Translation and cross-cultural adaptation of the Get Active Questionnaire for Pregnancy (kwestionariusz "Badź Aktywna w Ciąży") to support physical activity among pregnant women in Poland

INTRODUCTION

Physical activity during pregnancy is established to derive clinically meaningful improvements in pregnancy, childbirth, and postpartum health outcomes. Evidence-based pre-screening tools have been developed to support the implementation of physical activity programmes, and enhance communication between health care providers, exercise professionals and pregnant women. The Get Active Questionnaire for Pregnancy (GAQ-P) and the Health Care Provider Consultation Form for Prenatal Physical Activity (HCPCF) empower pregnant women to identify whether they require additional counselling from their obstetric health care provider in terms of physical activity. However, these tools are not available in Polish. This work details the process taken to translate the GAQ-P and HCPCF into Polish.

MATERIAL AND METHODS

We followed the translation process outlined by the Translation and Cultural Adaptation International Society for Pharmacoeconomics and Outcomes Research (ISPOR) guidelines between August 2022 and August 2023. We formed an expert group that included representatives of the Polish Society of Sports Medicine, The Polish Society of Gynaecologists and Obstetricians, practitioners, and scientists in physical activity during pregnancy. We implemented 9 of the 10 steps recommended by ISOPR in the translation process. At the Cognitive Debriefing stage, we collected opinions on the Polish version of GAQ-P and HCPCF from 70 stakeholders on the clarity and cultural appropriateness of the translation.

RESULTS AND CONCLUSIONS

Target users have positively evaluated the Polish version of GAQ-P and HCPCF. Thanks to the ISPOR methodology, we obtained a trustworthy, evidence-based screening tools, which can reduce the barriers for most women to be physically active during pregnancy.

Technological and Modelling Progress in Green Engineering and Sustainable Development: Advancements in Energy and Materials Engineering

Due to a growing number of environmental issues, including global warming, water scarcity, and fossil fuel depletion, the topic of modern materials in energy is becoming crucial for our civilization. The technological advancements that have been observed bring many innovations that significantly impact how energy can be generated, stored, and distributed. Moreover, new opportunities have emerged in energy and materials engineering due to the increasing computational capability of current data processing systems. Methods that are highly demanding, time-consuming, and difficult to apply may now be considered when developing complete and sophisticated models in many areas of science and technology. Combining computational methods and AI algorithms allows for multi-threaded analyses solving advanced and interdisciplinary problems. Therefore, knowledge and experience in this subject, as well as the investigation of new, more efficient, and environmentally friendly solutions, currently represent one of the main directions of scientific research. The Special Issue "Advances in Materials: Modelling Challenges and Technological Progress for Green Engineering and Sustainable Development" aims to bring together research on material advances, focusing on modelling challenges and technological progress (mainly for green engineering and sustainable development). Original research studies, review articles, and short communications are welcome, especially those focusing on (but not limited to) artificial intelligence, other computational methods, and state-of-the-art technological concepts related to the listed keywords within energy and materials engineering.

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC's nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments.

Artificial Intelligence Modeling-Based Optimization of an Industrial-Scale Steam Turbine for Moving toward Net-Zero in the Energy Sector

