Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study.

BACKGROUND: According to the Morbidity and Mortality Weekly Report, polysubstance use among pregnant women is prevalent, with 38.2% of those who consume alcohol also engaging in the use of one or more additional substances. However, the underlying mechanisms, contexts, and experiences of polysubstance use are unclear. Organic information is abundant on social media such as X (formerly Twitter). Traditional quantitative and qualitative methods, as well as natural language processing techniques, can be jointly used to derive insights into public opinions, sentiments, and clinical and public health policy implications. OBJECTIVE: Based on perinatal polysubstance use (PPU) data that we extracted on X from May 1, 2019, to October 31, 2021, we proposed two primary research questions: (1) What is the overall trend and sentiment of PPU discussions on X? (2) Are there any distinct patterns in the discussion trends of PPU-related tweets? If so, what are the implications for perinatal care and associated public health policies? METHODS: We used X's application programming interface to extract >6 million raw tweets worldwide containing ≥2 prenatal health- and substance-related keywords provided by our clinical team. After removing all non-English-language tweets, non-US tweets, and US tweets without disclosed geolocations, we obtained 4848 PPU-related US tweets. We then evaluated them using a mixed methods approach. The quantitative analysis applied frequency, trend analysis, and several natural language processing techniques such as sentiment analysis to derive statistics to preview the corpus. To further understand semantics and clinical insights among these tweets, we conducted an in-depth thematic content analysis with a random sample of 500 PPU-related tweets with a satisfying κ score of 0.7748 for intercoder reliability. RESULTS: Our quantitative analysis indicates the overall trends, bigram and trigram patterns, and negative sentiments were more dominant in PPU tweets (2490/4848, 51.36%) than in the non-PPU sample (1323/4848, 27.29%). Paired polysubstance use (4134/4848, 85.27%) was the most common, with the combination alcohol and drugs identified as the most mentioned. From the qualitative analysis, we identified 3 main themes: nonsubstance, single substance, and polysubstance, and 4 subthemes to contextualize the rationale of underlying PPU behaviors: lifestyle, perceptions of others' drug use, legal implications, and public health. CONCLUSIONS: This study identified underexplored, emerging, and important topics related to perinatal PPU, with significant stigmas and legal ramifications discussed on X. Overall, public sentiments on PPU were mixed, encompassing negative (2490/4848, 51.36%), positive (1884/4848, 38.86%), and neutral (474/4848, 9.78%) sentiments. The leading substances in PPU were alcohol and drugs, and the normalization of PPU discussed on X is becoming more prevalent. Thus, this study provides valuable insights to further understand the complexity of PPU and its implications for public health practitioners and policy makers to provide proper access and support to individuals with PPU.

Elucidation on Abnormal Capacity Increase in SiO2@C Core-Shell Nanospheres Anode for Lithium-Ion Battery.

An abnormal capacity increase stage has been observed in nanostructured SiO2 after the initial capacity drop stage. To investigate the Li+ storage kinetic mechanism for each stage, SiO2@C core-shell nanospheres with a total diameter of ∼108 to 170 nm but an adjustable C shell thickness of ∼4 to 31 nm have been fabricated. First, the existence form and specific content of SiO2 nanoparticles with a size of ∼6-10 nm, which are embedded in the outer C shell of SiO2@C core-shell nanospheres, were confirmed by SEM, TEM, BET, and TGA, respectively. It was found that the initial stage for capacity drop happens at 15-43 cycles and is followed by an enhancement stage, which presents an increase of ∼120 to 180% in capacity relative to the lowest capacity value during cycling. Among them, the sample of P-1 with a diameter of 109 nm for the SiO2 core and thickness of 31 nm for the C shell delivers the highest specific capacity of 1060 mAh/g at 100 mA/g and a capacity increase rate of ∼180% through 300 cycles. XPS analysis for the delithiation process indicates that the capacity drop and increase stage involves the partial oxidation of Li silicate, which is correlated to the formation of Li2Si2O5. Our study can be used to explain the mechanism of the abnormal capacity increase phenomenon for the SiO2 anode and provide a high-capacity anode material for LIB application.

