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Cross-state prediction of dynamic ferroelectric catalysis: Efficient screening for bypassing the Sabatier limit
Ferroelectric (FE) switching offers a pathway to bypass the Sabatier limit by toggling binding states, yet the computational cost for screening such dynamic materials remains prohibitive. Here, we present a machine learning-accelerated approach to discover two-dimensional FE metal–organic frameworks for switchable hydrogen evolution. We establish a geometric-electronic descriptor that enables quantitative cross-state prediction of adsorption energies, effectively halving the computational cost by forecasting the switched state solely from the initial-state features. Using this model, we identify candidate materials where polarization reversal drives the hydrogen adsorption free energy (ΔGH) from negative to positive, facilitating a direct transition from strong adsorption to spontaneous desorption. Microscopically, polarization-driven coordination field reconfiguration serves as a geometric switch to tune the energy level and occupation of the metal dz2 orbitals, while the magnitude of spin-polarization splitting ultimately governs the thermodynamic stability. This work provides a systematic framework for discovering intrinsic switchable catalysts via efficient cross-state prediction.
Texture analysis on muscle T2 maps can reveal changes in upper trapezius muscles related to primary headache disorders
Abstract Migraine and tension-type headache (TTH) are highly prevalent primary headache disorders. Neck pain is common among patients with migraine or TTH, but objective biomarkers for the neck’s myofascial involvement within the trigemino-cervical complex (TCC) are lacking. This study aimed (1) to apply texture analysis (TA) to magnetic resonance imaging (MRI) covering the upper trapezius muscles with T2 maps, which are particularly sensitive to subtle edematous changes such as those following inflammation; and (2) to associate demographics, characteristics of sleep and sports, headache, and neck pain with muscle T2 values and derived texture features. Seventy-one participants (mean age 24.0 ± 3.0 years, 59 females; 22 healthy controls [HC], 21 migraine, 16 TTH, 12 migraine with TTH) underwent MRI of the upper trapezius muscles, followed by bilateral muscle segmentations and extraction of muscle T2 and first- and second-order texture features. Comparisons between HC and participants with primary headache disorders were performed following removal of outliers with the robust regression followed by outlier identification (ROUT) method (Mann-Whitney U tests, adjustment for multiple comparisons). Principal component analysis (PCA), linear, and logistic regression analyses (using bootstrapping with 5,000 permutations) were conducted based on image-derived parameters and headache and neck pain characteristics. Significant group differences were found between HC and participants with primary headache disorders for muscle T2 (30.14 ± 1.05 vs. 31.10 ± 0.92 ms, p < 0.001), sumaverage (0.007163 ± 0.0011 vs. 0.006366 ± 0.0012, p = 0.017), kurtosisglobal (1.15 ± 0.32 vs. 1.63 ± 0.81, p = 0.024), and energy (0.003514 ± 0.0006 vs. 0.004176 ± 0.0012, p = 0.043). According to PCA, a cluster including age, days with headache over the last three months, neck pain, muscle T2, kurtosisglobal, and skewnessglobal was identified, with a cluster close to the opposite direction including average hours of sports per week, average hours of sleep per week, sex, and varianceglobal. Muscle T2 ( p = 0.015) and sumaverage ( p = 0.022) were significantly associated with days with headache over the last three months. Furthermore, sumaverage was significantly associated with the presence of neck pain ( p = 0.024). T2 mapping with TA may provide objective and quantitative parameters for myofascial involvement and peripheral sensitization within the TCC, partially associated with clinical parameters such as the number of days with headache.
