Reliable Strategy Research Articles

Clinical and radiographic outcomes of negative pressure wound therapy combined with polymethylmethacrylate sealant for wound management of Gustilo type III open tibia fractures.

This study aimed to introduce a new wound management method combining negative pressure wound therapy and polymethylmethacrylate sealant for Gustilo type III open tibia fractures and to evaluate its clinical outcomes. Among 186 patients who visited our institution for the treatment of open tibia fractures between January 2016 and December 2019, 20 male patients who sustained Gustilo type III open tibia fractures and were compelled to undergo delayed flap coverage using negative pressure wound therapy combined with polymethylmethacrylate sealant due to initial critical condition were enrolled in this study. We retrospectively investigated patients' demographics, interval between the injury and flap coverage, number of negative pressure wound therapy changes, flap survival, bone union time, and infection-induced complications. The mean interval from injury until flap coverage was 27.8 (range, 8-63) days. Most soft-tissue defects were reconstructed using free flaps (14/20, 70%); the anterolateral thigh flap was the most frequently used flap (12/20, 60%) in this study. Among 20 flaps trans- ferred, 16 flaps (80%) survived uneventfully, 1 flap (5%) developed partial necrosis, and 3 flaps (15%) failed. The mean follow-up period was 22.7 (range, 12- 43) months. A total of 17 patients (85%) achieved tibia fracture union. The mean bone union time was 31 (range, 12-81) weeks. With regard to infection-induced complications, 3 patients (15%) developed osteomyelitis and no patient showed superficial surgical site infection. Combination therapy using negative pressure wound therapy and polymethylmethacrylate sealant serves as a useful and reliable therapeutic strategy for wound management of Gustilo type III open tibia fractures, especially when delayed soft-tissue recon- struction is unavoidable. Corresponding author: Yoo Joon Sur yoojoon@catholic.ac.kr Content of this journal is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Level IV, Therapeutic Study.

Mechanism analysis of toxic and side effects of chemicals on human body

The exposure of the human body to different chemical substances poses a critical hazard to public well-being. Chemical toxicity is fundamentally ascribed to the disturbance of typical biological processes and can result in unfavorable health results. Understanding the components by which chemical substances apply their harmful impacts is vital for surveying and moderating these dangers. In this research, it will discuss the different routes of exposure, such as inhalation ingestion and dermal contact through which chemicals can enter the body. This research investigates the complex instruments at the atomic and cellular levels, counting oxidative stretch DNA harm and disturbance of enzymatic pathways by which harmful impacts are actuated. The evaluation of chemical toxicity includes a range of toxicological considerations, including acute and chronic toxicity tests, genotoxicity measures, and carcinogenicity evaluations. The development of reliable toxicity evaluation strategies, such as in vitro and in silico models, plays an urgent part in predicting the adverse impacts of chemical substances. Administrative systems and hazard evaluation techniques are discussed to guarantee peoples and the environments security. A comprehensive understanding of the components and assessment of poisonous side impacts is essential for defending open health and minimizing the hindering effects of chemical exposure.

Prediction and adjustment of elastic properties in three‐dimensional orthogonal woven composites through dual‐scale modeling

AbstractThree‐dimensional (3D) orthogonal woven composites can overcome the drawback of weak interlaminar strengths in traditional laminated composites and exhibit excellent resistance to out‐of‐plane impact, however, the significant difference in properties in the in‐plane orthogonal direction will limit the potential range of application thereof. Predicting elastic properties and exploring methods of adjustment are therefore of paramount importance. Using computed tomography (CT) scanning to obtain detailed parameter models, a corresponding dual‐scale model of microscopic representative volume element (RVE) and mesoscopic RVE was established, and the accuracy of the model was experimentally validated, which can predict the elastic properties of materials. In addition, the influences of the yarn fiber volume fraction and weaving distance on elastic properties were evaluated using the elastic modulus visualization method, and a formula integrating these two factors is provided for adjustment of the in‐plane orthogonal Young's modulus.Highlights Experimentally validated microscale and mesoscale RVE models were established. The influences of factors on elastic properties were visualized. The relationship between Young's modulus and influencing factors was derived. A reliable strategy for adjusting the in‐plane Young's modulus was proposed.