VO2-Based Spacecraft Smart Radiator with High Emissivity Tunability and Protective Layer.

In the extreme space environment, spacecraft endure dramatic temperature variations that can impair their functionality. A VO2-based smart radiator device (SRD) offers an effective solution by adaptively adjusting its radiative properties. However, current research on VO2-based thermochromic films mainly focuses on optimizing the emissivity tunability (Δε) of single-cycle sandwich structures. Although multi-cycle structures have shown increased Δε compared to single-cycle sandwich structures, there have been few systematic studies to find the optimal cycle structure. This paper theoretically discusses the influence of material properties and cyclic structure on SRD performance using Finite-Difference Time-Domain (FDTD) software, which is a rigorous and powerful tool for modeling nano-scale optical devices. An optimal structural model with maximum emissivity tunability is proposed. The BaF2 obtained through optimization is used as the dielectric material to further optimize the cyclic resonator. The results indicate that the tunability of emissivity can reach as high as 0.7917 when the BaF2/VO2 structure is arranged in three periods. Furthermore, to ensure a longer lifespan for SRD under harsh space conditions, the effects of HfO2 and TiO2 protective layers on the optical performance of composite films are investigated. The results show that when TiO2 is used as the protective layer with a thickness of 0.1 µm, the maximum emissivity tunability reaches 0.7932. Finally, electric field analysis is conducted to prove that the physical mechanism of the smart radiator device is the combination of stacked Fabry-Perot resonance and multiple solar reflections. This work not only validates the effectiveness of the proposed structure in enhancing spacecraft thermal control performance but also provides theoretical guidance for the design and optimization of SRDs for space applications.

Millimeter-wave high-wavenumber scattering diagnostic developments on EAST and NSTX-U.

A pioneering 4-channel, high-k poloidal, millimeter-wave collective scattering system has been successfully developed for the Experimental Advanced Superconducting Tokamak (EAST). Engineered to explore high-k electron density fluctuations, this innovative system deploys a 270 GHz mm-wave probe beam launched from Port K and directed toward Port P (both ports lie on the midplane and are 110° part), where large aperture optics capture radiation across four simultaneous scattering angles. Tailored to measure density fluctuations with a poloidal wavenumber of up to 20 cm-1, this high-k scattering system underwent rigorous laboratory testing in 2023, and the installation is currently being carried out on EAST. Its primary purpose lies in scrutinizing ion and electron-scale instabilities, such as the electron temperature gradient (ETG) mode, by furnishing measurements of the kθ (poloidal wavenumber) spectrum. This advancement significantly bolsters the capacity to probe high-k electron density fluctuations within the framework of EAST. Beam tracing and data interpretation modules developed for both EAST and NSTX-U high-k scattering diagnostics are described.

Highly efficient semi-hydrogenation in strained ultrathin PdCu shell and the atomic deciphering for the unlocking of activity-selectivity.

Excellent ethylene selectivity in acetylene semi-hydrogenation is often obtained at the expense of activity. To break the activity-selectivity trade-off, precise control and in-depth understanding of the three-dimensional atomic structure of surfacial active sites are crucial. Here, we designed a novel Au@PdCu core-shell nanocatalyst featuring diluted and stretched Pd sites on the ultrathin shell (1.6 nm), which showed excellent reactivity and selectivity, with 100% acetylene conversion and 92.4% ethylene selectivity at 122 °C, and the corresponding activity was 3.3 times higher than that of the PdCu alloy. The atomic three-dimensional decoding for the activity-selectivity balance was revealed by combining pair distribution function (PDF) and reverse Monte Carlo simulation (RMC). The results demonstrate that a large number of active sites with a low coordination number of Pd-Pd pairs and an average 3.25% tensile strain are distributed on the surface of the nanocatalyst, which perform a pivotal function in the simultaneous improvement of hydrogenation activity and ethylene selectivity. Our work not only develops a novel strategy for unlocking the linear scaling relation in heterogeneous catalysis but also provides a paradigm for atomic 3D understanding of lattice strain in core-shell nanocatalysts.

