Search Results (735)

This pilot study investigated how viewers perceive Monica Geller’s personality using three evidence-based personality models: Big Five, HEXACO, and Cloninger’s Biopsychosocial Model. Additionally, it examined how these perceptions are associated to audiences’ engagement in parasocial relationships with this iconic character from the sitcom Friends. A sample of sixty-three participants assessed Monica’s personality by responding to the Big Five Inventory (BFI), the HEXACO-60, and the Temperament and Character Inventory (TCI-60). Participants also completed the Multidimensional Measure of Parasocial Relationships (MMPR). Personality scores were contextualized against U.S. population norms (N_BFI = 711, N_HEXACO = 1126, N_TCI = 1948) and Pearson correlations were conducted to explore associations between personality traits and the Affective, Behavioral, Cognitive, and Decisional dimensions of parasocial engagement. Normative comparisons revealed Monica’s perceived Openness and Agreeableness in the Big Five and her Openness and Agreeableness in the HEXACO as significantly below average, while her Big Five Neuroticism and her HEXACO Conscientiousness were significantly above average. In the Biopsychosocial Model, Monica’s Persistence was significantly higher than population norms, while Cooperativeness was significantly lower. Big Five Agreeableness showed correlations across all parasocial engagement dimensions. HEXACO Emotionality was strongly linked to the Affective and Behavioral dimensions, while Honesty–Humility was associated with Cognitive parasocial engagement. In the Biopsychosocial Model, Reward Dependence and Cooperativeness were associated with Cognitive and Affective parasocial engagement, while Self-Directedness was linked to the Behavioral dimension. The Biopsychosocial Model offered the most comprehensive insights, capturing the multidimensional nature of viewer–character engagement. The Big Five and HEXACO models added valuable perspectives, particularly in explaining that traits associated with trust and kindness are linked to decision making. These findings emphasize the importance of integrating multiple personality frameworks to advance the understanding of parasocial relationship engagement, shedding light on the nuanced ways personality traits shape audience perceptions and relationships with media characters, with significant implications for media psychology and personality research. Limitations and avenues for future developments are discussed, building on the insights from this pilot study. Full article

Sequential decision-making in dynamic and interconnected environments is a cornerstone of numerous applications, ranging from communication networks and finance to distributed blockchain systems and IoT frameworks. The multi-armed bandit (MAB) problem is a fundamental model in this domain that traditionally assumes independent and identically distributed (iid) rewards, which limits its effectiveness in capturing the inherent dependencies and state dynamics present in some real-world scenarios. In this paper, we lay a theoretical framework for a modified MAB model in which each arm’s reward is generated by a hidden Markov process. In our model, each arm undergoes Markov state transitions independent of play in a way that results in varying reward distributions and heightened uncertainty in reward observations. The number of states for each arm can be up to three states. A key challenge arises from the fact that the underlying states governing each arm’s rewards remain hidden at the time of selection. To address this, we adapt traditional index-based policies and develop a modified index approach tailored to accommodate Markovian transitions and enhance selection efficiency for our model. Our proposed proposed Markovian Upper Confidence Bound (MC-UCB) policy achieves logarithmic regret. Comparative analysis with the classical UCB algorithm reveals that MC-UCB consistently achieves approximately a 15% reduction in cumulative regret. This work provides significant theoretical insights and lays a robust foundation for future research aimed at optimizing decision-making processes in complex, networked systems with hidden state dependencies. Full article

