Browse Articles

Fabrication of cation exchange sponges based on melamine-formaldehyde sponges

Analytical study of mode filtering in a duct with resistive layers

This paper presents an analytical mode-matching framework to examine acoustic wave propagation in a cylindrical waveguide structure featuring a central porous cavity bounded by flexible membrane discs. Unlike conventional models that consider rigid or purely absorptive boundaries, the proposed approach accounts for the dynamic response of membranes and the coupled behavior of air and porous media, enabling accurate representation of fluid–structure interactions. The acoustic field is decomposed into symmetric and anti-symmetric modal components to capture key physical phenomena such as mode conversion, energy dissipation, and complex reflection–transmission mechanisms. Continuity conditions at the interfaces are applied to determine the interaction of wave modes between subdomains, allowing the calculation of reflected, transmitted, and absorbed acoustic powers. Numerical results demonstrate strong reflection and efficient low-frequency absorption, with negligible transmission. Parametric analysis reveals that increasing the length of the porous cavity enhances sound attenuation by intensifying dissipative effects. These findings highlight the effectiveness of the multilayered configuration as a frequency-selective acoustic filter, offering a tunable and practical solution for silencers and noise control in engineering structures.

An adaptive, continuous-learning framework for clinical decision-making from proteome-wide biofluid data

Abstract Mass spectrometry (MS)-based proteomics provides deep molecular insights from patient samples, but clinical use has been limited by missing values, static biomarker panels, and the need for targeted assay development. We present a framework – Adaptive Diagnostic Architecture for Personalized Testing by Mass Spectrometry (ADAPT-MS) – that enables direct diagnostic and prognostic interpretation of discovery-mode proteomics data at the level of individual samples. ADAPT-MS dynamically retrains simple, robust classifiers based on the proteins quantified in each sample, eliminating the need for imputation or fixed panels. Applied to plasma and cerebrospinal fluid datasets across diseases and clinical centers, it achieves high performance and generalizability using robust, transparent and generalizable statistical models. A single proteomic measurement can support multiple diagnostic questions via retrospective cohort matching, with each classification taking only seconds. As population-scale proteomics datasets grow, this approach lays the foundation for scalable, real-time, and personalized diagnostics directly from proteome-wide data. Such a community effort may help to transform discovery proteomics into a routine clinical tool.

Sustainable design of organic solar cells utilized machine and deep learning

Abstract In this work, an Organic Solar Cell (OSC) with a structure of ITO/PEDOT: PSS/PBDB-T: IT-M/PFN-Br/Al is extensively simulated and optimized. The impact of layer thicknesses and materials on device performance is simulated using a one-dimensional solar cell simulator (SCAPS-1D). The simulation model is first validated using experimental data, and it shows a high degree of alignment. Among the various Electron Transport Layers (ETLs) that are investigated, PFN-Br has the highest Power Conversion Efficiency ( PCE ) of 12.04%. The PFN-Br thickness is shown to be most effective at 5 nm. A simulated PCE of 19.50% results from the active layer reaching its optimum efficiency at 300 nm. PEDOT: PSS is the most effective Hole Transport Layer (HTL) with reliable performance at thicknesses ranging from 30 to 100 nm. Due to optical interference, the short-circuit current density ( $$\:{J}_{sc}$$ ) slightly increases. Additionally, based on structural parameters, PCE and open-circuit voltage ( $$\:{V}_{oc}$$ ) are predicted by using Artificial Intelligence (AI) models, including Convolutional Neural Networks (CNN) and Support Vector Regression (SVR). CNN achieves the highest prediction accuracy in modelling PCE , demonstrating its ability to model nonuniform photovoltaic behavior. This combined approach using both detailed simulations and AI‑based prediction doesn’t just make organic solar cells more efficient. It also supports the larger goal of making clean energy more accessible and sustainable. By fine‑tuning device designs, cutting down material waste, and simplifying fabrication, this work can help move the world closer to achieving key Sustainable Development Goals (SDG 7, 9, 12, and 13). In this way, advances in solar technology can play a meaningful role in addressing climate and energy challenges.

Pathways to promote the performance of healthcare financial expenditure from an audit perspective: Evidence from Hunan Province

Strengthening the audit supervision of healthcare financial expenditures and improving the performance of healthcare expenditures are critical to achieving the Healthy China strategy. This study uses data from 14 cities in Hunan Province from 2013 to 2022 and employs the DEA-Malmquist analysis method to analyze the existing problems and institutional incentives for healthcare financial expenditures in Hunan Province on the basis of estimating the performance of healthcare financial expenditures in each city. The results show that the overall performance level of healthcare financial expenditure in Hunan Province is low, and the efficiency of healthcare expenditure is trending downward. The majority of cities are in the state of increasing scale efficiency of healthcare expenditure, with insufficient scale of inputs. The main reason for the decline in efficiency is the low technological progress change index. The fundamental reasons are the shortcomings of the healthcare financial expenditure system, insufficient binding force, and inadequate supervision. Based on this, the article explores the audit mechanism of changes in expenditure performance, and then proposes specific ways for the audit to promote the improvement of healthcare financial expenditure performance, in order to give full play to the supervision and guarantee role of the audit in promoting healthcare financial expenditure performance.

