Efficient Removal of Diclofenac Sodium and Hg(II) on Graphene Oxide/UiO-66-(OH) Composites.

Developing efficient adsorbents for removal of organic pollutants and heavy metals is essential for environmental protection. In this study, a series of GO/UiO-66-(OH) composites were synthesized and characterized using XRD, FT-IR, and SEM, confirming enhanced thermal stability, reduced aggregation, and maintained crystallinity of UiO-66-(OH) due to GO incorporation. Batch adsorption experiments showed that GO increased the adsorption capacity, with GO-8/UiO-66-(OH) achieving 324.

A Mixed-Valence and Mixed-Spin Two-Dimensional Ferromagnetic Metal-Organic Coordination Framework.

Spin-mixed systems with distinct magnetic sublattices present rich physical behaviors and hold promise for magnetic memory, thermomagnetic recording, and optoelectronics. However, most experimental studies remain confined to molecular magnetic salts rather than monolayer two-dimensional (2D) systems. Here, we report the synthesis and characterization of a 2D metal-organic framework (MOF) of Fe(Fe-DPyP), constructed from 5,15-di(4-pyridyl)-10,20-diphenylporphyrin (DPyP) molecules and iron atoms on a Au(111) substrate.

Deciphering metabolic disease mechanisms for natural medicine discovery via graph autoencoders.

Metabolic diseases, such as diabetes, pose significant risks to human health due to their complex pathogenic mechanisms, complicating the use of combination drug therapies. Natural medicines, which contain multiple bioactive components and exhibit fewer side effects, offer promising therapeutic potential. Metabolite imbalances are often closely associated with the pathogenesis of metabolic diseases.

Evaluation approach of prefabricated components based on multi-layer complex network model combined with improved topsis method.

Prefabricated buildings face greater and different prefabricated components throughout their entire lifecycle, leading to a significant increase in management difficulty. This article proposes an evaluation method based on a multi-layer complex network model combined with an improved topsis. Firstly, by combining relevant regulations, literature, and engineering experience, the factors affecting the connection of components in prefabricated building are identified and the relationships between these factors are clarified to construct a multi-layered complex network model.

Integrating Radiative Cooling and Solar Heating for On-Demand Thermal Management.

Passive radiative cooling has been extensively explored as a sustainable alternative to traditional cooling systems. However, relying solely on this cooling mode restricts their application in temperature-fluctuating environments and may cause overcooling on cold days. To address this challenge, researchers are increasingly developing dual-mode devices that integrate radiative cooling with solar heating, utilizing the Sun's continuous heat source for passive heating.

Optimization analysis of air cooled open cathode proton exchange membrane fuel cell flow channel structure.

The cathode channel of air-cooled open-cathode proton exchange membrane fuel cell (AO-PEMFC) is both a reactant supply channel and a cooling and heat dissipation channel, and its structural design is a key factor affecting its output performance. Firstly, the numerical study of AO-PEMFC with different cathode channel bending angles was carried out, and the results showed that the output performance of a single cell with a cathode bending angle of 2.5° was improved by 3.

Adaptability assessment of the Enning road heritage district in China based on GA-BP neural network.

In complex urban systems, heritage districts must adapt beyond their original functions, requiring innovative reuse strategies to meet urban development demands. This study integrates socio-cultural and qualitative factors to enhance adaptive reuse predictions while fostering inclusive, community-driven renewal. Using a GA-BP neural network model, stakeholder mapping, and focus group interviews, the findings highlight two key aspects: (1) cultural significance, per capita consumption, and functional type serve as critical indicators for sustainable adaptive reuse, and (2) participatory governance and transparent decision-making are essential for effective implementation, with professional mediators and targeted support aiding conflict resolution.

Lateral Walking Gait Recognition and Hip Angle Prediction Using a Dual-Task Learning Framework.

Lateral walking exercise is beneficial for the hip abductor enhancement. Accurate gait recognition and continuous hip joint angle prediction are essential for the control of exoskeletons. We propose a dual-task learning framework, the "Twin Brother" model, which fuses convolutional neural network (CNN), long short-term memory (LSTM), neural networks (NNs), and the squeezing-elicited attention mechanism to classify the lateral gait stage and estimate the hip angle from electromyography (EMG) signals.

Vis/NIR Spectroscopy and Chemometrics for Non-Destructive Estimation of Chlorophyll Content in Different Plant Leaves.