Heterologous expression and activity of α-helical antimicrobial peptide SW in Bacillus subtilis

The antimicrobial peptide Cecropin P1 (CP1) was isolated from the pig-intestinal parasitic nematode Ascaris lumbricoides and had potent antimicrobial activity. However, its cytotoxicity is high. Herein, Using CP1 as the parent peptide, we designed a derivative peptide SW by replacing amino acids based on the structure and function relationship of antimicrobial peptides (AMPs) to reduce the toxicity of CP1. Subsequently, the gene sequence encoding SacB-6 ×His-SUMO-SW was constructed into the recombinant expression vector PHY-P43 of Bacillus subtilis WB800N. The fusion proteins with concentrations of 26.97 mg/L were obtained after purification by a Ni–NTA column. A total of 5.37 mg of SW was obtained from 1 L fermentation cultures. Recombinant SW (rSW) exhibits potent antimicrobial activity against gram-negative bacteria by inducing membrane instabilities. In addition, rSW showed low hemolytic activity and cytotoxicity against human red blood cells and IPEC-J2, respectively. In the mice model of peritonitis infection, rSW could reduce Escherichia coli-loading in the liver, spleen, lung, and kidney of mice. These results indicate that rSW production by Bacillus. subtilis is a safe and reliable strategy, and rSW has the potential to be a novel antimicrobial agent against gram-negative bacterial infections.

Highly efficient photocatalytic decomposition of triazophos using novel In2O3/WO3 nanocomposites with oxygen defects and S-Scheme heterojunctions

Confronted with the substantial environmental threat posed by organophosphorus pesticides, the urgency to develop reliable and efficient mitigation strategies is paramount. Photocatalytic technology, which catalyzes the generation of potent oxidizing radicals, emerges as a promising solution. In this study, we have successfully synthesized In2O3/WO3 (IO/WO) nanocomposites, endowed with oxygen defects and S-scheme heterojunctions, exhibiting exceptional photocatalytic degradation activity and mineralization efficiency. Notably, the WO material synthesized in this study is blue in color, unlike the traditional yellow color of WO, indicating a rich presence of oxygen defects. The 60-IO/WO nanocomposite, containing 60 % IO, achieved superior photocatalytic degradation, reducing triazophos pesticide from 100 % to 21.29 % within 60 min, outperforming the individual materials IO (56.97 %) and WO (48.02 %). This nanocomposite also exhibited remarkable corrosion resistance across multiple cycles, showcasing significantly enhanced stability compared to the individual IO and WO materials. Electron paramagnetic resonance (EPR) spectroscopy confirmed the presence of oxygen defects in the blue WO, while both EPR and theoretical calculations substantiated the formation of the S-scheme heterojunction in the 60-IO/WO nanocomposite. The new nanocomposite's excellent photocatalytic degradation activity is influenced by various factors such as differing surface areas, composite amounts, photocurrent responses, and resistances, all of which impact the degradation performance of triazophos. Compared to traditional photocatalytic materials, the IO/WO nanocomposite demonstrates a significant edge in photocatalytic efficiency and chemical stability, offering considerable potential for environmental remediation, especially in the degradation of organophosphorus pesticides.