Augmentation of energy efficiency in the power generation systems can aid in decarbonizing the energy sector, which is also recognized by the International Energy Agency (IEA) as a solution to attain net-zero from the energy sector. With this reference, this article presents a framework incorporating artificial intelligence (AI) for improving the isentropic efficiency of a high-pressure (HP) steam turbine installed at a supercritical power plant. The data of the operating parameters taken from a supercritical 660 MW coal-fired power plant is well-distributed in the input and output spaces of the operating parameters. Based on hyperparameter tuning, two advanced AI modeling algorithms, i.e., artificial neural network (ANN) and support vector machine (SVM), are trained and, subsequently, validated. ANN, as turned out to be a better-performing model, is utilized to conduct the Monte Carlo technique-based sensitivity analysis toward the high-pressure (HP) turbine efficiency. Subsequently, the ANN model is deployed for evaluating the impact of individual or combination of operating parameters on the HP turbine efficiency under three real-power generation capacities of the power plant. The parametric study and nonlinear programming-based optimization techniques are applied to optimize the HP turbine efficiency. It is estimated that the HP turbine efficiency can be improved by 1.43, 5.09, and 3.40% as compared to that of the average values of input parameters for half-load, mid-load, and full-load power generation modes, respectively. The annual reduction in CO₂ measuring 58.3, 123.5, and 70.8 kilo ton/year (kt/y) corresponds to half-load, mid-load, and full load, respectively, and noticeable mitigation of SO₂, CH₄, N₂O, and Hg emissions is estimated for the three power generation modes of the power plant. The AI-based modeling and optimization analysis is conducted to enhance the operation excellence of the industrial-scale steam turbine that promotes higher-energy efficiency and contributes to the net-zero target from the energy sector.

Research on Waste Combustion in the Aspect of Mercury Emissions

The topic of waste combustion/co-combustion is critical, given the increasingly restrictive legal regulations regarding its environmental aspects. In this paper, the authors present the test results of selected fuels of different compositions: hard coal, coal sludge, coke waste, sewage sludge, paper waste, biomass waste and polymer waste. The authors conducted a proximate and ultimate analysis of the materials and mercury content in them and their ashes. An interesting element of the paper was the chemical analysis of the XRF of the fuels. The authors conducted the preliminary combustion research using a new research bench. The authors provide a comparative analysis of pollutant emissions-especially mercury emission-during the combustion of the material; this is an innovative element of this paper. The authors state that coke waste and sewage sludge are distinguished by their high mercury content. The value of Hg emission during the combustion depends on the initial mercury content in the waste. The results of the combustion tests showed the adequacy of mercury release compared to the emissions of other compounds considered. Small amounts of mercury were found in waste ashes. The addition of a polymer to 10% of coal fuels leads to a reduction in mercury emissions in exhaust gases.

Acetone-Gasoline Blend as an Alternative Fuel in SI Engines: A Novel Comparison of Performance, Emission, and Lube Oil Degradation

The disproportionate use of petroleum products and stringent exhaust emissions has emphasized the need for alternative green fuels. Although several studies have been conducted to ascertain the performance of acetone-gasoline blends in spark-ignition (SI) engines, limited work has been done to determine the influence of fuel on lubricant oil deterioration. The current study fills the gap through lubricant oil testing by running the engine for 120 h on pure gasoline (G) and gasoline with 10% by volume acetone (A10). Compared to gasoline, A10 produced better results in 11.74 and 12.05% higher brake power (BP) and brake thermal efficiency (BTE), respectively, at a 6.72% lower brake-specific fuel consumption (BSFC). The blended fuel A10 produced 56.54, 33.67, and 50% lower CO, CO₂, and HC emissions. However, gasoline remained competitive due to lower oil deterioration than A10. The flash-point and kinematic viscosity, compared to fresh oil, decreased by 19.63 and 27.43% for G and 15.73 and 20.57% for A10, respectively. Similarly, G and A10 showed a decrease in total base number (TBN) by 17.98 and 31.46%, respectively. However, A10 is more detrimental to lubricating oil due to a 12, 5, 15, and 30% increase in metallic particles like aluminum, chromium, copper, and iron, respectively, compared to fresh oil. Performance additives like calcium and phosphorous in lubricant oil for A10 decreased by 10.04 and 4.04% in comparison to gasoline, respectively. The concentration of zinc was found to be 18.78% higher in A10 when compared with gasoline. A higher proportion of water molecules and metal particles were found in lubricant oil for A10.

Artificial Intelligence and Computational Issues in Engineering Applications

High-performance supercomputers and emerging computing clusters created in research and development centres are rapidly increasing available computing power, which scientists are eager to use to implement increasingly advanced computing methods [...].

