Search Results (9)

Background: Human care represents the essence of nursing but faces challenges from increasing technological advancement and healthcare system bureaucratization. Objective: To understand how nursing students balance technical demands with human aspects of care during pre-professional practice experiences. Methods: An interpretive phenomenological study was conducted with 17 nursing students (12 women, 5 men) in their eighth and ninth semesters from a public university in northern Ecuador. The data were collected through focused interviews during the first quarter of 2025. Analysis followed a four-stage phenomenological process: epoché, phenomenological reduction, eidetic reduction, and transcendental reduction, culminating in phenomenological interpretation. Data saturation was achieved, and methodological rigor criteria were applied including triangulation with external analysts. Results: Six main strategies emerged that students develop to balance technical demands with humanized care: Time Management and Optimization, Integration of Human and Technical Dimensions, Patient Communication About Time Constraints, Emotional Regulation and Boundary Setting, Resistance to Dehumanization, and Institutional Context Adaptation. Students transform technical procedures into therapeutic opportunities and develop resilient competencies that preserve nursing’s humanistic values. Conclusions: Nursing students develop integrative competencies that balance technical excellence with human sensitivity. Curriculum modifications are needed to include specific competencies in emotional regulation, therapeutic communication, and dehumanization resistance strategies. Full article

We propose a self-training scheme, SURABHI, that trains deep-learning keypoint detection models on machine-annotated instances, together with the methodology to generate those instances. SURABHI aims to improve the keypoint detection accuracy not by altering the structure of a deep-learning-based keypoint detector model but by generating highly effective training instances. The machine-annotated instances used in SURABHI are hard instances—instances that require a rectifier to correct the keypoints misplaced by the keypoint detection model. We engineer this scheme for the task of predicting keypoints of cattle from the top, in conjunction with our Eidetic Cattle Recognition System, which is dependent on accurate prediction of keypoints for predicting the correct cow ID. We show that the final cow ID prediction accuracy on previously unseen cows also improves significantly after applying SURABHI to a deep-learning detection model with high capacity, especially when available training data are minimal. SURABHI helps us achieve a top-6 cow recognition accuracy of 91.89% on a dataset of cow videos. Using SURABHI on this dataset also improves the number of cow instances with correct identification by 22% over the baseline result from fully supervised training. Full article

This article reviews historically significant phenomenological studies of visual mental imagery (VMI), starting with Fechner in 1860 and continuing to the present. This synthesis of diverse VMI phenomenological studies in healthy adults serves as a unique resource for investigators of individual differences, cognitive development and clinical and neurological conditions. The review focuses on two kinds of VMI, “memory imagery” and “eidetic imagery”. Ten primary studies are drawn from three periods of the scholarly literature: early (1860–1929), middle (1930–1999) and recent (2000–2023). It is concluded that memory and eidetic imagery are two forms of constructive imagery, varying along a continuum of intensity or vividness. Vividness is a combination of clarity, colourfulness and liveliness, where clarity is defined by brightness and sharpness, colourfulness by image saturation and liveliness by vivacity, animation, feeling, solidity, projection and metamorphosis. The findings are integrated in a template that specifies, as a tree-like structure, the 16 properties of VMI vividness in healthy adult humans. The template takes into account the weight of evidence drawn from the accounts and reveals an extraordinary degree of consistency in reported VMI characteristics, revealed by specialized studies of healthy adult humans across time, space and culture. Full article

Accurate prediction of future chlorophyll-a (Chl-a) concentrations is of great importance for effective management and early warning of marine ecological systems. However, previous studies primarily focused on chlorophyll-a inversion and reconstruction, while methods for predicting Chl-a concentrations remain limited. To address this issue, we adopted four deep learning approaches, including Convolutional LSTM Network (ConvLSTM), Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Eidetic 3D LSTM (E3D-LSTM), and Self-Attention ConvLSTM (SA-ConvLSTM) models, to predict Chl-a over the Yellow Sea and Bohai Sea (YBS) in China. Furthermore, 14 environmental variables obtained from the remote sensing data of Moderate-resolution Imaging Spectroradiometer (MODIS) and ECMWF Reanalysis v5 (ERA5) were utilized to predict the Chl-a concentrations in the study area. The results showed that all four models performed satisfactorily in predicting Chl-a concentrations in the YBS, with SA-ConvLSTM exhibiting a closer approximation to true values. Furthermore, we analyzed the impact of the Self-Attention Memory Module (SAM) on the prediction results. Compared to the ConvLSTM model, the SA-ConvLSTM model integrated with the SAM module better captured subtle large-scale variations within the study area. The SA-ConvLSTM model exhibited the highest prediction accuracy, and the one-month Pearson correlation coefficient reached 0.887. Our study provides an available approach for anticipating Chl-a concentrations over a large area of sea. Full article

