This multi-site experimental study investigated the Hue-Heat Hypothesis (HHH), which posits that light hues can influence human thermal perception, as well as broader cross-modal interactions between visual and thermal domains. Across 464 experimental sessions in eight test rooms around the world, participants were exposed to varied thermal conditions (∼20 °C, ∼24 °C, ∼26 °C, and ∼28 °C) and typical white-light Correlated Color Temperatures (CCT, warm light: ∼3000 K; neutral: ∼4000 K; cool light: ∼6000 K) from LED sources (horizontal illuminance: ∼500 lx). The study assessed thermal, visual, and overall perceptions. Results revealed that thermal sensation and preference were predominantly influenced by thermal conditions, gender, and the laboratory setting, indicating that no statistically significant effects were found in support of the HHH. Similarly, visual perceptions were influenced by lighting conditions but not by the thermal environment. For instance, cool light was perceived as brighter than warm light, leading participants to prefer brighter light under warm light hues. Ultimately, this research revealed the significant challenges of interlaboratory experiments in this field, as local climate and test-room characteristics complicate both the conduct and the standardization of data analysis. Our findings highlight both the limited role of white-light CCT in shaping thermal sensations and the methodological challenges of multi-site comfort research, underscoring the need for careful data harmonization and context-aware analyses in future international collaborations.

Transient phenomena and their control are of high relevance in magnetic confinement fusion plasmas to guarantee a stable and safe plasma operation. Interpretative simulations can maximize the insights gained from experiments on present machines and predictive simulations can help in the preparation of design, mitigation techniques and operational scenarios for future devices. In this article, we provide an overview of recent advances and novel scientific results obtained with the 3D non-linear hybrid fluid-kinetic code JOREK, covering physics of plasma transients from the core to the scrape-off layer (SOL) both for tokamak and stellarator devices. Substantial progress was made in the physics understanding, model validation with experiments and experiment interpretation, thus, giving confidence for predictions to devices like DTT, ITER and DEMO. The topics addressed comprise a wide range: the edge physics of new operation scenarios and edge localized mode suppression; major disruptions with a focus on runaway electrons and vertical displacement events as well as disruption mitigation by shattered pellet injection; the physics mechanisms and operational limits of the flux pumping regime for sawtooth control; MHD limits of stellarators and work towards incorporating advanced edge/SOL/exhaust dynamics; continuing improvements of the code for more efficient hybrid simulations on conventional and accelerated high performance computing architectures.

With a diverse range of applications in both private and public sector, the market value of Unmanned Aerial Vehicles (UAVs) skyrocketed to 17.31 billion USD in 2024 and is expected to reach 32.95 billion USD by 2030. 3GPP considered UAVs in Release 15 and will include them in Release 18 as part of the 5G-Advanced technology. To provide smooth and safe inclusion in the current airspace, fast and reliable communications between UAVs and between ground base stations and UAVs are needed. Several research studies have been conducted, but there is no comprehensive picture of their advancements in terms of wireless communications and networking for UAVs. This survey paper provides detailed information on the current status of UAV communications and networking, including important aspects such as architectural solutions, protocols and design options related to spectrum management, resource optimization and security requirements. Efforts related to standardization and integration with different applications are also covered. The survey will help researchers and practitioners in the field of wireless communications, UAV service provision and telecommunications learn about the current state of the art and open the door to future research and development avenues in their fields.

Driving infrared (IR)-active phonons to large amplitudes to enable non-equilibrium crystal lattice distortions, known as non-linear phononics, can initiate phase transitions along non-thermal pathways, providing transient control of various material properties beyond the equilibrium limits. Yet, how these non-thermal lattice-driven states evolve and thermalize remains unresolved. Here, we explore the crossover from non-thermal to thermal magnetization dynamics in dysprosium orthoferrite (DyFeO₃), driven by the resonant excitation of IR-active phonons. Using mid-infrared light pulses, we induce a transition from the collinear antiferromagnetic to the weakly ferromagnetic (WFM) phase, resulting in the emergence of net magnetization. Time-resolved single-shot magneto-optical imaging across multiple timescales reveals two distinct regimes. First, magnetization emerges as a spatially uniform state whose direction is controlled by the pump polarization, indicative of a non-thermal mechanism driven by non-linear phononics. On longer timescales, this state relaxes into a multidomain pattern that is insensitive to the pump polarization, consistent with thermal equilibration. The crossover occurs on a timescale of about 200 ps, far exceeding the IR phonon coherence time and consistent with the spin-lattice relaxation time in the WFM phase. These findings provide direct temporal and spatial fingerprints of non-linear-phononics-driven magnetic phase control, defining intrinsic limits for reversible ultrafast manipulation of magnetic order.

