In the digital era of e-commerce, effective content management is crucial for engaging and retaining online consumers. Traditional manual approaches to content creation often fall short in terms of speed, scalability, and adaptability. With over 26.5 million e-commerce stores worldwide, staying competitive requires leveraging all available tools. This research paper investigates the efficiency and effectiveness of AI-driven content generation compared to traditional methods. We examine AI technologies for creating titles, subtitles, and SEO optimization against content writers. The study involves five authors and an AI tool generating content for five products, with time taken for content creation measured and compared. Additionally, a group of 15 participants will evaluate the professional quality and click ability of the generated content. Using Python, we will analyze the potential time savings for generating 100 titles and assess the overall quality improvement. The results aim to provide empirical evidence on the benefits of AI in content creation for e-commerce. Our findings reveal that AI significantly reduces the time required for content creation. Specifically, AI-generated titles are 84.17% faster and AI-generated subtitles are 77.31% faster compared to those created by content writers. The content writers worked without the aid of any tools, relying solely on provided specifications. Additionally, 81.33% of participants preferred the titles generated by AI, while 88% favoured the AI-generated subtitles. These results underscore the potential of AI to enhance efficiency and effectiveness in e-commerce content management.

BACKGROUND AND PURPOSE The Rasch-Built Pompe-Specific Activity (R-PAct) scale is a patient-reported outcome measure specifically designed to quantify the effects of Pompe disease on daily life activities, developed for use in Dutch- and English-speaking countries. This study aimed to validate the R-PAct for use in other countries. METHODS Four other language versions (German, French, Italian, and Spanish) of the R-PAct were created and distributed among Pompe patients (≥16 years old) in Germany, France, Spain, Italy, and Switzerland and pooled with data of newly diagnosed patients from Australia, Belgium, Canada, the Netherlands, New Zealand, the USA, and the UK and the original validation cohort (n = 186). The psychometric properties of the scale were assessed by exploratory factor analysis and Rasch analysis. RESULTS Data for 520 patients were eligible for analysis. Exploratory factor analysis suggested that the items separated into two domains: Activities of Daily Living and Mobility. Both domains independently displayed adequate Rasch model measurement properties, following the removal of one item ("Are you able to practice a sport?") from the Mobility domain, and can be added together to form a "higher order" factor as well. Differential item functioning (DIF)-by-language assessment indicated DIF for several items; however, the impact of accounting for DIF was negligible. We recalibrated the nomogram (raw score interval-level transformation) for the updated 17-item R-PAct scale. The minimal detectable change value was 13.85 for the overall R-PAct. CONCLUSIONS After removing one item, the modified-R-PAct scale is a valid disease-specific patient-reported outcome measure for patients with Pompe disease across multiple countries.

The aim of this study was to evaluate the phytotoxic, genotoxic, cytotoxic and antimicrobial effects of the Mentha arvensis L. essential oil (EO). The biological activity of M. arvensis EO depended on the analyzed variable and the tested oil concentration. Higher concentrations of EO (20 and 30 µg mL-1) showed a moderate inhibitory effect on the germination and growth of seedlings of tested weed species (Bellis perennis, Cyanus segetum, Daucus carota, Leucanthemum vulgare, Matricaria chamomilla, Nepeta cataria, Taraxacum officinale, Trifolium repens and Verbena × hybrida). The results obtained also indicate that the EO of M. arvensis has some genotoxic, cytotoxic and proliferative potential in both plant and human in vitro systems. Similar results were obtained for antimicrobial activity against eight bacteria, including multidrug-resistant (MDR) strains [Bacillus subtilis, Enterococcus faecalis, Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), Escherichia coli, extended-spectrum beta-lactamase-producing (ESBL) E. coli, Pseudomonas aeruginosa and Salmonella enterica subsp. enterica serovar Enteritidis], with the effect on multidrug-resistant bacterial strains. Research indicates that the EO of M. arvensis shows phytotoxic, genotoxic, cytotoxic and antimicrobial effects, as well as its potential application as a herbicide and against various human diseases.

