Hasil untuk "Special situations and conditions"

Gulay Aras Bayram, Gizem Ergezen Sahin, Gizem Yilmaz et al.

Abstract Background With the advancement of technology, it is considered an important step to transfer assessment methods to the virtual environment as it provides individuals with the opportunity for equal feedback, improves test performance and allows for testing with maximum participation. The aim of this study was to evaluate the effects and differences between the classic Wingate Anaerobic Test (WAnT) and a virtual reality-based Wingate Test (VR-WAnT) on the test performance of athletes and to investigate their applicability to athletes. Methods Thirty male athletes aged between 18 and 25 years from professional football teams were included in the study. The athletes’ age, height, weight, total years of sport experience, scores on the system usability scale and satisfaction with the two different testing methods were assessed. A scenario covering all phases of the WAnT and requiring no external cues was prepared by the project team and integrated into the virtual reality headset. Athletes were first assessed using the classic WAnT in a controlled laboratory environment, and two days later the same athletes were assessed using the VR-WAnT in the same environment. Maximum power, minimum power, average power and fatigue index data from the test system were recorded for analysis. Results The results of the study showed no statistically significant differences in maximum power, minimum power, average power and fatigue index values between the two methods (p > 0.05). However, according to the satisfaction measurement, the results of the VR-WAnT were statistically significantly higher compared to the classic WAnT (p = 0.026). Conclusions VR-WAnT may be considered a promising alternative for anaerobic performance testing due to its potential to enhance user experience and satisfaction. It is also believed that the test may offer greater comfort for both practitioner and athletes, while introducing a novel dimension to physiotherapy and rehabilitation assessment processes. Trial registration NCT06661395 (Registration Date: 24 Oct 2024).

Abdul Majid, Farhana Rafiq, Tufail Shafi et al.

Francisca Ogochukwu Onukansi, Collins Chibueze Anokwuru, Stanley Chinedu Eneh et al.

Abstract Traditional medicine (TM) has been a cornerstone of healthcare across various cultures, especially in Africa, where it has played an integral role in the management of diseases such as malaria. Despite the popularity and historical significance of TM, scientific validation remains a key challenge, hindering its widespread acceptance in modern healthcare systems. This study explores the potential of traditional African medicine, particularly in the context of Nigeria, as a vital resource in the fight against malaria. Drawing on the success of plants like Artemisia annua in the development of modern anti-malarial drugs, the research emphasizes the need for comprehensive investment in TM research. With Nigeria facing the highest malaria burden globally, the research advocates for increased funding, scientific investigations into the efficacy of traditional remedies, and enhanced regulation of herbal medicine. The paper also highlights the growing trust and reliance on herbal remedies in rural areas of Nigeria and the importance of ensuring their safety through pharmacological testing. This study examines these issues through an analysis of existing literature, historical applications, and documented successes of herbal treatments. By integrating traditional medicine into national health systems, Nigeria could unlock new strategies for combating malaria and other infectious diseases, advancing toward sustainable health outcomes.

Tim Puphal, Vipul Ramtekkar, Kenji Nishimiya

Improving automated vehicle software requires driving data rich in valuable road user interactions. In this paper, we propose a risk-based filtering approach that helps identify such valuable driving situations from large datasets. Specifically, we use a probabilistic risk model to detect high-risk situations. Our method stands out by considering a) first-order situations (where one vehicle directly influences another and induces risk) and b) second-order situations (where influence propagates through an intermediary vehicle). In experiments, we show that our approach effectively selects valuable driving situations in the Waymo Open Motion Dataset. Compared to the two baseline interaction metrics of Kalman difficulty and Tracks-To-Predict (TTP), our filtering approach identifies complex and complementary situations, enriching the quality in automated vehicle testing. The risk data is made open-source: https://github.com/HRI-EU/RiskBasedFiltering.

Tsvetomila Mihaylova, Stefan Reitmann, Elin A. Topp et al.