Novel electrolyte assisted ultralow-temperature zinc battery

Secondary battery is an indispensable component in energy storage as it can uninterruptedly store the energy and release it when being required. Among them, zinc (Zn) rechargeable battery gains much attention due to its cost advantage. However, poor climate adaptation much weaken the competitiveness, and temperature-induced deterioration can be mainly blamed on the slow reaction-kinetics of Zn anode under low temperature. Under this scenario, an anti-freezing electrolyte with Zinc (II)Bis(trifluoromethanesulfonyl)imide (Zn(TFSI)2) salt and ternary solvents of acetonitrile (AN), methyl acetate (MA) and dichloromethane (DCM) is proposed. It successfully broadens the working temperature of Zn secondary battery to − 90 °C. The elaborately regulated solvation can ensure smooth ion-transfer in liquid zone, more importantly, it expedites the desolvation without much affecting the interface transportation. With the optimized electrolyte configuration, reversible Zn plating/stripping at ultra-low temperature has been realized. The Zn|polytriphenylamine (PTPAn) battery thus can reserve 70 % capacity at − 80 °C, and present extremely stable cycling and impressive rate capability at − 80 °C and − 60 °C. The results well address the kinetics issues encountered in the low-temperature Zn secondary battery, and reveals that only with appropriate solvation, the high ion-permeability of the interface as well as easy de-solvation can be guaranteed. The work provides a guideline for designing advanced electrolyte, and supplies a reliable and effective strategy for the all-weather electrochemical energy storage.

Potentialities of the combined use of underwater fluorescence imagery and photogrammetry for the detection of fine-scale changes in marine bioconstructors

Marine communities are facing both natural disturbances and anthropogenic stressors. Bioconstructor species are endangered by multiple large-scale and local pressures and the early identification of impacts and damages is a primary goal for preserving coral reefs. Taking advantage of the recent development in underwater photogrammetry, the use of photogrammetry and fluorimetry was coupled to design, test and validate in laboratory a multi-sensor measuring system that could be potentially exploited in open water by SCUBA divers for assessing the health status of corals and detecting relevant biometric parameters with high accuracy and resolution. The approach was tested with fragments of the endemic coral Cladocora caespitosa, the sole zooxanthellate scleractinian reef-builder in the Mediterranean. The most significant results contributing to the scientific advancement of knowledge were: 1) the development of a cost-effective, flexible and easy-to-use approach based on emerging technologies; 2) the achievement of a sub-centimetric resolution for measuring relevant biometric parameters (polyp counting, colony surface areas and volumes); 3) set up of a reliable and repeatable strategy for multi-temporal analyses capable of quantifying changes in coral morphology with sub-centimeter accuracy; 4) detect changes in coral health status at a fine scale and under natural lighting through autofluorescence analysis. The novelty of the present research lies in the coupling of emerging techniques that could be applied to a wide range of 3D morphometrics, different habitats and species, thus paving the way to innovative opportunities in ecological research and more effective results than traditional in-situ measurements. Moreover, the possibility to easily modify the developed system to be installed on an underwater remotely operated vehicle further highlights the possible concrete impact of the research for ecological monitoring and protection purposes.

Mesopore engineering of Co3O4 nanoplates for enhanced detection of toluene vapor

It remains a significant challenge for efficient detection of toluene vapor because of the low chemical reactivity. In this paper, the Co3O4 nanoplates with various mesopore widths (5.1, 12.6, and 19.8 nm) onto their surfaces have been successfully achieved using a simple hydrothermal and followed annealing route. Moreover, the sensor based on this Co3O4 nanoplate with mesopore width of 5.1 nm presents an obvious toluene-sensing response (including actual detection limit of 1 ppm, and excellent selectivity) at a low working temperature (140 °C). The improved toluene-sensing can be tracked from suitable mesopore size and specific catalytic activity of the Co3O4 nanoplates, which are advantageous for gas adsorption and diffusion, as well as facilitating the rapid oxidation of toluene gas. This work announces a reliable strategy to detect low reactive gas by constructing rational mesopores-width over the catalytic oxide.

Genomics landscape of mitochondrial DNA variations in patients from South Italy affected by mitochondriopathies