Vegetation biochemical and biophysical variables, especially chlorophyll content, are pivotal indicators for assessing drought's impact on plants. Chlorophyll, crucial for photosynthesis, ultimately influences crop productivity. This study evaluates the mean squared Euclidean distance (MSD) method, traditionally applied in soil analysis, for estimating chlorophyll content in five diverse leaf types across various months using visible/near-infrared (vis/NIR) spectral reflectance.

Does environmental, social, and governance news coverage affect the cost of equity? A textual analysis of media coverage.

Introduction: Amid growing global environmental challenges and the pursuit of sustainable development, Environmental, Social, and Governance (ESG) has become an important framework for promoting green and responsible business practices. This paper investigates how ESG-related media coverage affects the cost of equity, with a focus on how improved information transparency can influence firms' financing outcomes.

Methods: We construct an ESG performance index using a machine learning approach, based on ESG-related news text data and the level of media attention received by listed companies.

Metal Phosphorus Chalcogenide Nanosheet-Modified SnO Electron Transport Layers for Efficient Perovskite Solar Cells.

The electron transport layer (ETL) of tin dioxide (SnO) plays a pivotal role in n-i-p perovskite solar cells (PSCs) by facilitating the extraction of photogenerated electrons and blocking the transport of holes. However, the presence of oxygen vacancies in SnO adversely affects the quality of the ETLs and impairs the electron transport properties, reducing the performance of PSCs. Here, we present a novel interfacial engineering route by incorporating an exfoliated two-dimensional (2D) metal-phosphorus-chalcogen complex of the SnPS nanosheets into the SnO ETL.

Numerical Investigation on Electrothermal Performance of AlGaN/GaN HEMTs with Nanocrystalline Diamond/SiNx Trench Dual-Passivation Layers.

In this work, AlGaN/GaN high-electron-mobility transistors (HEMTs) with a nanocrystalline diamond (NCD)/SiN trench dual-passivated (TDP) structure were promoted, which demonstrated superior performance with a higher saturation output current () of 1.266 A/mm, a higher maximum transconductance () of 0.329 S/mm, and a lower resistance () of 2.

Advancements in Carbon-Based Piezoelectric Materials: Mechanism, Classification, and Applications in Energy Science.

The piezoelectric phenomenon has garnered considerable interest due to its distinctive physical properties associated with the materials involved. Piezoelectric materials, which are inherently non-centrosymmetric, can generate an internal electric field under mechanical stress, enhancing carrier separation and transfer due to electric dipole moments. While inorganic piezoelectric materials are often investigated for their high piezoelectric coefficients, they come with potential drawbacks such as toxicity and high production cost, which hinder their practical applications.

Investigation of coplanar waveguide fed SWB antenna with controllable stop band characteristics.

This study presents a coplanar waveguide (CPW)-fed monopole antenna engineered for super-wideband (SWB) applications. The antenna is designed to resonate at frequencies ranging from 2.44 GHz to over 25 GHz.

DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions.

Background: Numerous studies have shown that circRNA can act as a miRNA sponge, competitively binding to miRNAs, thereby regulating gene expression and disease progression. Due to the high cost and time-consuming nature of traditional wet lab experiments, analyzing circRNA-miRNA associations is often inefficient and labor-intensive. Although some computational models have been developed to identify these associations, they fail to capture the deep collaborative features between circRNA and miRNA interactions and do not guide the training of feature extraction networks based on these high-order relationships, leading to poor prediction performance.

Transition metal-doped cobalt phosphide for efficient hydrazine oxidation: a density functional theory study.

Hydrazine oxidation reaction (HzOR) provides a sustainable alternative to the sluggish oxygen evolution reaction (OER), with a low theoretical thermodynamic potential (-0.33 V RHE). However, developing efficient non-precious-metal catalysts for HzOR remains challenging.

The development of CC-TF-BiGRU model for enhancing accuracy in photovoltaic power forecasting.

In the face of escalating global energy crises and pressing challenges of environmental pollution, the imperative for sustainable energy solutions has never been more pronounced. Photovoltaic (PV) power generation is recognized as a cornerstone in transition towards a clean energy paradigm. This study introduces a groundbreaking short-term PV power forecasting methodology based on teacher forcing (TF) integrated with bi-directional gated recurrent unit (BiGRU).