Simulation of conflict situations for autonomous driving research is crucial for understanding and managing interactions between Automated Vehicles (AVs) and human drivers. This paper presents a set of exemplary conflict scenarios in CARLA that arise in shared autonomy settings, where both AVs and human drivers must navigate complex traffic environments. We explore various conflict situations, focusing on the impact of driver behavior and decision-making processes on overall traffic safety and efficiency. We build a simple extendable toolkit for situation awareness research, in which the implemented conflicts can be demonstrated.

Løseth Sissel, Nebuchennykh Maria, Brokstad Ruth Therese et al.

We aimed to investigate to what extent small fiber tests were abnormal in an unselected retrospective patient material with symptoms suggesting that small fiber neuropathy (SFN) could be present, and to evaluate possible gender differences.

Eri Otaka, Aiko Osawa, Kenji Kato et al.

Abstract BackgroundInterventions and care that can evoke positive emotions and reduce apathy or agitation are important for people with dementia. In recent years, socially assistive robots used for better dementia care have been found to be feasible. However, the immediate responses of people with dementia when they are given multiple sensory modalities from socially assistive robots have not yet been sufficiently elucidated. ObjectiveThis study aimed to quantitatively examine the immediate emotional responses of people with dementia to stimuli presented by socially assistive robots using facial expression analysis in order to determine whether they elicited positive emotions. MethodsThis pilot study adopted a single-arm interventional design. Socially assistive robots were presented to nursing home residents in a three-step procedure: (1) the robot was placed in front of participants (visual stimulus), (2) the robot was manipulated to produce sound (visual and auditory stimuli), and (3) participants held the robot in their hands (visual, auditory, and tactile stimuli). Expression intensity values for “happy,” “sad,” “angry,” “surprised,” “scared,” and “disgusted” were calculated continuously using facial expression analysis with FaceReader ResultsA total of 29 participants (mean age 88.7, SD 6.2 years; n=27 female; Japanese version of Mini-Mental State Examination mean score 18.2, SD 5.1) were recruited. The expression intensity value for “happy” was the largest in both the subjective and objective assessments and increased significantly when all sensory modalities (visual, auditory, and tactile) were presented (median expression intensity 0.21, IQR 0.09-0.35) compared to the other 2 patterns (visual alone: median expression intensity 0.10, IQR 0.03-0.22; PP ConclusionsBy quantifying the emotional responses of people with dementia, this study highlighted that socially assistive robots may be more effective in eliciting positive emotions when multiple sensory stimuli, including tactile stimuli, are involved. More studies, including randomized controlled trials, are required to further explore the effectiveness of using socially assistive robots in dementia care.

Samuel Gibbon, Audrey Low, Charlene Hamid et al.

Abstract INTRODUCTION We tested associations between two retinal measures (optic disc pallor, peripapillary retinal nerve fiber layer [pRNFL] thickness) and four magnetic resonance imaging markers of cerebral small vessel disease (SVD; lacunes, microbleeds, white matter hyperintensities, and enlarged perivascular spaces [ePVSs]). METHODS We used PallorMetrics to quantify optic disc pallor from fundus photographs, and pRNFL thickness from optical coherence tomography scans. Linear and logistic regression assessed relationships between retinal measures and SVD markers. Participants (N = 108, mean age 51.6) were from the PREVENT Dementia study. RESULTS Global optic disc pallor was linked to ePVSs in the basal ganglia in both left (β = 0.12, standard error [SE] = 0.05, P < 0.05) and right eyes (β = 0.13, SE = 0.05, P < 0.05). Associations were also noted in different disc sectors. No pRNFL associations with SVD markers were found. DISCUSSION Optic disc pallor correlated with ePVSs in the basal ganglia, suggesting retinal examination may be a useful method to study brain health changes related to SVD. Highlights Optic disc pallor is linked to enlarged perivascular spaces in basal ganglia. There is no association between peripapillary retinal nerve fiber layer thickness and cerebral small vessel disease markers. Optic disc examination could provide insights into brain health. The sample included 108 midlife adults from the PREVENT Dementia study.

