte demokracije, uglavnom na načine koje još ne možemo pojmiti. Ključne riječi: umjetna inteligencija; demokracija, izborni proces.

Heavy metals ubiquitously found in soil and water, as a serious environmental problem, are disrupting plant mineral nutrition homeostasis, osmotic balance, and metabolism. Application of some biostimulants can alleviate the disruption. Melatonin as a signal molecule, and antioxidant plays an important role in plant growth and stress tolerance due to its ability to directly neutralize reactive oxygen and nitrogen species. The reduction or mitigation of heavy metals adverse effects in valerian plants grown in open field conditions using melatonin was investigated in this paper. HPLC-FLD technique was used to identify and quantify melatonin concentration in valerian root extracts. Also, physiological, and biochemical plant status under abiotic stress was examined, especially in 100 ?M melatonin pre-treated plants. Higher concentrations of endogenous melatonin were measured in roots of Cd and Zn treated plants. Melatonin application alleviated the negative effect of Cd, particularly evident in Cd-Melatonin treatment which restored or enhanced bioactive compound levels. Melatonin effectively mitigates Cd and Zn-induced stress in valerian by enhancing both non-enzymatic and enzymatic antioxidant systems and promoting the synthesis of protective compounds. These findings highlight melatonin potential as a sustainable biostimulant to support plant resilience and productivity in heavy metal-stressed environments.

Red clover is one of the most important perennial forage legumes in livestock feed production. It also plays a significant role in organic farming, as it enriches the soil with nitrogen through symbiotic fixation by nodule-forming bacteria, reducing the need for excessive use of mineral nitrogen. The application of foliar biofertilizers can have a significant impact on the productivity and nodulation of red clover. Since the productivity and quality of red clover largely depend on soil fertility, environmental conditions, variety selection, and the plant’s developmental stage at the time of mowing, the aim of this research was to determine the influence of red clover variety and foliar biofertilizer (BF0, BF1, BF2, BF4) on dry matter yield, crude protein content, and the abundance of nodule-forming bacteria. The research results showed that variety selection and the application of biofertilizer at higher concentrations had a significant effect on dry matter yield and crude protein content. However, the total number of nodules on red clover roots decreased with increasing biofertilizer concentration. The highest annual dry matter yield was achieved in the BF4 variant for the Una variety (12.71 t ha-1) and the Global variety (11.43 t ha-1). Similarly, the highest crude protein yield was recorded in the BF4 variant for the Una variety (1896.4 kg ha-1) and the Global variety (1678.0 kg ha-1).

Sweet corn (Zea mays L. var. saccharata) is one of the popular varieties of corn in the human diet. Its quality is influenced by various properties such as grain moisture, colour, ear weight, ear length, texture, and sugar content, while its health benefits are attributed to its total phenolic content and antioxidant activity. The aim of this research is to determine the impact of N fertiliser application and sowing date on yield indicators, total phenol content and antioxidant capacity of sweet corn. The treatments of the experiment consisted of a combination of two factors, two different nitrogen regimes and two different sowing dates. The results show that the applied treatments significantly influenced the researched traits of sweet corn. Dehusked and husked ear mass, ear length, and yield were higher when sown earlier (385 g, 264 g, and 21 cm, respectively) than later sowing (364 g, 242 g, and 20 cm, respectively). Additionally, higher values of dehusked and husked ear mass, ear length, were recorded with a higher dose of fertiliser. Furthermore, total phenol contents ranged from 57.0 to 80 mg GAE 100 g-1 and depended on sowing date, fertilisation, and year of study.

Deformation analysis is a complex procedure where, based on several periodic geodetic measurements, displacements of points in the geodetic network are detected and determined. On this basis, movements and deformations of the built and natural environment are detected. The article discusses the Squared Msplit estimation, an extension of the maximum likelihood method, which is one of the procedures used in deformation analysis. The equations of the Squared Msplit estimation are derived and the method is presented on 2D geodetic network case study. The effectiveness of the presented method is compared with the results of other deformation analysis approaches performed with the same numerical example. The results obtained using the Squared Msplit estimation slightly differ from the simulated values, with the maximum discrepancy being 11.5 mm at unstable points and 10.4 mm at stable points, which are satisfactory results. The findings indicate that the Squared Msplit estimation provides results comparable to other methods. Therefore, it is considered suitable for deformation analysis and can be regarded as one of the applicable procedures in this field.

In this study, ZnO as a semiconductor and RuO2 as a metal-like conductor were combined in a composite and tested as a photoanode for water splitting, i.e. green hydrogen and oxygen production. ZnO/RuO2 composite in the mass ratio of 2:1 was prepared using microwave processing of a precipitate. To investigate the influence of oxygen vacancies as defects in the crystal structure on (photo)electrocatalytic efficiency for hydrogen and oxygen production, the composite was annealed at 300 and 600?C. The phase composition, morphology, and optical properties of as-prepared and annealed composites were analyzed in detail. The (photo)electrocatalytic activity of composites for HER and OER was examined in NaOH and H2SO4 using linear sweep voltammetry. The (photo)electrocatalytic properties of the ZnO/RuO2 composites were correlated with their physicochemical characteristics with emphasize on oxygen vacancies.