Multi-level decisions for addressing trade-off in the cross-regional water-environment-agriculture interactive system under constraint of water ecological carrying capacity.

The complex-enhanced hierarchical relationship among multiple stakeholders in the water-environment-agriculture interactive system has been overlooked. This study develops a leader-follower-enhanced framework (named as FCMLP) that integrates variable-weight combination prediction model, multi-level programming, and fuzzy credibility constrained programming, which can effectively address the above problems under uncertainties. Five water ecological carrying capacity (WECC) statuses are treated as a critical constraint into the modeling framework to improve the accuracy of decision-making. An interactive fuzzy satisfaction algorithm is advanced for solving this multi-level problem, in which COD discharge minimization, economic benefits maximization, and grain yield maximization are taken as the upper-, middle-, and lower-level goals, respectively. The framework is applied to plan the cross-regional water-environment-agriculture interactive system in the Beijing-Tianjin-Hebei and Yangtze River Economic Belt. Solutions reveal that increased WECC status and credibility level would decrease 1.40%-1.74%, 0.71%-9.61%, and 1.63%-2.26% of water resources allocation, COD emissions, and economic benefits, respectively. Crop area and grain yield would dramatically decline by 4.13%-4.46% and 4.03%-4.67% when a credibility level increases from 0.8 to 1, respectively. The overall satisfactory degree would range from 0.58 to 0.70, which illustrates interactive decision-making process of multiple stakeholders. Significant differences can be observed in the optimized schemes of water resources allocation and environmental-economic-agricultural performances among various models. The amounts of allocated water resources, pollutant discharge, and economic output from the FCMLP model would be respectively 11.30%-13.45%, 14.90%-15.21%, and 73.12%-73.48% higher than those from the environment- and agriculture-oriented schemes, yet 13.81%, 32.05%, and 15.29% lower than those from the economy-oriented scheme. Some water adaptability countermeasures are given for ensuring the scientific operation of the South-to-North Water Transfer Project and alleviating conflicts between water source and receiving areas. Further exploration of the optimization scheme of water-environment-energy-agriculture system driven by climate change is still required for guaranteeing the dynamic balance of regional resources.

A Weakly Solvating Ether Electrolyte Enables Fast-Charging and Wide-Temperature Lithium-Ion Pouch Cells.

Graphite-based lithium-ion batteries have succeeded greatly in the electric vehicle market. However, they suffer from performance deterioration, especially at fast charging and low temperatures. Traditional electrolytes based on carbonated esters have sluggish desolvation kinetics, recognized as the rate-determining step. Here, a weakly solvating ether electrolyte with tetrahydropyran (THP) as the solvent is designed to enable reversible and fast lithium-ion (Li+) intercalation in the graphite anode. Unlike traditional ether-based electrolytes which easily cointercalate into the graphite layers, the THP-based electrolyte shows fast desolvation ability and can match well with the graphite anode. In addition, the weak interconnection between Li+ and THP allows more anions to come into the solvating shell of Li+, inducing an inorganic-rich interface and thus suppressing the side reactions. As a result, the lithium iron phosphate/graphite pouch cell (3 Ah) with the THP electrolyte shows a capacity retention of 80.3% after 500 cycles at 2 C charging, much higher than that of the ester electrolyte system (7.6% after 200 cycles). At 4 C charging, the discharging capacity is increased from 2.29 Ah of esters to 2.96 Ah of THP. Furthermore, the cell can work normally over wide working temperatures (-20 to 60 °C). Our electrolyte design provides some understanding of lithium-ion batteries at fast charging and wide temperatures.

Hyper-methylation and DNMT3A mediated LTC4S downregulation promoted lung adenocarcinoma tumorigenesis via mTORC1 signaling pathway.

