Search Results (5,626)

This article re-examines the national theory of Austro-Marxism as a response to the dual crisis of the late Habsburg Empire: the paralysis of imperial governance and the erosion of cross-national class solidarity. Karl Renner and Otto Bauer proposed a non-territorial federal scheme based on the personal principle and cultural autonomy, reconstructing the nation as a cultural community grounded in individual registration. By severing the link between nation, sovereignty and territory, they sought to reopen space for class politics while preserving the imperial state. The article argues that this scheme was an institutional proposal shaped by the specific contradictions of the Empire’s socio-economic structure. Its failure reveals a tension that recurs in contemporary discussions of non-territorial autonomy: the success or failure of institutional designs for plural societies is determined less by their internal coherence than by their capacity to respond to the material conditions of the societies they seek to govern. Full article

In single-aspect studio apartments, daylight sufficiency and sunlight exposure constrain window design simultaneously. A studio reference room in Bangkok, Thailand was evaluated using Radiance through Ladybug Tools and a TMYx weather file. Six main-window configurations, three visible-light transmittance (VLT) levels (0.45, 0.65, 0.88), and four orientations formed a complete factorial set of 72 cases, assessed with spatial daylight autonomy (sDA_300/50%), useful daylight illuminance (UDI_100–3000), and annual sunlight exposure (ASE_1000,250). The room was also simulated with the balcony door alone, giving a simulated baseline. Within the investigated design space, orientation accounted for 93.16% of the variation in ASE and 63.36% in UDI, but only 3.39% in sDA, which was governed instead by VLT (69.10%) and window configuration (23.23%). sDA ranged from 52.17% to 100.00% and 19 cases did not reach 75%; ASE ranged from 1.09% to 53.26%. The door alone gave a mean sDA of 47.10%, and the smallest window raised it by 25.00 percentage points. A screening rule informed by LEED v5 retained 29 cases and no west-facing case; substituting finer-grid values for four near-threshold cases reduced this to 28, testing that subset rather than grid independence across the dataset. Orientation and solar exposure should be assessed first, transmittance second, and window area last. Full article

Facility-based birth is an important strategy for reducing maternal and neonatal mortality, yet institutionalization has also been associated with overmedicalized and disrespectful care. Midwifery centers (MCs) may offer an alternative, but evidence on their implementation in low- and middle-income countries (LMICs) remains limited. This study explored barriers and facilitators to MC implementation and functioning in LMICs. A scoping review conducted in 2020 identified 15 publications. Ten key informants were interviewed in 2020 to complement and contextualize the literature findings. Findings were analyzed thematically and organized within a SWOT framework. A literature update conducted in 2026 identified 13 additional publications, resulting in 28 included publications. Facilitators included enabling environments for midwives, internal standards, sustainable financing, community-centered care, and professional collaboration. Barriers included workforce and education gaps, insufficient professional and regulatory recognition, weak health-system integration, and inadequate maternity care infrastructure. Expert insights complemented the literature by highlighting practical implementation challenges. Successful MC implementation requires context-sensitive approaches supported by adequate health-system infrastructure, professional autonomy, and functional referral networks to enable safe and respectful maternity care. Full article

Online brand communities enable knowledge exchange, peer support, content creation, and value co-creation, yet technically simple participation can feel costly while objectively demanding activity can feel smooth. This conceptual article develops the Effortless Brand Community Engagement Framework (EBCEF) to explain that anomaly. A structured integrative review directly consulted 58 cited sources, using a published review of 88 records and 41 included studies as inherited synthesis rather than as a newly screened corpus. Abductive theory development distinguishes perceived participation effort as a seven-dimensional resource appraisal from interaction fluency as the subsequent technological, interpretive, and social smoothness of participation. The five-stage framework links design and governance to psychological and relational mechanisms, effort, fluency, consumer engagement, observable participation behavior, continued participation, and downstream outcomes. Twelve proposition sets specify core paths and selected moderators, while the effortlessness paradox predicts when high-intensity or low-control features generate overload, privacy concern, reactance, or fatigue. The EBCEF advances theory by separating engagement from its behavioral and longitudinal consequences and offers managers a diagnostic basis for removing unnecessary burdens while preserving autonomy, meaningful challenge, trust, and consumer control. The constructs and dimensions remain theoretical expectations requiring empirical validation. Full article