The growing availability of GPU-accelerated open-source solvers has boosted the capability of tackling complex single-phase and multiphase turbulent flows by means of direct and large-eddy simulations. GPU-accelerated solvers can leverage the heterogeneous computing architectures that are available in leading high-performance computing centers worldwide, taking advantage of the higher throughput and greater energy efficiency offered by GPUs as compared to CPUs. However, porting CPU-based numerical solvers to GPUs entails many outstanding challenges, such as parallelism exposure, inter-GPU communication, memory allocation constraints, and shared memory limitations. To overcome these challenges, GPU-friendly algorithms, performance portability strategies, and careful selection of computational paradigms and programming languages must be developed. Besides, adaptive mesh refinement and data compression may be integrated to mitigate I-O bottlenecks and enable simulations of more complex geometries on top of the existing requirements imposed by incompressible flows. When compressibility effects become significant, further considerations related to the adoption of high-performance preconditioners and multigrid solvers become crucial for tackling large, sparse linear systems and extending simulations to high-Mach flows. Finally, reduced-precision arithmetic can further enhance performance, energy efficiency, and scalability. In this work, we survey current applications of GPU-accelerated solvers in the broad area of fluid mechanics and turbulence simulations and discuss the main challenges and bottlenecks associated with code porting and optimization. We then conclude our analysis with an outlook on future perspectives for enabling efficient GPU-based exascale computing of turbulence.

Young children are at increased risk for respiratory tract infections and are frequently colonized by respiratory pathogens. However, how the mucosal immune system differs between children and adults is relatively unknown. We collected nasal samples from 50 young children (aged 1–5 years) and 318 young adults (aged 18–34 years) to study how the mucosal immune system and host-microbe interactions differ with age. We used multi-omics data integration to combine host (immunophenotyping, transcriptomic, and cytokines) and microbial (16S-rRNA amplicon sequencing, viral PCRs, and pneumococcal culture) datasets. Young children had a paucity of mucosal granulocytes, while B and T cell subsets were increased. Children also had increased immune activation and inflammation, which associated with the presence of Haemophilus spp. and pneumococcus, but not viruses. In adults, Haemophilus spp. associated with T cell and monocyte recruitment, while Dolosigranulum negatively associated with neutrophil degranulation. Thus, nasal immune composition and host-pathogen interactions were clearly age dependent.

Heterogeneity in disease severity and treatment response in inflammatory bowel disease (IBD) likely evolves from individual differences in host-microbiota-immune interactions. Histological evaluation of intestinal biopsies is central to diagnosis, but histological parameters that define underlying immune mechanisms are limited. We investigated histological features that distinguish individual patient immune profiles in therapy-naive pediatric IBD patients (age 6-18 years) using biopsy immunohistochemistry and transcriptomics and plasma proteomics across two cohorts. High colonic epithelial expression of secretory leukocyte protease inhibitor (SLPI), a microbiota-induced regulator of epithelial function, occurred in IBD patients with high clinical disease activity and more severe endoscopic and microscopic disease activity. SLPI expression was related to increased neutrophil infiltration, transcriptomic signatures of activation, and genes known to associate with therapeutic resistance. High SLPI colocalized with high densities of IL-17-secreting cells and was associated with high plasma concentrations of Th17-related immune proteins. Additionally, patients with high intestinal SLPI had an intrinsically different immunotype, in which circulating neutrophils exhibited altered transcription of genes involved in neutrophil granule formation, phagocytosis, oxidative phosphorylation, and interferon signaling. Thus, high colonic SLPI expression at diagnosis associates with severe IBD, increased IL-17A-neutrophil pathway responses, and altered transcriptomic wiring of circulating neutrophils.

Halide perovskite solar cells have demonstrated a rapid increase in power conversion efficiencies. Understanding and mitigating remaining carrier losses in halide perovskites is now crucial to enable further increases to approach their practical efficiency limits. Recent observations in halide perovskites have revealed processes such as shallow carrier trapping, which give rise to an apparent non-radiative bimolecular channel that is difficult to distinguish from intrinsic radiative recombination. Here, we quantify this shallow-trap manifestation by jointly analyzing time-resolved photoluminescence and quantum efficiency to separate the total second-order term into radiative (η_esck_2r) and shallow-trap-mediated non-radiative contributions (k_2non), and evaluate their device impact. We show that k_2non is strongly modulated by temperature and surface chemistry and thus depends on extrinsic factors and its origin is independent from deep traps, whereas the intrinsic radiative coefficient and intrinsic second-order recombination follow detailed-balance expectations and align with theoretical evaluations through van Roosbroeck–Shockley relations. Based on density functional theory simulations and Quasi-Fermi level calculations, we propose that surface states are the primary origin of this shallow-trap-related second-order component, contributing up to ∼80 mV of the overall reduction in V_oc at room temperature. This work reveals that the origin of carrier losses from two non-radiative recombination types (first and second order) are not linked, emphasizing the need for distinctive mitigation strategies targeting each type to unlock the full efficiency potential of perovskite solar cells.