Oligoprotein type I interferon signatures, but not TREX1 variants, increase risk of systemic lupus erythematosus in UK Biobank

Abstract The 3′ − 5′ DNA exonuclease, TREX1, is a negative regulator of the type I interferon response, while TREX1 variants are considered to confer risk for non-monogenic systemic lupus erythematosus (SLE). Here we analyse TREX1 sequences in 469,229 UK Biobank participants together with multi-omics data from the UK Biobank Pharma Proteomics Project to reappraise the contribution of reported TREX1 risk variants in SLE. We find that TREX1 variants are not associated with increased risk for SLE in UK Biobank, and most reported risk variants are functionally neutral in mutagenesis experiments. Deriving an oligoprotein interferon signature from broad capture proteomics, we find that this signature is associated with elevated SLE risk, but is not elevated in TREX1 variant carriers. Furthermore, TREX1 variants are not associated with other autoimmune diseases with a prominent oligoprotein interferon signature. Finally, meta-analysis of published studies confirms the lack of support for the association between SLE and TREX1 risk variants. In summary, we find that, while oligoprotein type I interferon signatures increase risk of SLE, TREX1 variants do not.

A hybrid fuzzy-PIDD² control strategy for coordinated LFC and AVR in renewable-integrated multi-area power systems

Abstract This paper presents a novel hybrid control strategy that integrates a Fuzzy Proportional–Integral–Derivative Double Derivative (FPIDD²) controller with a conventional PIDD² controller for Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) in multi-area interconnected power systems, respectively. The proposed FPIDD²+PIDD² hybrid scheme enhances the overall dynamic stability and robustness of power systems operating under high renewable energy penetration. Controller parameters are optimally tuned using different metaheuristic algorithms, namely the Particle Swarm Optimization (PSO), Gorilla Troops Optimizer (GTO), and Marine Predators Algorithm (MPA). The proposed hybrid controller’s performance is evaluated against conventional PID and standalone PIDD² controllers under various disturbances, including step load changes, random load variations, and renewable energy fluctuations, where control performance is evaluated based on the Integral of Time-weighted Absolute Error (ITAE) criterion. Within the simulated test cases, the proposed FPIDD²+PIDD² controller achieves notable performance improvement, reducing ITAE by up to 94% and 90% compared to conventional PID and standalone PIDD² controllers, respectively. These results confirm the hybrid controller’s smooth transient response, enhanced damping, and improved robustness against nonlinearities and system uncertainties.

Inner synchronization of controlled multi-valued logical networks

This paper studies the inner synchronization problem of multi-valued logical networks by introducing an external single node, which is also called the driving node. Firstly, for the case where the synchronized state of all network nodes equals the state of the driving node, the inner synchronization model of the controlled multi-valued logical network is established, and a necessary and sufficient condition is obtained using the semi-tensor product. Secondly, based on the above synchronization model, a more general model of inner synchronization is discussed, where all nodes of the multi-valued logical network synchronize with each other, but not necessarily to the same as state of the driving node; inner synchronization criteria are established through theoretical proof. Finally, two simulation examples are given to verify the validity of the conclusions.

A spatially resolved atlas of gastric cancer characterises a lymphocyte-aggregated region

Multifunctional application of zeolite for ammonium removal and ammonia emission mitigation in wastewater, carcass leachate, and paddy

Children’s perspectives of their everyday food practices: insights to inform policy and interventions

Children’s everyday food practices have a profound impact on their physical, mental, cultural and social health and wellbeing. Grounded in social practice theory, the focus of this paper is the examination of the performance of food practices, rather than the practitioner. This approach supports health promoting efforts to move away from victim blaming and instead explore the intersections between individual, social and structural determinants of food practices. With foundations in the New Sociology of Childhood, this article explores eight- to twelve-year-old children’s perspectives of the enablers and constraints to their performances of everyday food practices through a social practice theory lens. Children participated in sequential creative draw-and-tell interviews and Photovoice methods. Through abductive analysis of qualitative data, diverse interlinking configurations of the meanings, materials and competences were attributed by children as either facilitating or constraining food practice performances further impacted by transitioning times, places, social settings and contexts. A case study of food shopping practices was able to present a holistic narrative of how individual, social and structural determinants intertwined across the temporal and spatial dimensions. This study showcases how a social practice led approach that privileges children’s voices can be used to inform more holistic, equitable, engaging and effective health policy and practice that endeavour to impact children’s routine and habitual food practices.

