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Clinical Outcomes and Predictors of Mortality in Patients with Difficult-to-Treat Resistant Pseudomonas aeruginosa Infections: A Retrospective Cohort Study
No full textBackground: Difficult-to-treat resistant Pseudomonas aeruginosa (DTR-PA) infections are associated with high morbidity and mortality, but data on prognostic factors remain limited. Given the limited real-world data on outcomes of DTR-PA infections, we aimed to identify clinical predictors of mortality and response to therapy in this setting. Methods: We conducted a single-center retrospective cohort study of 51 patients with DTR-PA infections. The primary endpoint was 30-day all-cause mortality; secondary endpoints were clinical and microbiological cure at end of therapy. An exploratory analysis evaluated 30-day infection-related mortality. Logistic regression models (univariable, multivariable and Firth bias-reduced) were used to identify independent predictors. Results: Median age was 64 years (IQR 22); 63% were male and 71% were in the ICU at infection onset. Sepsis occurred in 80% and septic shock in 45%. Thirty-day all-cause mortality was 49% (25/51). According to multivariable analysis, septic shock was an independent predictor of mortality (aOR 5.52, 95% CI 1.04–29.27; p = 0.045) as younger age (aOR 1.06, 95% CI 1.00–1.12; p = 0.052), whereas targeted therapy with ceftazidime/avibactam or ceftolozane/tazobactam is a protective factor (aOR 0.15, 95% CI 0.02–1.17; p = 0.070) did not reach significance in the final model. Clinical cure occurred in 33% (17/51) and was negatively associated with device burden and bloodstream infection, whereas microbiological cure (45%, 23/51) was more likely with targeted therapy and absence of sepsis. The exploratory analysis of infection-related mortality (35%) showed similar predictors. Conclusions: DTR-PA infections are associated with high mortality. Septic shock and older age predict death, while the use of novel β-lactam/β-lactamase inhibitors is associated with improved outcomes. Early recognition of severe illness and timely administration of active therapy may improve survival in these infections
Diagnostic Gap in Rural Maternal Health: Initial Validation of a Parsimonious Clinical Model for Hypertensive Disorders of Pregnancy in a Honduran Hospital
No full textBackground/Objectives: In low-resource settings, diagnostic delays and limited specialist access worsen health inequalities, making hypertensive disorders of pregnancy (HDPs) defined by new-onset blood pressure ≥ 140/90 mmHg after 20 weeks of gestation, with or without proteinuria, a major cause of maternal morbidity and mortality. This study evaluated the diagnostic effectiveness of a rural-applicable clinical model for detecting HDPs in a real-world population from Hospital General San Felipe (Tegucigalpa, Honduras). Methods: A cross-sectional diagnostic accuracy study was conducted on 147 consecutive pregnant women in February 2025. Clinical documentation from the initial appointment defined HDP. We modeled HDP risk using penalized logistic regression and common factors such maternal age, gestational age, blood pressure, BMI, primary symptoms, semi-quantitative proteinuria, and medical history. Median imputation was utilized for missing numbers and stratified five-fold cross-validation assessed performance. We assessed AUROC, AUPRC, Brier score, calibration, and operational utility at a data-driven threshold. Results: Of patients, 27.9% (41/147) had HDP. The model had an AUROC of 0.614, AUPRC of 0.461 (cross-validation averages), and Brier score of 0.253. The threshold with the highest F1-score (0.474) had a sensitivity of 0.561, specificity of 0.679, positive predictive value of 0.404, and negative predictive value of 0.800. HDP had higher meaning systolic/diastolic/mean arterial pressure (130.7/82.9/98.9 vs. 120.5/76.1/90.9 mmHg) and ordinal proteinuria (0.59 vs. 0.36 units). Conclusions: The model had moderate but clinically meaningful discriminative performance using low-cost, commonly obtained variables, excellent calibration, and a good negative predictive value for first exclusion. These findings suggest modification of predictors, a larger sample size, and clinical usefulness assessment using decision curves and process outcomes, including quick referral and prophylaxis. This approach aligns with contemporary developments in the 2023–2025 European Society of Cardiology (ESC) and 2024 American Heart Association (AHA) guidelines, which emphasize earlier identification and risk-stratified management of hypertensive disorders during pregnancy as a cornerstone of women’s cardiovascular health
Exploring Greek Upper Primary School Students’ Perceptions of Artificial Intelligence: A Qualitative Study Across Cognitive, Emotional, Behavioral, and Ethical Dimensions
No full textThis study investigates the perceptions of Greek sixth-grade students regarding Artificial Intelligence (AI). Understanding students’ pre-instructional conceptions is essential for developing targeted interventions that build on existing knowledge rather than assuming conceptual deficits. A qualitative design was employed with 229 students from seven elementary schools in Athens, Greece. Data were collected through open-ended questions and word association tasks, then analyzed using Walan’s AI perceptions framework as an integrated set of analytical lenses (cognitive, affective, behavioral/use, and ethical considerations). Findings revealed that students hold multifaceted conceptions of AI. Cognitively, they described AI as robots, computational systems, software tools, and autonomous learning programs. Affectively, they expressed ambivalence, balancing appreciation of AI’s usefulness with concerns over potential risks. Behaviorally, they identified interactive question–answer functions, creative applications, and everyday assistance roles. Ethically, students raised issues of responsible use, societal implications, and human–AI relationships. This study contributes to international research, highlighting that primary students’ understandings of AI are more nuanced than is sometimes assumed, and offer empirical insights for designing culturally responsive, ethically informed AI literacy curricula