Using a pre-post design, this study investigated an educational sustainability initiative’s impact on ethical decision-making, science motivation, and classroom environment perceptions among 60 pre-service teachers at Sakhnin College in northern Israel. Data were collected through self-report questionnaires and analyzed with multivariate analysis of covariance (MANCOVA), structural equation modeling (SEM), and hierarchical linear modeling (HLM). The results indicated significant improvements in ethical decision-making skills, moderated by baseline moral reasoning. Motivation to learn science also increased, influenced by perceived content relevance and intrinsic motivation, with socioeconomic status and teaching experience acting as moderators. A three-way interaction of gender, religiosity, and collaborative group work involvement predicted improvements in the classroom atmosphere. These findings suggest that sustainability education enhances ethical reasoning, motivation, and classroom dynamics, with demographic factors playing important roles. The study highlights the value of collaborative learning environments in teacher education and the relevance of sustainability topics in fostering critical thinking about ethical issues. It demonstrates how sustainability can inspire teachers to embed values of responsibility and cooperation into their practice, enhancing the quality of the educational environment and encouraging a broader commitment to sustainability within the educational system. These findings highlight the value of sustainability education in enhancing pre-service teachers’ ethical reasoning, motivation, and classroom dynamics, offering insights for teacher-education programs to foster responsibility and cooperation among future educators. Full article

Recent legislation in Texas changes the legal civic engagement landscape. With Diversity, Equity, and Inclusion programs now prohibited on public university campuses, advocates of affirmative steps to reach historically underserved groups may face unexpected obstacles. And recent Supreme Court decisions, on the use of race as a factor in college admissions, further increase the challenges. Due to these shifts in the goals public universities can legally pursue, what are the most appropriate civic engagement policy steps to eliminate barriers to success and realize a diverse student body? Building on the Town Hall program at Tarleton State University, and the specific ways in which it leverages trust, we make three recommendations: (1) Institutions should maintain an openness to outreach, through the leadership of student groups and invited guest speakers and other initiatives, to those on campus who struggle with the burden of invisibility; (2) Town Hall and related civic engagement programs should fine-tune the selection of advanced peer leaders, making it easier for them to pursue expertise in the classroom, in turn facilitating their ability to attract speakers as recommended in (1); and (3) institutions should ensure an opening for representatives to travel to underserved parts of the state, with the effect if not University-wide intention of increasing inclusion. Building on the research of Eric Morrow, Boleslaw Z. Kabala, and Christine Hartness in 2023, we seek to leverage trust for the sake of a genuinely inclusive environment, consistent with current legal limitations on civic engagement in Texas. Full article

Communication for development and social change is an evolving field both in research and practice, transcending paradigms of conventional communication towards engaging and somewhat exposing some of the real-life communicative disorders experienced by communities. While public health and communication for development and social change operate from diverse paradigmatic thinking and are applied quite independently as disciplinary fields of study, health communication converges these fields in research and practice. In this paper, I discuss these interdisciplinary perspectives that draw from communication for development and social change principles and public health through a process of divergence and convergence towards new ways of thinking about decision making. Much of this discourse stems from understanding many health problems as a development problem first, one that recognises the role of community responses during pandemics yet at the same time places the agency back with individuals to make informed choices. Communicating for health decision making from this perspective is what I call Communicating for Health-as-Development (C4HD). C4HD foregrounds health as development, which caters to the messy, unidirectional, non-process-orientated, non-measurable and often non-data-driven approaches to health outcomes. It is in these messy health communication efforts that real development takes place. This paper, using examples from HIV and COVID-19, discusses these ongoing developments in the field and the convergence of public health and communication for development and social change from an interdisciplinary perspective, by exploring three key concepts: community engagement to influence decision making, community agency and ownership, and context and collaboration, which contribute to understanding communication for health-as-development. Full article

At the end of the past century, the introduction of Total Mesorectal Excision (TME), preceded by either short-course radiotherapy (SCRT) or chemoradiation (CRT), established the new standard of care for locally advanced rectal cancer (LARC). Recently, significant advancements were achieved for both dMMR/MSI and pMMR/MSS LARC patients. For the 2–3% of dMMR/MSI LARCs, ablative immunotherapy emerged as a curative approach, offering the possibility of avoiding chemotherapy (CT), radiotherapy, and surgery altogether. In pMMR/MSS LARCs, the intensification of preoperative treatments with Total Neoadjuvant Treatment (TNT) afforded three outcomes: (a) a reduction of distant metastases, positively impacting on survival endpoints, (b) a significant increase of complete clinical response (cCR) rate, paving the way for non-operative management (NOM), and (c) the selective omission of radiotherapy following induction CT. The choice of the most appropriate therapeutic strategy can only be made through the shared decision-making process between physician and patient based on risk stratification and patient preferences. Full article