Comprehensive Knowledge-Driven AI System for Air Classification Process

Air classifier devices have a distinct advantage over other systems used to separate materials. They maximize the mill's capacity and therefore constitute efficient methods of reducing the energy consumption of crushing and grinding operations. Since improvement in their performance is challenging, the development of an efficient modeling system is of great practical significance. The paper introduces a novel, knowledge-based classification (FLClass) system of bulk materials. A wide range of operating parameters are considered in the study: the mean mass and the Sauter mean diameter of the fed material, classifier rotor speed, working air pressure, and test conducting time. The output variables are the Sauter mean diameter and the cut size of the classification product, as well as the performance of the process. The model was successfully validated against experimental data. The maximum relative error between the measured and predicted data is lower than 9%. The presented fuzzy-logic-based approach allows an optimization study of the process to be conducted. For the considered range of input parameters, the highest performance of the classification process is equal to almost 362 g/min. To the best of our knowledge, this paper is the first one available in open literature dealing with the fuzzy logic approach in modeling the air classification process of bulk materials.

Experimental Investigation of an Intensified Heat Transfer Adsorption Bed (IHTAB) Reactor Prototype

The first experience in the operation of intensified heat transfer adsorption bed reactor designed for low-pressure adsorption processes is presented in this paper. This work aims to assess the possibility of fluidizing the porous media bed induced by the pressure difference between the evaporator and the adsorption reactor. The conducted experimental research allowed indicating the type of silica gel recommended to use in fluidized beds of adsorption chiller. The fixed bed of silica gel was observed for the lower pressure differences, while fluidization appeared in the case of the pressure difference between the evaporator and the adsorption chamber higher than 1000 Pa. The most significant differences in the adsorption process between the fixed bed and the fluidized bed are revealed in the changes of sorbent temperatures. The silica gel bed was fluidized with water vapor generated in the evaporator.

Cutaneous larva migrans in a beach volleyball player

Athletes playing beach volleyball come into contact with sand and may contract skin parasites. We present a case of cutaneous larva migrans in a 20-year-old Polish female beach volleyball player. The athlete participated in The World Tour in Asia (China, Malaysia, Cambodia) a month before. In the beginning, her skin lesions were misdiagnosed as allergic reactions and treated with antihistamines. The disease in the form of a pruritic, migratory serpiginous skin eruption on legs was diagnosed during routine medical examination at the National Centre for Sports Medicine in Warsaw. She was treated successfully with albendazole and cetirizine. The skin lesions resolved entirely within two weeks.

A Comprehensive Three-Dimensional Analysis of a Large-Scale Multi-Fuel CFB Boiler Burning Coal and Syngas. Part 1. The CFD Model of a Large-Scale Multi-Fuel CFB Combustion

The paper is focused on the idea of multi-fuel combustion in a large-scale circulating fluidized bed (CFB) boiler. The article discusses the concept of simultaneous coal and syngas combustion. A comprehensive three-dimensional computational fluid dynamics (CFD) model is developed, which allows us to describe complex phenomena that occur in the combustion chamber of the CFB boiler burning coal and syngas produced from coal sludge.

The Effect of Adhesive Additives on Silica Gel Water Sorption Properties

Adsorption chillers are characterized by low electricity consumption, lack of moving parts, and high reliability. The disadvantage of these chillers is their large weight due to low adsorbent sorption capacity. Therefore, the attention is turned to finding a sorbent with a high water sorption capacity and enhanced thermal conductivity to increase chiller efficiency. The article discusses the impact of selected adhesives used for the production of an adsorption bed in order to improve heat exchange on its surface. Experiments with silica gel with three commercial types of glue on metal plates representing heat exchanger were performed. The structure of samples was observed under a microscope to determine the coverage of adsorbent by glue. To determine the kinetics of the free adsorption, the amounts of moisture adsorbed and the desorption dynamics the prepared samples of coated bed on metal plates were moisturized and dried in a moisture analyzer. Samples made of silica gel mixed with the adhesive 2-hydroxyethyl cellulose, show high adsorption capacity, low dynamic adsorption, and medium dynamic desorption. Samples containing adhesive poly(vinyl alcohol) adsorb less moisture, but free adsorption and desorption were more dynamic. Samples containing the adhesive hydroxyethyl cellulose show lower moisture capacity, relatively dynamic adsorption, and lower dynamic desorption.

