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This research aimed to present the database construction process using some plant species found in the sample area. In addition to aerial photography, the characteristic plant species were determined through fieldwork, and their coordinates were recorded with the iPoint software. In the course of the research, DJI Phantom 4 Pro and Mavic Mini drones were used to take aerial photographs of Zimányi-island in Kis-Balaton. Several photographs were taken of the individual plants for identification and assessment of association characteristics, thereby broadening the spectrum of processed data. The aerial photos obtained during the recordings were initially processed with Agisoft PhotoScan 1.4.3 (Metashape after version 1.5), then for comparison with Agisoft Metashape 2.0.3 and Agisoft Cloud software. By combining the aerial photos, a high-resolution TIFF orthophoto was obtained for the entire area. After that, the visual data sets required for the 3D model-based vegetation map were created, pre-processed and processed. The integration of visual and non-visual data sets were integrated into the GIS system. In the research area, non-image data were also collected, which were entered into Microsoft Office Excel tables. QGIS software was used to insert these tables into the database. The completed project shows the coordinates of the 27 plant species recorded in 2019 and the 28 plant species recorded in 2020. The process of querying the developed database was also presented. Finally, a comparative analysis of two different versions of the software was presented and used for matching in the past period. The method can be widely used in precision agriculture as well, such as weed detection, which is pivotal to increasing crop yields.

Abstract While the rise of antibiotic resistance poses a global health challenge, the development of new antibiotics has slowed down over the past decades. This turned the attention of researchers towards the rational design of drug combination therapies to combat antibiotic resistance. In this review we discuss how drug combinations can exploit the deleterious pleiotropic effects of antibiotic resistance and conclude that each drug interaction has its prospective therapeutic application.

Bioconvective non-Newtonian fluids with motile microorganisms have diverse applications in biology and medicine, offering numerous research opportunities. This article presents a comprehensive investigation into the non-similar analysis of bio-convective micropolar flow induced by a Darcy-Forchheimer exponentially stretchable sheet, considering the effects of suction/injection and thermal radiation in a three-dimensional framework. The fluid under scrutiny is a viscoelastic tangent hyperbolic nanofluid, the impact of Cattaneo-Christov heat subjected to Riga plate is considered for novelty. The role of activation energy and heat source are also computed. The governing equations of viscoelastic tangent hyperbolic nanofluids are transformed into couple of ordinary differential equations via similarity approximations. The resulting ODEs are tackled numerically via bvp4c tool of MATLAB. The impression of appropriate parameters like magnetic parameter, bio-convection parameter, viscoelasticity parameter suction/injection parameter etc. on involved profiles are computed via graphical and tabulated trends. It is observed that velocity layer f′ is dwindled for growing value of Forchheimer number Fr, while reverse relation in velocity curve is noted for developing value of mixed convection parameter δ. Micropolar fluids find biomedical engineering applications in modeling blood flow in microvessels, understanding cerebrospinal fluid dynamics, and optimization of biomedical devices and therapies and simulating drug delivery in tissues.

Abstract Living cells have spontaneous ultraweak photon emission derived from metabolic reactions associated with physiological conditions. The ORCA-Quest CMOS camera (Hamamatsu Photonics, Japan) is a highly sensitive and essential tool for photon detection; its use with a microscope incubator (Olympus) enables the detection of photons emitted by embryos with the exclusion of harmful visible light. With the application of the second law of thermodynamics, the low-entropy energy absorbed and used by embryos can be distinguished from the higher-entropy energy released and detectable in their environment. To evaluate higher-entropy energy data from embryos, we developed a unique algorithm for the calculation of the entropy-weighted spectral fractal dimension, which demonstrates the self-similar structure of the energy (photons) released by embryos. Analyses based on this structure enabled the distinction of living and degenerated mouse embryos, and of frozen and fresh embryos and the background. This novel detection of ultra-weak photon emission from mouse embryos can provide the basis for the development of a photon emission embryo control system. The ultraweak photon emission fingerprints of embryos may be used for the selection of viable specimens in an ideal dark environment.