Background: Lung adenocarcinoma is a malignancy characterized by high mortality rates and unfavorable prognosis. However, the role of Leukotriene C4 Synthase (LTC4S) in lung cancer remains uninvestigated. Methods: The expression and prognostic value of LTC4S in LUAD were analyzed using the GEPIA online database. Subsequently, the function of LTC4S in lung cancer cells was examined through gain-of function experiments, using assays to evaluate tumor malignant behavior. Subcutaneous xenograft experiments in vivo was used for investigating the functions of LTC4S. Then, tumor hallmark pathways were analyzed by GSEA. Western blot assay was used to validate the impact of LTC4S on mTORC1 pathway. Finally, the correlation of mRNA and methylation of LTC4S were analyzed by cBioPortal. qRT-PCR, ChIP-qPCR and ChIP-Atlas were used to verify the regulation factors of LTC4S low expression in LUAD cells. Results: LTC4S presented significant decreased expression and favorable prognostic significance in LUAD. LTC4S was correlated with clinical stages in LUAD, which showed decreased expression gradually and significantly along with TNM stages. LTC4S-co-expressed genes were closely related to Ras signaling pathway, and MAPK signaling pathway. Overexpression of LTC4S inhibited cancer malignant phenotype and tumor growth in vitro and vivo. GSEA analysis and Western blot assay suggested low expression of LTC4S activated mTORC1 signaling pathway in LUAD. Moreover, the DNA methylation level of LTC4S in LUAD tissue was markedly elevated compared to normal tissue. The hypermethylation of the LTC4S promoter by DNMT3A leads to the decreased expression of LTC4S in LUAD. Conclusions: In conclusion, low expression of LTC4S serves as an unfavorable prognostic marker and the critical function of LTC4S in controlling the progression of LUAD. This highlights the promise for exploring the clinical benefits of manipulating LTC4S in LUAD targeted therapies.

Crystallization and electrochemical properties of KxV2O5 nano-ribbons obtained via a solvothermal process as a promising cathode for PIBs.

In this research, a series of K+-intercalated quasi-1D vanadium-based nano-ribbons (KxV2O5 NRs) were synthesized via a facile solvothermal method. The solvation and reductive effects of vanadium oxide precursors (V2O5 powder) on the crystallization and growth of KxV2O5 NRs were studied. Besides, post-heat treatment was performed to improve the crystallinity of KxV2O5 NRs. These KxV2O5 NRs were adopted as active cathodes for potassium-ion batteries (PIBs), whose K+ storage properties were systematically evaluated using various electrochemical methods. The relationship among the morphology, crystallinity, working voltage window and electrochemical reversible K+ storage performance of KxV2O5 NRs was studied and established. Results reveal that KxV2O5-HG, which was prepared via a solvothermal reaction involving a solvation process (using H2O2) and a proper reducing condition (proper dose of glucose) with V2O5 powder as the raw material, would be more beneficial for the reversible storage of K+ when used as the cathode for PIBs compared to other contrast samples. In addition, the enhanced crystallinity and slightly broadened working voltage window of KxV2O5-HG could hinder its long-term cycling stability upon repeated K+ insertions/extractions.

Advances of Nanomaterials for High-Efficiency Zn Metal Anodes in Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries (AZIBs) have emerged as one of the most promising candidates for next-generation energy storage devices due to their outstanding safety, cost-effectiveness, and environmental friendliness. However, the practical application of zinc metal anodes (ZMAs) faces significant challenges, such as dendrite growth, hydrogen evolution reaction, corrosion, and passivation. Fortunately, the rapid rise of nanomaterials has inspired solutions for addressing these issues associated with ZMAs. Nanomaterials with unique structural features and multifunctionality can be employed to modify ZMAs, effectively enhancing their interfacial stability and cycling reversibility. Herein, an overview of the failure mechanisms of ZMAs is presented, and the latest research progress of nanomaterials in protecting ZMAs is comprehensively summarized, including electrode structures, interfacial layers, electrolytes, and separators. Finally, a brief summary and optimistic perspective are given on the development of nanomaterials for ZMAs. This review provides a valuable reference for the rational design of efficient ZMAs and the promotion of large-scale application of AZIBs.

