Browse Articles

A digital twin-driven multi-agent deep reinforcement learning framework for synergistic resource scheduling in revolutionary heritage and sports tourism integration

Correction for Wang et al., The role of reduced aerosol masking from air pollutant emission reductions in recent global warming acceleration (2013–2023)

Artificial neural network modeling to predict corrective stress of a two-layer composite plate under fully reversed cyclic loading using the finite element method & morrow method

Abstract In this study, a single-hidden-layer feedforward Artificial Neural Network was developed to predict the maximum stress of a two-layer composite plate based on the Morrow correction method under fully reversed cyclic loading. A rectangular two-layer plate made of Epoxy Carbon Woven (230 GPa) was analyzed using the Finite Element Method for various fiber orientations of each layer (0°, 15°, 30°, 45°, 60°, 75°, and 90°) relative to the transverse axis. The results indicate that a 0° fiber orientation in both layers produced the maximum stress, potentially weakening the plate under tensile load, whereas a 90° orientation minimized stress and enhanced tensile strength. Increasing the second-layer angle while keeping the first layer fixed reduced stress, whereas decreasing the first-layer angle for a fixed second-layer angle increases stress. Maximum stress regions shifted from localized points to linear distributions, sometimes moving from uniform edge distributions to mid-edge concentrations. When both layers had identical angles, the stress magnitude increased, and the maximum stress shifted from the loaded edge to a corner, indicating stress concentration and a potential reduction in lifespan. The Artificial Neural Network demonstrated excellent predictive performance, achieving an optimal validation Mean Squared Error of 3.2266 × 10⁻ 4 at iteration 22, with a minimum overall Mean Squared Error of 6.5566 × 10⁻ 4 across all datasets. The correlation coefficients for the training, validation, test, and entire datasets were 0.99508, 0.98649, 0.99484, and 0.99485, respectively, indicating a strong agreement between the Mean Squared Error predictions and Finite Element Method-simulated values.

A reset clock cannot keep time: Thermal overprinting obscures Great Unconformity origins in North China

Associations of extreme temperature and relative humidity with hematological disease mortality in Chuzhou, China

European beech reproduction is not reduced by drought, including the 2003, 2018, and 2022 extremes

Climate change is intensifying drought stress in temperate forests, but its effects on tree reproduction, central to forest regeneration and migration capability, remain poorly understood. Here, we analyze 221 time series of beech ( Fagus sylvatica ) seed production across Europe to test whether drought reduces seed output. We isolate drought exposure during the flowering, pollination, and seed maturation phases of reproduction, and test for legacy effects on future reproduction. Seed production was not impaired by summer drought, and dry spring conditions were associated with increased output, likely via enhanced pollen dispersal. Thus, once initiated, beech reproduction is not reduced by drought, with no suppression of reproduction the following year. Reproduction was not reduced at the driest sites during exceptional European summer droughts in 2003, 2018, and 2022. Considered alongside prior evidence that drought suppresses forest growth and elevates mortality, these findings indicate that vital rates can respond in opposite directions to the same stressor. Such contrasts may sustain forest reproduction during heat–drought events yet shift demographic balance toward higher mortality and turnover as climatic extremes intensify.

Prevalence and risk factors associated with urinary tract infections and sexually transmitted diseases among young adults in Poland

Abstract The global burdens of urinary tract infections (UTIs) and sexually transmitted diseases (STDs) are on the rise, underscoring the importance of tailored prevention and treatment approaches for specific groups. We conducted a cross-sectional, online survey among Polish students aged ≥ 18 years. Recruitment was conducted through social media and verbal invitations. The prevalence of UTI and STD and their associated risk factors were assessed. A total of 617 young adults (mean age: 21 years) participated in the study, including 79.4% women. Among all study participants, approximately 50.0% reported at least one episode of UTI, and 37.6% experienced recurrent UTIs. In multivariable logistic regression, sexual activity (OR = 7.57, 95% CI: 4.34–13.20), family history of UTIs (OR = 4.35, 95% CI: 2.73–6.95), urine retention (OR = 3.45, 95% CI: 2.13–5.58) and inadequate daily water intake (OR = 2.42, 95% CI: 1.44–4.08) were significantly associated with UTIs, with recurrent infections additionally associated with the use of intimate hygiene products. Overall, nearly 78% were sexually active, and about 10% of them engaged in chemsex. The findings highlight the high UTI burden in young adults and the need for targeted prevention. The high rate of risky sexual behaviors emphasizes the importance of STDs testing in young adults.