Mitochondrial DNA (mtDNA) is a 16,569 base pairs, double-stranded, circular molecule that contains 37 genes coding for 13 subunits of the respiratory chain plus 2 rRNAs and 22 tRNAs. Mutations in these genes have been identified in patients with a variety of disorders affecting every system in the body. The advent of next generation sequencing technologies has provided the possibility to perform the whole mitochondrial DNA sequencing, allowing the identification of disease-causing pathogenic variants in a single platform. In this study, the whole mtDNA of 100 patients from South Italy affected by mitochondrial diseases was analyzed by using an amplicon-based approach and then the enriched libraries were deeply sequenced on the ION Torrent platform (Thermofisher Scientific Waltham, MA, USA). After bioinformatics analysis and filtering, we were able to find 26 nonsynonymous variants with a MAF <1% that were associated with different pathological phenotypes, expanding the mutational spectrum of these diseases. Moreover, among the new mutations found, we have also analyzed the 3D structure of the MT-ATP6 A200T gene variation in order to confirm suspected functional alterations. This work brings light on new variants possibly associated with several mitochondriopathies in patients from South Italy and confirms that deep sequencing approach, compared to the standard methods, is a reliable and time-cost reducing strategy to detect all the variants present in the mitogenome, making the possibility to create a genomics landscape of mitochondrial DNA variations in human diseases.

Radiation-Variation Insensitive Coarse-to-Fine Image Registration for Infrared and Visible Remote Sensing Based on Zero-Shot Learning

Infrared and visible remote sensing image registration is significant for utilizing remote sensing images to obtain scene information. However, it is difficult to establish a large number of correct matches due to the difficulty in obtaining similarity metrics due to the presence of radiation variation between heterogeneous sensors, which is caused by different imaging principles. In addition, the existence of sparse textures in infrared images as well as in some scenes and the small number of relevant trainable datasets also hinder the development of this field. Therefore, we combined data-driven and knowledge-driven methods to propose a Radiation-variation Insensitive, Zero-shot learning-based Registration (RIZER). First, RIZER, as a whole, adopts a detector-free coarse-to-fine registration framework, and the data-driven methods use a Transformer based on zero-shot learning. Next, the knowledge-driven methods are embodied in the coarse-level matches, where we adopt the strategy of seeking reliability by introducing the HNSW algorithm and employing a priori knowledge of local geometric soft constraints. Then, we simulate the matching strategy of the human eye to transform the matching problem into a model-fitting problem and employ a multi-constrained incremental matching approach. Finally, after fine-level coordinate fine tuning, we propose an outlier culling algorithm that only requires very few iterations. Meanwhile, we propose a multi-scene infrared and visible remote sensing image registration dataset. After testing, RIZER achieved a correct matching rate of 99.55% with an RMSE of 1.36 and had an advantage in the number of correct matches, as well as a good generalization ability for other multimodal images, achieving the best results when compared to some traditional and state-of-the-art multimodal registration algorithms.

Machine learning models for capacitance prediction of porous carbon-based supercapacitor electrodes

Energy storage devices and systems with better performance, higher reliability, longer life, and wiser management strategies are needed for daily technology advancement. Among these devices, the supercapacitor is the most preferable due to its high-limit capacitance that esteems more than different capacitors. Today, it is considered a significant challenge to design high-performance materials for supercapacitors by exploring the interaction between characteristics and structural features of materials. Because of this, it is essential to predict capacitance when assessing a material’s potential for use in constructing supercapacitor-electrode applications. Machine learning (ML) can significantly speed up computation, capture complex mechanisms to enhance the accuracy of the prediction and make the best choices based on detailed status data. We aimed to develop a new strategy for the assisted design of high-performance supercapacitor materials by applying ML to analyze the relationship between capacitance and structural features of porous carbon materials (PCMs) using hundreds of experimental data in the literature. In the present study, Linear Regression (LR), Regression Tree (RT), and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to estimate the supercapacitor’s capacitance. The effectiveness of the ML models was evaluated in terms of the root mean square error (RMSE), mean absolute error (MAE), and the correlation between expected yield and system-provided yield. The developed ANFIS model, with RMSE, MAE, and R values of 22.8, 39.7647, and 0.90004, respectively, compares favourably regarding prediction performance to other models built for this purpose.

