This paper is the first to analyse the role of women authors in fostering justice-relevant topics in climate adaptation research. As representation, citation and payment patterns remain gender-biased across scientific disciplines, we explore the case of climate science, particularly adaptation, as its most human-oriented facet. In climate research and policy, there has been a recent surge of interest in climate justice topics: mentions of justice have increased almost tenfold in Intergovernmental Panel on Climate Change Working Group 2 reports between the latest assessment cycles (AR5 and AR6). We conduct a systematic examination of the topic space in the adaptation policy scholarship. As it is a vast and rapidly growing field, we use topic modelling, an unsupervised machine learning method, to identify the literature on climate justice and related fields, as well as to examine the relationship between topic prevalence and the gender of the authors. We find climate change adaptation policy research to be male dominated, with women holding 38.8% of first and 28.8% of last authorships. However, we observe topic-specific variability, whereby the share of female authors is higher among publications on justice-relevant topics. Female authorship is highly linked to topics such as Community, Local Knowledge, and Governance, but less to Food Security and Climate Finance. Our findings corroborate the evidence that female authors play a significant role in advancing the research and dialogue on the relationship between climate change and areas that have meaningful impact on lives of women and other marginalised groups.

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.

While control barrier functions (CBFs) are employed in addressing safety, control synthesis methods based on them generally rely on accurate system dynamics. This is a critical limitation, since the dynamics of complex systems are often not fully known. Supervised machine learning techniques hold great promise for alleviating this weakness by inferring models from data. We propose a novel approach for safe event-triggered learning of Gaussian process models in CBF-based continuous-time control for unknown control-affine systems. By applying a finite excitation at triggering times, our approach ensures a sufficient information gain to maintain the feasibility of the CBF-based safety condition with high probability. Our approach probabilistically guarantees safety based on a suitable GP prior and rules out Zeno behavior in the triggering scheme. The effectiveness of the proposed approach and theory is demonstrated in simulations.

The most significant contribution to the development of dentistry was made by Pierre Fauchard (1678-1761), whom we rightly consider the "father of modern dentistry". He wrote down his observations, thoughts, and innovations and in 1728 published "Le Chirurgien Dentiste ou Traite des Dentes". It is the first scientific textbook in this field and is considered to be the basis of a new age in dentistry. For the next hundred years, it was a basic textbook in dentistry. He managed to separate dental medicine from surgery, which has since been called odontology and set it on its own feet as an independent profession. As a result of Fauchard’s efforts, dental practice has changed for the better.

Varicella-zoster virus (VZV) belongs to the group of alpha herpesviruses, and causes two epidemiologically and clinically distinct diseases, chickenpox or varicella as the primary VZV infection, while shingles respresents the endogenous reactivation of latent VZV infection, typically occuring in older individuls and rarely in younger ones. This is a case report of a 12-year-old boy who was hospitalized at the Clinic for Infectious Diseases at the University Clinical Center Tuzla, diagnosed with meningitis from February 20, 2023, to March 7, 2023. Cerebrospinal fluid analysis upon admission showed moderate pleocytosis with mild proteinorrhoea and hypoglycorrhoea. Cerebrospinal fluid was also subjected to microbiological analysis, which returned a positive PCR result for varicella-zoster virus. Laboratory findings showed stable parameters of inflammation throughout the hospitalization. Parenteral antiviral therapy (acyclovir ampoules) was initiated upon admission and continued for 14 days. Follow-up cerebrospinal fluid analysis showed significant improvement. The boy was discharged home in a recovered state with recommendations for follow-up tests and examinations. Varicella-zoster meningitis is a rare but serious and potentially life-threatening complication following primary infection with the varicella-zoster virus, particularly in immunocompromised patients with symptoms of CNS involvement.

Abstract 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.

This study investigates the use of neural network and their ability to predict disease progression based on clinical data and biomarkers. Using deep neural networks, a model was developed that efficiently analyzes the complex relationship between various factors and predict the probability of disease. The model was validated using retrospective analysis which indicated a good predictive ability that could be further utilized in better diagnostics and personalized treatment methods. More importantly, reserch detected specific pattern in the data, which enabled a more accurate prediction of disease at different stages. The study tried to improve a model by fine-tuned neural networks and tested other frameworks to gain the highets precision. This research also provides a basic for future work in directing the development of personalized therapeutic approaches based on individual patient characteristics.

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.

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.

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.

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

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.