Towards Zero-Waste Valorization of African Catfish By-Products Through Integrated Biotechnological Processing and Life Cycle Assessment
No full textAfrican catfish (Clarias gariepinus, AC) is one of the most widely farmed freshwater fish species in Central Europe. Processing operations generate up to 55% by-products (BPs), predominantly carcasses rich in proteins, lipids, and minerals. This study develops a comprehensive valorization process for ACBPs to recover gelatin, protein hydrolysate, fish oil, and pigments. The processing protocol consisted of sequential washing, oil extraction, demineralization, and biotechnological treatment to disrupt the collagen quaternary structure. A two-factor experimental design was employed to optimize the processing conditions. The factors included the extraction temperatures of the first (35–45 °C) and second fraction (50–60 °C). We hypothesized that enzymatic conditioning, combined with sequential hot-water extraction, would yield gelatin with properties comparable to those of mammalian- and fish-derived gelatins, while enabling a near-zero-waste process. The integrated process yielded 18.2 ± 1.2% fish oil, 9.8 ± 2.1% protein hydrolysate, 1.7 ± 0.7% pigment extract, and 25.3–37.8% gelatin. Optimal conditions (35 °C/60 °C) produced gelatin with gel strength of 168.8 ± 3.6 Bloom, dynamic viscosity of 2.48 ± 0.02 mPa·s, and yield of 34.76 ± 1.95%. Life cycle assessment (LCA) identified two primary environmental hotspots: water consumption and energy demand. This near-zero-waste biorefinery demonstrates the potential for comprehensive valorization of aquaculture BPs into multiple value-added bioproducts
Electromobility Implementation Challenges and Opportunities in Urban Parcel Delivery: A Case Study of a Fictive Delivery Company in Miskolc
No full textThe growing demand for parcel delivery plays an important role in the integration of electromobility and urban logistics into urban delivery systems, especially in a mid-sized Central European city. This study investigates the challenges and opportunities of adopting electric vehicles (EVs) for last-mile delivery in the Miskolc region, Hungary. The author introduces a practical approach to describe the cost-based optimization of urban parcel delivery, formulated as an Electric Vehicle Routing Problem (EV-VRP) that builds on classical Vehicle Routing Problem (VRP) concepts. The developed model focuses on route and vehicle allocation and examines the impact of charging infrastructure and fleet composition on delivery performance, while explicitly evaluating five cost categories: vehicle (including maintenance and service), driver, infrastructure, operation center, and environmental energy. The numerical results validate the model and show that partial fleet electrification can improve cost efficiency and reduce environmental impact even in regions with limited charging capacity. The proposed approach makes it possible to analyze the operational costs of electromobility strategies on last-mile logistics under realistic routing, capacity, and energy constraints. The results confirm that the integration of electric vehicles into city logistics can contribute to more flexible, sustainable, and cost-effective delivery systems. The numerical analysis shows that under the conditions examined, the model results in approximately 20% lower total operational cost compared to the conventional vehicle fleet operating under similar conditions. The cost structure is dominated by labor and vehicle-related components, while infrastructure, operational management, and environmental–energy factors appear with lower intensity
Are All Species Created Equal? A Critique of the “Equal Fitness Paradigm”
No full textMy article criticizes the view held by many ecologists that species have evolved essentially equivalent levels of fitness, thus permitting their coexistence. I show that a recently proposed version of this view called the “equal fitness paradigm” (EFP) has multiple problems, empirically and conceptually. Some of these problems are (1) an energetic fitness measure (OPG = lifetime production of surviving offspring per parental body mass) that ignores the critical effect of the timing of reproduction; (2) flawed methods and data used to calculate and interpret the body-size scaling invariance of OPG upon which the EFP is based; (3) omission of the profound effects of population size and geographical range size on species-level fitness; and (4) lack of recognition that if the EFP were true, species-level selection would not be able to operate. By contrast, the “variable fitness paradigm” (VFP), which is a mainstay of modern evolutionary biology, is supported by numerous lines of evidence at multiple levels of biological organization. Extensive fitness variation allows natural selection to operate at all these levels. Distinguishing fitness and adaptiveness as reproductive power and efficiency of resource acquisition, respectively, helps explain species coexistence within the conceptual framework of the VFP. No EFP is needed
Model Predictive Control of Doubly Fed Induction Motors Based on Fuzzy Logic