Socioeconomic disparities in children’s neurodevelopment before and during primary education: Evidence from Bagamoyo, Tanzania
Background Socioeconomic disparities in children’s neurodevelopment constitute a critical yet understudied developmental challenge in low- and middle-income countries (LMICs), yet longitudinal evidence from Sub-Saharan Africa (SSA) remains limited. This study aimed to evaluate the relationship between household wealth and neurocognitive trajectories in a cohort of Tanzanian children aged 6 months to 10 years. Methods We randomly selected 590 children aged 6 months to 10 years in Bagamoyo district, a low to moderate-malaria-endemic area in Tanzania. Participants completed comprehensive, age-appropriate neurodevelopmental assessments. The family’s socioeconomic status was derived from their household assets. Standardized, age-adjusted neurodevelopmental scores were regressed on socioeconomic status tertiles and by developmental periods: early childhood (6 months-3 years), preschool (4–5 years), and school age (6–10 years). Results While children from high- and low-Socioeconomic status (SES) families start with similar neurodevelopmental scores, a significant and sustained gap begins to emerge around age 2 years. This divergence results in a substantial disadvantage for children from the poorest households, with scores showing a difference of −0.36 Standard Deviation (SD) (95% CI: −0.64 to −0.08) during the preschool years and −0.41 SD (95% CI: −0.73 to −0.09) at school age. Conclusion Our results suggest that programs targeting the preschool period may be most effective in mitigating disparities in neurodevelopment.
Experimental evidence of resonant tunneling transport in GaN-based terahertz quantum cascade heterostructures
We report the first experimental evidence of resonant tunneling transport in GaN-based terahertz (THz) quantum cascade (QCL) heterostructures. A GaN/AlGaN resonant-phonon three–quantum-well design was grown and fabricated on a c-plane free-standing GaN substrate and electrically characterized. The measured current–voltage characteristics exhibit a pronounced negative differential resistance (NDR), arising from resonant alignment and subsequent detuning of quantized states within the multi-period structure. The NDR signature persists up to ∼200 K, demonstrating coherent transport in a nitride QCL-like heterostructure at elevated temperatures. Temperature-dependent measurements reveal a progressive suppression of the NDR due to enhanced inelastic scattering and level broadening, while Arrhenius analysis indicates a transition from tunneling-dominated transport at low temperatures to thermally activated carrier injection over the contacts' barrier layers at higher temperatures. These results constitute a direct experimental validation of the fundamental transport mechanism in GaN-based THz QCL structures and establish a key step toward high-temperature THz devices based on III-nitride heterostructures.
Targeting NLRP3 with GDC-2394 ameliorates airway inflammation and smooth muscle hyperplasia in experimental asthma by suppressing the IL-6/JAK2/STAT3 axis
Police emergency dispatch model based on emergency level analysis and traffic planning
Emergency dispatching and rescue during emergencies have become a hot research topic in the field of transportation planning. Therefore, to address the low efficiency of cross-regional police emergency dispatch, the study carries out relevant exploration on the basis of emergency event level analysis and transportation planning. The emergency rescue demand evaluation system is constructed using the superior and inferior solution distance method to carry out the emergency hierarchy analysis. The police emergency dispatch model is constructed and solved using the improved particle swarm algorithm. The validation revealed that the improved solution algorithm improved the iteration efficiency by 54.33% on average and reduced the iteration time overhead by 56.10% on average over the particle swarm algorithm and the beetle antennae search algorithm. In the scheduling of emergency 1, the material demand satisfaction rate of all demand points was above 80%, among which the vegetable material demand satisfaction rate was 100%. In the scheduling of emergency 2, the demand for supplies at all demand points was above 91.3%, with the demand satisfaction rate for tent supplies as high as 100%. The above results indicate that the police emergency dispatch method can leverage the full advantages of transportation networks. By integrating intelligent optimization algorithms with artificial intelligence technology, the method achieves material dispatch for cross-regional emergency rescue incidents. This method is both feasible and practical.
UV-ozone-induced quasi-tunnel layer for charge-trapping synaptic transistors and its application in neuromorphic computing
Charge-trapping thin-film transistor (CT-TFT) is a reliable structure for fabricating neuromorphic devices, owing to its non-volatile memory characteristics. However, the performance of charge-trapping synaptic transistors is critically limited by the requirement for high-quality tunnel layers, which typically rely on costly vacuum-based fabrication processes. Thus, developing a low-cost and scalable strategy for engineering tunneling interfaces remains a key challenge in neuromorphic electronics. In this work, an ultraviolet-ozone treatment was employed to grow, in situ, a dense and smooth alumina quasi-tunneling layer on a low-temperature annealed, solution-processed alumina charge-trapping layer. After the treatment, the alumina surface became smoother and exhibited significantly reduced defect density, leading to an increase in the Ion/off ratio from 104 to 106. The programming and light-assisted erasing properties of the resulting CT-TFTs were systematically evaluated under various applied voltages and light power densities. By modulating presynaptic action potential signals, typical synaptic behaviors were successfully simulated. Finally, a vision transformer-based neural network was employed to evaluate system-level performance, achieving a recognition accuracy of 89.5% on the classification of the Yale face image dataset. This work provides a simple and scalable route for engineering quasi-tunnel interfaces in oxide electronics and highlights their potential for low-cost, high-performance neuromorphic computing systems.
