This paper introduces a pioneering approach to robot environment representation by integrating a novel hypergraph-based method for modeling fuzzy signatures with a quadtree-like structure for obstacle detection. By structuring fuzzy signatures through hypergraphs, we establish a robust framework that not only streamlines information representation but also simplifies the aggregation-based decision-making process. This synergy is applied to the domain of mobile robotics, where accurate and efficient environment representation is essential. Utilizing a quadtree-like structure for data organization, our technique systematically evaluates feature points against a set of fuzzy operations, determining the significance of obstacles and reconstructing the environmental model through the traversal of the quadtree-like structure. Furthermore, the hypergraph-based formalism sets the stage for a future transition to a tensor-based representation of fuzzy signatures, as envisioned in future work.
This paper tackles the challenge of achieving Input-to-state stable (ISS) synchronization in actuator-saturated sampled-data control (SDC) networks for Markovian jump (MJ) Lur'e networks. We investigate the impacts of actuator saturation on system performance and stability, proposing a control strategy that ensures synchronization in the presence of external disturbances. Our analysis employs a Wirtinger-based integral inequality alongside a modified free matrix-based integral inequality (MFMBII), providing a framework for examining Lur'e networks. Initially, we create an MFMBII that combines the dynamics of MJ Lur'e networks and takes into consideration time-varying delays. Second, we formulate two sufficient conditions for the SDC design that ensure mean-square ISS error of specification for the hybrid closed-loop system. We do this by combining the MFMBII method with the Lyapunov-Krasovskii functional (LKF). Through a systematic methodology, we demonstrate that the proposed method maintains bounded state responses and converges to a common trajectory at an exponential rate. The results highlight the effectiveness of integrating ISS with SDC in managing complex dynamical networks. Finally, the proposed ISS method is validated through a numerical example, confirming its efficacy.
OBJECTIVE:Caregiving for individuals with disabilities significantly affects caregivers' physical, emotional and social well-being. This study investigates whether caregiver burden differs between caregivers of individuals with physical versus mental/psychological disabilities, considering disability severity and further evaluates the impact of general psychological symptom levels and separation anxiety on caregiver burden. METHODS:The study included 121 volunteer participants aged 18 and above, who provided care to individuals with a disability level of 40% or higher, either physical or mental/psychological. Data collection involved a sociodemographic and clinical data form, the Depression, Anxiety and Stress Scale-Short Form (DASS-21), the Zarit Burden Care Scale (ZBCS) and the Adult Separation Anxiety Questionnaire (ASA). Statistical analyses were conducted using independent sample t-test and hierarchical linear regression analysis. RESULTS:Caregivers of physically disabled individuals reported significantly higher depression, stress and separation anxiety scores than those caring for mentally/psychologically disabled individuals (p < 0.05). Higher disability severity (≥ 80%) was associated with greater psychological symptoms and caregiver burden (p < 0.05). Regression analysis showed that general psychological symptoms predicted higher burden, while separation anxiety predicted lower burden (p < 0.05). CONCLUSIONS:Caregiver burden is influenced not only by disability type and severity but also by psychological factors of the caregiver, such as general symptom levels and separation anxiety. The findings emphasise the importance of addressing caregivers' emotional needs through targeted psychosocial interventions. Incorporating caregiver-focused support into health and social care policies may help reduce burden, improve psychological well-being and ultimately strengthen the quality of care provided.
Contemporary rehabilitation is evolving dynamically in response to changing social and penitentiary realities. It has shifted from a punitive, isolation-based model toward a supportive approach focused on reintegration, personal development, and strengthening social competences. Modern practices emphasize educational, psychological, and vocational interventions, addressing not only long-term inmates but also those in temporary detention. Despite progress in the Polish system, challenges such as social exclusion and limited post-release support remain. The article highlights the role of rehabilitation—especially work—in preventing recidivism and outlines recommendations to improve its effectiveness in current social conditions.
OBJECTIVES:The study aimed to investigate the determinants of problematic social media use (PSMU) among Polish adolescents by accounting for time spent on social media, sociodemographic characteristics, individual resources, social environment, and health factors, and to compare the findings with previous research. MATERIAL AND METHODS:A cross-sectional, anonymous, online survey was conducted in 2024. The study was performed among adolescents in the Lubuskie Voivodeship, Poland and included 9073 students aged 12-19 years (mean [M] ± standard deviation [SD] 15.16±1.56 years). Problematic social media use was assessed using the 9-item Social Media Disorder Scale (SMDS). Independent variables included sociodemographic characteristics, time spent on social media, health literacy, future orientation, school achievements, subjective health complaints, well-being, school stress, parent and peer relations, and school climate, measured with validated instruments derived mainly from the Health Behaviour in School-aged Children (HBSC) survey protocol and the KIDSCREEN-27 questionnaire. RESULTS:Problematic social media use was identified in 12.7% of participants. Higher PSMU was observed among younger adolescents. The strongest predictor was the time spent on social media >5 h/day. Poorer health and well-being - including multiple psychosomatic complaints, lower well-being, and higher school stress - were strongly associated with PSMU. Lower future orientation, low health literacy, and poorer relationships with parents increased the likelihood of PSMU, whereas older age, higher future orientation, and supportive parent relationships decreased. CONCLUSIONS:Multiple factors influenced PSMU among adolescents, although the overall model fit remained modest. Boys were more likely to experience PSMU, representing a novel observation. Higher future orientation, supportive relationships with parents, and older age were key protective factors. A non-linear relationship was found between PSMU and peer support as well as school climate. Int J Occup Med Environ Health. 2026;39(3):313-32.