Engineering Artificial Protrusions of Zn Anodes for Aqueous Zinc Batteries.

Uncontrollable dendrite growth can jeopardize the cycle life of aqueous Zn batteries. Here, we propose a general strategy of engineering artificial protrusions (APs) on the electrode surface to regulate the distribution of the electrode interface electric field and induce stable Zn plating/stripping for Zn batteries. The junction-free AP-Cu network is constructed on Cu foil by an ultrafast Joule-heating-welding method.

Optimizing Molecular Packing and Interfacial Contact via Halogenated N-Glycidyl Carbazole Small Molecules for Low Energy Loss and Highly Efficient Inverted Perovskite Solar Cells.

Nonideal interfacial contact and non-radiative voltage loss in self-assembled monolayers (SAMs)-based inverted perovskite solar cells (PSCs) limit their further development. Herein, two carbazole-based molecules with different halogen atoms (X-OCZ, X = Cl or Br) are developed as efficient interfacial regulators. The halogen effect not only finely modulates the molecular packing, crystallinity, and surface contact potential of the MeO-2PACz analogue via self-induced intermolecular interactions but also significantly influences the subsequent crystal growth of perovskite, thus resulting in the formation of high-quality films with enhanced crystallinity, improved energy level alignment, and depressed non-radiative recombination.

Pore Engineering in Isoreticular Titanium-Isophthalate Coordination Polymers.

Pore engineering through chemical environment modification is vital for developing industrial porous materials. Understanding the effects of substitutions in isoreticular porous coordination polymers-such as steric hindrance, vibrational capabilities, electronic influences, and hydropathy-is key to elucidating structure-property relationships. However, accurately assessing the impact of functional groups on properties remains challenging due to limitations in current methodologies.

The Effects of Home Quarantine Duration, Parental Emotional Intelligence, and Family Socioeconomic Status on Children's Anxiety During the Pandemic: A Survey of 29,550 Parents.

Background: The pandemic has led to unprecedented home quarantine measures affecting children's anxiety levels due to routine disruptions. This study investigated the role of the length of the quarantine period, parents' emotional intelligence, and family socioeconomic status (SES) in influencing children's anxiety.

Objective: This study aims to examine the relationship between quarantine duration and children's anxiety and to explore the mediating role of parents' emotional intelligence and the moderating role of family socioeconomic status in this relationship.

HNF-DDA: subgraph contrastive-driven transformer-style heterogeneous network embedding for drug-disease association prediction.

Background: Drug-disease association (DDA) prediction aims to identify potential links between drugs and diseases, facilitating the discovery of new therapeutic potentials and reducing the cost and time associated with traditional drug development. However, existing DDA prediction methods often overlook the global relational information provided by other biological entities, and the complex association structure between drug diseases, limiting the potential correlations of drug and disease embeddings.

Results: In this study, we propose HNF-DDA, a subgraph contrastive-driven transformer-style heterogeneous network embedding model for DDA prediction.

Piezoelectric properties improvement in soft membrane with wet-spinning prepared barium titanate/polyvinylidenefluoride composites fiber.

Piezoelectric composite materials have demonstrated significant potential for developing high-performance wearable sensors. However, optimizing the piezoelectric output performance in polymer-based devices remains challenging due to the suboptimal synergy between the piezoelectric reinforcement phase and substrate materials. Moreover, the instability of response signals further hampers the sensor's practical utility.

Amino-functionalized Fe/Co bimetallic MOFs for accelerated Fe (III)/Fe (II) cycling and efficient degradation of sulfamethoxazole in Fenton-like system.

Metal-organic frameworks (MOFs) are recognized as important Fenton-like materials for environmental remediation. However, their applications are often hindered by slow cycling between Fe (III) and Fe (II). This study aimed to address the slow Fe (III)/Fe (II) cycling limitation of Fe-MOFs through dual modification strategy: bimetallic modification and amino functionalization.

Dynamic Sensor-Based Data Management Optimization Strategy of Edge Artificial Intelligence Model for Intelligent Transportation System.

In the intelligent transportation field, object recognition, detection, and location applications face significant real-time challenges. To address these issues, we propose an automatic sensor-based data loading and unloading optimization strategy for algorithm models. This strategy is designed for artificial intelligence (AI) application systems that leverage edge computing.