Jadhav Abhijeet Vasant, H Bhakare Shilpa

Introduction: Multiple layers of vulnerability pose challenges for rural elderly to access health. Enrollment in government schemes is also limited by this section of society. This study focused on access to medicines and status welfare schemes for rural elderly. Subjects and Methods: It was a cross-sectional survey done in 84 villages in six districts of Rajasthan with 1266 elderly participants. The data were captured through a pretested questionnaire which was filled by trained data collectors. Results: The knowledge, as well as the actual enrollment of the elderly in various health care and welfare schemes, was very poor. Gender and caste analysis showed that women and lower castes were at the worst end in the enrollment and availing entitlements. Knowledge of health schemes was also less among them. The monthly average expenditure for participants on regular medication was Rs. 1570.35 and the time to procure the same was 6.10 h. Discussion: The elderly are vulnerable to the worst health outcomes and gender and cast categories add to it. Access to medicines is an essential component of health accessibility. However, it is largely neglected. Money and time in accessing required medicines seem to be too high to afford for these elderly people. Limited availability of public health facilities, poverty in old age, and the absence of private pharmacies in villages have contributed to the problem significantly. Welfare schemes have the potential to address these issues; however, enrollment and actual reach of benefits still need to be improved in rural areas.

Lino, Matheus Henrique dos Santos

Objetivos: analisar as dificuldades enfrentadas pelas pessoas idosas em relação à condução veicular, bem como avaliar a importância que atribuem a essa atividade. Métodos: estudo transversal quantitativo avaliou 61 pessoas idosas motoristas utilizando dois questionários desenvolvidos pelos pesquisadores: 1) dados sociodemográficos, 2) questões relacionadas às dificuldades e à importância da condução para pessoas idosas. Resultados: a maioria dos participantes relatou apenas acidentes leves e não teve problemas significativos com condições climáticas, horários de direção ou estado das estradas. Os participantes usavam o carro para atividades diárias e lazer, dirigindo em média cerca de duas horas por dia. A prática de dirigir é vista como crucial para manter a autonomia e a conexão com a família, e a ideia de parar de dirigir é considerada um grande desafio. Conclusão: a capacidade de dirigir é vital para o bem-estar emocional e a qualidade de vida das pessoas idosas, mas o estudo também destaca os riscos associados à condução nessa idade, como a presença em acidentes leves durante a condução veicular. Portanto, é fundamental encontrar um equilíbrio entre manter a independência das pessoas idosas e garantir a segurança no trânsito

Katarzyna Stawarz, Ian Ju Liang, Lyndsay Alexander et al.

BackgroundOlder adults are at increased risk of falls, injury, and hospitalization. Maintaining or increasing participation in physical activity during older age can prevent some of the age-related declines in physical functioning that contribute to loss of independence and low reported quality of life. Exercise snacking may overcome some commonly cited barriers to exercise and encourage older adults to engage in muscle strength and balance activity, but the best way to deliver and support this novel format remains unknown. ObjectiveOur aim was to explore how the novel exercise snacking approach, that is, incorporating short bouts of strength and balance activities into everyday routines, could be supported by technology within a home setting and what types of technologies would be acceptable for older adults who are prefrail. MethodsFollowing a user-centered design process, 2 design workshops (study 1) were conducted first to understand older adults’ (n=11; aged 69-89 years) attitudes toward technology aimed at supporting exercise snacking at home and to inform the design of 2 prototypes. Next, based on the findings of study 1, an exploratory pilot study (study 2) was conducted over 1 day with 2 prototypes (n=5; aged 69-80 years) at the participants’ homes. Participants were interviewed over the telephone afterward about their experience. Transcripts were analyzed using framework analysis. ResultsThe results showed that the participants were positive toward using technology at home to support exercise snacking, but both exercises and technology would need to be simple and match the participants’ everyday routines. Workshop discussions (study 1) led to the design of 2 prototypes using a pressure mat to support resistance and balance exercises. The exploratory pilot study (study 2) participants reported the potential in using smart devices to support exercise snacking, but the design of the initial prototypes influenced the participants’ attitudes toward them. It also hampered the acceptability of these initial versions and highlighted the challenges in fitting exercise snacking into everyday life. ConclusionsOlder adults were positive about using technology in their homes to support strength and balance exercise snacking. However, although promising, the initial prototypes require further refinement and optimization before feasibility, acceptability, and efficacy testing. Technologies to support exercise snacking need to be adaptable and personalized to individuals, to ensure that users are snacking on balance and strengthening exercises that are appropriate for them.