Polyhedral meshing in numerical analysis of conjugate heat transfer

Computational methods have been widely applied in conjugate heat transfer analysis. The very first and crucial step in such research is the meshing process which consists in dividing the analysed geometry into numerous small control volumes (cells). In Computational Fluid Dynamics (CFD) applications it is desirable to use the hexahedral cells as the resulting mesh is characterized by low numerical diffusion. Unfortunately generating such mesh can be a very time-consuming task and in case of complicated geometry - it may not be possible to generate cells of good quality. Therefore tetrahedral cells have been implemented into commercial pre-processors. Their advantage is the ease of its generation even in case of very complex geometry. On the other hand tetrahedrons cannot be stretched excessively without decreasing the mesh quality factor, so significantly larger number of cells has to be used in comparison to hexahedral mesh in order to achieve a reasonable accuracy. Moreover the numerical diffusion of tetrahedral elements is significantly higher. Therefore the polyhedral cells are proposed within the paper in order to combine the advantages of hexahedrons (low numerical diffusion resulting in accurate solution) and tetrahedrons (rapid semi-automatic generation) as well as to overcome the disadvantages of both the above mentioned mesh types. The major benefit of polyhedral mesh is that each individual cell has many neighbours, so gradients can be well approximated. Polyhedrons are also less sensitive to stretching than tetrahedrons which results in better mesh quality leading to improved numerical stability of the model. In addition, numerical diffusion is reduced due to mass exchange over numerous faces. This leads to a more accurate solution achieved with a lower cell count. Therefore detailed comparison of numerical modelling results concerning conjugate heat transfer using tetrahedral and polyhedral meshes is presented in the paper.

Seasonal Vitamin D Status in Polish Elite Athletes in Relation to Sun Exposure and Oral Supplementation

Vitamin D does not only influence the musculoskeletal health and mineral homeostasis but it also affects cardiovascular, endocrine, nervous, immune and mental functions, thus it is of considerable importance for both physically active people and elite athletes. However, vitamin D deficiency is common worldwide and results from inadequate endogenous skin synthesis (insufficient ultraviolet B exposure) and diet. To improve the vitamin D status elite athletes often travel to lower latitude during winter. The aim of the study was to evaluate the seasonal vitamin D status in Polish elite athletes according to the sun exposure and oral supplementation. Serum concentration of 25-hydroxyvitamin D (25(OH)D) was measured in the years 2010–2014 in 409 elite athletes, who were divided into the following groups: OUTD—outdoor sports, represented by track and field athletes, who trained in Poland; IND—weightlifters, handball and volleyball players who trained indoors in Poland; SUN—track and field athletes who trained during Polish winter in lower latitude with high sunshine exposure; SUPL—track and field athletes who trained in Poland, had an inadequate vitamin D status (25(OH)D < 30 ng/ml) and were supplemented orally. Inadequate Vitamin D status was observed in 80% of OUTD and 84% of IND athletes in winter, whereas in summer the values amounted to 42% and 83%, respectively. The athletes exposed to sun in winter had significantly higher vitamin D concentration than OUTD group. Oral supplementation improved vitamin D concentration by 45%, whereas winter sun exposure caused its increase by 85%. Except for a few summer months an inadequate status of vitamin D was found in the majority of Polish elite athletes, with the deficiency level being similar to the one observed in non-athletic population. The most serious deficiency was observed in indoor disciplines. Adequate vitamin D status can be achieved by both increased sun exposure, especially in winter, and oral supplementation. Athletes should therefore routinely assess their vitamin D status and be educated how to approach their sunlight exposure, diet and supplementation.