One of the questions human-robot interaction (HRI) research needs to address prior to in-home robot deployment is when optimal moments for everyday interaction might occur. These can vary based on robot users' existing routines and personal preferences. As part of a larger project to design a conversational robot that can assist older adults in recognizing and maintaining their ikigai (sense of meaning and purpose in life), we explored the question "when might be good times for the robot to engage older adults in activities?". 11 older adults who were familiar with our prototype robot from prior participation in our research took part in a two week-long "diary study" to identify their habits and preferred times of engagement with the robot. The diary was performed by sending text messages to the older adults twice daily, asking what they were doing at the moment and whether this was a suitable time for interacting with the robot. The findings of the study allowed us to determine optimal times for interaction with the robot' - commonly before and after lunch and before sleep. Insights from this approach contribute to designing robots that can be integrated into the daily lives of older adults.

We explore the integration of a visual and thermal camera to approximate physiological changes as markers of cognitive load and child's engagement with a robot. The aim of our data pipeline is to enable non-invasive engagement tracking for a desktop social robot developed by Honda Research Institute named Haru. From utilizing these two cameras we can recognize engagement during child-robot interactions (CRI) using changes in nose-tip temperature. We tested our algorithm on data collected while a child participant interacted with Haru during a passive activity as well as an active activity. Then, we did a preliminary modeling of engagement with Hidden Markov models. This paper describes our experimental setup, our data collection, multi-modal pipeline, and some preliminary results from modeling the data.

Social robots are being studied for a wide variety of user populations, such as older adults, but programming these social robots typically requires deep technical knowledge. In this study, we developed a no-code end-user robot programming interface, with the goal of our interface being to empower individuals with no programming background to easily create social robot interactions with older adults using natural language. We evaluated five individuals with connections to adults older than 65 without robot programming experience. They were tasked with designing a simple conversation with the robot. We recorded their experiences using a survey and found that participants successfully used the interface to make the robot communicate with older adults. Overall, the participants found the interface easy to use and enjoyed the process. Thus, we provide recommendations on how to improve no-code end-user robot programming interfaces further.

A new design approach to discrete time sliding-mode-based controllers with disturbance compensation is proposed in this paper. The approach is applicable for linear time invariant plants with matched disturbances. Starting from the known methods for disturbance estimation (i) using discrete time nominal plant model and (ii) using original sliding mode control design method, full integration of those two algorithms into single one is proposed. Besides, the proposed algorithm can be additionally simplified for a small sampling time. The simplified algorithm does not directly depend on the equivalent control but only on the present and previous values of the sliding variable and previous value of the control. The obtained results are compared with the corresponding system with disturbance estimator based on sliding variable measurement. It is established that both methods give identical results in the nominal case. The method is illustrated in a positional servo system design. Comparative analysis of different methods is done by computer simulation.

Background Melanoma, a worldwide widespread skin cancer with over 325,000 yearly incidences, demands a thorough understanding of its molecular components to create effective therapeutics. This study looks at the PRAME (cutaneous melanoma-associated antigen) and BAP1 (gene controlling gene-environment interactions) proteins, which are important in melanoma development and are important for understanding the molecular landscape of melanoma. Introduction While playing a crucial role in melanoma, the structural and functional characteristics of PRAME and BAP1 remain unidentified. This work tries to unravel their complexities by investigating conserved residues, sequence invariance, and other molecular characteristics that contribute to their importance in melanoma. Promising therapeutic targets for melanoma therapy are identified by analyzing these proteins at the molecular level. Methods The study makes extensive use of bioinformatics methods to analyze PRAME and BAP1, including sequence conservation, inherent disorder, polyglutamic acid presence, and polarity alterations. Established approaches are used to investigate residue changes and their effects on protein folding, aggregation, and interactions. Results PRAME and BAP1 conserved residues highlight their critical roles in protein function and interaction. Sequence invariance indicates the possibility of functional relevance and evolutionary conservation. In intrinsically disordered proteins (IDPRs), PRAME has enhanced intrinsic disorder and flexibility, whereas BAP1 has changed disorder-promoting residue sequences. Polyglutamic acid strings are found in both proteins, emphasizing their modulatory involvement in protein interactions. Protein folding and aggregation are influenced by polarity shifts, with a balanced distribution of acidic and basic residues preserving native structures. The ratios and distributions of amino acids, particularly neutral residues, have a profound influence on interactions and gene dysregulation. Conclusion PRAME and BAP1 structural and functional understanding pave the way for diagnostic and tailored treatment options in melanoma. Differences in residue alterations, polarity distributions, and amino acid ratios provide intriguing drug design options. This research contributes to a better knowledge of melanoma-associated two proteins, opening the path for novel diagnostic and therapy techniques in skin cancer and beyond.