Aisha Urooj Khan, Hilde Kuehne, Bo Wu et al.

Answering questions about complex situations in videos requires not only capturing the presence of actors, objects, and their relations but also the evolution of these relationships over time. A situation hyper-graph is a representation that describes situations as scene sub-graphs for video frames and hyper-edges for connected sub-graphs and has been proposed to capture all such information in a compact structured form. In this work, we propose an architecture for Video Question Answering (VQA) that enables answering questions related to video content by predicting situation hyper-graphs, coined Situation Hyper-Graph based Video Question Answering (SHG-VQA). To this end, we train a situation hyper-graph decoder to implicitly identify graph representations with actions and object/human-object relationships from the input video clip. and to use cross-attention between the predicted situation hyper-graphs and the question embedding to predict the correct answer. The proposed method is trained in an end-to-end manner and optimized by a VQA loss with the cross-entropy function and a Hungarian matching loss for the situation graph prediction. The effectiveness of the proposed architecture is extensively evaluated on two challenging benchmarks: AGQA and STAR. Our results show that learning the underlying situation hyper-graphs helps the system to significantly improve its performance for novel challenges of video question-answering tasks.

Zining Zhu, Haoming Jiang, Jingfeng Yang et al.

Natural language is among the most accessible tools for explaining decisions to humans, and large pretrained language models (PLMs) have demonstrated impressive abilities to generate coherent natural language explanations (NLE). The existing NLE research perspectives do not take the audience into account. An NLE can have high textual quality, but it might not accommodate audiences' needs and preference. To address this limitation, we propose an alternative perspective, \textit{situated} NLE. On the evaluation side, we set up automated evaluation scores. These scores describe the properties of NLEs in lexical, semantic, and pragmatic categories. On the generation side, we identify three prompt engineering techniques and assess their applicability on the situations. Situated NLE provides a perspective and facilitates further research on the generation and evaluation of explanations.

Stefan Schiffer, Astrid Rosenthal-von der Pütten, Bastian Leibe

We report on our effort to create a corpus dataset of different social context situations in an office setting for further disciplinary and interdisciplinary research in computer vision, psychology, and human-robot-interaction. For social robots to be able to behave appropriately, they need to be aware of the social context they act in. Consider, for example, a robot with the task to deliver a personal message to a person. If the person is arguing with an office mate at the time of message delivery, it might be more appropriate to delay playing the message as to respect the recipient's privacy and not to interfere with the current situation. This can only be done if the situation is classified correctly and in a second step if an appropriate behavior is chosen that fits the social situation. Our work aims to enable robots accomplishing the task of classifying social situations by creating a dataset composed of semantically annotated video scenes of office situations from television soap operas. The dataset can then serve as a basis for conducting research in both computer vision and human-robot interaction.

