28579 research outputs found
Sort by
Love's object, love's aim
Full text linkOn a standard approach, love’s proper object is construed in terms of personhood or rational agency. Some philosophers in this broadly Kantian tradition deny that love has a proper aim: specifically, they reject the idea that love properly aims at the good of the beloved. They worry about paternalism and encroachment. In this chapter, we show how Kierkegaard’s Works of Love advances a rival approach: one which provides an account of how love can properly aim at the good of the beloved, without thereby becoming objectionably paternalistic or encroaching, together with an alternative conception of love’s object. We bring out the significant advantages of this approach, which emphasizes our human interdependence and mutual vulnerability. Through a comparison with the ethical thought of K. E. Løgstrup, whose philosophy of love we present as standing in significant continuity with Kierkegaard’s, we further show how the expressly theological framework advanced in Works of Love may also be developed in a more secular direction
The Impact of Toxic Masculinity on Restrictive Emotionality and Mental Health Seeking Support
Full text linkMany men struggle, at least occasionally, to talk about their feelings and to seek mental health support. Previous research has attributed this to gendered social norms requiring men to be tough and confident. In the present research, we investigate, across two studies, the role toxic masculinity, defined as the over-exaggeration of masculine social norms that perpetuate misogyny, plays in restrictive emotionality and intention to seek health support, as well as underlying mechanisms. Consistent with our predictions, we found that toxic masculinity, and associated variables such as aggression and dominance, were strongly linked to restrictive emotionality. Contrary to our predictions however, restrictive emotionality, but not toxic masculinity, predicted men’s avoidance in seeking help for emotional problems and having suicidal thoughts. We discuss implications, limitations, and directions for future research to address issues surrounding men’s mental health and improving service accessibility
Exploring sport-related concussion guidelines and medical management approaches
Full text linkSport-related concussion (SRC) remains a complex and evolving challenge in both clinical and sporting environments, with ongoing inconsistencies in how the injury is defined, managed, and implemented across different contexts. Despite increasing awareness and the publication of international consensus statements, gaps persist between formal SRC guidance and real-world clinical practice, particularly within high-performance sport. This thesis investigates these gaps through two complementary research studies. The first study employed a PRISMA–guided scoping review to systematically map SRC policies, protocols, and guidelines across sports and international contexts. A total of 115 documents across 22 sports were analysed using template analysis to identify patterns in prevention strategies, sideline assessment, return-to-play (RTP) protocols, follow-up care, and documentation requirements. Findings revealed substantial variation in SRC definitions, audience targeting, and implementation procedures, with many organisations relying on generalised frameworks rather than sport-specific guidance. The second study used qualitative methods to explore practitioner perspectives on SRC management within high-performance sport. Semi-structured interviews were conducted with six healthcare professionals working in elite sporting environments. Reflexive thematic analysis identified key themes related to the invisible and evolving nature of SRC, variability in practitioner confidence and training, and the challenge of applying standardised protocols within dynamic performance settings. Participants emphasised the importance of clinical judgement, relational trust, and contextual flexibility in SRC care. Together, these studies provide a layered understanding of SRC governance and implementation. By examining both the structural landscape of concussion guidance and the lived experiences of practitioners, this thesis highlights the need for SRC policies that are not only evidence-informed but also practically adaptable to the realities of high-performance sport
Four symbolic moments in Bad Bunny’s Super Bowl halftime show
No full textOn the biggest stage in US popular culture, the performance pushed Latin visibility at the highest mainstream level. Against the scale of the spectacle, and the controversy it provoked, a message glowed quietly in the background: “The only thing more powerful than hate is love.
MMW/60GHz liquid crystal tuneable periodic filters
Full text linkThis thesis presents a design method for liquid‑crystal–tuneable periodic microstrip filters at 60 GHz built around a three‑stage synthesis. (1) Odd–even mode analysis provides closed‑form starting dimensions for a symmetric unit cell on an anisotropic, voltage‑biased LC substrate, placing the shunt/series resonances, target impedances and coupling needed for compact selectivity. (2) Reflection‑coefficient (Γ) optimisation then refines the geometry using an analytical Γ expression for the unit cell, improving matching across the intended passband/stopband while preserving manufacturability; the criterion naturally incorporates the LC’s bias‑dependent effective permittivity. (3) Periodic cascade prediction forms the full filter by chaining optimised cells via the ABCD matrix to extract the Bloch propagation constant, locate the Bragg edges, and forecast insertion and return loss versus the high‑level targets (centre frequency, selectivity and tuning range). Validation relies on full‑wave electromagnetic simulation in two independent platforms, Keysight ADS (Momentum) and CST Studio Suite, with harmonised substrate stacks, metallisation and bias conditions. The results show continuous, voltage‑controlled frequency tuning around 60 GHz, low insertion loss in the passband and strong return loss, with close agreement between matrix‑based predictions and EM responses. Cross‑tool correlation substantiates the robustness of the synthesis and the practicality of biasing LC substrates at millimetre‑wave. The contribution is an LC‑aware, synthesis workflow that unifies odd–even sizing, Γ‑based optimisation and ABCD/Bloch prediction, together with a reproducible cross‑platform validation protocol. The method provides a tractable path to reconfigurable 60‑GHz front‑end filtering and is readily extendable to other periodic topologies and frequency bands
Adorno and Kant