Media control under contemporary autocratization extends beyond overt censorship, operating through legal regulation, economic dependence, and digital infrastructures. Yet, critical political economy, media-systems research, media-capture scholarship, and work on digital repression have largely theorized these forms within separate analytical domains. This article develops a structured conceptual synthesis rather than a primary-data comparative study, taking the mechanism, not the country, as its unit of analysis: twenty-three country-period illustrations across fourteen contexts show how mechanisms operate, not how often they occur. The mapping compares legal, economic, and digital mechanisms across three positions on the autocratization spectrum—democratic backsliding, competitive authoritarianism, and hegemonic electoral authoritarianism—in terms of instruments, targets, proximate effects, and institutional form. The ordering is ideal-typical and directional, not a historical sequence: legal control from deterrent uncertainty to institutionalized exclusion; economic control from discretionary dependence to closed resource architectures; and digital control from visibility manipulation to pre-emptive governance. Because the three families operate through shared dependencies linking the executive, state apparatus, capital fractions, and media ownership, they are relationally connected rather than independent. The mapping offers journalism and media scholarship a comparative framework for analyzing how media actors’ resources, autonomy, and visibility are reorganized within formally plural media markets. Full article

Machine learning is increasingly used for spacecraft telemetry monitoring, fault diagnosis, health assessment, mission planning, visual navigation, and execution review. In space missions, explainability is a foundation of trustworthy artificial intelligence because engineers must understand the evidence behind model outputs before incorporating them into operational decisions. Explainability should therefore transform internal model computations into evidence that engineers can inspect during mission execution and integrate into an intuitive mental model of spacecraft state, model rationale, and possible action consequences. Such evidence may include channel–time patterns, rule paths, prototype events, active constraints, or subsystem propagation hypotheses. It must remain traceable to the model, consistent with spacecraft modes and physical constraints, and usable in reviewable decisions. This review distinguishes the mechanism that generates an explanation from the strength of its spacecraft validation. It examines interpretable-by-design models and six post-hoc families, separating direct spacecraft evidence from methods transferable from adjacent domains. A V0–V5 scale describes evidence ranging from generic experiments to measured mission-support benefit. Finally, the review discusses the Open-Box method and examines how exact and consistent regional representations may be relevant to piecewise-linear network families within verified operating regions. Full article

Background/Objectives: Robotic-assisted surgery (RAS) teaching, using simulation, has been examined widely. Less is known about teaching in the intraoperative environment. We conducted a systematic review of skills, strategies and facilities necessary for intraoperative RAS teaching. Methods: A systematic review of evidence on RAS curricula and teaching was conducted using MEDLINE, PubMed, Embase, CINAHL and PsycINFO in February 2024, updated in June 2025. A total of 10,000 references were screened for eligibility using the PICO (population, intervention, comparator, outcomes) framework, with a focus on surgeons and intraoperative RAS teaching. Data were extracted and analysed thematically using NVivo 14. Methodological quality was assessed using the MMERSQI (Modified Medical Education Research Study Quality Instrument) criteria and the Joanna Briggs (JBI) critical appraisal tool. The review was registered with PROSPERO under CRD42024566778. Results: A total of 16 publications met the inclusion criteria. Most studies were small, used qualitative methodologies and were conducted in general or colorectal surgery. Verbal instruction was the most common teaching method. Force sensitivity, robotic control, including retraction, perception of the field and team management were skills taught intraoperatively. RAS training-the-trainer publications focused on enhancing autonomy. Conclusions: The volume of available evidence is low. Trainee autonomy is the main challenge in intraoperative RAS training and may be enhanced by training-the-trainer skills training. Verbal teaching accompanied by a demonstrative gesture appears to be useful. Intraoperative RAS skills taught include third arm retraction, awareness of the field and management of the bedside team. The use of a dual console to facilitate teaching is endorsed by most RAS trainers but is not an absolute requirement for training. Full article

Wearable and implantable biosensors are becoming small distributed biomedical systems rather than isolated transducers. Their practical performance depends on how the sensing interface, analog front end, power source, local computation, wireless link, packaging, and therapeutic output interact over time. The analysis focuses on that cross-layer problem, with emphasis on nanomaterial interfaces, energy autonomy, edge intelligence, and long-term reliability. Graphene, carbon nanotubes, MXenes, and transition-metal dichalcogenides are discussed across electrochemical, field-effect, impedance, optical, and radio-frequency transduction. Mechanical nanogenerators, biofuel cells, wireless power transfer, and hybrid storage are compared using the energy actually available after rectification and regulation rather than peak generator output alone. Quantitative re-plots illustrate non-monotonic carbon-nanotube loading in triboelectric layers and voltage-tunable few-layer-graphene microwave components. Edge AI is treated as part of the power and measurement architecture: local inference can reduce radio traffic and latency, but introduces model drift, uncertainty, and update requirements. The final sections connect biofouling, encapsulation, mechanical fatigue, calibration drift, wireless safety, and algorithm lifecycle to a common validation ladder for wearable, insertable, and implantable systems. Full article