Phenomenological philosophy was developed by Husserl for the eidetic sciences, which are interested in the general essences or persistent characteristics of things. By contrast, the empirical sciences are sciences of facts, interested in the concrete, singular, contextual and accidental qualities of phenomena. We do not encounter general, pure essences in concrete reality; instead, we meet phenomena, which present themselves as the particular actualisations of the essences. For this reason, it is legitimate to distinguish between the eidetic essence, which is constituted by a set of essential predicates that necessarily belong to the thing, and the essence of the concrete, which is constituted by a set of predicates that characterises that unique and singular thing in the space and time in which it manifests itself. Starting from these considerations, this article presents an original interpretation of Husserl’s phenomenological method to develop an empirical phenomenological theory. The ‘empirical phenomenological method’ (EPM) grounded in this theory will first be described, and two examples of its application, in healthcare and educational research, will then be presented. Full article

Eidetic memory has been reported in children and in patients with synesthesia but is otherwise thought to be a rare phenomenon. Presented herein is a patient with right-sided language dominance, as proven via multiple functional imaging and neuropsychometric methods, who has a seizure onset zone in the right temporo-parietal-occipital cortex. This patient’s medically refractory epilepsy and thus hyperactive cortex could possibly contribute to near eidetic ability with paired-associates learning tasks (in both short-term and long-term retention). There are reports of epilepsy negatively affecting memory, but as far as the authors are aware to date, there is limited evidence of any lesion enhancing cognitive functions (whether through direct lesion or via compensatory mechanism) that would be localized to a seizure onset zone in the dominant temporo-parietal-occipital junction. Full article

The paper analyses Peirce’s hypoiconicity through the lens of Husserlian intentionality. Peirce’s triple structure of hypoiconicity as resemblance relation, diagrammatical reasoning and metaphoric displacement is shown to require intentional acts in its production and interpretation. Regarding hypoiconicity as a semiotic schematization of Vorstellung, the paper places it in the context of Husserl’s conception of intentionality in which iconicity appears as a stepping-stone towards the skeletonization of resemblance in diagrammatical abstraction and as schematic displacement in metaphor. As such, hypoiconic intentionality is argued to play a role also in Peirce’s community conception of language. The paper’s core claim is that intentionality provides an avenue for revealing hypoiconicity as a major, critical concept of semiotics, functioning as paradigm case for investigating the convergence of semiotics and phenomenology. Full article

The widespread nature of the coronavirus disease 2019 (COVID-19) pandemic is gradually changing people’s lives and impacting economic development worldwide. Owing to the curtailment of daily activities during the lockdown period, anthropogenic emissions of air pollutants have greatly reduced, and this influence is expected to continue in the foreseeable future. Spatiotemporal variations in aerosol optical depth (AOD) can be used to analyze this influence. In this study, we comprehensively analyzed AOD and NO₂ data obtained from satellite remote sensing data inversion. First, data were corrected using Eidetic three-dimensional-long short-term memory to eliminate errors related to sensors and algorithms. Second, taking Hubei Province in China as the experimental area, spatiotemporal variations in AOD and NO₂ concentration during the pandemic were analyzed. Finally, based on the results obtained, the impact of the COVID-19 pandemic on human life has been summarized. This work will be of great significance to the formulation of regional epidemic prevention and control policies and the analysis of spatiotemporal changes in aerosols. Full article

Domestic abuse of women is a serious problem worldwide that has economic, physical, and psychological consequences, yet in many countries and cultures, victims often have little access to psychological support. Using a pre-post design, we investigated the effects of psychological intervention using an imagery-based therapy in women showing post-traumatic stress disorder (PTSD) resulting from spousal domestic abuse. Forty women, referred from outpatient clinics in Pakistan and meeting inclusion criteria, underwent individual trauma counseling for 10–12 weeks using the principles of Eidetic Therapy, an imagery-based therapy that circumvents heavy reliance on verbal skills and narratives. Women showed significant reductions in PTSD by the end of treatment. Predictors of treatment gains included type of abuse, PTSD level at the outset of therapy, and years in the relationship. Neither economic resources or literacy, nor abuser or victim characteristics, predicted the amount of improvement. In conclusion, therapy was associated with a reduction in PTSD symptoms regardless of literacy level of participants. This reduction in PTSD was notable because, unlike many situations involving spousal abuse, these women were generally not in a position to leave their relationship, and hence the women might have experienced continued exposure to abuse. Context/cultural-based explanations for these findings are presented and discussed. Full article