No full textModel predictive control (MPC) has become an attractive solution for doubly fed induction motors (DFIMs) due to its fast dynamic response and multi-variable constraint handling capability. However, the performance of conventional MPC relies on the accuracy of the system model. To further enhance the control performance and adaptability, this paper proposes a fuzzy logic-based model predictive control (FL-MPC) strategy. The proposed method continuously monitors the current tracking errors and their rates of change, utilizing a fuzzy inference system to dynamically optimize the weight distribution within the predictive model. This enables the controller to autonomously adjust its behavior for optimal performance across a wide range of operating conditions. Both simulation and experimental results demonstrate that, compared to the conventional MPC, the proposed FL-MPC strategy achieves superior dynamic response
Early-Life Galacto-Oligosaccharide Supplementation Induces Persistent Immunoglobulin and Metabolic Alterations in Holstein Dairy Calves by Shaping Gut Microbiota
No full textEarly-life development of immune functions is crucial for calf health, growth, and future productivity. Galacto-oligosaccharides (GOSs) have been reported to facilitate ruminal microbial establishment and improve growth in Holstein dairy calves, but their prolonged influence on immunoglobulin levels, hindgut microbiota, and metabolic regulation remains insufficiently understood. This study evaluated the effects of early-life GOS supplementation on immune-related indicators, intestinal microbial ecology, and metabolic profiles in Holstein calves. Twenty-four newborn Holstein female dairy calves were randomly assigned to a control group (CON, n = 12) or a GOS group (GOS, n = 12; 10 g/day from birth to day 28). After supplementation ceased on day 28, calves previously receiving GOS were referred to as the GOSS group (n = 6). Immunoglobulin levels, gut microbiota, and fecal and serum metabolomes were evaluated during supplementation and six weeks after withdrawal. GOS supplementation significantly increased serum IgA and IgG levels during the treatment, with IgG levels remaining elevated for six weeks after discontinued supplementation. Although overall microbial diversity was not markedly altered, GOS selectively enriched bacterial taxa and function pathways linked to amino acid synthesis, unsaturated fatty acid production, and coenzyme-related metabolism. On day 70, GOSS group displayed distinct fecal and serum metabolomic profiles, with altered metabolites primarily associated with vitamin B6, folate, cobalamin metabolism, branched-chain amino acid biosynthesis, and purine and arginine pathways. These results demonstrate that early-life GOS supplementation promotes sustained immune and metabolic alterations following supplementation cessation, potentially mediated by modulation of gut microbial functions. These findings suggest that early dietary GOS supplementation may support physiological maturation in calves and could be useful as a nutritional strategy in calf-rearing systems
An ML-Based Approach to Leveraging Social Media for Disaster Type Classification and Analysis Across World Regions
No full textOver the past decade, the frequency and impact of both natural and human-induced disasters have increased significantly, highlighting the urgent need for effective and timely relief operations. Disaster response requires efficient allocation of resources to the right locations and disaster types in a cost- and time-effective manner. However, during such events, large volumes of unverified and rapidly spreading information—especially on social media—often complicate situational awareness and decision-making. Consequently, extracting actionable insights and accurately classifying disaster-related information from social media platforms has become a critical research challenge. Machine Learning (ML) approaches have shown strong potential for categorizing disaster-related tweets, yet substantial variations in model accuracy persist across disaster types and regional contexts, suggesting that universal models may overlook linguistic and cultural nuances. This paper investigates the categorization and sub-categorization of natural disaster tweets using a labeled dataset of over 32,000 samples. Logistic Regression and Random Forest classifiers were trained and evaluated after comprehensive preprocessing to predict disaster categories and sub-categories. Furthermore, a country-specific prediction framework was implemented to assess how regional and cultural variations influence model performance. The results demonstrate strong overall classification accuracy, while revealing marked differences across countries, emphasizing the importance of context-aware, culturally adaptive ML approaches for reliable disaster information management
Cemeteries and Urban Planning in Vienna
No full text(1) Background: As social infrastructures, cemeteries have always played a central role in various human cultures. The changing function of cemeteries and the recognition of their potential as green spaces have resulted in the fact that cemeteries are a subject of considerable urban planning research. However, there still is a knowledge gap for the case of Vienna. In this study, from the perspective of urban planning and the city of Vienna as an operator of interdenominational cemeteries on the one hand, and of operators of denominational cemeteries on the other hand, consideration of cemeteries in strategic urban planning is discussed, and prospects for the future are outlined. (2) Methods: A qualitative content analysis of relevant strategic planning documents and a qualitative theme-centred stakeholder survey using guideline interviews were conducted. The results were put into the context of the international literature. (3) Results: Cemeteries are an integral part of urban morphology and fabric. Interdenominational cemeteries serve multiple purposes, for example, as places of remembrance, leisure and recreation. In addition, the growing importance of interdenominational cemeteries in particular as green infrastructure for the public is evident. (4) Conclusions: Despite population growth and the associated pressure on land and densification, no changes such as the decommissioning of cemeteries are to be expected in the medium term