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

Effective preprocessing of electroencephalography (EEG) data is fundamental for deriving meaningful insights. Independent component analysis (ICA) serves as an important step in this process by aiming to eliminate undesirable artifacts from EEG data. However, the decision on which and how many components to be removed remains somewhat arbitrary, despite the availability of both automatic and manual artifact rejection methods based on ICA. This study investigates the influence of different ICA-based artifact rejection strategies on EEG-based auditory attention decoding (AAD) analysis. We employ multiple ICA-based artifact rejection approaches, ranging from manual to automatic versions, and assess their effects on conventional AAD methods. The comparison aims to uncover potential variations in analysis results due to different artifact rejection choices within pipelines, and whether such variations differ across different AAD methods. Although our study finds no large difference in performance of linear AAD models between artifact rejection methods, two exeptions were found. When predicting EEG responses, the manual artifact rejection method appeared to perform better in frontal channel groups. Conversely, when reconstructing speech envelopes from EEG, not using artifact rejection outperformed other approaches.

The integration of artificial intelligence (AI) and the internet of things (IoT) is bringing revolutionary changes to the hospitality industry, enabling the advancement of sustainable practices. This research, conducted using a quantitative methodology through surveys of hotel managers in the Republic of Serbia, examines the perceived contribution of AI and IoT technologies to operational efficiency and business sustainability. Data analysis using structural equation modeling (SEM) has determined that AI and IoT significantly improve operational efficiency, which positively impacts sustainable practices. The results indicate that the integration of these technologies not only optimizes resource management but also contributes to achieving global sustainability goals, including reducing the carbon footprint and preserving the environment. This study provides empirical evidence of the synergistic effects of AI and IoT on hotel sustainability, offering practical recommendations for managers and proposing an innovative framework for enhancing sustainability. It also highlights the need for future research to focus on the long-term impacts of these technologies and address challenges related to data privacy and implementation costs.

Autophagy is the primary intracellular degradation system, and it plays an important role in many biological and pathological processes. Studies of autophagy involvement in developmental processes are important for understanding various processes. Among them are fibrosis, degenerative diseases, cancer development, and metastasis formation. Diabetic kidney disease is one of the main causes of chronic kidney disease and end-stage renal failure. The aim of this study was to investigate the immunohistochemical expression patterns of LC3B, LAMP2A, and GRP78 during different developmental stages of early-developing human kidneys and in samples from patients with type II diabetes mellitus. During the 7/8th DW, moderate expression of LC3B and LAMP2A and strong expression of GRP78 were found in the mesonephric glomeruli and tubules. In the 9/10th DW, the expression of LC3B and LAMP2A was even more pronounced in the mesonephric tubules. LC3B, LAMP2A, and GRP78 immunoreactivity was also found in the paramesonephric and mesonephric ducts and was stronger in the 9/10th DW compared with the 7/8th DW. In addition, the expression of LC3B, LAMP2A, and GRP78 also appeared in the mesenchyme surrounding the paramesonephric duct in the 9/10th DW. In the 15/16th DW, the expression of LC3B in the glomeruli was weak, that of LAMP2A was moderate, and that of GRP78 was strong. In the tubuli, the expression of LC3B was moderate, while the expression of LAMP2A and GRP78 was strong. The strongest expression of LC3B, LAMP2A, and GRP78 was observed in the renal medullary structures, including developing blood vessels. In postnatal human kidneys, the most extensive LC3B, LAMP2A, and GRP78 expression in the cortex was found in the epithelium of the proximal convoluted tubules, with weak to moderate expression in the glomeruli. The medullary expression of LC3B was weak, but the expression of LAMP2A and GRP78 was the strongest in the medullary tubular structures. Significantly lower expression of LC3B was found in the glomeruli of the diabetic patients in comparison with the nondiabetic patients, but there was no difference in the expression of LC3B in the tubule–interstitial compartment. The expression of LAMP2A was significantly higher in the tubule–interstitial compartments of the diabetic patients in comparison with the nondiabetic patients, while its expression did not differ in the glomeruli. Extensive expression of GRP78 was found in the glomeruli and the tubule–interstitial compartments, but there was no difference in the expression between the two groups of patients. These data give us new information about the expression of LC3B, LAMP2A, and GRP78 during embryonic, fetal, and early postnatal development. The spatiotemporal expression of LC3B, LAMP2A, and GRP78 indicates the important role of autophagy during the early stages of renal development. In addition, our data suggest a disturbance in autophagy processes in the glomeruli and tubuli of diabetic kidneys as an important factor in the pathogenesis of diabetic kidney disease.