Immature anophelines and their habitat characteristics in an urban setting of central Ethiopia
Phenotypic variations of naturally grown Iris persica L. accessions as revealed using multivariate analytical methods
Iris persica L. is a high-value ornamental species naturally distributed across montane regions of Iran, yet its intraspecific morphological variation remains underexplored. Understanding phenotypic diversity among wild accessions is critical for identifying superior genotypes suitable for conservation and horticultural breeding. This observational study was conducted on 78 naturally occurring I. persica accessions collected from seven ecogeographical regions of Markazi Province, Iran. Each accession represented a single independently growing individual plant, and 39 morphological and colorimetric traits were evaluated using multivariate statistical analyses. The results revealed considerable variation among accessions. Descriptive statistics showed that flower diameter ranged from 34.52 to 80.56 mm, fall length from 35.39 to 57.70 mm, and spathe length from 25.86 to 64.56 mm. Principal component analysis identified ten principal components explaining 82.46% of the total variation, with the first component (33.30%) driven primarily by flower size, fall length, and spathe length. The heatmap analysis clustered accessions into four distinct morphological groups, indicating clear phenotypic differentiation. Correlation analysis revealed significant positive associations between flower diameter and flower surface ( r = 0.87, p < 0.01), fall length and flower surface (r = 0.76, p < 0.01), and flower diameter and flower length ( r = 0.76, p < 0.01). Stepwise regression analysis indicated that fall length, flower diameter, and spathe length were key predictors of flower diameter. This study demonstrates extensive morphological diversity in I. persica , providing a strong basis for the selection of superior genotypes for ornamental breeding programs. Accessions such as ‘Alibolaghi-6’, ‘Sorkhe-4’, ‘Sorkhe-14’, ‘Shahbaz-11’, ‘Sorkhe-11’, ‘Sorkhe-12’, ‘Sorkhe-6’, ‘Palangdarreh-8’, ‘Sorkhe-5’, and ‘Bolagh-8’ exhibited outstanding floral characteristics and are recommended as potential candidates for future cultivar development and conservation strategies.
Dislocation dynamics in noble-metal high-entropy alloys under nanoindentation: Neuroevolution potential insights
Neuroevolution-potential molecular-dynamics simulations reveal that stacking-fault-energy (SFE) governs nanoindentation plasticity in the noble alloys, AuPdAg and AuPdAgPt. The addition of platinum increases the SFE, delaying Shockley partial nucleation and suppressing early prismatic dislocation loop formation. AuPdAgPt therefore exhibits dense dislocation tangling and sessile junctions, reduced frequency of plastic events, and enhanced deformation resistance via forest hardening. In contrast, AuPdAg shows burst-like plasticity with dislocation density decaying due to loop annihilation. These results establish the SFE as a key descriptor for dislocation-mediated plasticity in noble-metal high-entropy alloys.