The decisions made by autonomous robots hold substantial influence over how humans perceive their behavior. One way to alleviate potential negative impressions of such decisions by humans and enhance human comprehension of them is through explaining. We introduce visual and textual explanations integrated into robot navigation, considering the surrounding environmental context. To gauge the effectiveness of our approach, we conducted a comprehensive user study, assessing user satisfaction across different forms of explanation representation. Our empirical findings reveal a notable discrepancy in user satisfaction, with significantly higher levels observed for explanations that adopt a multimodal format, as opposed to those relying solely on unimodal representations.

A notable advancement in fuzzy set theory is the q-rung linear diophantine fuzzy set. The soft set theory was expanded into the hypersoft set theory. By combining both the q-rung linear diophantine fuzzy set and hypersoft set, this study describes the notion of q-rung linear diophantine fuzzy hypersoft set that can handle multi sub-attributed q-rung linear diophantine fuzzy situations in the real world. Furthermore, some of its algebraic operations such as union, intersection and complement are described in this study. In addtion, the entropy measure of the q-rung linear diophantine fuzzy hypersoft set is established as it is helpful in determining the degree of fuzziness of q-rung linear diophantine fuzzy hypersoft sets. A multi-attribute decision making algorithm based on suggested entropy is presented in this study along with a numerical example of selecting a suitable wastewater treatment technology to demonstrate the effectiveness of the proposed algorithm in real-life situations. A comparative study was undertaken that describes the validity, robustness and superiority of the proposed algorithm and notions by discussing the advantages and drawbacks of existing theories and algorithms. Overall, this study describes a novel fuzzy extension that prevails over the existing ones and contributes to the real world with a valid real-life multi-attribute decision making algorithm that can cover many real-world problems that are unable to be addressed by the existing methodology.

In the paper was analysed the influence of three different container types, used for cultivation of Pinus nigra and Pinus sylvestris seedlings, on dimensions of their anatomical (resin ducts width, resin ducts number, tracheid number, tracheid width, wood rays height) and morphological (height, root collar diameter, sturdiness coefficient) elements, and on proportion of wood, bark and pith, as well. Two-factorial ANOVA showed that container type affects a lot all investigated anatomical traits by both species, but on the other side, these species varied between each other just in terms of tracheid width and wood rays height. Based on descriptive statistics, significantly lower values of all studied anatomical elements were recorded by biodegradable compared to plastic containers. As for P. nigra seedlings, they showed the best anatomical performance in Plantagrah I, while Hiko V-120 SS was the most suitable for P. sylvestris. The highest proportion of pith and bark was recorded in biodegradable container. As for morphological parameters, such as height and root collar diameter, higher values were recorded by plastic containers.

Stroke is a leading cause of death and disability worldwide, and early diagnosis and prompt medical intervention are thus crucial. Frequent monitoring of stroke patients is also essential to assess treatment efficacy and detect complications earlier. While computed tomography (CT) and magnetic resonance imaging (MRI) are commonly used for stroke diagnosis, they cannot be easily used onsite, nor for frequent monitoring purposes. To meet those requirements, an electromagnetic imaging (EMI) device, which is portable, non-invasive, and non-ionizing, has been developed. It uses a headset with an antenna array that irradiates the head with a safe low-frequency EM field and captures scattered fields to map the brain using a complementary set of physics-based and data-driven algorithms, enabling quasi-real-time detection, two-dimensional localization, and classification of strokes. This study reports clinical findings from the first time the device was used on stroke patients. The clinical results on 50 patients indicate achieving an overall accuracy of 98% in classification and 80% in two-dimensional quadrant localization. With its lightweight design and potential for use by a single para-medical staff at the point of care, the device can be used in intensive care units, emergency departments, and by paramedics for onsite diagnosis.

Solid-state physics has important applications in the development of modern technologies. Although solid-state concepts, such as electric and thermal conductivity, are included in the curricula at all educational levels, even university students have many incorrect ideas about them. The incorrect ideas identified in previous studies are mainly related to macroscopic aspects of solid-state physics. With the aim of gaining a more comprehensive insight into students’ understanding of solid-state physics, we have developed a multiple-choice concept inventory on microscopic models of electric and thermal conductivity of solids (METCS). The inventory has been field-tested with a sample consisting of 233 first-year medical faculty and engineering students from the University of Rijeka (Croatia). METCS proved to have good psychometric features and it helped to uncover many incorrect ideas that have not been reported in the earlier physics education literature. The findings from this study could be a good starting point for the development of evidence-based, university-level tutorials on microscopic models of electric and thermal conductivity.

