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On the absence of the ultimate regime in turbulent thermal convection
Quantifying heat transport in turbulent convection remains a challenge. The two competing models of heat transport predict that the nondimensional heat flux, known as the Nusselt number (Nu), is proportional to Ra 1 / 3 (classical scaling) and Ra 1 / 2 (ultimate-regime scaling), where Ra is the Rayleigh number. Some experiments and simulations report that the Nusselt number transitions from near classical scaling, Ra 0.30 , to a larger power law when the boundary layer turns turbulent near Ra ≈ 10 14 . However, others find Ra 0.30 scaling to continue for larger Ra. In this work, we perform a comparative study of Rayleigh-Bénard, compressible, and periodic convection in two and three dimensions using direct numerical simulations. We show that up to Ra = 10 16 in two dimensions and up to Ra = 10 13 in three dimensions, the positive and negative energy fluxes in Rayleigh-Bénard and compressible convection are nearly equal. However, in the distribution function, the positive fluxes have longer tails than the negative ones, and the differences between the positive and negative fluxes scale as Ra − 0.20 , which leads to Nu ∼ Ra 0.30 . The above robust and universal properties, even in the presence of a logarithmic layer in compressible convection, indicate a likely absence of the ultimate regime in turbulent thermal convection. In contrast, periodic convection, which is related to the ultimate regime, exhibits a predominantly positive heat flux.
Deep multi-metrics learning for mobile app defect prediction using code and process metrics
Two-stage cluster sampling to assess SARS-CoV-2 seroprevalence without pre-enumeration: An example from Madagascar
Implementing population-based surveys in resource-constrained settings presents logistical challenges when detailed population enumeration is unavailable. We developed a field mapping system integrated into a cluster sampling approach to eliminate pre-enumeration requirements for a SARS-CoV-2 seroprevalence survey in Madagascar. We conducted a cross-sectional observational study in urban Fianarantsoa, Madagascar, between February and June 2021. Using probability proportional to size sampling, we selected clusters from administrative areas (fokontany) and randomly generated GPS coordinates within these clusters. Field teams navigated to coordinates using OpenStreetMap software on tablets, identified eligible households, and conducted health surveys with blood sampling. We employed a mobile-compatible system for real-time household mapping and data collection, functioning without continuous network connectivity. Sample size calculation targeted 650 households (SARS-CoV-2 seroprevalence 30%, precision ±5%, design effect 2.0). Our specific objectives were to develop and implement a geographic cluster sampling method that did not require pre-enumeration; to assess the feasibility of this method through participation rates; and to evaluate potential selection biases related to socioeconomic factors. We identified households at 95.3% (696/730) of randomly generated GPS coordinates. Of contacted households, 96.8% (674/696) participated, representing 1,121 individuals across 57 clusters. Participation rates varied geographically, with a modest inverse correlation with household wealth (participation decreased by 0.85% per wealth quintile increase, 95% CI: −3.54% to 1.84%). Demographic characteristics of our sample matched census data for urban Fianarantsoa, supporting the representativeness of our approach. This integrated field mapping system created a virtual household map simultaneously with survey implementation, enabling cost-effective two-stage cluster sampling without pre-enumeration. The approach enabled evaluation of selection bias, simplified logistics, and provided a permanent geo-referenced database of surveyed households. This methodology offers a practical solution for population-based surveys in resource-constrained settings with incomplete enumeration data and has applications beyond COVID-19 research for various public health surveillance activities.