Quality of life and associated factors of adults with physical and visual disabilities residing in care-homes in the capital of a lower middle-income country: Sri Lanka
Bacterial profile and antimicrobial resistance patterns of bloodstream infections at Amhara Public Health Institute, Bahir Dar, Ethiopia
Background Managing bloodstream infections in resource-constrained regions like Ethiopia is challenging due to scarce blood culture surveillance data. To guide empirical therapy, this study determines the bacterial profiles and antimicrobial resistance patterns among patients with suspected bloodstream infections at the Amhara Public Health Institute. Methods This retrospective study analyzed blood culture records from the Amhara Public Health Institute spanning January 1, 2020, to December 30, 2023. Blood samples were processed using standardized manual culture techniques in accordance with World Health Organization (WHO) protocols. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method following Clinical and Laboratory Standards Institute (CLSI) guidelines. Statistical analysis was conducted using SPSS version 20, employing descriptive statistics and regression models, with statistical significance defined as p < 0.05. Results True bacterial pathogens were isolated from 50.3% (N = 340) of the 676 patients, with Gram-negative bacteria predominating (61.2%, N = 208) over Gram-positive bacteria (38.8%, N = 132). Notably, ESKAPEE pathogens accounted for 96.5% (N = 328) of all isolates, led by Klebsiella spp. (25.9%, N = 88), Enterococcus spp. (20.9%, N = 71), and S. aureus (15.6%, N = 53). Among Gram-positive isolates, high resistance was observed against oxacillin (74.5%, N = 41), penicillin (72%, N = 36), and vancomycin (51.1%, N = 24). Gram-negative isolates exhibited critical resistance to national frontline therapeutics, including ampicillin (100%, N = 24), ceftriaxone (92.4%, N = 157), and trimethoprim-sulfamethoxazole (89.4%, N = 126). Overall, multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) profiles were detected in 43.8% (N = 149), 30.5% (N = 104) and 5.3% (N = 18) of isolates with similar distributions observed among ESKAPEE strains. Sex and age were the only independent predictors of culture positivity, with female sex reducing bloodstream infection odds by 44% (p = 0.002). Conversely, neonates (≤ 28 days) and young adults (15–24 years) had 4.7 times (p = 0.001) and 9.5-times (p = 0.001) higher odds compared to elderly patients. Conclusions This study reveals a severe 50.3% (N = 340) bloodstream infection rate dominated by highly resistant Gram-negative and ESKAPEE pathogens, disproportionately affecting males, neonates, and young adults. Combating this threat requires immediate antibiotic stewardship, updated guidelines, and advanced laboratory testing (anaerobic culture, minimum inhibitory concentration, and molecular sequencing) to track and manage resistance.
Theoretical roadmap for suppressing electrically induced spin decoherence in silicon T centers via dynamical decoupling
Silicon T centers are highly promising for scalable quantum networks, yet the critical transition from optical pumping to practical electrical injection introduces severe decoherence challenges. Specifically, macroscopic charge transport generates aggressive itinerant carrier scattering and stochastic local electric field fluctuations, which drastically degrade the spin phase memory of the localized electron. To quantify and address this fundamental vulnerability, we develop a comprehensive open quantum system model to map these current-driven noise channels. Our dynamics simulations demonstrate that applying active dynamical decoupling sequences effectively filters the dominant low-frequency charge noise and successfully reverses the coherence collapse. Furthermore, we extract a universal engineering scaling law revealing that microwave control rates exceeding 50 MHz can sustain fault-tolerant single-qubit gate fidelities above 99% at high device brightness. This established theoretical framework provides a quantitative blueprint for realizing fully integrated, electrically driven optoelectronic quantum nodes.
Investigation on the effect of waved struts on the energy absorption of BCC base mechanical metamaterials
Temporal trends in children pertussis burden in China and worldwide from 1990 to 2023: An analysis of the Global Burden of Disease Study 2023
Objective To evaluate the burden trends of children pertussis worldwide and in China from 1990 to 2023, and predict the disease burden for the next 10 years using a secondary analysis of Global Burden of Disease (GBD) 2023 data. Methods The primary metrics were mortality, disability-adjusted life - years (DALYs), prevalence, and incidence. A join – point regression model was used to estimate the average annual percentage change (AAPC). The autoregressive integrated moving average (ARIMA) model was used to predict the disease burden of pertussis from 2024 to 2033, and its adequacy was confirmed by the Ljung‑Box test. Results From 1990 to 2023, childhood pertussis mortality, DALYs, prevalence, and incidence declined sharply worldwide and in China. The global mortality rate in infants aged 1–5 months decreased by 57.7%, from 108.09 per 100,000 in 1990 to 45.73 per 100,000 population in 2023. Global age-standardized rates for both sexes, as well as those in all SDI regions, also showed steady downward trends. The rates of all four metrics peaked among infants aged 1–5 months in China and declined steadily with increasing age. For this infant group, the APC of pertussis prevalence and incidence in China decreased significantly during three different periods (1995–2004, 2009–2018, 2018–2021), but rose in two intervals (2004–2009, 2021–2023). ARIMA model projections revealed that age-standardized mortality and DALY rates will rise over the next decade, while prevalence and incidence will continue to decline. Notably, prevalence and incidence among infants aged 1–5 months are expected to increase slightly, rising from 277.59 and 2,026.43 per 100,000 in 2024 to 284.04 and 2,073.46 per 100,000 in 2033, respectively. Conclusion These findings underscore the disproportionate and persistent burden of pertussis in infants, indicating that prevention and treatment strategies should be adjusted to prevent further increase.