Abstract The effectiveness of psychological interventions (PI) for malignant diseases is controversial. We aimed to investigate the effect of PI on survival and quality of life (QoL) in patients with cancer. We performed a systematic search of MEDLINE, Cochrane, and Embase databases to identify randomized controlled trials comparing PI to standard care (PROSPERO registration number CRD42021282327). Outcomes were overall survival (OS), recurrence-free survival (RFS), and different domains of QoL. Subgroup analysis was performed based on the provider-, type-, environment-, duration of intervention; cancer stage, and type. Pooled hazard ratios (HR) and standardized mean difference (SMD) with 95% confidence intervals (CI) were calculated using a random-effects model. The OS and RFS did not differ significantly between the two groups (OS:HR = 0.97; CI 0.87–1.08; RFS:HR = 0.99; CI 0.84–1.16). However, there was significant improvement in the intervention group in all the analyzed domains of QoL; in the global (SMD = 0.65; CI 0.35–0.94), emotional (SMD = 0.64; CI 0.33–0.95), social (SMD = 0.32; CI 0.13–0.51) and physical (SMD = 0.33; CI 0.05–0.60) domains. The effect of PI on QoL was generally positive immediately, 12 and 24 weeks after intervention, but the effect decreased over time and was no longer found significant at 48 weeks. The results were better in the breast cancer group and early stages of cancer. PIs do not prolong survival, but they significantly improve the QoL of cancer patients. PI should be added as standard of care 3–4 times a year, at least for patients with early-stage cancer.

Abstract The present study aimed to investigate whether the strength of mental health competencies and the severity of mental disorder symptoms, and their interaction, differ in the strength of their associations with several dimensions of well-being in Hungarian adult psychiatric and non-clinical samples. All respondent in the psychiatric sample (129 patients (44 male, 85 female)) and in the non-clinical community sample (253 adults (43 male, 210 female)) completed the Mental Health Test, six measures of well-being and mental health, and the Symptom Checklist-90-Revised. Including both mental health competencies and mental disorder symptoms in a regression model in both samples can predict patients’ well-being even more accurately. Mental health competencies were positively related; mental disorder symptoms were negatively related to subjective well-being. In all models and in both samples, mental health competencies were found to be stronger determinants of well-being than mental disorder symptoms. The interaction of mental health competencies and mental disorder symptoms is no more predictive of well-being in either psychiatric or non-clinical samples than when the effects of each are considered separately. The assessment of mental health competencies has an important predictive value for well-being in the presence of psychopathological symptoms and/or mental disorders.

Abstract Numerous heat transfer applications, such as heat exchangers, solar trough collectors, and fields including food processing, material research, and aerospace engineering, utilize hybrid nanofluids. Compared to conventional fluids, hybrid nanofluids exhibit significantly enhanced thermal conductivity. The aim of this work is to explore flow and heat transmission features under of magneto-hydrodynamic bioconvective flow of carbon nanotubes over the stretched surface with Dufour and Soret effects. Additionally, comparative dynamics of the carbon nanotubes (SWCMT − MWCNT/C2H6O2 with SWCMT − MWCNT/C2H6O2 − H2O) flow using the Prandtl fluid model in the presence of thermal radiation and motile microorganisms has been investigated. Novel feature Additionally, the focus is also to examine the presence of microorganisms in mixture base hybrid nanofluid. To examine heat transfer features of Prandtl hybrid nanofluid over the stretched surface convective heating is taken into consideration while modeling the boundary conditions. Suitable similarity transform has been employed to convert dimensional flow governing equations into dimensionless equations and solution of the problem has been obtained using effective, accurate and time saving bvp-4c technique in MATLAB. Velocity, temperature, concentration and microorganisms profiles have been demonstrated graphically under varying impact of various dimensionless parameters such as inclined magnetization, mixed convection, Dufour effect, Soret effect, thermal radiation effect, and bioconvection lewis number. It has been observed that raising values of magnetization (0.5 ≤ M ≤ 4), mixed convection (0.01 ≤ λ ≤ 0.05) and inclination angle (0° ≤ α ≤ 180°) enhance fluid motion rapidly in Ethylene glycol based Prandtl hybrid nanofluid (SWCMT − MWCNT/C2H6O2) when compared with mixture base working fluid of carbon nanotubes SWCMT − MWCNT/C2H6O2 − H2O). Raising thermal radiation (0.1 ≤ Rd ≤ 1.7) and Dufour number (0.1 ≤ Du ≤ 0.19) values improves temperature profile. Moreover, a good agreement has been found between the current outcome and existing literature for skin friction outcomes.