Data-driven models that act as surrogates for computationally costly 3D topology optimization techniques are very popular because they help alleviate multiple time-consuming 3D finite element analyses during optimization. In this study, one such 3D CNN-based surrogate model for the topology optimization of Schoen’s gyroid triply periodic minimal surface unit cell is investigated. Gyroid-like unit cells are designed using a voxel algorithm and homogenization-based topology optimization codes in MATLAB. A few such optimization data are used as input–output for supervised learning of the topology-optimization process via the 3D CNN model in Python code. These models could then be used to instantaneously predict the optimized unit cell geometry for any topology parameters. The high accuracy of the model was demonstrated by a low mean square error metric and a high Dice coefficient metric. The model has the major disadvantage of running numerous costly topology optimization runs but has the advantages that the trained model can be reused for different cases of TO and that the methodology of the accelerated design of 3D metamaterials can be extended for designing any complex, computationally costly problems of metamaterials with multi-objective properties or multiscale applications. The main purpose of this paper is to provide the complete associated MATLAB and PYTHON codes for optimizing the topology of any cellular structure and predicting new topologies using deep learning for educational purposes.

Using the strong-field-approximation theory beyond the dipole approximation we investigate above-threshold ionization induced by the monochromatic and bichromatic laser fields. Particular emphasis is on the approach based on the saddle-point method and the quantum-orbit theory which provides an intuitive picture of the underlying process. In particular, we investigate how the solutions of the saddle-point equations and the corresponding quantum orbits and velocities are affected by the nondipole effects. The photoelectron trajectories are two dimensional for linearly polarized field and three dimensional for two-component tailored fields, and the electron motion in the propagation direction appears due to the nondipole corrections. We show that the influence of these corrections is not the same for all contributions of different saddle-point solutions. For a linearly polarized driving field, we focus our attention only on the rescattered electrons. On the other hand, for the tailored driving field, exemplified by the ω–2ω orthogonally polarized two-color field, which is of the current interest in the strong-field community, we devote our attention to both the direct and the rescattered electrons. In this case, we quantitatively investigate the shift which appears in the photoelectron momentum distribution due to the nondipole effects and explain how these corrections affect the quantum orbits and velocities which correspond to the saddle-point solutions. Published by the American Physical Society 2024

The emergence of bacteria with antibiotic resistance and multiple resistance is characteristic of animal and human pathogens. It is wide known that bee products, which have been used in alternative medicine since ancient times, have antimicrobial potential. Application of bee products for therapeutic purposes is defined as apitherapy. The study aimed to evaluate the antimicrobial activity of commercial chestnut honey, pollen and propolis produced in western Bosnia and Herzegovina (Sanski Most) individually and in five combinations (apimixtures). The antimicrobial properties of samples were investigated using the agar well diffusion method against three Gram-positive bacteria (Bacillus subtilis subsp. spizizenii ATCC 6633, Methicillin-resistant Staphylococcus aureus ATCC 33591, Enterococcus faecalis ATCC 29212); three Gram-negative bacteria (ESBL producing Escherichia coli ATCC 35218, Salmonella enterica subsp. enterica serovar Enteritidis ATCC 13076, Pseudomonas aeruginosa ATCC 9027) and one fungal species (Candida albicans ATCC 10231). Pure bee pollen inhibited the growth of only Gram-negative bacteria, concentrated chestnut honey was active against all Gram-negative and Gram-positivebacteria, while 20% propolis extract and apimixtures A2 (80% honey and 20% propolis) and A3 (60% honey, 20% pollen and 20% propolis extract) inhibited the growth of all tested microorganisms. Chestnut honey andthree apimixtures (A1, A2 and A3) showed the highest antibacterial action against all tested Gram-negative bacteria and MRSA compared to other investigated samples. In this study, examined honeybee products from Bosnia and Herzegovina and their mixtures had significant activity against tested bacteria, including strains with proven resistance to conventional antibiotics, MRSA and ESBL producing E. coli.