Reply to McDannell et al.: Thermal overprinting does not obscure the tectonic origin of the Great Unconformity

16,648 reasons to live instead of dying by suicide: insights from a computer-assisted content analysis

Abstract Most research on suicide focuses on the progression toward lethal action. Fewer studies have looked at individuals’ past experiences with the desire to die and why they did not die by suicide. Moreover, the existing use of reasons to live in assessment and treatment is generally grounded in inventories of questions that, while groundbreaking and well validated, were developed decades ago and without a focus on individuals’ lived experiences. In this study, an online user’s query to formerly suicidal people on the popular Reddit platform afforded a novel opportunity to investigate reasons people lived in a large, naturally occurring sample of 16,648 self-reports about their experiences. Using a new method for computer-assisted qualitative content analysis, we identify categories, and themes organizing those categories, that affirm prior work and also provide new perspectives on that work, as well as suggesting connections between ideas in the literatures on reasons people die, reasons people live, and subjective and psychological well-being. The study highlights the value of computer-assisted methods as a way of achieving both scale and interpretable results, and it identifies a number of theoretical and clinical avenues for further investigation.

Assessment of diverse deep brain stimulation targets uncovers a common neural pathway for instantaneous antidepressant effects in rats

Deep brain stimulation (DBS) is a promising therapeutic modality for managing treatment-resistant depression. Most DBS research has focused on single brain regions resulting in unclear optimal stimulation targets and vague mechanisms. Here, we introduce an experimental paradigm in which multiple graphene fiber stimulating electrodes were implanted in various brain regions of the same depressive animal for behavioral testing and DBS-functional MRI studies. We observed an instantaneous alleviation of depressive-like symptoms with a high response rate in Wistar-Kyoto rats following DBS at the medial forebrain bundle (MFB), lateral habenula (LHb), ventral tegmental area (VTA), and dorsal raphe nucleus (DRN), with a highly similar blood-oxygenation-level-dependent (BOLD) activation pattern, engaging the cortical areas, limbic, serotonin, and dopamine system where the BOLD activation levels in the medial prefrontal cortex (mPFC) and cingulate cortex showed strongest correlation with the degree of depression alleviation. No antidepressant effects were observed in DBS at the mPFC or nucleus accumbens. Lesion of VTA dopaminergic neurons resulted in a decrease in the extent of depression alleviation and BOLD activation levels. These results indicate that DBS targeting the MFB, LHb, VTA, and DRN might represent a rapid-acting antidepressant therapy by activating a highly overlapping dopamine-related neural network.

Multi-UAV cooperative path planning based on multi-strategy enhanced multi-objective phototropic growth algorithm