In this study, three-dimensional steady-state laminar flow simulations were conducted in a horizontal pipe using CuO and multi-walled carbon nanotubes (MWCNT) nanoparticles with engine oil as the base fluid. Various nanoparticle volume fractions were examined under a constant heat flux boundary condition applied to the pipe wall. The main goal was to assess and compare the effects of different nanoparticle volume concentrations, including CuO and MWCNT in ratios of 1:1 and 1:2, on convective heat transfer. A second-order discretisation method was employed for solving the equations, and the SIMPLE algorithm was used for pressure–velocity coupling in the CFD code. The study focused on the impact of nanoparticle volume fraction on the convective heat transfer coefficient and the Nusselt number at a Reynolds number of 750. The findings indicate that increasing the nanoparticle volume fraction enhances both the convective heat transfer coefficient and the Nusselt number, with MWCNT having a more pronounced effect compared to CuO. Specifically, adding 2% CuO increases the heat transfer coefficient by 65%, while a mixture of 1% CuO and 1% MWCNT boosts it by 75%. The thermal boundary layer thickness also grows with higher nanoparticle concentrations, with 1% CuO and 3% CuO increasing the thickness by 1.5% and 3.6%, respectively. A formula for the thermal boundary layer thickness in CuO-oil nanofluids is provided based on volume fraction, and a scale analysis of the average heat transfer coefficient confirms that the simulation results are consistent with this analysis.

This study explores the influence of thermal radiation and heat source on magnetized flow micropolar nanofluid through a Stretchable Sheet in the presence of mobile microbes. The presence of microorganisms adds a biological dimension to the problem, affecting fluid dynamics and heat transfer, which are central to this investigation. To motivate the problem, the flow is induced by a Darcy porous exponentially stretching sheet with generalized boundary conditions. A regression analysis is conducted to analyze the interplay of various parameters on the flow and heat transfer characteristics. Additionally, similarity transformations are implemented to transform the set of partial differential equations (PDEs) into a set of ordinary differential equations (ODEs). The resulting equations are solved numerically using the shooting approach via the bvp4c platform in Matlab. The regression model quantifies the impact of each parameter and their interactions on the flow field, temperature distribution, and Darcy effects. Furthermore, the impact of involved parameters on flow, energy, volumetric concentration, density of microbes, and micro-rotations distribution are analyzed and discussed through graphs, literature, and tables. The findings of this research are crucial for various engineering, industrial, and pharmaceutical applications, including biofilm formation, geothermal energy extraction, and wastewater treatment processes.

To understand the complex problem of surface growth phenomena, we developed a model in which the regular diffusion equation is coupled to the Kardar–Parisi–Zhang (KPZ) equation. The fundamental or Gaussian solution of the regular diffusion equation is considered as an external noise or source term in the KPZ equation. The obtained system of partial differential equations is analytically solved by a self-similar Ansatz and expressed the solution as a combination of elementary and special functions. Using this solution, the effects of the physical parameters were explicitly investigated. Our recent explicit numerical method, the leapfrog-hopscotch algorithm, is also tested for this problem. It is shown that this method can be safely used with orders of magnitude larger time step sizes than the usual explicit (Euler) scheme as well if we are far from the cusp-like solutions. We pointed out that the cusps themselves cannot be properly simulated by any method that we know.