Revealing emergent human-like conceptual representations from language prediction
People acquire concepts through rich physical and social experiences and use them to understand and navigate the world. In contrast, large language models (LLMs), trained solely through next-token prediction on text, exhibit strikingly human-like behaviors. Are these models developing concepts akin to those of humans? If so, how are such concepts represented, organized, and related to behavior? Here, we address these questions by investigating the representations formed by LLMs during an in-context concept inference task. We found that LLMs can flexibly derive concepts from linguistic descriptions in relation to contextual cues about other concepts. The derived representations converge toward a shared, context-independent structure, and alignment with this structure reliably predicts model performance across various understanding and reasoning tasks. Moreover, the convergent representations effectively capture human behavioral judgments and closely align with neural activity patterns in the human brain, providing evidence for biological plausibility. Together, these findings establish that structured, human-like conceptual representations can emerge purely from language prediction without real-world grounding, highlighting the role of conceptual structure in understanding intelligent behavior. More broadly, our work suggests that LLMs offer a tangible window into the nature of human concepts and lays the groundwork for advancing alignment between artificial and human intelligence.
Fertilizer type and intercropping influence the metabolic and nutritional profiles of borage and peanut
Effect of dopamine on TGF-β2 secretion by human retinal pigment epithelial cells and the underlying mechanism
Background Dopamine is known to play a role in the development of myopia. In this study, we investigated the effect of dopamine (DA) on the secretion of transforming growth factor-β2 (TGF-β2) in human retinal pigment epithelial (RPE) cells. Additionally, we examined the effects of SCH23390 (D1 receptor antagonist) and sulpiride (D2 receptor antagonist) on TGF-β2 levels in ARPE-19 cells to elucidate the underlying mechanism of DA in myopia development. Methods Human RPE cells were cultured with or without different concentrations of DA, SCH23390, or sulpiride. Cell proliferation was examined using the CCK-8 assay. Cell migration was assessed by performing a cell scratch (wound healing) assay. The expression of TGF-β2 was evaluated at the mRNA and protein levels by real-time PCR and western blotting, respectively. Furthermore, the secretion of TGF-β2 into the ARPE-19 cell supernatant was quantified using ELISA. Results Treatment with 20 μg/mL of DA significantly increased ( P < 0.05) the mRNA and protein expression levels of DRD1, DRD2, YAP, and TEAD and decreased TGF-β2 levels compared with that in control group. However, treatment with 24 μg/mL of SCH23390 for 24 h significantly decreased ( P < 0.05) DRD1 and TGF-β2 mRNA expression and increased DRD2 , YAP , and TEAD mRNA expression in ARPE-19 cells compared with that in the control group. Additionally, the protein expression levels of TGF-β2, YAP, TEAD, and SMAD7 were consistent with the mRNA levels. Notably, treatment with sulpiride (14 μg/mL) increased ( P < 0.05) DRD1 and TGF-β2 expression and decreased DRD2 , YAP , and TEAD expression in the cells at both the mRNA and protein levels compared with that in the control group. Conclusions Our findings suggest that dopamine suppresses TGF-β2 secretion in human retinal pigment epithelial cells primarily through activation of D2 receptors, which appears to involve the YAP-TGF-β-Smad signaling pathway. This regulatory mechanism may contribute to the control of scleral remodeling and thus influence the development of myopia.
A conductive folding metamaterial via laser-induced biomimetic electrospinning
Conductive folding metamaterials (CFMs) represent a class of cross-physical-domain new-type metamaterials. However, the inherently nonfoldable nature of intrinsic conductive materials and the incompatibility between conductivity and extreme foldability have posed formidable challenges for their design and fabrication. To overcome these limitations, we developed a laser–electric-field coupled biomimetic spinning (LECBS) technique, which couples laser induction with cocoon/lotus-root-inspired biomimicry in a fast electrospinning Taylor cone reaction. Using this approach, we report the fabrication of CFMs composed of hierarchically adaptive carbon nanofiber networks. The CFMs constitute a new class of artificially microstructured composites with extraordinary physical properties absent in nature, filling a critical gap in the metamaterials family. The resulting CFMs endure up to 10 7 cycles, and potentially unlimited cycles, of true folding without damage, in arbitrary directions and with unrestricted 360° flexibility. Simultaneously, they achieve electrical conductivities on the order of 10 3 S·m − 1 , nearly one order of magnitude higher than comparable systems without carbon nanotubes. Mechanistic studies reveal that LECBS can effectively modulate Taylor cone hydrodynamics and jet behavior through photo-electro-matter interactions, which yields thinner nanofibers, enhanced sliding freedom of nanofibers, and axial alignment of CNTs in carbon nanofibers. Real-time SEM observations demonstrate the formation of characteristic M-shaped creases with “separated layers–smooth arcs–slidable grooves” during folding, which successfully disperse stress, in excellent agreement with finite element simulations. This work not only represents a breakthrough in metamaterials but also a technological revolution, opening new opportunities for flexible and foldable electronics fields.