Evolution of manganese low-energy photoredox catalysis from high-energy visible light photocatalysis

Life expectancy after kidney transplantation in a population-based retrospective cohort

Correction: Retraction: Downregulation of FBP1 promotes tumor metastasis and indicates poor prognosis in gastric cancer via regulating epithelial-mesenchymal transition

Vegetation greening drives long-term dust mitigation in Eastern Asia

Differential mechanisms of SARS-CoV-2 inactivation by anionic surfactants: a comparative study of fatty acid salts and synthetic surfactants

Correction of the curve of spee using clear aligner therapy: A finite element analysis of three lower anterior intrusion protocols

Background Correction of the curve of Spee (COS) often requires lower anterior intrusion, which remains one of the least accurate tooth movements in clear aligner therapy (CAT). This limited accuracy may be influenced by the anchorage system or the design of the intrusion strategy. This study aimed to evaluate the movement trends and stress distribution in the lower anterior teeth subjected to three different intrusion protocols using finite element analysis (FEA). Methods Three-dimensional models of the mandibular dentition, periodontal ligaments (PDLs), bone, attachments, and clear aligners were constructed using Materialise Mimics and Materialise 3-matic software. The assembly of the anatomical structures was developed using Autodesk Inventor, and FEA was performed using FeBio software. Three protocols with different anterior intrusion designs were evaluated: S1 (simulation 1) — intrusion displacements of 0.25 mm were applied simultaneously to the canines, central, and lateral incisors; S2 (simulation 2) — intrusion displacements of 0.25 mm were applied only to the lateral and central incisors; S3 (simulation 3) — intrusion displacements of 0.25 mm were applied only to the canines. Total displacement, equivalent strain, and the distribution of minimum and maximum principal stresses were analyzed. Results Simultaneous intrusion (S1) produced the most balanced movement with the lowest stress in the target teeth and controlled bone displacement. Intruding only the incisors (S2) increased PDL stress and anchorage extrusion but also caused minor canine intrusion, indicating force propagation through the aligner. Canine-only intrusion (S3) elevated stress in the canines and produced slight incisor intrusion. Posterior teeth functioned effectively as anchorage in all simulations. Conclusion Simultaneous intrusion of canines and incisors is the most biomechanically efficient approach for COS correction with aligners, minimizing stress and unwanted side effects. Isolated intrusion of either group requires careful planning to manage secondary movements and anchorage control.

Unveiling the environmental impact of earthquakes in Europe

Forage quality shapes physiological and gut microbial responses in moose (Alces alces) of Isle Royale National Park

Abstract Plant secondary compounds (PSCs) impose physiological and nutritional constraints on herbivores, yet many species continue to rely on PSC-rich forage during critical periods of the year. Moose ( Alces alces ) on Isle Royale National Park depend heavily on balsam fir ( Abies balsamea ) during winter, exposing them to a chemically defended and nutritionally limited diet. To investigate how this foraging strategy shapes both physiological responses and gut microbial communities, we integrated fecal diet composition, urinary markers of detoxification and nutritional status, 16S rRNA gene sequencing, and shotgun metagenomic profiling from free ranging moose of two separated populations from the western and eastern region of the island. Balsam fir consumption varied strongly by region and was positively associated with glucuronic acid to creatinine (GA:C) and urea nitrogen to creatinine (UN:C) ratios, indicating increased detoxification activity and reduced nutritional condition. Microbial alpha diversity declined with higher fir intake in nutritionally limited individuals, while beta diversity differed by region, balsam fir consumption, and UN:C. Several bacterial genera responded to PSC exposure, including increases in the butyrate-producing genus Roseburia and shifts in network prominence of Phascolarctobacterium . Metagenomic data revealed pathways involved in the degradation of aromatic and terpenoid PSCs, although pathway abundances did not differ significantly with balsam fir consumption after multiple testing correction. These results show that winter foraging on balsam fir produces coordinated dietary, physiological, and microbial patterns, with both host and gut microbial detoxification capacities interacting to accommodate the chemical and nutritional challenges of a PSC-rich winter diet.

Unveiling the molecular mechanisms of burn injury through integrated single-cell and bulk transcriptomic analysis

Purpose Burn injuries are prevalent and have a significant effect on patients’ quality of life and healthcare costs. Current treatment modalities, such as wound care and surgical interventions, often face challenges due to complications like infection and inadequate healing. Methods This study adopted single-cell RNA sequencing (scRNA-seq) to investigate the cellular landscape of the burn microenvironment. After rigorous quality control filtering, 9,248 cells were retained for analysis. Using UMAP dimensionality reduction, these cells were annotated into 14 subpopulations, including Neutrophils, Macrophages, and T cells. Differential gene analysis and machine learning techniques, such as LASSO regression and random forest selection, were employed to identify marker genes. Results Macrophages exhibited significant interactions with other cell types, indicating their pivotal role in immune signaling within the burn microenvironment. A total of 155 genes were identified as markers for Macrophages, with AP2A2, CCL7, and TF emerging as key features. Immune infiltration analysis also revealed notable differences in the proportions of immune cells, particularly Mast cells and Neutrophils, highlighting on their involvement in disease progression. Conclusion This study provides novel insights into the immunological microenvironment of burn injuries. Despite limitations including a modest sample size and lack of experimental validation, our findings establish a foundation for future investigations into targeted immunotherapeutic strategies, potentially improving clinical outcomes and advancing personalized treatment approaches for burn patients.