Accurate medium-horizon trajectory prediction, spanning roughly one to three seconds ahead, is essential for the safety and autonomy of uncrewed aerial vehicle (UAV) systems. Trajectory prediction assists UAVs in performing collision avoidance, path planning, and cooperative airspace coordination. Deep sequence models are now widely used for trajectory prediction. The gated recurrent unit (GRU) and long short-term memory (LSTM) models are among the most widely used architectures. However, published comparisons of GRU and LSTM encoder–decoder models rarely use identical data, splits, and hyperparameter budgets. This makes it difficult to attribute reported accuracy differences to the recurrent cell itself. We present a controlled comparison in which two otherwise identical velocity-based encoder–decoder networks jointly predict three future 3D velocity waypoints at +10, +20, and +30 steps ahead. Both networks share an identical 5-fold cross-validation protocol, held-out test split, fixed seed, and 81-point hyperparameter grid, for 405 runs per architecture and 810 runs total. At each architecture’s best configuration, the LSTM model reaches 7.2% lower validation Mean Squared Error (MSE) than GRU. On the held-out test set, LSTM achieves 6.5% lower test MSE under each architecture’s independently selected best configuration (best-practice comparison); a complementary matched-configuration comparison, in which each architecture is retrained under the other’s configuration, shows this advantage is concentrated in robustness to hyperparameter choice rather than in the recurrent cell alone. We also report per-waypoint, per-dimension, and Monte Carlo dropout (MC-dropout) epistemic-uncertainty metrics for both architectures. These metrics are pooled over test windows dominated by synthetic, near-planar flight data (~74%) and should not be read as general conclusions for real, free-form UAV flights. Vertical-velocity error is consistently higher than horizontal-velocity error for both models, reflecting limitations in how well the training data represent vertical movement. The MC-dropout epistemic-uncertainty intervals show 34–36% empirical coverage, substantially lower than the nominal Gaussian-reference target of 68.3% at 1σ. On our 8 × H200 GPU cluster, LSTM’s training time is 51% longer than GRU’s per run, a training-side cost that should not be read as a proxy for embedded inference cost. These results show that LSTM’s main advantage over GRU is its greater robustness to suboptimal hyperparameter settings, rather than substantially better performance when both architectures are well tuned. They also show that the uncertainty estimates from both architectures require post hoc calibration before they can be reliably used as safety bounds. Full article

Background/Objectives: Immune checkpoint inhibitors have transformed oncology by inducing unexpected and sustained remissions in some patients; however, this atypical survival may be accompanied by significant psychosocial and existential challenges. The objective was to synthesize the available scientific evidence on the psychosocial burden of the ‘Lazarus Effect’, characterized by survivor guilt, identity shift, and discontinuation anxiety. Methods: A systematic review was conducted following the PRISMA2020 guidelines, based on a preregistered protocol on the OSF. Searches were performed in PubMed, Scopus, Web of Science, and APA PsycINFO using PICOS-based eligibility criteria. Seven primary empirical studies were included, and their methodological quality and risk of bias were assessed using the MMAT 2018. Results: Survivor guilt stems interpersonally from peer deaths and intrapersonally from perceived autonomy loss. Identity shift involves transitioning into an “existential limbo,” re-establishing self-identity while off active treatment. Discontinuation anxiety relates to recurrence fears, absence of curative biomarkers, and uncertainty regarding treatment duration. Interactively, these dimensions drive broader psychosocial burden, including social isolation, “scanxiety,” and a discrepancy between physical recovery and emotional vulnerability. Conclusions: Current evidence—limited to seven heterogeneous studies concentrated in high-income settings—indicates exceptional responses to immunotherapy may involve nuanced psychosocial challenges. Given small sample sizes, melanoma overrepresentation, potential report retrieval bias, and non-standardized assessment tools, findings require cautious interpretation. They offer an exploratory foundation for future research rather than definitive clinical conclusions, supporting preliminary psycho-oncological screening during treatment transitions. Full article