Towards Stabilized Few-Shot Object Detection with Less Forgetting via Sample Normalization.

Few-shot object detection is a challenging task aimed at recognizing novel classes and localizing with limited labeled data. Although substantial achievements have been obtained, existing methods mostly struggle with forgetting and lack stability across various few-shot training samples. In this paper, we reveal two gaps affecting meta-knowledge transfer, leading to unstable performance and forgetting in meta-learning-based frameworks. To this end, we propose sample normalization, a simple yet effective method that enhances performance stability and decreases forgetting. Additionally, we apply Z-score normalization to mitigate the hubness problem in high-dimensional feature space. Experimental results on the PASCAL VOC data set demonstrate that our approach outperforms existing methods in both accuracy and stability, achieving up to +4.4 mAP@0.5 and +5.3 mAR in a single run, with +4.8 mAP@0.5 and +5.1 mAR over 10 random experiments on average. Furthermore, our method alleviates the drop in performance of base classes. The code will be released to facilitate future research.

The mutation of Japanese encephalitis virus envelope protein residue 389 attenuates viral neuroinvasiveness.

The envelope (E) protein of the Japanese encephalitis virus (JEV) is a key protein for virus infection and adsorption of host cells, which determines the virulence of the virus and regulates the intensity of inflammatory response. The mutation of multiple aa residues in the E protein plays a critical role in the attenuated strain of JEV. This study demonstrated that the Asp to Gly, Ser, and His mutation of the E389 site, respectively, the replication ability of the viruses in cells was significantly reduced, and the viral neuroinvasiveness was attenuated to different degrees. Among them, the mutation at E389 site enhanced the E protein flexibility contributed to the attenuation of neuroinvasiveness. In contrast, less flexibility of E protein enhanced the neuroinvasiveness of the strain. Our results indicate that the mechanism of attenuation of E389 aa mutation attenuates neuroinvasiveness is related to increased flexibility of the E protein. In addition, the increased flexibility of E protein enhanced the viral sensitivity to heparin inhibition in vitro, which may lead to a decrease in the viral load entering brain. These results suggest that E389 residue is a potential site affecting JEV virulence, and the flexibility of the E protein of aa at this site plays an important role in the determination of neuroinvasiveness.

Sensing Based on Plasmon-Induced Transparency in H-Shaped Graphene-Based Metamaterials.

Graphene can support surface plasmon polaritons (SPPs) in the terahertz band, and graphene SPP sensors are widely used in the field of terahertz micro- and nano-optical devices. In this paper, we propose an H-shaped graphene metasurface and investigate the plasmon-induced transparency (PIT) phenomenon in the proposed structure using the finite-difference time-domain (FDTD) method. Our results show that the Fermi energy levels, as well as certain shape parameters, can effectively modulate the PIT phenomenon in the proposed structure. Interestingly, changing some of these shape parameters can excite two dips into three. In terms of sensing performance, the maximum values of sensitivity and figure of merit (FOM) are 1.4028 THz/RIU and 17.97, respectively. These results offer valuable guidance for the use of terahertz optical graphene SPP sensors.

High-Entropy Alloy Activating Laves-Phase Network for Multi-Component Metallic Coatings with High Hardness.

The low hardness and poor wear resistance of laser-cladding 316L stainless steel impose significant constraints on its practical applications. In this study, a strategy for strengthening laser-cladding 316L stainless steel with WMoTaNb refractory high-entropy alloy as a reinforcement material is proposed. The results confirm that the coating primarily comprises a body-centered cubic (BCC) Fe-based solid solution, a network-distributed hexagonal Fe2X (X = W, Mo, Ta, and Nb) Laves phase, and a diffusely distributed face-centered cubic (FCC) (Ta, Nb)C phase. The Fe-based solid solution distributes along columnar and fine dendrites, while the Laves phase and (Ta, Nb)C phase are in the inter-dendrites. The presence of a significant number of network Laves phases exhibiting high strength and hardness is the primary factor contributing to the enhancement of coating microhardness. The hardness of the composite coating is increased by nearly twice compared to that of the 316L coating, resulting in an improved wear resistance. The present work can shed light on designing and fabricating 316L stainless steel coating with enhanced hardness and wear resistance.

