Ventilator-associated pneumonia in intensive care units: A comparison of pre-pandemic and COVID-19 periods

Background/Objectives: The COVID-19 pandemic has significantly increased the burden of ventilator-associated pneumonia (VAP) in intensive care units (ICUs) globally. However, epidemiological data on VAP in Slovak ICUs, particularly in the context of the pandemic, remain limited. This study aimed to evaluate the incidence, microbial profiles, and risk factors of VAP in Slovak ICU settings, particularly during the COVID-19 pandemic. Methods: A retrospective analysis of VAP data was conducted for respiratory intensive care unit (ICU) patients in a Slovak university hospital, comparing data from the pre-pandemic and pandemic periods. The CDC/NHSN definitions for VAP were applied, and statistical analyses were performed using STATISTICA 13.1. Results: A total of 803 patients were analyzed, representing 8385 bed days and 5836 mechanical ventilator days. VAP rates increased significantly during the pandemic by 111%, from 8.46 to 17.86 events per 1000 MV days (p < 0.001). VAP rates in non-COVID-19 patients increased by 86% during the pandemic compared to pre-pandemic levels. Pandemic conditions also increased ICU mortality from 25.66% to 40.52% (p < 0.001). VAP was identified as a critical determinant of ICU mortality, contributing to a 21.62% higher mortality rate among patients during the pandemic. Younger age, prolonged mechanical ventilation, and medical (vs. surgical) hospitalizations were associated with higher VAP incidence. Gram-negative bacteria dominated the pathogen profiles, with significant increases observed in Pseudomonas aeruginosa (183%), Klebsiella pneumoniae (150%), and Acinetobacter spp. (100%). Conclusions: The COVID-19 pandemic has significantly affected the incidence and epidemiology of VAP in Slovak ICUs, highlighting systemic vulnerabilities in HAI surveillance and IPC practices.Catholic University in Ruzomberok [016 KU-4/2023

The growth-adjusted impact factors of Physics of Fluids

From Phan-Thien and Giacomin [“Growth-adjusted impact factor,” Phys. Fluids 36, 050402 (2024)], we learn that journal growth decreases impact factor (all else being held equal). In this Editorial, we apply the teachings of Phan-Thien and Giacomin [“Growth-adjusted impact factor,” Phys. Fluids 36, 050402 (2024)] to growth-adjust the impact factors of the journal Physics of Fluids. We do so for the years for which the data are available, 2001-2023. We find that, over the course of its history, the growth of Physics of Fluids often suppressed its impact factor

Time series pattern recognition via SoftComputing

In this paper we develop two methods that are able to analyze and recognize patterns in time series. The first model is based on analytic programming (AP), which belongs to softcomputing. AP is based as well as genetic programming on the set of functions, operators and so-called terminals, which are usually constants or independent variables. The second one uses an artificial neural network that is adapted by backpropagation. Artificial neural networks are suitable for pattern recognition in time series mainly because of learning only from examples. There is no need to add additional information that could bring more confusion than recognition effect. Neural networks are able to generalize and are resistant to noise. On the other hand, it is generally not possible to determine exactly what a neural network learned and it is also hard to estimate possible recognition error. They are ideal especially when we do not have any other description of the observed series. This paper also includes experimental results of time series pattern recognition carried out with both mentioned methods, which have proven their suitability for this type of problem solving.Ostravská Univerzita v Ostravě, (SGS23/PĜF/2011, MSM 7088352101); Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT, (GACR 102/09/1680); European Regional Development Fund, ERDF, (CZ.1.05/2.1.00/03.0089

