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.

elevated nocturnal BP clinic BP monitoring alone is inadequate. ABPM should become golden standard to confirm adequate BP control in patients with kidney disease.

This paper introduces a "lifecycle perspective" on social robot design and human-robot interaction, and explores the practices of maintenance, repair, and letting go of social robots. Drawing on interviews with robot owners and representatives of robot development and repair companies, we argue that these previously disregarded aspects of everyday use provide a context for negotiating the social value and meaning of interactions with robots. We discuss owner concerns about robot obsolescence, as well as company support for long term human-robot interaction through repair, reuse, and giving owners closure in letting go of robots they can no longer use. Our work expands the purview of HRI study and design beyond the common focus on initial design and adoption and to perceptions and practices that can foster more enduring relationships with social robots, support sustainability in robot design, and address owners’ emotional attachment to robots.

The sources of a person’s ikigai—their sense of meaning and purpose in life—often change as they age. Reflecting on past and new sources of ikigai may help people renew their sense of meaning as their life circumstances shift. Building on insights from an initial Wizard-of-Oz robot prototype [1], we describe the design of an autonomous robot that uses a semi-structured conversation format to help older adults reflect on what gives their life meaning and purpose. The robot uses both pre-determined (scripted) and Large Language Model (LLM) generated questions to personalize conversations with older adults around themes of social interaction, planning, accomplishments, goal setting, and the recent past. We evaluated the autonomous robot with 19 older adult participants in a lab setting and at two eldercare facilities. Analysis of the older adults’ conversations with the robot and their responses to an evaluative survey allowed us to identify several design considerations for an autonomous robot that can support ikigai reflection. Interweaving simple yet detailed predetermined questions with LLM-generated follow-up questions yielded enjoyable, in-depth conversations with older adults. We also recognized the need for the robot to be able to offer relevant suggestions when participants cannot recall events and people they find meaningful. These findings aim to further refine the design of an interactive robot that can support users in their exploration of life’s purpose.

Using socially assistive robots (SARs) as specialized companions for those living with depression to manage symptoms provides a unique opportunity for exploration of robotic systems as comfort objects. Moreover, the robotic components allow for specialized behavioral responses to particular stimuli, as preferred by the user. We have conducted semi-structured interviews with 10 participants about the zoomorphic robot’s Therabot™ desired behaviors and focus groups with five additional participants regarding the preferred sensors within the Therabot™ system. In this paper, using the data from interviews and focus groups, we explore SAR input and output for depression management. While participants overall expected the robot to respond in much similar ways as a well-trained service animal, they expressed interest in the robot understanding unique information about the environment and the user, such as when the user might need interaction.

Under UNICEF’s Policy guidance on AI for children, child-centered AI should always ‘ensure inclusion of and for children.’ To spotlight youth visions for robots, we led co-design workshops with children between 5-14 years old. Youth designs were expressive, customized, relatable, and approachable. Based on 54 drawings and descriptions of the social robot Haru, we suggest that future child-centered robots should 1) be expressive across verbal and non-verbal channels of communication, 2) allow for customization to give children more agency when interacting with the robot, 3) adapt to children’s style and hobbies to make them feel seen, and 4) aesthetically keep proportions of robot faces consistent and cartoon-like to make robots more approachable.

Past research with participants in the United States showed that, in competitive group tasks, they have more positive attitudes and behaviors toward robots on their team over humans in another team. Here we present a study in which two Japanese students and two robots, placed in a randomly assigned group, compete with another student-and-robot team in a digital game. We explored participants’ moral behavior towards the robots, measured through their assignment of loud noise blasts to human and robot participants, and their perceptions of and attitudes towards the robots. We then compared this data to that which was collected within the United States. Results indicated that participants in Japan favored their ingroup humans and robots over outgroup agents and differentiated ingroup members more than outgroup members, as within the US. Japanese participants also anthropomorphized robots more than US participants and treated them more positively than US participants.

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.

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.

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.