Enabling Quasi-Zero-Strain Behavior of Layered Oxide Cathodes via Multiple-cations Induced Order-to-Disorder Transition.

The chemically pre-intercalated lattice engineering is widely applied to elevate the electronic conductivity, expand the interlayer spacing, and improve the structural stability of layered oxide cathodes. However, the mainstream unitary metal ion pre-intercalation generally produces the cation/vacancy ordered superstructure, which astricts the further improvement of lattice respiration and charge-carrier ion storage and diffusion. Herein, a multiple metal ions pre-intercalation lattice engineering is proposed to break the cation/vacancy ordered superstructure. Taking the bilayer V2O5 as an example, Ni, Co, and Zn ternary ions are simultaneously pre-intercalated into its interlayer space (NiCoZnVO). It is revealed that the Ni─Co neighboring characteristic caused by Ni(3d)-O(2p)-Co(3d) orbital coupling and the Co-Zn/Ni-Zn repulsion effect due to chemical bond incompatibility, endow the NiCoZnVO sample with the cation/vacancy disordered structure. This not only reduces the Li+ diffusion barrier, but also increases the diffusion dimension of Li+ (from one-dimension to two-dimension). Particularly, Ni, Co, and Zn ions co-pre-intercalation causes a prestress, which realizes a quasi-zero-strain structure at high-voltage window upon charging/discharging process. The functions of Ni ion stabilizing the lattice structure and Co or Zn ions activating more Li+ reversible storage reaction of V5+/V4+ are further revealed. The cation/vacancy disordered structure significantly enhances Li+ storage properties of NiCoZnVO cathode.

Strong-Yet-Ductile Eutectic Alloys Employing Cocoon-Like Nanometer-Sized Dislocation Cells.

Eutectic alloys (EAs) with superior fluidity are known to be the easiest to cast into high-quality ingots, making them the alloys of choice for making large-sized structural parts. However, conventional EAs (CEAs) have never reached strength-ductility combinations on par with the best in other alloy categories. Via thermomechanical processing of cast Ni-32.88wt%Fe-9.53wt%Al CEAs, a cocoon-like nano-meshed (as fine as 26 nm) network of dislocations (CNN-D) is produced via recovery annealing, through the rearrangement of cold-work-accumulated dislocations anchored by dense pre-existing nanoprecipitates. In lieu of traditional plasticity mechanisms, such as TWIP and TRIP, the CNN-D is particularly effective in eutectic lamellae with alternating phases, as it instigates nanometer-spaced planar slip bands that not only dynamically refine the microstructure but also transmit from the FCC (face-centered-cubic) layers into the otherwise brittle B2 layers. These additional mechanisms for strengthening and strain hardening sustain stable tensile flow, resulting in a striking elevation of both strength and ductility to outrank not only all previous CEAs, but also the state of the art-additively manufactured eutectic high-entropy alloys. The CNN-D thus adds a novel microstructural strategy for performance enhancement, especially for compositionally complex alloys that increasingly make use of nanoprecipitates or local chemical order.

High-Energy Earth-Abundant Cathodes with Enhanced Cationic/Anionic Redox for Sustainable and Long-Lasting Na-Ion Batteries.