Light Detection and Ranging (LiDAR) has become a benchmark sensing modality for autonomous unmanned aerial vehicle (UAV) navigation in GPS-denied and obstacle-dense environments such as forests, urban canyons, and indoor structures. This paper presents a structured review of the LiDAR-based UAV autonomy pipeline, spanning raw point-cloud processing, three-dimensional environment representation and mapping, simultaneous localization and mapping (SLAM), multi-sensor fusion, and real-time obstacle avoidance and trajectory planning. Reactive geometric methods, volumetric and distance-field mapping frameworks, tightly coupled LiDAR–inertial and LiDAR–inertial–visual odometry systems, gradient- and sampling-based trajectory optimizers, and learning-based end-to-end policies are compared with respect to computational cost, robustness, and applicability to resource-constrained micro-UAV platforms. The review further synthesizes current technical bottlenecks, including onboard computational limits, LiDAR performance degradation under adverse atmospheric conditions, and the difficulty of tracking fast-moving dynamic obstacles, as well as emerging research directions such as solid-state LiDAR integration, kinodynamic trajectory optimization, multi-sensor fusion (including radar- and event-camera-assisted schemes), learning-based exploration and foundation-model-based control, multi-UAV collaborative mapping, and simulation-to-reality transfer. The synthesis indicates that LiDAR remains a strong perceptual backbone for UAV autonomy, but that state-of-the-art systems increasingly combine it with inertial, visual, radar, and learning-based components rather than relying on LiDAR in isolation. Full article

Despite increasing global attention to reproductive health, significant knowledge gaps and misconceptions about abortion and contraception persist among young adults, including medical students. Understanding their knowledge and attitudes is crucial for developing effective educational strategies. This study aimed to assess the knowledge and attitudes regarding abortion and contraceptive methods among undergraduate Romanian health-professions students. A cross-sectional study was conducted between April and December 2024, using a validated, self-administered questionnaire distributed online. The final sample included 510 students from various medical fields. Data were analyzed using descriptive statistics and chi-square tests, with a p-value < 0.05 considered statistically significant. Most participants were female (77.45%), reflecting the feminization trend in medical education. Overall, 95.88% of respondents declared awareness of abortion, yet significant knowledge gaps remained, particularly regarding legal gestational limits for medical abortion. Notably, 66.47% identified infertility as a potential complication of abortion, though this did not differ significantly by gender. Regarding attitudes, students generally supported abortion in cases involving maternal health risks (74.12%) or sexual assault (79.22%), while acceptance decreased in socio-economic or personal contexts, especially among male students. Contraceptive knowledge was high for condoms (99.22%) and oral contraceptives (95.88%), with no significant gender differences for individual methods after correction for multiple comparisons. Importantly, 64.35% of male students believed that condoms reduce sexual pleasure, and 87.85% of female students expressed concern about the side effects of oral contraceptives. Furthermore, 60.59% of participants believed that access to abortion services in Romania is insufficient, and nearly 80% advocated for legal measures to improve accessibility. Male students were significantly more likely than female students to report not knowing what surgical abortion on demand is (16.52% vs. 2.53%; OR = 0.13, female vs. male, 95% CI 0.06–0.29, p < 0.0001), a gender gap that remained significant after correction for multiple comparisons. In multivariable linear regression, year of study was the strongest independent predictor of objective knowledge (β = 0.31, 95% CI 0.14–0.47, p < 0.001), and students enrolled in Dentistry/Pharmacy programs scored significantly lower than those in General Medicine (β = −0.83, 95% CI −1.32 to −0.34, p = 0.001), whereas gender and age were not independently associated with knowledge after adjustment (p = 0.581 and p = 0.519–0.794, respectively). The findings reveal substantial gaps in knowledge and persistent misconceptions about abortion and contraception among future healthcare providers, particularly regarding legal gestational limits. Gender differences were significant for attitudes toward abortion in non-medical contexts, but were not robust for most individual knowledge items once corrected for multiple comparisons. Targeted educational interventions are urgently needed to address misinformation, promote reproductive autonomy, and prepare future healthcare professionals to provide comprehensive, unbiased reproductive healthcare. Full article