No full textAdorno’s philosophy is deeply influenced by Kant. While Adorno criticises Kant’s philosophy throughout his writings, he is sympathetic to Kant’s “rescuing urge”, his attempt to salvage the achievements of traditional metaphysics under post-critical conditions. Adorno’s criticism of Kant is that he has reified the basic concepts of his philosophy and therefore cannot account for their historical context and their meaning in social and political struggles. This is true of concepts such as autonomy, the will and the “cardinal propositions of metaphysics”, freedom, the immortality of the soul, and the existence of God. Adorno argues that Kant’s philosophy, understood as a principled defence of human autonomy and dignity, codifies the self-understanding of an ascendent bourgeois class. However, the horrors of the twentieth century and especially the Holocaust force us to reconsider the achievements of the Enlightenment project, to acknowledge the limits of Kant’s abstract normative concepts and find new grounds for social hope
A Quantum Multilayer Perceptron for Intraoperative Nociception Prediction
Full text linkPain pathways and interpatient variability represent an ongoing challenge for nociception monitoring. Inter- and intrapatient variability require large patient data for training conventional nociception predictive models. In this paper, we propose a quantum multilayer perceptron (QMLP) model for nociception prediction utilizing quantum features such as entanglement which enables the capturing of complex parameter dependencies using less data, by representing intralayer connections between parameters. Our QMLP architecture encodes input physiological parameters into quantum states which are processed through entangled quantum circuits, and optimized using parameter shift rule for gradient estimation. Our nociception prediction model is trained and evaluated on surgical data collected from two hospitals, with features extracted from electrocardiogram, photoplethysmography, and electroencephalogram. Through systematic comparative analysis across multiple datasets using two sampling approaches (patient-wise and downsampling), we demonstrate that our QMLP model consistently outperforms different classical baselines including deep learning models, treebased ensembles, and linear models across all evaluation metrics. Clinical evaluation on different populations of patients confirms the QMLP model’s superior ability to predict nociceptive changes during surgical events including Intubation, Incision, and Extubation. Expressivity analysis reveals that QMLP models achieve approximately twice the local effective dimension of classical baselines with identical parameter counts. Entanglement topology analysis demonstrates that circular configuration consistently achieves lower training loss compared to linear, pairwise, and non-entangled architectures, with quantum advantage driven by entanglement structure independent of data quantity. Our findings suggest quantum neural networks might offer advantages for nociception monitoring in anesthesia applications, particularly in data-limited scenarios where complex interrelated parameters influence clinical outcomes. The code used in this research can be accessed from: https://github.com/oyanoth/qmlp-nociception
A Novel UAV-assisted VANET Routing Protocol for Post-Disaster Emergency Communications
Full text linkAfter natural disasters, such as earthquakes or tsunamis, terrestrial communication networks often become inoperative due to infrastructure collapse. Simultaneously, damage to roads and transportation systems inevitably isolates different parts of the affected area, making it challenging for emergency vehicles to reach critical locations and deploy mobile Base Stations (BSs). In such scenarios, Unmanned Aerial Vehicles (UAVs) serve as a flexible and efficient solution. With the capability to establish temporary communication links, UAVs can provide emergency coverage for ground entities. In this paper, we propose a Dynamic Priority-based UAV-assisted Vehicular Ad-hoc Network (VANET) Routing (DPUVR) protocol for post-disaster message transmission. Specifically, DPUVR is a trajectory-based method for controlling the direction of message forwarding. DPUVR utilizes a multi-attribute decision-making method to adaptively evaluate the message delivery capability of candidate nodes (in this paper, nodes refer to both UAVs and vehicles), taking into account trajectory similarity, surplus energy, link survival time, remaining distance cost and queuing delay. In addition, we propose a dynamic prioritization delivery model. It evaluates the priority of messages in node buffers, selects appropriate candidate nodes and then chooses the best relay for message forwarding to trigger timely and efficient message delivery. Extensive simulation results show that DPUVR significantly outperforms other baseline methods in terms of delivery ratio, overhead, average delivery latency and average buffering time
Decoding semantic categories: Insights from an fMRI ALE meta analysis
Full text linkObjective.The human brain organizes conceptual knowledge into semantic categories; however, the extent to which these categories share common or distinct neural representations remains unclear. This study aims to clarify this organizational structure by identifying consistent, modality-controlled activation patterns across several widely used and frequently investigated semantic domains in functional magnetic resonance imaging (fMRI) research. By quantifying the distinctiveness and overlap among these patterns, we provide a more precise foundation for understanding the brain's semantic architecture, as well as for applications such as semantic brain-computer interfaces (BCI).Approach.Following PRISMA guidelines, we conducted a systematic review and meta-analysis of 75 fMRI studies covering six semantic categories: animals, tools, food, music, body parts, and pain. Using activation likelihood estimation, we identified convergent activation patterns for each category while controlling for stimulus modality (visual, auditory, tactile, and written). Subsequently, Jaccard-based overlap analyses were performed to quantify the degree of neural commonality and separability across concept-modality pairs, thereby revealing the underlying structure of representational similarity.Main results.Distinct yet partially overlapping activation networks were identified for each semantic category. Tools and animals showed shared activity in the lateral occipital and ventral temporal regions, reflecting common object-based visual processing. In contrast, food-related stimuli primarily recruited limbic and subcortical structures associated with affective and motivational processing. Music and animal sounds overlapped within the superior temporal and insular cortices, whereas body parts and pain engaged occipito-parietal and cingulo-insular networks, respectively. Together, these findings reveal a hierarchically organized and modality-dependent semantic architecture in the human brain.Significance.This meta-analysis offers a quantitative and integrative characterization of how semantic knowledge is distributed and differentiated across cortical systems. By demonstrating how conceptual content and sensory modality jointly shape neural organization, the study refines theoretical models of semantic cognition and provides a methodological basis for evaluating conceptual separability. These insights have direct implications for semantic neural decoding and for the development of BCI systems grounded in meaning-based neural representations