Effect of carbon black properties on cut and chip wear of natural rubber

The effect of carbon black colloidal properties on cut and chip wear of natural rubber compounds is investigated across a wide range of applied impact normal forces using an Instrumented Cut and Chip Analyzer (ICCA). The objective of the study is to determine the basic fatigue and fracture mechanisms that drive cut and chip wear. Natural rubber compounds reinforced with eight different carbon blacks varying in structure and surface area are studied. The loading of the carbon blacks in the rubber compounds is fixed at 50 parts per hundred rubber (phr). The cut and chip performance strongly correlates to both the carbon black morphological properties and the resulting compound mechanical and fracture properties. The cut and chip performance also depends on the applied impact normal force level. At low forces, high structure carbon blacks result in compounds which are stiffer and deflect less under the applied impact normal forces and minimize cut and chip wear. At high forces, low structure carbon black compounds, which are softer and more readily able to crystallize under force-controlled deflection, minimize cut and chip wear. It is argued that at low applied impact normal forces, the cut and chip behavior is dominated by a force-controlled fatigue crack growth mechanism which transitions to a critical tearing energy dominated mechanism at high applied impact normal forces. It is therefore important to understand the severity of application to select optimum compound properties such as the carbon black type to minimize cut and chip wear in application.Birla Carbon USA Inc.; Birla Carbon; Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT, (RP/CPS/2022/006, RP/CPS/2024/28/006); Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMTBirla Carbon USA Inc., Marietta, GA, USA; Ministry of Education, Youth and Sports of the Czech Republic [RP/CPS/2024/28/006

Assessing the moderating role of technological innovation on food security in poverty reduction within the Visegrad region

The global shift for sustainable development has elicited nations and governments to develop policies to safeguard humankind and the environment. The investigation premised on the poverty reduction within the Visegrad communities (Czech Republic, Hungary, Poland, and Slovakia). The evaluation employed panel data from 2000 to 2022 on the variables of poverty (POV), food security (FOD), foreign direct investment inflow (FDI), economic progress (ECP), population growth (POG), inflation growth (ING), and technological innovation (TIN). Various preliminary assessment of cross-sectional dependence, unit root, and cointegration was evaluated to ensure data reliability and validity. The econometric approach of Cross-Sectional Augmented Distributed Lag (CS-ARDL) model was adopted to study the short- and long-term affiliation. The findings revealed that (a) FOD, FDI, POG, and TIN had a material influence on poverty reduction. (b) However, ECP and ING appreciation poverty rate within the Visegrad region. (c) Again, there was a serial moderating effect of TIN on the affiliation between FOD and POV in the Visegrad region. Furthermore, the Dumitrescu-Hurlin causality test indicated a unidirectional nexus between FOD, FDI, POG, and TIN with POV reduction. While a bidirectional was established on ECP and ING with POV reduction. The outcome serves as a policy and practical supplement to government and institutional agencies in charge of poverty mitigation. The outcome recommend that government should invest in technological innovation to improve food security and poverty reduction to achieve the SDG1 by 2030

Decision-making support system for travel planning for people with disabilities based on fuzzy set theory

Research background: In recent years, there has been increasing attention to the needs of tourists with disabilities. Several international studies confirm that this target group has been marginalized in tourism due to physical, economic, social, and environmental barriers. However, the integration of intelligent decision-support systems can significantly enhance accessibility and inclusion in tourism. Purpose of the article: This research aims to develop effective methods and algorithms for constructing intelligent systems and software that generate precise and high-quality travel plans for tourists with disabilities. The primary objective is to create a decision support system for trip planning, using the example of Visegrad Group countries (the Czech Republic, Hungary, Poland, Slovakia). Methods: The decision support system is structured around two core components: the data level and the knowledge level. The data layer compiles a structured database of actual visits by disabled tourists. The knowledge layer consists of mathematical models forming a comprehensive decision-making framework. The formalization of the system employs fuzzy set theory, fuzzy logic, expert evaluation, and intelligent knowledge analysis. This research introduces: an information model for assessing the accessibility of destinations; fuzzy method of determining the degree of accessibility of destination, considering the level of limited capabilities of the participant of the tourist movement; decision-making method when travel planning on the accessibility of the region on goal needs. Findings & value added: The decision-making support system was verified and tested on real data from 41 participants in the Visegrad Group countries. A distinctive feature of this research is the development of a dynamic, adaptive decision-support mechanism that evolves with real-world user data. Unlike standard accessibility evaluation approaches, this system provides personalized travel recommendations and continuously refines its ranking model based on user experiences. This ensures a long-term impact on smart tourism, sustainable travel planning, and enhanced accessibility for people with disabilities.Ministerstvo školstva, vedy, výskumu a športu Slovenskej republiky; Slovenská Akadémia Vied, SAV, (1/0700/25); Slovenská Akadémia Vied, SAVScientific Grant Agency of the Ministry of Education, Science, Research, and Sport of the Slovak Republic; Slovak Academy Sciences [1/0700/25