Layered iron/manganese-based oxides are a class of promising cathode materials for sustainable batteries due to their high energy densities and earth abundance. However, the stabilization of cationic and anionic redox reactions in these cathodes during cycling at high voltage remain elusive. Here, an electrochemically/thermally stable P2-Na0.67Fe0.3Mn0.5Mg0.1Ti0.1O2 cathode material with zero critical elements is designed for sodium-ion batteries (NIBs) to realize a highly reversible capacity of ≈210 mAh g-1 at 20 mA g-1 and good cycling stability with a capacity retention of 74% after 300 cycles at 200 mA g-1, even when operated with a high charge cut-off voltage of 4.5 V versus sodium metal. Combining a suite of cutting-edge characterizations and computational modeling, it is shown that Mg/Ti co-doping leads to stabilized surface/bulk structure at high voltage and high temperature, and more importantly, enhances cationic/anionic redox reaction reversibility over extended cycles with the suppression of other undesired oxygen activities. This work fundamentally deepens the failure mechanism of Fe/Mn-based layered cathodes and highlights the importance of dopant engineering to achieve high-energy and earth-abundant cathode material for sustainable and long-lasting NIBs.

Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models.

OBJECTIVES: The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care. MATERIALS AND METHODS: We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-class classification. We examined 3 traditional machine learning models, 9 BERT-based language models, 6 fusion models, and 2 ensemble models. RESULTS: The outcomes of our experimentation underscore the superior performance achieved by BERT-based models in comparison to traditional machine learning models. Remarkably, our fusion model emerges as the top-performing solution, delivering a notably improved accuracy score of 77.67 ± 2.74% and an F1 score of 74.37 ± 3.70% in macro-average. DISCUSSION: This study highlights the feasibility and effectiveness of multi-class classification for patient primary concern detection and the proposed fusion framework for enhancing primary concern detection. CONCLUSIONS: The use of multi-class classification enhanced by a fusion of multiple pretrained LMs not only improves the accuracy and efficiency of patient primary concern identification in PPMs but also aids in managing the rising volume of PPMs in healthcare, ensuring critical patient communications are addressed promptly and accurately.

Decoding Active Sites for Highly Efficient Semihydrogenation of Acetylene in Palladium-Copper Nanoalloys.

Accurately decoding the three-dimensional atomic structure of surface active sites is essential yet challenging for a rational catalyst design. Here, we used comprehensive techniques combining the pair distribution function and reverse Monte Carlo simulation to reveal the surficial distribution of Pd active sites and adjacent coordination environment in palladium-copper nanoalloys. After the fine-tuning of the atomic arrangement, excellent catalytic performance with 98% ethylene selectivity at complete acetylene conversion was obtained in the Pd34Cu66 nanocatalysts, outperforming most of the reported advanced catalysts. The quantitative deciphering shows a large number of active sites with a Pd-Pd coordination number of 3 distributed on the surface of Pd34Cu66 nanoalloys, which play a decisive role in highly efficient semihydrogenation. This finding not only opens the way for guiding the precise design of bimetal nanocatalysts from atomic-level insight but also provides a method to resolve the spatial structure of active sites.

Turning Ultra-Low Coercivity and Ultra-High Temperature Stability Within 897 K via Continuous Crystal Ordering Fluctuations.

High-performance soft magnetic materials are important for energy conservation and emission reduction. One challenge is achieving a combination of reliable temperature stability, high resistivity, high Curie temperature, and high saturation magnetization in a single material, which often comes at the expense of intrinsic coercivity-a typical trade-off in the family of soft magnetic materials with homogeneous microstructures. Herein, a nanostructured FeCoNiSiAl complex concentrated alloy is developed through a hierarchical structure strategy. This alloy exhibits superior soft magnetic properties up to 897 K, maintaining an ultra-low intrinsic coercivity (13.6 A m-1 at 297 K) over a wide temperature range, a high resistivity (138.08 µΩ cm-1 at 297 K) and the saturation magnetization with only a 16.7% attenuation at 897 K. These unusual property combinations are attributed to the dual-magnetic-state nature with exchange softening due to continuous crystal ordering fluctuations at the atomic scale. By deliberately controlling the microstructure, the comprehensive performance of the alloy can be tuned and controlled. The research provides valuable guidance for the development of soft magnetic materials for high-temperature applications and expands the potential applications of related functional materials in the field of sustainable energy.