Self-dispersed bimetallic NiRu nanoparticles on CeO2 for CO2 methanation

Redispersing bimetallic active nanoparticles in a heterogeneous catalyst can significantly improve metal utilization and catalytic performance, but it is very challenging. In this work, we report a feasible method to redisperse large bimetallic NiRu particles (30–40 nm) on the CeO2 support into small alloyed NiRu nanoparticles (3–5 nm) in an Ar gas atmosphere (NiRu/CeO2-Ar). During the high-temperature treatment, Ru metal in big bimetallic NiRu particles migrated to the surface of small alloyed nanoparticles because of the metal-phase separation, forming more Ni−Ru metal interfaces. As a result, NiRu/CeO2-Ar showed much better catalytic performance in CO2 methanation than the pristine catalyst (NiRu/CeO2) and the catalysts treated in air, H2, and reactant gases, respectively. Experimental and theoretical calculation results reveal that the newly generated Ni−Ru metal interfaces are conducive to the adsorption of CO2 and further direct dissociation into CO*, thus enhancing the catalytic performance. This work provides a reliable strategy to redisperse bimetallic NiRu nanoparticles into small ones with more intermetallic interfaces.

Photochemically Controlled Release of the Glucose Transporter 1 Inhibitor for Glucose Deprivation Responses and Cancer Suppression Research.

Cancer cells need a greater supply of glucose mainly due to their aerobic glycolysis, known as the Warburg effect. Glucose transport by glucose transporter 1 (GLUT1) is the rate-limiting step for glucose uptake, making it a potential cancer therapeutic target. However, GLUT1 is widely expressed and performs crucial functions in a variety of cells, and its indiscriminate inhibition will cause serious side effects. In this study, we designed and synthesized a photocaged GLUT1 inhibitor WZB117-PPG to suppress the growth of cancer cells in a spatiotemporally controllable manner. WZB117-PPG exhibited remarkable photolysis efficiency and substantial cytotoxicity toward cancer cells under visible light illumination with minimal side effects, ensuring its safety as a potential cancer therapy. Furthermore, our quantitative proteomics data delineated a comprehensive portrait of responses in cancer cells under glucose deprivation, underlining the mechanism of cell death via necrosis rather than apoptosis. We reason that our study provides a potentially reliable cancer treatment strategy and can be used as a spatiotemporally controllable trigger for studying nutrient deprivation-related stress responses.

Dual-Catalyzed Stereodivergent Electrooxidative Homocoupling of Benzoxazolyl Acetate.

The development of a reliable strategy for stereodivergent radical reactions that allows convenient access to all stereoisomers of homocoupling adducts with multiple stereogenic centers remains an unmet goal in organic synthesis. Herein, we describe a dual-catalyzed electrooxidative C(sp3)-H/C(sp3)-H homocoupling with complete absolute and relative stereocontrol for the synthesis of molecules with contiguous quaternary stereocenters in a general and predictable manner. The stereodivergent electrooxidative homocoupling reaction is achieved by synergistically utilizing two distinct chiral catalysts that convert identical racemic substrates into inherently distinctive reactive chiral intermediates, dictate enantioselective radical addition, and allow access to the full complement of stereoisomeric products via simple catalyst permutation. The successful execution of the dual-electrocatalytic strategy programmed via electrooxidative activation provides a significant conceptual advantage and will serve as a useful foundation for further research into cooperative stereocontrolled radical transformations and diversity-oriented synthesis.

Illuminating a Solvent-Dependent Hierarchy for Aromatic CH/π Complexes with Dynamic Covalent Glyco-Balances.

CH/π interactions are prevalent among aromatic complexes and represent invaluable tools for stabilizing well-defined molecular architectures. Their energy contributions are exceptionally sensitive to various structural and environmental factors, resulting in a context-dependent nature that has led to conflicting findings in the scientific literature. Consequently, a universally accepted hierarchy for aromatic CH/π interactions has remained elusive. Herein, we present a comprehensive experimental investigation of aromatic CH/π complexes, employing a novel approach that involves isotopically labeled glyco-balances generated in situ. This innovative strategy not only allows us to uncover thermodynamic insights but also delves into the often less-accessible domain of kinetic information. Our analyses have yielded more than 180 new free energy values while considering key factors such as solvent properties, the interaction geometry, and the presence and nature of accompanying counterions. Remarkably, the obtained results challenge conventional wisdom regarding the stability order of common aromatic complexes. While it was believed that cationic CH/π interactions held the highest strength, followed by polarized CH/π, nonpolarized CH/π, and finally anionic CH/π interactions, our study reveals that this hierarchy can be subverted depending on the environment. Indeed, the performance of polarized CH/π interactions can match or even outcompete that of cationic CH/π interactions making them a more reliable stabilization strategy across the entire spectrum of solvent polarity. Overall, our results provide valuable guidelines for the selection of optimal interacting partners in every chemical environment, allowing the design of tailored aromatic complexes with applications in supramolecular chemistry, organocatalysis, and/or material sciences.