The present analysis examines the magnetohydrodynamic (MHD) flow of non-Newtonian Casson fluid on an exponentially shrinking surface under constant and exponentially varying wall temperature with suction. The main objective is to investigate multiple solutions of self-similar coupled nonlinear ordinary differential equations derived semi-numerically via the shifted Chebyshev collocation approach. The occurrence of a dual solution is found and variations in the velocity and temperature profiles are analyzed under different physical flow governing factors. The stability analysis is performed and it confirms that the first solution is stable and the second solution is unstable. The obtained results are confirmed by comparing them with earlier published results and show good agreement. The skin friction coefficient and wall temperature gradient increase for the first solution and decline for the second solution with enhancement in Hartmann number and suction parameter in case of exponentially varying surface temperature. Whereas, for constant surface temperature, increasing the Hartmann number and suction parameter results in the intensification of the wall temperature gradient. The velocity and temperature profiles decrease with improving the Casson parameter. As the Prandtl number strengthens, the heat transfer rate in a constant surface temperature situation is comparatively higher than exponentially varying surface temperature situation.

Management of invasive alien plants is an increasing problem throughout the world. In some cases native rare or protected species can appear or even prefer habitats dominated by invasive alien plants, which raises questions about the optimal treatment of such areas. Erythronium dens-canis in Hungary is a protected species which only have several occurrences in the country and a number of these populations situated in Robinia pseudoacacia stands developed after harvesting native forests. In this study a total of five populations of E. dens-canis were surveyed between 2020 and 2022 in southwestern Hungary examining and comparing the ongoing demographic changes under native and Robinia stands by monitoring individual plants. Two populations were situated in forests composed of native tree species, two in Robinia pseudoacacia-dominated stands and one in a Robinia-native tree species mixed stand. We categorized the plants into five age-state categories: dormant, seedling, juvenile, vegetative adult, and reproductive adult. We found some considerable differences (e.g. leaf size, reproduction rate) between the populations situated in native and in Robinia stands, whereas the population in mixed forest showed intermediate character in most examined factors. Based on our results, R. pseudoacacia have a significant effect on the phenology and life history of E. dens-canis, and this effect is greater with higher proportion of R. pseudoacacia in a forest stand where the E. dens-canis occurs.

The boundary-layer flow on a shrinking/contracting sheet has abundant industrial applications, which include continuous glass casting, metal or polymer extrusions, and wire drawing. In this regard, the present analysis focuses the hybrid nanofluid flow on an exponentially extending sheet. The water-based hybrid nanofluid flow contains CoFe2O4 and TiO2 nanoparticles. Heat transfer rate analysis involves the utilization of the Cattaneo–Christov heat flux model. Moreover, the Brownian motion and thermophoresis effects are used in this novel work. The mathematical model is presented in the form of system of partial differential equations, which is then transformed into system of ordinary differential equations (ODEs) using the similarity variables. The system of ODEs is evaluated by homotopy analysis method. The variation in the flow profiles has been investigated using figures and tables. The conclusions demonstrate that the effect of magnetic parameter is 52% better for hybrid nanofluid flow than for the pure water. Conversely, the increasing magnetic parameter diminishes the thermal transfer rates for water, TiO2–H2O, CoFe2O4–H2O, and TiO2–CoFe2O4/H2O. The increasing thermophoresis parameter upsurges the thermal flow rate of nanofluids and hybrid nanofluid, while the increasing Brownian motion parameter lessens the thermal transfer rates of nanofluids and hybrid nanofluid. The increasing effect of thermophoresis parameter is 39% better for hybrid nanofluid than for the base fluid. However, the declining impression of Brownian motion factor is 48% greater for hybrid nanofluid related to pure water.