Correction: Intraspecific variation in sex-biased dispersal of a threatened ecotone butterfly between forest patches in a mosaic landscape
Harnessing genetic diversity: The genomic and transcriptomic insights of Eugenia uniflora for environmental resilience
Pitanga ( Eugenia uniflora L.), a member of the Myrtaceae family, is native to the Brazilian Atlantic Forest and distributed across various ecological environments, including regions with contrasting edaphoclimatic conditions. Known for its production of secondary metabolites with significant biological activity, pitanga holds considerable pharmacological potential. Genomic and transcriptomic resources for this species are therefore valuable for understanding the genetic mechanisms that enable its adaptation to diverse ecosystems and for identifying candidate genes relevant for crop improvement and bioprospection. To explore whether genetic diversity is associated with population adaptation to environmental conditions, we first generated a draft genome of E. uniflora, totaling 385.1 Mbp with an N50 value of 26,199 bp, assembled de novo from Illumina-sequence reads. Likewise, gene prediction, based on Viridiplantae protein references, identified 30,663 protein-coding genes. Comparative genomics revealed 2,219 orthologous clusters, 40% of which were functionally annotated and encompassing 1,772 gene ontology terms. This draft genome also facilitated the identification of microsatellite markers, whose variation was analyzed across pitanga samples from two contrasting natural environments: Restinga and Riparian forest. The microsatellite profile showed a natural bias towards monomeric repeats, with genetic diversity differences across both populations that could be used as molecular markers for phenotype selection and plant breeding. Furthermore, RNA sequencing coupled with a Transcriptogram approach revealed significant differences in gene expression between the two populations. Pitangas from the Restinga ecosystem exhibited a stronger stress response, with distinct gene expression patterns associated with osmoprotection, cell wall modification, detoxification, nutrient balance, and epigenetic regulation. These patterns are likely linked to enhanced adaptation to the water and osmotic stress conditions, characteristic of this environment. Together, these findings enhance our knowledge of genetic diversity within E. uniflora populations and the molecular basis of their environmental adaptability. Such insights are critical for understanding how plants rapidly adapt to climate change and how these adaptations affect population dynamics, important for conservation strategies, population management, and the development of resilient cultivars.
Rats pursue food and leisure following the same rational principles
Animals in the wild must balance multiple, potentially mutually exclusive goals simultaneously in order to survive. Yet laboratory tests of decision-making often investigate how animals optimize their behavior to achieve a single, well-defined goal, which is often a nutritive reward. Thus, how animals solve multiobjective optimization problems is not well understood. Here, we devised an ethologically inspired decision-making task to examine how rats balance the pursuit of food and nonfood reinforcement. Rats performed a free-choice patch-foraging task, in which they could earn food in one location (food patch) or interact with a rodent play structure in a different location (toy patch). The cost of switching between patches was manipulated by requiring rats to endure a long or short “travel time” penalty during which they were not able to access either patch. Rats devoted a considerable amount of their limited foraging time to patches of both types, showing a small but significant preference for food patches. In accordance with theoretical models of foraging, when the cost of switching patches was high rats chose longer stay durations in both types of patches, suggesting that similar rational principles guided their pursuit of food and nonfood rewards. Examining the within-session dynamics of time allocation revealed that rats showed an early preference for spending time in toy patches that reversed over the course of the session. Satiety manipulations demonstrated that patch residence time decisions were under goal-directed control and responsive to current needs and recent consumption.