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.

Volumetric additive manufacturing (VAM) presents several advantages, notably reduced printing times and high surface quality. Yet, a persistent challenge is sedimentation during printing, impacting the geometric fidelity of printed objects. This study proposes an innovative solution using a viscoplastic resin, aiming to alleviate sedimentation and enable translation-free printing. Through numerical simulations, this approach’s efficacy is showcased. A comparative analysis between a viscoplastic fluid and a Newtonian case elucidates the disparities in viscosity and shear rate fields and their impact on sedimentation dynamics. Moreover, the study investigates the intricate relationships between viscoplastic parameters, resin attributes, and setup parameters to unveil their collective influence on sedimentation behavior. This methodology offers valuable insights into selecting optimal viscoplastic behavior and printing parameters to effectively control sedimentation in VAM.

In this article, I explore how the memories of the missing men that perished in the Bosnian War have been framed, forged and relayed among the surviving family members by means of photography. I analyse three cases of the use of photography and its creative processing among the surviving relatives through which they sought to add a sense of individuality to the objects of camera – their missing family members. The data for this article are derived from my ethnographic engagement with the Bosnian communities of genocide survivors resettled in Australia and the United States, combined with the visual analysis of artworks relative to the topic of lost family members. The article also highlights the conductivity of photography through which the post-generation identifies with and processes the ancestral trauma of genocide. The findings from this article re-visit the importance of materiality in the service of memory, through which the loss is mediated, transformed, transmitted and embraced. I argue that closer scholarly engagement with personal(ised) modes of honouring and remembering the individual victims of genocide can foster a better understanding of its emotional reverberations and impact on the healing of affected societies.

Blasting is a key process that plays a significant role in various industries, including mining and construction. To measure the effectiveness and potential impact of a blast generated by different explosives, industry professionals use a widely accepted parameter known as TNT (trinitrotoluene) equivalent. This manuscript provides an overview of the approach based on the application of the explosive equivalency principle in the prediction of the seismic effects caused by the detonation of different explosives. The explosive equivalents of studied explosives are derived from the results of thermochemical calculations using the EXPLO5 code and compared to field tests. The results have demonstrated that the equivalency approach can potentially be a useful tool in the assessment of blast-induced seismic effects.

Genetic diversity is essential for maintaining healthy populations and ecosystems. Several approaches have recently been developed to evaluate population genetic trends without necessarily collecting new genetic data. Such “genetic diversity indicators” enable rapid, large-scale evaluation across dozens to thousands of species. Empirical genetic studies, when available, provide detailed information that is important for management, such as estimates of gene flow, inbreeding, genetic erosion and adaptation. In this article, we argue that the development and advancement of genetic diversity indicators is a complementary approach to genetic studies in conservation biology, but not a substitute. Genetic diversity indicators and empirical genetic data can provide different information for conserving genetic diversity. Genetic diversity indicators enable affordable tracking, reporting, prioritization and communication, although, being proxies, do not provide comprehensive evaluation of the genetic status of a species. Conversely, genetic methods offer detailed analysis of the genetic status of a given species or population, although they remain challenging to implement for most species globally, given current capacity and resourcing. We conclude that indicators and genetic studies are both important for genetic conservation actions and recommend they be used in combination for conserving and monitoring genetic diversity.

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 that 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 (α,β,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 (ν,ρ,μ) 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.