Introduction: Hip dysplasia, characterized by an insufficient acetabular coverage of the femoral head, increases hip joint stress and predisposes to degenerative changes. A novel 3D-printed, patient-specific extracapsular shelf implant was developed to increase femoral head coverage. Accurate implant placement is crucial. This cadaveric study compared CT-only surgical planning with combined CT- and MRI-based planning to evaluate whether MRI integration improves positioning accuracy. Methods: Two cohorts of non‑dysplastic cadaveric hips were studied. In cohort 1 (five hips), implant design was based solely on CT imaging. In cohort 2 (four hips), both CT and MRI datasets were used, incorporating capsular soft‑tissue anatomy. Postoperative implant positioning was compared with preoperative plans using point-cloud analyses, clockface coverage graphs, and Dice coefficients. Acceptable placement was defined as: median Euclidean distance < 5 mm, median angular deviation < 5°, and Dice > 0.75 respectively. Results: In the CT‑only cohort, three of five implants failed one or more accuracy thresholds, with Euclidean distances up to 8.5 mm, coverage deviations up to 6°, and Dice coefficients as low as 0.37. CT‑only designed implants consistently tilted away from the acetabular rim, reflecting underestimation of hip capsule thickness and insertion height. In the CT+MRI cohort, all four implants met the <5 mm and <5° deviation thresholds, and three achieved Dice ≥0.75. No consistent deviation patterns were observed. Conclusion: Combined CT and MRI planning improved implant positioning accuracy by better accounting for variations in hip capsule morphology. MRI integration demonstrated superior performance over CT‑only planning for patient‑specific shelf implant placement.

Vitality capacity (VC) reflects a physiological state and is a determinant domain of intrinsic capacity but has so far remained mainly theoretical. This study validates the vitality capacity domains ‘energy and metabolism’ and ‘neuromuscular function’ and examines its link to locomotor capacity and quality of life (QoL). Exploratory factor analysis (EFA) was performed on the combined dataset from the Fatigue Resistance AMErsfoort study (FRAME, n = 1000) and the Fatigue Plot study (FATPLOT,n = 620). Confirmatory factor analyses (CFA) were subsequently performed on data from the AMersfoort COhort study on functional decline, Healthy aging and Frailty (AMCOHF,n = 367) and the BrUssels sTudy on The Early pRedictors of FraiLtY (BUTTERFLY,n = 491), to validate VC in both middle-aged and older adults. Linear hierarchical regression analysis was used to investigate the relationship between VC, locomotor capacity, and QoL. EFA indicated a one-factor model and CFA validated this with good model fit in the dataset (BUTTERFLY) (Robust CFI; 0.960, SRMR: 0.040) and (AMCOHF) (Robust CFI; 0.942, SRMR: 0.055). This model validated maximal grip strength (GSmax), 30-s chair stand test (30CST), Multidimensional Fatigue Inventory (MFI-20) and Capacity to Perceived Vitality ratio physical (CPV-physical) to measure VC. Several assessments show a significant relationship with locomotor capacity and QoL. This study indicated that VC is a coherent domain and has a relationship with locomotor capacity and QoL.

Background: Technologies such as assistive devices and social robots show promise in supporting people with dementia and their caregivers. However, their long-term cost-effectiveness remains unclear, and existing health-economic models are limited in capturing the relevant outcomes. Objective: This study aims to conceptualize a health-economic model to assess the potential impact of care technologies in dementia care on lifetime quality of life and care use. Methods: We summarized an impact pathway of three care technologies and conceptualized a health-economic model to estimate the long-term impact on quality of life and care use, drawing on literature and multidisciplinary expert input. Results: We conceptualized a cohort-based Markov state-transition model simulating states of dementia severity progression (mild, moderate, severe), care setting transitions (no formal care, home care, nursing home), and mortality. Intervention effects are modeled through surrogate outcomes such as functional status and caregiver burden associated to care transitions and quality of life. Conclusions: This model offers a framework for early health technology assessment of assistive technologies in dementia, supporting extrapolation of effects beyond limited trial data. Future work should focus on developing and operationalizing this model, applying it to establish the value of dementia care technologies.