Christian Kohlschmidt, Mahnaz Sadat Qafari, Wil M. P. van der Aalst

Process mining is a set of techniques that are used by organizations to understand and improve their operational processes. The first essential step in designing any process reengineering procedure is to find process improvement opportunities. In existing work, it is usually assumed that the set of problematic process instances in which an undesirable outcome occurs is known prior or is easily detectable. So the process enhancement procedure involves finding the root causes and the treatments for the problem in those process instances. For example, the set of problematic instances is considered as those with outlier values or with values smaller/bigger than a given threshold in one of the process features. However, on various occasions, using this approach, many process enhancement opportunities, not captured by these problematic process instances, are missed. To overcome this issue, we formulate finding the process enhancement areas as a context-sensitive anomaly/outlier detection problem. We define a process enhancement area as a set of situations (process instances or prefixes of process instances) where the process performance is surprising. We aim to characterize those situations where process performance/outcome is significantly different from what was expected considering its performance/outcome in similar situations. To evaluate the validity and relevance of the proposed approach, we have implemented and evaluated it on several real-life event logs.

Xiaojian Ma, Silong Yong, Zilong Zheng et al.

We propose a new task to benchmark scene understanding of embodied agents: Situated Question Answering in 3D Scenes (SQA3D). Given a scene context (e.g., 3D scan), SQA3D requires the tested agent to first understand its situation (position, orientation, etc.) in the 3D scene as described by text, then reason about its surrounding environment and answer a question under that situation. Based upon 650 scenes from ScanNet, we provide a dataset centered around 6.8k unique situations, along with 20.4k descriptions and 33.4k diverse reasoning questions for these situations. These questions examine a wide spectrum of reasoning capabilities for an intelligent agent, ranging from spatial relation comprehension to commonsense understanding, navigation, and multi-hop reasoning. SQA3D imposes a significant challenge to current multi-modal especially 3D reasoning models. We evaluate various state-of-the-art approaches and find that the best one only achieves an overall score of 47.20%, while amateur human participants can reach 90.06%. We believe SQA3D could facilitate future embodied AI research with stronger situation understanding and reasoning capability.

Emilio De Santis, Fabio Spizzichino

Referring to a standard context of voting theory, and to the classic notion of voting situation, here we show that it is possible to observe any arbitrary set of elections' outcomes, no matter how paradoxical it may appear. On this purpose we use results, presented in a recent paper of us, that hinge on the concept of ranking pattern concordant with a probability model for non-negative random variables and on a related role of special load-sharing models. Our results here will be obtained by suitably extending those therein, and by converting them into the context of voting.

D. Parena, N. Kuka, W. Masmoudi et al.

The project 'Assessment of vehicle-track interaction with special reference to dynamic safety in operating conditions' (DYSAF), and supported as Brite-Euram Programme investigates dynamic phenomena at stake in derailment and overturning of vehicles. The project is led by a consortium of end-users, manufacturers of vehicles and experts in railway dynamics simulation and measurement techniques from five European countries. Among the main research items of DYSAF is also 'Modelling of dynamic interaction, close to limits' performed with multibody software. Compared to previously published benchmarks of codes applied to freight traffic situations at relatively low speed, DYSAF focuses on situations of high speed with short dynamic components compared to quasi-stationary results. For the covering abstract see ITRD E117109.

Álvaro A. Faccini-Martínez, Sebastián Muñoz-Leal, Marcelo B. Labruna et al.

Michael A. Chen

An octogenarian presented to our hospital in shock after being “found down” at home. She was dehydrated, hypernatremic, and suffering from a urinary tract infection. Findings of a murmur and those on electrocardiography led to the performance of echocardiography, with all findings consistent with a diagnosis of hypertrophic obstructive cardiomyopathy. The patient was volume resuscitated and administered antibiotics; after stabilization, she was started on a low-dose beta-blocker. Hypertrophic cardiomyopathy is a common genetic disorder that is usually diagnosed in the second to fifth decades of life, rarely being diagnosed at an advanced age. It is also an uncommon cause or contributor to shock. We briefly review the diagnosis and management of hypertrophic cardiomyopathy in older adults, particularly in the setting of shock.