Abstract To address the bottlenecks faced by traditional ground transportation in hilly terrain due to topographical constraints, this study proposes a multi-strategy Enhanced Multi-Objective Phototropic Growth Algorithm (EMOPGA) to tackle the challenges of multi-Unmanned Aerial Vehicles (UAV) cooperative transport for material delivery tasks. This approach aims to overcome the limitations of standard Phototropic Growth Algorithm (PGA), such as susceptibility to local optima and suboptimal initial population quality. It constructs an optimization framework by integrating chaotic mapping for initialization, Lévy flight mutation operators, and an environmental selection mechanism based on Pareto dominance and elite retention strategies. Simulation experiments across nine scenarios demonstrate that EMOPGA achieves a 112.11% improvement in the Average Hypervolume (HV) metric and a 43.11% reduction in the Spacing (SP) metric compared to MOPGA. In comparative experiments against 11 representative algorithms in the complex scenario, EMOPGA achieved an average HV of 9.31 × 10 13 and an average SP of 0.0322. Specifically, EMOPGA achieves a 29.1% HV improvement over MOPGA (the best HV baseline) and a 75.0% SP reduction relative to MOEA/D (the best SP baseline). EMOPGA provides an efficient optimization paradigm for multi-UAV path planning in complex terrain, combining high convergence, strong uniformity, and robust performance. It demonstrates significant potential for practical applications in logistics and emergency response.

Reply to Górski et al.: Polarization requires opinions, not just negative ties

Quantitative contribution of dissolution-driven precipitation to Pb(II) removal by biochars during adsorption process

Two-step mechanism of Bruton’s tyrosine kinase membrane recruitment and activation

Peripheral membrane proteins (PMPs) are critical mediators of signaling cascades initiated at the cell surface. Their functions depend on their innate ability to interact dynamically with membranes in response to changing cellular conditions. This membrane recruitment may occur via high-affinity interactions with specific lipids/proteins or via transient, low-affinity interactions with the membrane. These weak and dynamic interactions, which are critical regulators of PMP function, are challenging to capture. Taking Bruton’s tyrosine kinase (BTK), a nonreceptor tyrosine kinase essential for B cell activation, we demonstrate a native mass spectrometry platform to understand lipid-mediated recruitment of PMPs by directly studying it from lipid bilayers customized to target membranes. Our data demonstrate that BTK recognizes phosphatidylserine (PS) independently of phosphatidylinositol (3, 4, 5) phosphate (PIP 3 ) binding. We show that PS-bound BTK retains PIP 3 binding via high-affinity sites, while exhibiting PIP 3 -independent basal membrane recruitment. Biochemical assays show that this PS-mediated recruitment sensitizes BTK to PIP 3 -mediated activation at near-physiological PIP 3 concentrations. Thus, we propose a two-step model for BTK membrane recruitment and activation. A low-affinity interaction with high-copy number PS enables plasma membrane recruitment of BTK and increases its membrane-bound concentration. Upon B cell activation, this prerecruited, membrane-bound BTK population localizes to PIP 3 -rich domains via electrostatic gliding along the membrane, driven by low-affinity PS and high-affinity PIP 3 binding. This indicates a cooperative mechanism in which PS can amplify B cell signaling by increasing membrane-bound BTK levels. Our work demonstrates a general model of regulation of PH domain–containing proteins by weak protein–lipid interactions, which can be extended to other PMPs.

Cognitively aligned pattern learning: a knowledge-sensitive adaptive framework for multi-class pattern recognition in sEMG systems

Pangenome-guided immunoinformatics design and in silico characterization of a multi-epitope vaccine candidate against Acinetobacter baumannii with nanoparticle assembly potential

Abstract Acinetobacter baumannii is a critical multidrug-resistant pathogen causing severe healthcare infections with high mortality, yet no licensed vaccine exists. This study aims to identify universally conserved surface antigens through pangenome analysis, predict immunogenic epitopes using integrated machine learning, and computationally design and in silico characterize a self-assembling nanoparticle vaccine with dual adjuvants. A computational framework integrating pangenome analysis of 712 complete genomes, epitope prediction, and structural vaccinology was employed to design a multi-epitope nanoparticle vaccine candidate for experimental evaluation. Pangenome analysis identified 3894 core genes with 42 outer membrane proteins, prioritizing OmpA, BamA, and OmpW as antigen targets. Protein language models predicted conformational B-cell epitopes, while NetMHCpan-4.2 predicted T-cell epitopes across 125 HLA alleles. The final construct (AB-VAX-01, 289 amino acids) incorporates 15 epitopes fused with dual adjuvants (RS09 TLR4 and cGAMP STING agonists) and a foldon domain for nanoparticle assembly. Microsecond molecular dynamics simulations with replicates demonstrated stability with TLR4 and STING. Conservation analysis across all 712 genomes showed 96.2–100% epitope identity. Immune simulations predicted Th1-biased responses with 94.2% global population coverage. In silico cloning confirmed favorable codon adaptation parameters. This in silico characterized vaccine construct represents a promising candidate requiring experimental validation against A. baumannii infections.