Abstract Nanofluid is a specially crafted fluid comprising a pure fluid with dispersed nanometer-sized particles. Incorporation these nanoparticles into pure fluid results in a fluid with improved thermal properties in comparison of pure fluid. The enhanced properties of nanofluids make them highly sought after, in diverse applications, consisting of coolant of devices, heat exchangers, and thermal solar systems. In this study hybrid nanofluid consisting of copper, alumina and titanium nanoparticles on a curved sheet has investigated with impact of chemical reactivity, magnetic field and Joule heating. The leading equations have converted to normal equations by using appropriate set of variables and has then evaluated by homotopy analysis method. The outcomes are shown through Figures and Tables and are discussed physically. It has revealed in this study that Cu-nanofluid flow has augmented velocity, temperature, and volume fraction distributions than those of Al2O3-nanofluid and TiO2-nanofluid. Also, the Cu-nanofluid flow has higher heat and mass transfer rates than those of Al2O3-nanofluid and TiO2-nanofluid.

This article presented micropolar hybrid nanofluid flow comprising copper and alumina nanoparticles over a flat sheet. The mixed convection phenomenon is studied under the effect of gravity. Some additional forces such as magnetic field, thermal radiation, Eckert number, heat source, and thermal slip condition are adopted in this analysis. The leading equations are transformed into dimensionless format by employing appropriate variables and then evaluated by homotopy analysis method (HAM). The obtained results are compared with published results and found a good agreement with those published results. Also, the results of HAM are compared with those of numerical method and found a good agreement as well. The fluctuations within the flow profiles are showcased utilizing figures and tables, followed by an in-depth discussion and analysis. The outcomes of this work show that the higher volume fractions of copper and alumina nanoparticles improved the hybrid nanofluid viscosity, which results in the augmenting variation in the velocity profiles. The higher volume fractions of copper and alumina nanoparticles improved the hybrid nanofluid thermal conductivity, which results in the augmenting variation in thermal distribution. The growing mixed convection factor amplifies the buoyancy force toward the stagnation point flow, which enlarges the velocity panel. The effects of hybrid nanoparticles (Cu-Al2O3/water) at the surface are smaller on friction force and larger in case of thermal flow rate when compared to the nanofluids (Cu/water and Al2O3/water).

Primary research data on food chain safety at consumer level is needed to help policymakers to decrease the risk of foodborne infections in the Lao People's Democratic Republic. Therefore, the objectives of this study are to 1) determine Lao people's food safety knowledge, attitudes, and intentions and identify the most influential factors that shape their food safety behaviour, and 2) to support the government in the development of more efficient risk communication programmes. A paper-based consumer survey was implemented to collect quantitative data on the selected topics about Laotian consumers, as well as on the equipment of households regarding the conditions and tools necessary for safe food preparation and storage. A model was developed based on the extended Theory of Planned Behaviour (TPB), and partial least squares structural equation modelling (PLS-SEM) was applied to analyse the factors that affect food safety behaviour. The elements of Knowledge and Perceived Behavioural Control positively influence behaviours, such as using separate chopping boards for raw and ready-to-eat foods. According to the model, only 10 % of the Intentions would be translated into Behaviours, which gap can be explained by the lack of a hygienic environment. Although the survey indicated that Laotian people intend to follow food safety guidelines, participants felt they lacked sufficient knowledge. This perception was validated by the knowledge test and behavioural part of the study. In the light of these findings, it is essential to raise awareness and promote food safety knowledge and interventions, such as enhancing food safety education in childhood. This would help to facilitate and encourage adopting safe practices to improve overall food safety at the consumer level, delivering positive impacts also to the food business sector.