Unlocking the potential of zinc phosphate nanoplatelets for alkyd coating formulation with advanced anti-corrosive protection at reduced pigment content

Novel zinc phosphate 2D nanoplatelets (ZPnp) were prepared by direct precipitation followed by a nano-milling process, effectively utilizing the preferential fragmentation of the lamellar precursor into thin platelets. The XRD analysis identified hopeite (Zn3(PO4)2·4H2O) as the crystalline phase, while SEM/TEM revealed rectangular, plate-like particles with lateral dimensions below 100 nm. DLS enabled tracking of the milling process, and BET was used to confirm the nanoscale character of ZPnp. The effect of incorporating 1.6 wt.% nano-milled ZPnp slurry (40 wt.% solids) into a mixed urethane–alkyd (UreAlkyd) topcoat on barrier (passive) and active-healing performance was compared with that of a coating containing 4 wt.% commercial Al-treated zinc phosphate (ZPA) micropowder. The performance of the coatings was assessed using EIS and directly compared through standard salt-spray testing. Ion release was quantified by AAS in saline solutions at different pH values. It was found that the more compact/denser inhibitive layer formation observed in long-term exposures for ZPnp prevails over the relatively better active-site-blocking effect of the commercial ZPA at initial immersion times. The ZPnp-containing formulation exhibited higher corrosion resistance, along with lower capacitance, in both artificially scratched and intact coatings compared to the commercial ZPA-containing sample. Hence, the development of a superior active/barrier anti-corrosion protection system that possesses prolonged healing activity at more than six times lower anti-corrosion pigment content was demonstrated.This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic \u2013 DKRVO ( RP/CPS/2024\u201328/007 and RP/CPS/2024\u201328/002 ) and Ministry of Industry and Trade of the Czech Republic ( CZ.01.1.02/0.0/0.0/20_321/0025211 ). We would like to express our sincere gratitude to Mr. Milad Motamedi, Ph.D., for his invaluable support, insightful review, and meticulous editing. Thanks also extended to the company Rokospol a.s. for paints\u2019 formulation and corrosion tests according to international ISO standards.Ministry of Education, Youth and Sports of the Czech Republic-DKRVO [RP/CPS/2024-28/007, RP/CPS/2024-28/002]; Ministry of Industry and Trade of the Czech Republic [CZ.01.1.02/0.0/0.0/20_321/0025211

Enhancing work–life balance in coworking environments: perspectives from professionals

Purpose: This study aims to examine the influence of coworking spaces (CSs) on work–life balance (WLB). Furthermore, it investigates the impact of demographic and professional attributes of CS users. Design/methodology/approach: The data for this exploratory study was obtained from a survey distributed to professionals working in CSs, primarily from Czechia, Portugal, Slovakia and Vietnam. The data was processed using descriptive and inferential statistics. Findings: Age and caregiving responsibilities emerged as influential factors in the perception of CSs as a conduit for achieving WLB. Strategic location, flexible business hours and a vibrant community are crucial elements contributing to an enriched WLB across demographics and professional groups. Professional development was also highlighted as highly beneficial. Originality/value: This study highlights that the design of CSs must evolve to match modern workforce needs. By targeting the preferences of specific demographic groups, CSs can gain advantages by promoting themselves as places conducive to resource gain and accumulation, as well as to WLB.This research was funded by the Ministry of Education, Youth and Sports, Czech Republic, programme INTER-EXCELLENCE, subprogramme INTER-COST, under Grant No. LTC20047 \u201CRegional development and public policy under creative economy: Mapping, knowledge sharing and management of New Working Spaces in the Czech Republic\u201D; COST Action under the Grant No. CA18214 \u201CThe Geography of New Working Spaces and the Impact on the Periphery\u201D, which is funded by the Horizon 2020 Framework Programme of the European Union; and Ministry of Education, Science, Research and Sport of the Slovak Republic, Scientific Grant Agency VEGA, under Grant No. 1/0249/22 \u201CCoworkings and the impact of the COVID-19 pandemic\u2013opportunities for urban economic development\u201D.Ministry of Education, Youth and Sports, Czech Republic [LTC20047]; Regional development and public policy under creative economy: Mapping, knowledge sharing and management of New Working Spaces in the Czech Republic; COST Action [CA18214]; Horizon 2020 Framework Programme of the European Union; Ministry of Education, Science, Research and Sport of the Slovak Republic, Scientific Grant Agency VEGA [1/0249/22