A first principles investigation into the mechanical properties and the strengthening mechanism of the graphene/aluminum interface structure
Effect of silver and graphene nanoparticles on the thermophysical performance of ethylene glycol-glycerol hybrid nanofluids
This study examines the thermophysical properties of ethylene glycol–glycerol (60:40 v/v) hybrid nanofluids containing graphene nanoplatelets (GNPs) and silver nanoparticles (Ag) at concentrations of 0.1–0.5 vol.%. The nanofluids were synthesized using a two-step method with Tween-80 surfactant to enhance dispersion stability. High-resolution transmission electron microscopy (TEM) and Raman spectroscopy confirmed the morphology, lateral size, few-layer structure of GNPs, and the attachment of Ag nanoparticles. The addition of surfactant increased the zeta potential from 15.7 mV to 35.2 mV for the 0.1 vol.% GNPs/Ag formulation, indicating a marked improvement in colloidal stability. Thermal conductivity enhancement reached 102.85% at 0.1 vol.% with only a 19.84% viscosity increase. Higher nanoparticle loadings improved conductivity further but caused significant viscosity increases and reduced stability. Specific heat capacity decreased by up to 46.45%, potentially benefiting rapid thermal response applications but limiting heat storage capacity. Comparison with recent literature showed that the present formulation outperforms several similar Ag- and GNP-based nanofluids in thermal conductivity enhancement while maintaining manageable viscosity. This study is the first to report such high conductivity improvement in an EG–GLY-based hybrid nanofluid at ultra-low loading, achieved through optimized surfactant use, validated structural characterization, and benchmarking against literature. Low-concentration GNPs/Ag hybrid nanofluids, particularly at 0.1 vol.%, offer strong potential for thermal management applications where high heat transfer performance and acceptable pumping requirements are critical. However, stability limitations at higher concentrations and viscosity–conductivity trade-offs highlight the need for further optimization before large-scale deployment.
Reevaluation of whether histones are asymmetrically segregated during asymmetric divisions of stem cells in <i>Drosophila</i>
Recent work suggests that asymmetric segregation of preexisting and newly synthesized canonical histone 3.1 (H3.1), but not variant histone 3.3A (H3.3A), plays an important role in the asymmetric outcome of Drosophila germline stem cell (GSC) and intestinal stem cell (ISC) divisions. However, this finding relied on the Gal4/UAS system and Flp-out technology to swap expression of exogenous fluorescent proteins—an approach that decouples H3.1 expression from the cell cycle and may be prone to artifacts. Here, by photoswitching photoconvertible H3-Dendra2 proteins expressed under their native controls in living flies, we find that preexisting and newly synthesized H3.1 and H3.3A are symmetrically segregated in dividing ISCs and somatic cyst stem cells (CySCs) in male testes. While H3.3A was found to be symmetrically segregated during GSC divisions, analysis of the H3.1 segregation in GSCs was complicated by our unexpected finding that H3.1-Dendra2 expressed under its normal control within the context of a histone transgene is not detectable in GSCs, owing to regulatory elements in the 3’UTR that mediate translational repression by the RNA-binding proteins Nanos and Pumilio. Nevertheless, when this repression is obviated by using a 3’UTR devoid of such elements, H3.1-Dendra2 is expressed in GSCs and symmetrically segregated without affecting lineage outcomes. We obtained similar results when the coding sequence of H3.3A was edited to encode H3.1 in the context of an H3.3A-Dendra2 knock-in allele. Our findings thus challenge the prevailing model of asymmetric histone segregation and reveal an unexpected molecular mechanism of posttranscriptional repression of H3.1 in GSCs.