Remote assistance for highly automated vehicles (HAVs), i.e., third-party assistance from support staff outside the vehicle in times of the need for assistance, presents a solution to extend the capabilities of HAVs by integrating a third party for decision making in uncertain situations. Similar to other control center positions, we expect the remote assistance tasks to exert high mental demands on the human operators. Therefore, we assessed impact of elevated mental workload during HAV remote assistance in a controlled environment in a user study (N = 37) with the goal of identifying cues to differentiate workload levels based on eye-tracking-related, skin conductance, and cardiovascular indicators. The results provide evidence that (A) elevated workload induced via a secondary task depreciates performance, and (B) we can identify workload levels person-independently as differences in tonic skin conductance (F(2,72) = 24.538, p < 0.001, partial η² = 0.405) and pupil dilation (F(2,72) = 13.872, p < 0.001, partial η² = 0.278), resulting in a classification accuracy of 58% in a three-class classification task. The results provide evidence that we are able to differentiate operator workload during remote assistance in a time-resolved way with the ultimate goal to provide adaptations to counteract task deficiencies. Full article

Background: Patients undergoing hemodialysis for chronic kidney failure experience various complications and physical and emotional difficulties, leading to decreased quality of life. Self-care behaviors are essential for preventing complications and reducing mortality rates. Effective self-care behaviors significantly depend on shared decision-making, health literacy, and self-care knowledge, each critical in patient self-care performance and disease management. This study aimed to determine the importance and relevance of shared decision-making, health literacy, and self-care knowledge. In particular, it enhances self-care behaviors among hemodialysis patients. Methods: Participants were 108 adult hemodialysis patients from the hemodialysis centers of three medical institutions in Cheongju City, Korea. Moreover, the study utilized a descriptive survey research design. Data were analyzed using descriptive statistics, independent t-tests, one-way ANOVA, Pearson’s correlation coefficients, and multiple linear regression analyses. Results: The average score for self-care behaviors was 125.28 out of 175 points, with high scores for medication and vascular management. Furthermore, there were low scores for social activities and dietary management. Factors influencing self-care behaviors in hemodialysis patients were identified as sex, age, economic status, health literacy, and self-care knowledge. These factors explained 45.2% of the variance in self-care behaviors. Conclusions: To promote self-care behaviors in hemodialysis patients, it is essential to improve health literacy and self-care knowledge, strengthen tailored educational programs, and promote the explanatory role of nurses and shared decision-making. Additionally, comprehensive interventions, including economic support, are necessary. Full article

It is very well-known that the reliable coupling relationship between water area and water level is very important in analyzing the risks of floods and droughts for big lakes, such as Dongting Lake, especially when remote sensing images are absent and in situ measurements cannot be carried out. To obtain this relationship, two types of mathematical models—polynomial regression (PR) based on the least square algorithm and machine learning regression (MLR) based on the BP (Backpropagation) neural network algorithm—are constructed using the water area data extracted from multiple temporal remote sensing images and water levels recorded at several representative hydrological stations for nearly 30 years. In this study, Dongting Lake is divided into three parts: East Dongting Lake (EDL), South Dongting Lake (SDL), and West Dongting Lake (WDL). This is because water slope exists on its surface, which is formed by several inflow rivers and the high and low terrain. To calculate the total water area of this lake, two ways are put forward by choosing the water levels: from EDL, SDL, and WDL in their turn; or from all three simultaneously. In other words, three univariate and one multivariate regression. For PR, there are perfect coefficients of determination (most nearly 0.95, the smallest being 0.76), which is in line with regression test relative errors (between 0.27% and 6.7%). For MLR, which was initially applied to this problem, the best node number (10 for the first way, 8 for the second way) in the hidden layer of the neural network is adaptively chosen, with coefficients of determination (similar to PR), together with training and testing error performances (between 1% and 10%). These results confirm the validity and reliability of them. The regression and prediction results on the two models are better than the documented way (only focus on the water level of EDL). These results can provide some references for researchers and decision makers in studying similar big Lakes. Full article