Multistate control in 2D CuCrP2S6/Sc2CO2 multiferroic heterostructures
The magnetoelectric (ME) coupling effect enables effective cross-control between electric and magnetic fields, providing a crucial pathway toward next-generation low-power electronic devices. Here, we propose a two-dimensional (2D) multistate multiferroic heterostructure (MMH) composed of out-of-plane polarized CuCrP2S6 and Sc2CO2 (CCPS/SCO) to realize electric field driven multistate spintronic devices. First-principles calculations demonstrate that the CCPS/SCO heterostructure can be reversibly switched among four nonvolatile polarization states (↑↑, ↑↓, ↓↓, ↓↑) using electrical pulses, enabling simultaneous control of electronic transport, magnetic ordering, and spin orientation within a single heterostructure. By encoding the four polarization states, three distinct quantum phases are identified, i.e., out-of-plane antiferromagnetic metal, in-plane ferromagnetic semiconductor, and out-of-plane ferromagnetic metal. The microscopic mechanism underlying this strong ME coupling originates from polarization-induced interfacial charge transfer and symmetry breaking, which synergistically shift the energy level and tune the orbital occupation of Cr-d orbitals. Our proposed CCPS/SCO MMH heterostructure establishes a promising platform for high-density, low-power, and functionally reconfigurable spintronic memory.
Bottom layer internal wave dynamics in the deep sea from decade-separated long-term observations
Leveraging free-text clinical records for heart disease classification through structured feature mapping
Hypertension and diabetes are major risk factors for heart disease, which remains among the leading causes of morbidity and mortality worldwide. Heart disease includes heart failure, myocardial infarction, stroke, and atherosclerosis. The identification and monitoring of these risk factors are crucial for early intervention and effective management. Machine learning techniques have the potential to improve the management and prevention of heart disease by enabling the automatic detection of risk factors, which in turn can help doctors personalize treatment and facilitate preventive interventions. In this study, heart disease risk factors were automatically extracted using a combination of multimodal data: both unstructured clinical narratives (e.g., the PrevComp corpus) and structured datasets (e.g., the UCI heart disease dataset) were used to predict the presence or absence of heart disease. The classification model is based on the Light Gradient Boosting Machine (LightGBM), a state-of-the-art implementation of the gradient boosting framework that employs tree-based learning algorithms. The developed classification model demonstrated a robust predictive accuracy of 83% for the presence/absence of heart disease, supporting its potential to accurately identify high-risk patients and improve clinical outcomes.
Stochastic spiking in magnetic droplet solitons
The nonlinear dynamics of droplet solitons make them highly promising candidates for brain-inspired computing, including neuromorphic systems, deep physical neural networks, physical spiking neural networks, and transformer-based physical architectures. Integrating droplet solitons into neuromorphic device architectures enables low energy consumption and ensures CMOS compatibility, positioning them for efficient hardware implementations of cognitive and perception-related tasks. However, previous studies have primarily relied on the application of external magnetic fields, which poses significant challenges for on-chip integration in practical computing applications. In this paper, we investigate in detail the nucleation, stability, and dynamics of droplet solitons in nanoconstriction-based spin Hall nano-oscillators (NC-SHNOs) by incorporating unconventional spin–orbit torque under bias-field-free conditions using micromagnetic simulations. We demonstrated stochastic spiking-like behavior in droplet solitons due to drift instability. The intrinsic stochastic spiking-like behavior can be implemented to generate true random numbers, which successfully pass the National Institute of Standards and Technology test suite. Our results reveal the nonlinear dynamics of droplet solitons in NC-SHNOs and deepen our understanding of their practical potential as hardware-based true random number generators, with promising implications for secure communication, neuromorphic computing, and reservoir computing architectures.