Amplitude and phase control in SIW structures by tuning multilayered graphene
Abstract Graphene is a unique 2D material that provides exceptional mechanical properties, ultra-high carrier mobility, and dynamically adjustable surface conductivity, making it an excellent choice for microwave devices. However, the dynamic manipulation of amplitude and phase in substrate integrated waveguides based on multilayered graphene has not been experimentally proven. In this paper, we propose a novel multilayered graphene based half mode SIW attenuator and phase shifter for the manipulation of amplitude and phase at microwave frequencies. The amplitude and phase are controlled by applying a bias voltage to graphene. The applied voltage is increased from 0 to 6.2 V, and the sheet resistance (Ω/□) of graphene can be tuned between 1302 and 60 Ω/□, depending on the gap size for deposition of graphene. The simulated and measured results of the proposed attenuator and phase shifter demonstrate the manipulation of microwave signals. The dynamic range achieved for amplitude is 13dB, and that of phase is 45 degrees. The proposed technique proves that the amplitude and phase of microwave signals can be tuned in SIW based devices without any localized surface mounted devices (SMD) or complex realization techniques.
Occupational risk of COVID-19 related hospital admission in Skåne, Sweden: A register-based cohort study
Purpose Given the paucity of data regarding workplace risk of COVID-19, particularly from countries with limited lockdowns, we aimed to quantify the occupational risks of COVID-19-related hospital admission among workers in Sweden. Methods We identified 607,179 employed individuals, 20−69 years of age, in Skåne, Sweden. From December 31 st , 2019—December 31 st 2021, 2,633 incident COVID-19-related admissions were identified. Using a job exposure matrix for risk of becoming infected with the SARS-CoV-2 virus in an occupational setting we delineated occupations with low work-related risk. Based on these reference occupations, incidence rate ratios (IRR) and 95% confidence intervals (CI) were computed by Poisson regression for four-digit occupations defined by the International Standard Classification of Occupations job codes (ISCO-08). Results After adjusting for various sociodemographic characteristics, risk compared to reference occupations was elevated among healthcare occupations as a group (IRR 1.31; 95% CI: 1.13–1.51), with nurses, healthcare assistants, and nursing aids having the highest IRRs (ranging from 1.28–1.54). In the educational sector, no apparent elevated overall risk was observed (IRR 1.03; 95% CI: 0.86–1.23). For the transportation sector, an overall excess risk was observed (IRR 1.34; 95% CI: 1.10–1.65), with bus and tram drivers having the highest risks. IRRs < 1 were observed among electricians, some builders, and software developers. Conclusion Excess risk of COVID-19-related hospital admission was observed in many patient-facing occupations across the healthcare sector and in multiple occupations within the transportation sector. However, despite limited lockdowns and legislation, no apparent increased risks were observed in the educational or retail sales sectors.
Synaptobrevin-2 disease variants reveal spatial constraints within the presynaptic active zone
Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins drive synaptic transmission in a temporally and spatially precise manner. Recent studies have identified several disease-causing SNARE variants that give rise to developmental and epileptic encephalopathies, defined as SNAREopathies. Here, we investigated nine synaptobrevin-2 (VAMP2) disease-causing variants and uncovered their specific SNARE complex affinity, stability, and conformational deficits that drive dysregulated neurotransmission. The neurotransmission deficits we observed parallel the symptomatic heterogeneity of the patients, with some variants displaying a disproportionate augmentation of spontaneous neurotransmitter release. When we examined the spatial organization of this excessive spontaneous release at nanoscale, we found that SNARE complexes composed of these variants formed exclusively outside of RIM scaffolding, revealing a preserved exclusion zone sparing evoked release from pathophysiology. Taken together with the phenotypes of previously reported disease-causing SNARE variants, these findings reveal shared patterns of aberrant neurotransmission across different SNAREs, highlighting the necessity for a functional classification of SNAREopathies to develop therapeutic interventions. The use of clinically relevant genetic manipulations to challenge the synapse provides mechanistic insight into rare diseases while simultaneously revealing fundamental aspects of synaptic physiology.