The paper aims to examine the relationships between behavioural biases (such as overconfidence and herding) and the rational behaviour of Australian female consumers when making financial decisions. In doing so, the paper showcases the financial illiteracy of Australian female consumers when confronted with irregularities within the Australian financial markets. From a theoretical standpoint, the study adopts the notions of the adaptive market hypothesis (AMH) to understand the reasoning behind the relationships between behavioural biases (such as overconfidence and herding) and the rational behaviour of Australian female consumers when making decisions rationally. Using a quantitative approach, a structural equation modelling (SEM) was conducted on the proposed theoretical framework with a cleaned dataset of 357 Australian female consumers, which revealed that behavioural biases significantly influence each stage of rational decision-making when making financial decisions. More precisely, the structural equation modelling (SEM) showcases that herding behaviour has a significant positive relationship with the information search and evaluation of alternative stages when making financial decisions. However, overconfidence behaviour has a significant negative relationship with demand identification and evaluation of alternative stages when making financial decisions. Moreover, the findings also showcase that the proposed theoretical model closely fits with the data utilised, indicating that Australian female consumers do follow rational decision-making when making financial decisions. Additionally, the findings revealed that the education and income levels of Australian female consumers positively influence the stages of rational decision-making. The findings also contend that Australian female consumers have a risk-averse attitude (i.e., within three key hypothetical scenarios) towards financial decisions due to the presence of financial illiteracy. Hence, it is strongly suggested that financial institutions highlight the calculative benefits and returns from financial product purchases in advertising and promotions in a way that appeals to female consumer segments. Full article

The increasing demand for hazelnut kernels is favoring an upsurge in hazelnut cultivation worldwide, but ongoing climate change threatens this crop, affecting yield decreases and subject to uncontrolled pathogen and parasite attacks. Technical advances in precision agriculture are expected to support farmers to more efficiently control the physio-pathological status of crops. Here, we report a straightforward approach to monitoring hazelnut trees in an open field, using aerial multispectral pictures taken by drones. A dataset of 4112 images, each having 2Mpixel resolution per tree and covering RGB, Red Edge, and near-infrared frequencies, was obtained from 185 hazelnut trees located in two different orchards of the Piedmont region (northern Italy). To increase accuracy, and especially to reduce false negatives, the image of each tree was divided into nine quadrants. For each quadrant, nine different vegetation indices (VIs) were computed, and in parallel, each tree quadrant was tagged as “healthy/unhealthy” by visual inspection. Three supervised binary classification algorithms were used to build models capable of predicting the status of the tree quadrant, using the VIs as predictors. Out of the nine VIs considered, only five (GNDVI, GCI, NDREI, NRI, and GI) were good predictors, while NDVI SAVI, RECI, and TCARI were not. Using them, a model accuracy of about 65%, with 13% false negatives was reached in a way that was rather independent of the algorithms, demonstrating that some VIs allow inferring the physio-pathological condition of these trees. These achievements support the use of drone-captured images for performing a rapid, non-destructive physiological characterization of hazelnut trees. This approach offers a sustainable strategy for supporting farmers in their decision-making process during agricultural practices. Full article

Fairness in competitive games such as the Ultimatum Game is often defined theoretically. According to some of the literature, in which fairness is determined only based on resource allocation, a proposal splitting resources evenly (i.e., 5:5) is generally assumed as fair, and minimal deviation (i.e., 4:6) is considered enough to classify the proposal as unfair. Relying on multinomial processing tree models (MPTs), we investigated where the boundaries of fairness are located in the eye of responders, and pit fairness against relative and absolute gain maximization principles. The MPT models we developed and validated allowed us to separate three individual processes driving responses in the standard and Third-Party Ultimatum Game. The results show that, from the responder’s perspective, the boundaries of fairness encompass proposals splitting resources in a perfectly even way and include uneven proposals with minimal deviance (4:6 and 6:4). Moreover, the results show that, in the context of Third-Party Ultimatum Games, the responder must not be indifferent between favoring the proposer and the receiver, demonstrating a boundary condition of the developed model. If the responder is perfectly indifferent, absolute and relative gain maximization are theoretically unidentifiable. This theoretical and practical constraint limits the scope of our theory, which does not apply in the case of a perfectly indifferent decision-maker. Full article