As the geopolitical situation changes, it is necessary to discuss how politics is structured by metaphor in the context of recent social phenomena, such as the European migrant crisis. This paper analyses the conceptual metaphors politics as war, politics as a game, politics as a trade, and politics as a theater in British and Bosnian-Herzegovinian newspapers. The goal of this study is to establish to what extent and in which situations journalists resort to figurative language to persuade the recipients to view politics in a desired way. The paper aims to reflect on the use of deliberate metaphor as a perspective-changing device by journalists striving to achieve their rhetorical goals and influence recipients’ perception of the political situation. The corpus comprises 174 British and 307 Bosnian-Herzegovinian articles collected from August 2015 to March 2016 (247,912 words). Relying on Steen et al.’s (2010) model of metaphor analysis, the paper investigates the types of metaphor in the corpus, the deliberate use of politics metaphors and their communicative function in migration discourse - discussing both the rhetorical goals of journalists and the rhetorical effects on recipients. It has been established that the analyzed set of metaphors has a divertive and persuasive function in migration discourse. Similar studies are encouraged to shed light on how deliberate metaphors related to politics may have diverging communicative functions in other types of discourse.

We present a new approach to high intraabdominal testis (IAT) for elongation of the testicular vessels without division. The technique entails fixation of the testis to a point one inch above and medial to the contralateral anterior superior iliac spine for 12 weeks. Subdartos orchiopexy is then done as the second stage. Both stages are laparoscopically assisted. The a new approach to high intraabdominal testis, two-stage laparoscopic traction-orchiopexy, is useful and resulted in significant elongation of the testicular vessels without atrophy. It is a safe and valid alternative to the two-stage laparoscopic Fowler–Stephens technique, which entails division of the main testicular vessels.

ABSTRACT Background This paper compares the most recent data on the incidence and prevalence of kidney replacement therapy (KRT), kidney transplantation rates, and mortality on KRT from Europe to those from the United States (US), including comparisons of treatment modalities (haemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KTx)). Methods Data were derived from the annual reports of the European Renal Association (ERA) Registry and the United States Renal Data System (USRDS). The European data include information from national and regional renal registries providing the ERA Registry with individual patient data. Additional analyses were performed to present results for all participating European countries together. Results In 2021, the KRT incidence in the US (409.7 per million population (pmp)) was almost 3-fold higher than in Europe (144.4 pmp). Despite the substantial difference in KRT incidence, approximately the same proportion of patients initiated HD (Europe: 82%, US: 84%), PD (14%; 13%, respectively), or underwent pre-emptive KTx (4%; 3%, respectively). The KRT prevalence in the US (2436.1 pmp) was 2-fold higher than in Europe (1187.8 pmp). Within Europe, approximately half of all prevalent patients were living with a functioning graft (47%), while in the US, this was one third (32%). The number of kidney transplantations performed was almost twice as high in the US (77.0 pmp) compared to Europe (41.6 pmp). The mortality of patients receiving KRT was 1.6-fold higher in the US (157.3 per 1000 patient years) compared to Europe (98.7 per 1000 patient years). Conclusions The US had a much higher KRT incidence, prevalence, and mortality compared to Europe, and despite a higher kidney transplantation rate, a lower proportion of prevalent patients with a functioning graft.

With the increasing need for efficient traffic surveillance systems, computer vision emerges as a promising technology to address various challenges in this domain. This paper aims to provide an overview of recent advancements in the application of computer vision in traffic surveillance. It commences by discussing fundamental concepts of computer vision and its role in traffic monitoring, followed by an exploration of various techniques and algorithms used in computer vision systems, including object detection, tracking, and classification. Furthermore, it investigates the integration of computer vision with other technologies such as machine learning and deep learning, emphasizing their impact on enhancing the accuracy and efficiency of traffic surveillance systems. The review explores specific applications of computer vision in traffic surveillance, such as traffic flow monitoring, anomaly detection, and license plate recognition. Additionally, it addresses challenges and limitations associated with the implementation of computer vision in real-world traffic scenarios. Synthesizing existing literature, case studies, and research findings, this review offers a comprehensive insight into the current state-of-the-art in the application of computer vision for traffic surveillance systems. The paper concludes with a discussion of future directions and potential research opportunities in this rapidly evolving field.