Metastable excited states of iodide–alkyl halide cluster anions: Insights from photodetachment spectroscopy and non-Hermitian quantum chemistry

We present experimental and theoretical results for photodetachment from a series of iodide–ethyl halide cluster anions, I−·C2H5X (X = Cl, Br, I). We also analyze previously reported results for the iodide–methyl halide series I−·CH3X, as comparisons between the two series are instructive. The photoelectron angular distributions for detachment from I−·C2H5Cl, I−·C2H5Br, and I−·CH3Cl are remarkably similar to detachment from unclustered iodide, while those of I−·C2H5I, I−·CH3Br, and I−·CH3I are clearly different, suggesting that autodetachment mediated by excited anion states competes with direct detachment. In addition, the I−·C2H5I and I−·CH3I cluster anions reveal a fragmentation pathway that is clearly inconsistent with direct detachment. By means of equation-of-motion coupled-cluster theory combined with a complex absorbing potential, we identify metastable excited anion states in the detachment continuum whose positions explain why the photoelectron angular distributions of only some of the cluster anions are influenced by autodetachment. However, these resonances do not evolve into bound anion states and, therefore, do not mediate photofragmentation. Rather, our calculations reveal for each cluster a second anion state that is related to virtual states in electron–molecule scattering. For such states, the Born–Oppenheimer approximation breaks down, resulting in a characteristic shape of the adiabatic potential energy surface and finite probability for decay into the detachment continuum even in regions where the anion state is below the neutral state.

Thick filament molecular interfaces play a critical role in the pathogenesis of hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) variants in genes encoding the myosin heavy chain (MHC) ( MYH7 ), myosin light chains ( MYL2 and MYL3 ), and cardiac myosin binding protein-C (cMyBP-C, MYBPC3 ) lead to cardiac hypertrophy, with abnormal contractility, relaxation, and energy consumption. Here, we defined the structural consequences of pathogenic and benign missense variants in these genes by mapping 233 variants ( MYH7 , n = 175; MYBPC3 , n = 41; MYL2 , n = 12; MYL3 , n = 5) onto a cryo-EM-based atomic model of the human cardiac thick filament. We identified HCM variants residing in 30 molecular interfaces of the complex thick filament interactome, including the two main interfaces of the myosin interacting-heads motif (IHM), and interfaces involving the MHC, essential and regulatory light chains, and cMyBP-C. None of the 21 variants classified as benign were within interfaces. We demonstrated earlier disease onset and adverse outcomes in HCM patients with pathogenic variants within vs. outside of molecular interfaces, emphasizing their importance in normal thick filament function and improving risk stratification of patients.

Enhancing real-time traffic risk prediction with a cost-sensitive learning approach

Seniority eigenstate configuration interaction

Zero-seniority methods have shown great promise for the description of strongly correlated electronic systems. Other seniority sectors have been much less explored, and in particular, the maximal seniority sector and zero seniority have the same underlying algebraic structure. We introduce a seniority eigenstate configuration interaction in which the wave function is constrained to have good fixed local seniority for each paired orbital, by which we mean we partition orbitals into a pairing set with seniority zero, and a spin set with seniority one. We show how to build the effective Hamiltonian for this ansatz, and demonstrate that high-seniority wave functions have unexpectedly excellent accuracy for strongly correlated fermionic systems, with accuracy competitive with or better than seniority zero for the Hubbard model and for the dissociation of the nitrogen molecule.