This study explored how rural youth cluster into physical activity (PA) profiles and whether psychological characteristics differ across these clusters. The primary objective was to identify PA-based profiles, and the secondary objective was to examine the differences in basic psychological needs across profiles. A 1-year exploratory prospective cohort study was conducted with 83 6th–8th grade students from an under-resourced rural middle school, with 48 participants having complete PA data for analyses. The sport-based PA intervention was implemented by college students in an undergraduate service-learning course. PA was assessed using Axivity AX3 accelerometers, and included light, moderate, vigorous, and total PA minutes/week. Psychological measures included the Basic Psychological Needs Satisfaction and Frustration. K-means cluster analysis identified PA profiles based on light, moderate, and vigorous PA levels (minutes/week). Analysis of variance (ANOVA) and Linear Mixed Models assessed profile differences based on (a) needs satisfaction, (b) needs frustration, (c) autonomy, (d) competence, (e) relatedness. Three PA profiles emerged: a low activity (n = 21), medium activity (n = 22), and high activity cluster (n = 5). These clusters differed significantly in PA levels (p < 0.001). Need satisfaction and frustration did not significantly differ across PA profiles; however, relatedness frustration differed significantly across timepoints (p = 0.036) and needs satisfaction showed descriptive trends across PA profiles. These findings demonstrate heterogeneity in PA engagement among rural youth and provide preliminary descriptive evidence of psychological patterns across these emerging PA profiles. Such differences may generate hypotheses for future research examining whether PA and psychological characteristics can meaningfully inform intervention tailoring. Full article

The rapid adoption of large language models (LLMs) has prompted extensive debate about their appropriate role in peer review, scholarly publishing’s primary quality-control mechanism. However, AI has not yet been formally approved as a peer-review tool by most academic journals. This study reviews the emerging AI-in-peer-review literature to identify research trends, synthesize empirical evidence across review tasks, and develop a conceptual framework for AI-assisted review. Using a PRISMA-guided Scopus search (176 records identified, 162 included), we combined three-layer content analysis (theme, editorial stance, and AI autonomy) with a synthesis of 18 empirical studies. The literature expanded from 6 records before 2023 to 45 records in the first half of 2026 and remains dominated by commentary and opinion (57%), with the remaining 43% comprising research studies, technical work, and reviews. Editorial perspectives are generally balanced, and authors overwhelmingly favor assistive, human-in-the-loop AI over human-only or full automation. Empirical evidence shows a task-contingent pattern: AI performs well on narrowly defined evaluative tasks (Pearson r > 0.9 in some settings) but less reliably when predicting editorial decisions (accuracy 40–67%; correlations as low as ρ = 0.00). AI legitimacy may depend more on task type than on any governance position, a pattern we formalize in a Task-Contingent Legitimacy framework offering a task-tiered policy approach and testable propositions. Full article

Physical education provides an important context for adolescents’ social development because students regularly interact with teachers and peers through cooperation, competition, and shared learning experiences. Although supportive teaching has been associated with a range of positive educational outcomes, limited research has examined how multidimensional teaching style is related to students’ prosocial and antisocial behavior through students’ perceptions of a teacher-supportive instructional climate in Chinese secondary-school PE. This cross-sectional study examined the relationships among students’ perceptions of PE teachers’ teaching style, perceived teacher-supportive instructional climate (PTSIC), and prosocial and antisocial behavior in 710 Chinese high school students. Teaching style was conceptualized as a multidimensional construct comprising autonomy support, structure, and involvement. PTSIC was assessed using the 15-item Sport Climate Questionnaire (SCQ), and prosocial and antisocial behavior were assessed using the Prosocial and Antisocial Behavior in Sport Scale. Confirmatory factor analysis and structural equation modeling were conducted, and indirect associations were examined using bias-corrected bootstrapping with 2000 resamples. Teaching style was positively associated with PTSIC (β = 0.486, p < 0.001). PTSIC was positively associated with prosocial behavior (β = 0.422, p < 0.001) and negatively associated with antisocial behavior (β = −0.175, p < 0.001). Teaching style was negatively associated with antisocial behavior (β = −0.261, p < 0.001), whereas the specified model showed no corresponding direct association with prosocial behavior (β = 0.073, p = 0.157). Positive and negative indirect associations through PTSIC were observed for prosocial behavior (β = 0.205, 95% CI [0.153, 0.264]) and antisocial behavior (β = −0.085, 95% CI [−0.141, −0.035]), respectively. These findings suggest a pattern in which students who perceived more supportive multidimensional teaching also tended to perceive a more teacher-supportive instructional climate and report more favorable social behavior. Given the cross-sectional design and the study’s methodological limitations, we should interpret these findings as preliminary structural associations within the specified model rather than evidence of temporal ordering or causal mediation. Full article