Natural killer (NK) cells are essential components of the innate immune system, with their activity significantly regulated by Killer cell Immunoglobulin-like Receptors (KIRs). The diversity and structural complexity of KIR genes present significant challenges for accurate genotyping, essential for understanding NK cell functions and their implications in health and disease. Traditional genotyping methods struggle with the variable nature of KIR genes, leading to inaccuracies that can impede immunogenetic research. These challenges extend to high-quality phased assemblies, which have been recently popularized by the Human Pangenome Consortium. This paper introduces BAKIR (Biologically-informed Annotator for KIR locus), a tailored computational tool designed to overcome the challenges of KIR genotyping and annotation on high-quality, phased genome assemblies. BAKIR aims to enhance the accuracy of KIR gene annotations by structuring its annotation pipeline around identifying key functional mutations, thereby improving the identification and subsequent relevance of gene and allele calls. It uses a multi-stage mapping, alignment, and variant calling process to ensure high-precision gene and allele identification, while also maintaining high recall for sequences that are significantly mutated or truncated relative to the known allele database. BAKIR has been evaluated on a subset of the HPRC assemblies, where BAKIR was able to improve many of the associated annotations and call novel variants. BAKIR is freely available on GitHub, offering ease of access and use through multiple installation methods, including pip, conda, and singularity container, and is equipped with a user-friendly command-line interface, thereby promoting its adoption in the scientific community.

The quantum-mechanical transition amplitudes for atomic and molecular processes in strong laser fields are expressed in the form of multidimensional integrals of highly oscillatory functions. Such integrals are ideally suited for the evaluation by asymptotic methods for integrals. Furthermore, using these methods it is possible to identify, in the sense of Feynman's path-integral formalism, the partial contributions of quantum orbits, which are related to particular solutions of the saddle-point equations. This affords insight into the physics of the problem, which would not have been possible by only solving these integrals numerically. We apply the saddle-point method to various quantum processes, which are important in strong-field physics and attoscience. The special case of coalescing or near-coalescing saddle points requires application of the uniform approximation. We also present two modifications of the saddle-point method, for the cases where a singular point of the subintegral function exactly overlaps with a saddle point or is located in its close vicinity. Particular emphasis is on the classification of the saddle-point solutions. This problem is solved for the one-dimensional integral over the ionization time, relevant for above-threshold ionization (ATI), while for two-dimensional integrals a classification by the multi-index $(\alpha,\beta,m)$ is introduced, which is particularly useful for the medium- and high-energy spectrum of high-order harmonic generation (HHG) and backward-scattered electrons (for high-order ATI). For the low-energy structures a classification using the multi-index $(\nu,\rho,\mu)$ is introduced for the forward-scattering quantum orbits. In addition to laser-induced processes such as ATI, HHG and high-order ATI, we consider laser-assisted scattering as an example of laser-assisted processes for which real solutions of the saddle-point equation exist. Particular attention is devoted to the quantum orbits that describe and visualize these processes. We also consider finite laser pulses, the semiclassical approximation, the role of the Coulomb field and the case of laser fields intense enough to lead into the relativistic regime.

As urbanization increases, cities face challenges related to sustainability and mobility. This study, conducted through interviews in March and April 2023, investigates the implementation of smart mobility solutions in German-speaking cities (Austria, Germany, and Switzerland) and Sarajevo, Bosnia and Herzegovina, through a comparative analysis of stakeholder perspectives. Using semi-structured interviews with 25 experts, we explored the opportunities and challenges associated with smart mobility in these distinct socio-economic contexts. The findings reveal significant differences in technological advancement, infrastructural support, and financial resources, providing valuable insights for policymakers and urban planners. This study contributes to the existing literature by bridging the gap between developed and developing regions, offering practical recommendations for achieving sustainable urban transportation systems.