A Comprehensive Reliability Strategy for Managing Assets of Redundant Customer Delivery Systems

A reliability strategy was developed in 2020 for the purpose of improving the reliability of the dual element spot network (DESN) stations. The strategy utilized the transmission outage data system (TODS) data-base and some reliability models to identify DESN stations with the worst reliability performance so that investment dollars can be directed towards the reliability improvement of those stations. Recently, a comprehensive reliability strategy has been developed to do a similar task of improving the overall reliability of the DESN stations. The new strategy first maps the delivery point interruption data to the TODS outage data to determine the frequencies of the main causes of supply interruptions to delivery points. Then, it identifies action plans (or remedial actions) that are needed in order to reduce the frequencies of the dominant outage causes. Finally, the strategy uses a benefit/cost analysis to select the preferred action plans in order to improve the overall reliability of the DESN stations. The new strategy is more practical and has numerous advantages over the existing one. The purpose of this paper is to describe the new reliability strategy, its advantages over the existing one and to show how to apply it in the DESN stations.

Facile fabrication of Co-doped cerium-manganese oxide for enhancing peroxymonosulfate activation to rapidly achieve simultaneous elimination of p-arsanilic and its oxidation by-product As(V)

Efficient purification of the wastewater containing organoarsenic by activated peroxymonosulfate (PMS) usually faces with a great challenge because the degradation of organoarsenic is coupled with the release of its byproduct As(V). Heterogeneous catalysts with catalytic and adsorption functions show great potential in activating PMS for the degradation of organoarsenic and the removal of secondary inorganic arsenic. In this study, Co-CeMnO was designed and fabricated to realize simultaneous elimination of p-arsanilic (p-ASA) and As(V) in Co-CeMnO (0.2 g/L)/PMS (0.25 mM) system, in which 50 µM p-ASA was almost completely degraded within 5 min and approximately 100% of the produced As(V) was removed within 30 min. The rate constant of the pseudo-first-order kinetics for the p-ASA degradation by PMS mediated with Co-CeMnO was high up to 0.65 min−1, approximately 6.5 times higher than that in the system of CeMnO/PMS. It was revealed that SO4•−, •OH and 1O2 acted as the main oxidant species responsible for the oxidation of organics and As(III), and the surface −OH of Co-CeMnO led to the adsorption of As(V) via ion exchange. The excellent reusability and stability of Co-CeMnO was verified by five cycles with high removal efficiencies of p-ASA (>92% within 10 min) and arsenic (>98% within 90 min) and low leached metal ion concentrations (Co ions < 0.27 mg/L; Mn ions < 0.15 mg/L; Ce ions ≈ 0). Under the condition of initial pH 5, p-ASA was degraded completely and over 98% of total arsenic was adsorbed in different water matrices, indicating the practical application potential of Co-CeMnO/PMS system. Thus, the present study provided a reliable PMS activation strategy by constructing bifunctional catalysts to achieve satisfactory treatment of the wastewater containing p-ASA.