Abstract The fluid flow over an extending sheet has many applications in different fields which include, manufacturing processes, coating, thin film decomposition, heat and mass transfer, biomedical applications, aerospace engineering, environmental science, energy production. Keeping in mind these applications, the non-Newtonian hybrid nanofluid flow comprising of Cu and CuO nanoparticles over an extending sheet is analyzed in this work. Two different base fluids called kerosene oil and water have been incorporated. The sheet is considered to be thermally convective along with zero mass flux condition. The main equations of modeled problem have been transformed to dimensionless form by using similarity variables. The designed problem is evaluated computationally by using bvp4c Matlab function. Validation of the present results is also performed. The impacts of magnetic, Brownian motion, chemical reaction, suction and thermophoresis factors are analyzed and discussed in details. The outcomes of the present investigation declare that the kerosene oil-based hybrid nanofluid flow has greater velocity and concentration profiles than that of the water-based hybrid nanofluid flow. The water-based hybrid nanofluid has greater temperature distribution than that of kerosene oil-based hybrid nanofluid flow. The streamlines of the kerosene oil-based Newtonian and non-Newtonian hybrid nanofluid flows are more stretched than water-based Newtonian and non-Newtonian hybrid nanofluid flows.

The objective of this study was to estimate the heritability of dairy production traits and that for dimensional traits and to calculate the correlation between the two heritability values in a Holstein Friesian cow herd bred in Hungary. Data of 15,032 Holstein Friesian cows born in the period 2008–2018 from 666 sires were collected for the study in 6 large dairy herds. Among the conformation traits, stature (ST), chest width (CW), body depth (BD), and rump width (RW), and for production traits, in the first lactation of cows, the 305-day milk yield (MY), milk butterfat yield (FY), and milk protein yield (MY) were evaluated. Heritability estimates of ST, CW, BD, and RW were 0.49, 0.25, 0.31, and 0.30, and those of MY, FY, and PY were 0.40, 0.35, and 0.30, respectively. BD and RW had no phenotypic (b = −0.01) or genetic (b = 0.00–0.01) change. The production traits (MY, FY, PY) increased to a greater extent (b = 2.2–43.3) than the examined conformation traits over time. Consequently, it is indicated that the selection for dairy production did not result in an increase in the studied dimensional traits.

The primary goal of this research was to empirically identify and validate the factors influencing student engagement in a learning environment where AI-based chat tools, such as ChatGPT or other large language models (LLMs), are intensively integrated into the curriculum and teaching–learning process. Traditional educational theories provide a robust framework for understanding diverse dimensions of student engagement, but the integration of AI-based tools offers new personalized learning experiences, immediate feedback, and resource accessibility that necessitate a contemporary exploration of these foundational concepts. Exploratory Factor Analysis (EFA) was utilized to uncover the underlying factor structure within a large set of variables, and Confirmatory Factor Analysis (CFA) was employed to verify the factor structure identified by EFA. Four new factors have been identified: “Academic Self-Efficacy and Preparedness”, “Autonomy and Resource Utilization”, “Interest and Engagement”, and “Self-Regulation and Goal Setting.” Based on these factors, a new engagement measuring scale has been developed to comprehensively assess student engagement in AI-enhanced learning environments.

Circadian clocks are biochemical timers regulating many physiological and molecular processes according to the day/night cycles. The function of the oscillator relies on negative transcriptional/translational feedback loops operated by the so-called clock genes and the encoded clock proteins. Previously, we identified the small GTPase LIGHT INSENSITIVE PERIOD 1 (LIP1) as a circadian-clock-associated protein that regulates light input to the clock in the model plant Arabidopsis thaliana. We showed that LIP1 is also required for suppressing red and blue light-mediated photomorphogenesis, pavement cell shape determination and tolerance to salt stress. Here, we demonstrate that LIP1 is present in a complex of clock proteins GIGANTEA (GI), ZEITLUPE (ZTL) and TIMING OF CAB 1 (TOC1). LIP1 participates in this complex via GUANINE EX-CHANGE FACTOR 7. Analysis of genetic interactions proved that LIP1 affects the oscillator via modulating the function of GI. We show that LIP1 and GI independently and additively regulate photomorphogenesis and salt stress responses, whereas controlling cell shape and photoperiodic flowering are not shared functions of LIP1 and GI. Collectively, our results suggest that LIP1 affects a specific function of GI, possibly by altering binding of GI to downstream signalling components.