In recent years, shared e-scooters have become increasingly popular as a mode of transportation in urban areas. Shared e-scooters have emerged as a convenient and sustainable transportation option in urban areas, providing users with a flexible and efficient way to travel short distances within a city. Many service providers and local municipalities are interested in implementing shared e-scooter operational models. However, determining which operating model to prefer and what the service areas will be is a significant problem. We aimed to solve the implementation of three different operational models, the site selection problem of station locations, and service areas for Erzurum, the metropolitan city in this study. As shared e-scooter is quite a new transportation mode; information collected to assess the operational models’ sustainability performance may be indeterminate and vague. In this study, the Geographic Information System (GIS)-based hybrid multi-criteria decision-making (MCDM) method is proposed for the solution of implementation, site selection, and service areas problems of three different shared e-scooter operational models. To this end, a four-step scientific and strategic solution approach is developed: (i) the identification and detailed explanation of 5 main and 24 sub-criteria, (ii) the weighting of criteria through the Analytical Hierarchical Process (AHP), Multi-Influencing Factor (MIF), and Best–Worst Method (BWM) in order to increase the sensitivity and robustness of the study, (iii) obtaining a suitability map for the solution of implementation, site selection, and service areas problems of operational models, and (iv) assigning shared e-scooter stations and analyzing their performance levels with COmplex PRoportional ASsessment (COPRAS). The results show that, in Erzurum, the central three districts are the most suitable for service areas. The paper’s solution methodology can help service providers and policymakers invest in sustainable shared e-scooter operational models, even in situations of high uncertainty. Full article

Rationale: Orthodontic archwires undergo chemical and structural changes in the complex intraoral environment. The present work aims to investigate the safe duration for intraoral use (related to the nickel release hypothesis) of different types of nickel-containing wires. By analyzing how the nickel content (NC) varies over time, we aim to provide practical recommendations for the optimal use of said archwires. Materials and Methods: Our analysis focuses on the following nickel-containing archwires: stainless steel, Ni-Ti superelastic, heat-activated NiTi and CuNiTi, and multi-force archwires. The studied archwires of each type were divided into three groups: group 1, as received; group 2, retrieved after intraoral exposure for less than 6 weeks; group 3, used for more than 8 weeks. To assess NC, measurements using scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), and laser-induced breakdown spectroscopy (LIBS) were performed in multiple regions of each wire. Statistical analysis of the measured values using one-way ANOVA and multiple group comparisons showed significant differences in nickel content between groups. The dynamic behavior of the statistical results for NC was then modeled using logistic regression and fitted with cubic splines. Conclusions: The proposed behavior model, with further refinement, could enable orthodontists to make informed, patient-specific decisions regarding the safe and effective use of orthodontic floss. The overall conclusion of the study is that due to stability, SS-CrNi, HA-Ni-Ti with Cu, and TriTanium^TM are suitable for long-term use, and due to higher nickel release, Ni-Ti-Superelastic, HA-Ni-Ti without Cu, and Bio-Active^TM are better for short- to medium-term use. Full article

The latest changes on the distribution network due to the presence of distributed energy resources (DERs) and electric vehicles make it necessary to monitor the grid using a real-time high-precision system. The present work centers on the development of an open-source software platform that allows for the joint management of, at least, power quality monitors (PQMs), phasor measurement units (PMUs), and smart meters (SMs), which are three of the most widespread devices on distribution networks. This framework could work remotely while allowing access to the measurements in a comfortable way for grid analysis, prediction, or control tasks. The platform must meet the requirements of synchronism and scalability needed when working with electrical monitoring devices while considering the large volumes of data that these devices generate. The framework has been experimentally validated in laboratory and field tests in two photovoltaic plants. Moreover, real-time Artificial Intelligence capabilities have been validated by implementing three Machine Learning classifiers (Neural Network, Decision Tree, and Random Forest) to distinguish between three different loads in real time. Full article