Alarm Webs: A Framework for Decoding RAN Alarm Dynamics

This paper introduces “Alarm Webs”, a pioneering framework designed to decode the dynamics of Radio Access Network (RAN) alarms, utilizing a novel graph-theoretic approach. Leveraging directed graphs (digraphs), this work uniquely encodes RAN alarm data, with each alarm represented as a node and its severity indicated by distinct colors. The edges of these graphs signify the sequence of alarms, creating a directional flow from one alarm to the next. Utilizing a comprehensive dataset from a major telecommunications service provider in the UK, encompassing alarms from 4G and 5G networks across over 7,000 base stations, the framework ofers an unprecedented analysis of alarm patterns and interactions. The proposed methodology involves the calculation of in-degrees and out-degrees for each node, identifying those with in-degrees higher than four as significant indicators of commonly resulting alarms. This threshold-based selection is instrumental in isolating the most impactful alarms. Additionally, the application of Sankey diagrams brings an intuitive visualization of alarm causality, based on the in-degree centrality of the nodes. This approach not only clarifies the complex interrelationships among alarms but also aids in identifying potential cascading issues within the network. By effectively mapping alarm sequences and identifying key alarms, this framework paves the way for enhanced network reliability and proactive maintenance strategies in the ever-evolving telecommunications landscape.

Chinese experts consensus on aldehyde metabolism disorder guided the early management of emergency and critical care medicine (2023)

Emergency and critical diseases is characterized by suddenness, complexity and unpredictability, which can lead to severe adverse prognosis such as shock or multiple organ failure. It has been confirmed that the common mechanism of aldehyde metabolism disorder leading to the accumulation of a large number of aldehydes, injury of cells and tissues caused by toxic aldehydes, and organ dysfunction existed in various emergency and critical diseases. However, the definition of the theory of aldehyde metabolism disorder, the detection methods of aldehydes, and the application of the theory of aldehyde metabolism disorder in guiding the early treatment of emergency and critical diseases have not been systematized and standardized. Therefore, Chinese Society of Emergency Medicine, Chest Pain Branch of China International Exchange and Promotive Association for Medical and Health Care, and Multidisciplinary Joint Committee on Cardiopulmonary Resuscitation and Extracorporeal Life Support of Shandong Medical Association organized multidisciplinary experts in emergency and critical care medicine, pharmacy, and molecular chemistry, etc., to comprehensively review the basic and clinical research on the effect of aldehyde metabolism disorder in the early stage of emergency and critical diseases at home and abroad, and jointly formulated the Chinese experts consensus on aldehyde metabolism disorder guided the early management of emergency and critical care medicine (2023). The novel and common consensus on the aldehyde metabolism disorder aims to further improve the treatment level of the emergency and critical diseases, so as to put forward a new, safe and reliable treatment strategy for the critical patients, and improve the overall survival rate of the critical patients.

A Transfer Learning Method to Generate Synthetic Synoptic Magnetograms

AbstractCurrent magnetohydrodynamics (MHD) models largely rely on synoptic magnetograms, such as the ones produced by the Global Oscillation Network Group (GONG). Magnetograms are currently available mostly from the front side of the Sun, which significantly reduces the accuracy of MHD modeling. Extreme Ultraviolet (EUV) images can instead be obtained from other vantage points. To investigate the potential, we explore the possibility of using EUV information from the Atmospheric Imaging Assembly (AIA) to directly generate the input for the state‐of‐the‐art 3D MHD model European Heliospheric FORecasting Information Asset (EUHFORIA). Toward this goal, we develop a method called Transfer‐Solar‐GAN which combines a conditional generative adversarial network with a transfer learning approach to overcome training data set limitations. The source domain data set is constructed from multiple pairs of the central portion of co‐registered AIA and Helioseismic and Magnetic Imager (HMI) line of sight (LOS) full‐disk images, while the target domain is constructed from pairs of portions of AIA and GONG sine‐latitude synoptic maps that we call segments. We evaluate Transfer‐Solar‐GAN by comparing modeled and measured solar wind velocity and magnetic field density parameters at the L1 Lagrange point and along the Parker Solar Probe (PSP) trajectory which were determined with EUHFORIA using both empirical GONG and artificial‐intelligence (AI)‐synthetic synoptic magnetograms as inputs. Our results demonstrate that the Transfer‐Solar‐GAN model can provide the necessary information to run solar physics models by EUV information. Our proposed model is trained with only 528 paired image segments and enforces a reliable data division strategy.