Polyester waste activated carbon assisted micropollutant methylene blue and Congo red dyes removal from wastewater: RSM modeling, kinetics, mechanism, and reusability study

This study explores the synthesis of activated carbon (AC) from polyester waste using zinc chloride (ZnCl2) as a chemical activator, designed to efficiently remove both positive methylene blue (MB) and negatively charged Congo red (CR) dyes from wastewater. Response Surface Methodology integrated with Central Composite Design was employed to optimize critical parameters, including adsorbent dosage, solution pH, dye concentration, and temperature, for enhanced dye removal. The results showed remarkable removal efficiencies of 100 % for MB and 99 % for CR under optimal conditions. The kinetic analysis showed that the pseudo-second-order model best described the adsorption process because of chemisorption, which includes ion exchange, complexation, π–π stacking, electrostatic interaction, and hydrogen bonding, while intra-particle diffusion was a key factor in the rate-limiting step. The results suggest MB followed the Langmuir isotherm, while the CR adsorption favored both Langmuir and Freundlich models. Thermodynamic studies revealed distinct adsorption behaviors: MB adsorption was exothermic, while CR adsorption was endothermic. Additionally, reusability tests confirmed the material's ability to maintain high performance over five adsorption–desorption cycles with no significant structural changes. These findings underscore the potential of polyester waste-derived AC as a sustainable and effective material for wastewater treatment.The authors are thankful to the Higher Education Commission (HEC) Government of Pakistan for funding this study under the NRPU program through Project No. 15188. We are thankful to Fiber Craft Industries (FCI) in Lahore, Pakistan, for supplying composite waste material. The authors (M.Y and V.S) gratefully acknowledge the support from the European Just Transition Fund within the Operational Programme: Just Transition under the aegis of the Ministry of the Environment of the Czech Republic, project CirkArena number CZ.10.03.01/00/22_003/0000045 and the Ministry of Education Youth and Sports of the Czech Republic, Operational Programme Johannes Amos Comenius OP JAC \u201CApplication potential development in the field of polymer materials in the context of circular economy compliance (POCEK)\u201D, number CZ.02.01.01/00/23_021/0009004. The authors are further grateful for co-funding from the development process of the Centre of Polymer Systems, Tomas Bata University in Zlin, program DKRVO (RP/CPS/2024-28/002) supported by the Ministry of Education Youth and Sports of the Czech Republic. M.Y also expresses his gratitude for support within the \u201CCreativity, Intelligence & Talent for the Zlin Region\u201D (CIT - ZK) program

Psychological ownership and knowledge sharing: Key psychological drivers of sustainable tourist behavior

As the green transformation sweeps across industries in the digital age, tourism stakeholders face a pressing need to utilize online platforms and digital influencers for sustainability messaging. Drawing on the Motivation-Opportunity-Ability framework, this study investigates the influence of green ownership psychology and green knowledge sharing on tourists' repatronage intentions. It focuses on the mediating role of cooperative green activity programs and the moderating impact of tourists' green trust in social media influencers. Results from a two-wave survey of 602 tourists in Vietnam show that green practices directly increase repatronage intentions. Cooperative green activity programs significantly mediate this relationship, enhancing the impact of green marketing practices on repatronage intentions. Furthermore, tourists' green trust in social media influencers is a crucial moderating factor. It increases the effectiveness of green ownership psychology and green knowledge sharing in influencing repatronage intentions through cooperative green activity programs. The study highlights how the emotional and cognitive aspects of green marketing contribute to tourists' decisions to revisit or continue using tourism services. Offering original insights into the interplay of these elements in green marketing within the tourism industry, this research enriches the application of the Motivation-Opportunity-Ability framework. It provides valuable implications for tourism companies aiming to foster sustainable practices and enhance customer loyalty, highlighting the role of digital influencer engagement and cooperative sustainability initiatives in green marketing strategies