Winds of change: meteorological influences on Strokkur’s geyser eruptions, Iceland
Abstract Geothermal eruptions are among the most spectacular phenomena in nature. However, the regularity of the eruptions and the internal or external driving factors of eruptions remain unclear due to the scarcity of long-term data. Our study fills this gap by presenting an unprecedented 4.5-year catalog of 650,000 water fountains observed at Strokkur geyser, Iceland. Our findings reveal a correlation between the wind speed and the recurrence interval of eruptions. Specifically, as the wind speed increases, the recurrence interval increases quadratically. This represents the most significant external modulator, influencing the system at least down to the bubble reservoir at a depth of 24 m. A secondary modulator is the temperature, with a linear increase in the recurrence interval as the temperature decreases. A heat loss model that accounts for the wind speed and temperature differences between water and air does not fully predict the observed behavior. However, the model does not account for heat loss during fountaining or for water loss from the catchment during eruption. The aim of this study is to quantify the relationship between the weather and the geyser to enable a correction and to focus on other internal and external drivers in future studies.
Abdominal computed tomography–assessed muscle quality and its prognostic value in patients with advanced chronic kidney disease initiating hemodialysis
Background Skeletal muscle density (SMD), assessed via L3 level computed tomography (CT), is a critical marker of muscle quality with remarkable prognostic value in various clinical settings. This study investigates prognostic values of the SMD of abdominal CT images and to verifies its relationship with other variables indicating sarcopenia in patients with advanced chronic kidney disease (CKD) patients. Methods All 458 patients initiating hemodialysis for maintenance were enrolled in this retrospective study. The sex-specific cut-off values of the SMD and skeletal muscle index (SMI) of L3 level abdominal CT were obtained by drawing the receiver operating characteristic curve for mortality. Cut-offs for identifying low SMD and SMI groups were applied. Results The mean age of all patients was 67 years, and 300 (65.6%) patients were male. A total of 204 (44.5%) patients died. In the fully adjusted Cox regression analysis, patients with low SMD had a higher risk of death than those with SMD above the reference cut-off (adjusted hazard ratio (adjHR): 1.805 95% confidence interval (CI): 1.263–2.579, p -value < 0.001). The continuous variable SMD had a prognostic value in the multivariate Cox proportional analysis (adjHR: 0.961, 95% CI: 0.942–0.980, p -value <0.001), while the continuous variable SMI did not have prognostic value after adjustment (adjHR: 1.002, 95% CI: 0.986–1.019, p -value = 0.778). The multivariate regression analysis for SMD with the clinical variable showed that male sex, younger age, lower body mass index (BMI), and higher albumin remained significantly and independently associated with higher SMD. SMD showed an inverse correlation with BMI in contrast to SMI. Conclusion The low SMD assessed by abdominal CT is independently associated with all-cause mortality in patients with advanced CKD initiating hemodialysis. In contrast to SMI, SMD showed a negative correlation with BMI, indicating that SMD might reflect dysfunctional sarcopenia better from perspective of the obesity paradox of CKD in this study population.
Glycosaminoglycans activate peptidylarginine deiminase 4 by enhancing calcium affinity
Rheumatoid arthritis is a chronic inflammatory disease driven by abnormal protein modifications. These include citrullination of arginine residues by the calcium-activated enzyme peptidylarginine deiminase 4 (PAD4). However, calcium in body fluids may not fully activate PAD4, suggesting the potential involvement of other activators. In this study, we investigated the ability of glycosaminoglycans (a class of negatively charged polysaccharides) to modulate PAD4 activity. We found that model glycosaminoglycans bind to the enzyme with a nanomolar affinity, increase its calcium sensitivity, and require enzyme dimerization for activation. These effects depend on the size and negative charge of the glycosaminoglycan, and its various natural forms activate PAD4. Thus, our findings elucidate a mechanism by which common physiological compounds modulate PAD4 activity, potentially contributing to disease etiology.