Search

Carbapenem-resistant Acinetobacter baumannii (CRAB) is a Priority 1 (Critical) pathogen urgently requiring new antibiotics. Polymyxins are a last-line option against CRAB-associated infections. This transcriptomic study utilized a CRAB strain to investigate mechanisms of bacterial killing with polymyxin B, colistin, colistin B, and colistin/sulbactam combination therapy. After 4 h of 2 mg/L polymyxin monotherapy, all polymyxins exhibited common transcriptomic responses which primarily involved disruption to amino acid and fatty acid metabolism. Of the three monotherapies, polymyxin B induced the greatest number of differentially expressed genes (DEGs), including for genes involved with fatty acid metabolism. Gene disturbances with colistin and colistin B were highly similar (89 % common genes for colistin B), though effects on gene expression were generally lower (0–1.5-fold in most cases) with colistin B. Colistin alone (2 mg/L) or combined with sulbactam (64 mg/L) resulted in rapid membrane disruption as early as 1 h. Transcriptomic analysis of this combination revealed that the effects were driven by colistin, which included disturbances in fatty acid synthesis and catabolism, and inhibition of nutrient uptake. Combination therapy produced substantially higher fold changes in 72 % of DEGs shared with monotherapy, leading to substantially greater reductions in fatty acid biosynthesis and increases in biofilm, cell wall, and phospholipid synthesis. This indicates synergistic bacterial killing with the colistin/sulbactam combination results from a systematic increase in perturbation of many genes associated with bacterial metabolism. These mechanistic insights enhance our understanding of bacterial responses to polymyxin mono- and combination therapy and will assist to optimize polymyxin use in patients.

MnCoGe-based alloys represent promising candidates for magnetic refrigeration due to their advantageous Curie temperature and structural transition temperature near room temperature, coupled with exceptional magnetocaloric effect (MCE). However, the practical application of these materials is constrained by their inferior mechanical properties. Although resin bonding enhanced these properties, it simultaneously detracted from the MCE. In order to overcome this challenge, a novel synthesis method combining arc melting and hot press sintering is proposed. This approach led to an enhancement in the mechanical properties of MnCoGe-based alloys without compromising their MCE. The results of our investigation indicated that the Mn1·16Co0.84Ge alloy has achieved an unprecedented compressive stress of 367 MPa. At room temperature, this alloy undergoes a first-order martensitic phase transformation characterized by a mixed crystal structure comprised of hexagonal austenite and orthorhombic martensite. Furthermore, the Mn0·91Co1.09Ge alloy demonstrated a maximum isothermal entropy change of 19.5 J/kg K under a 7 T magnetic field. This study establishes a robust framework for designing high-performance magnetic refrigeration materials that integrate excellent mechanical properties with superior MCE.

Background: In the recent decade, there has been substantial progress in the technologies and philosophies associated with diagnosing and treating anterior cruciate ligament (ACL) injuries in China. The therapeutic efficacy of ACL reconstruction in re-establishing the stability of the knee joint has garnered widespread acknowledgment. However, the path toward standardizing diagnostic and treatment protocols remains to be further developed and refined. Objective: In this context, the Chinese Association of Orthopaedic Surgeons (CAOS) and the Chinese Society of Sports Medicine (CSSM) collaboratively developed an expert consensus on diagnosing and treating ACL injury, aiming to enhance medical quality through refining professional standards. Methods: The consensus drafting team invited experts across the Greater China region, including the mainland, Hong Kong, Macau, and Taiwan, to formulate and review the consensus using a modified Delphi method as a standardization approach. As members of the CSSM Lower Limb Study Group and the CAOS Arthroscopy and Sports Medicine Study Group, invited experts concentrated on two pivotal issues: “Graft Selection” and “Clinical Outcome Evaluation” during the second part of the consensus development. Results: This focused discussion ultimately led to a strong consensus on nine specific consensus terms. Conclusion: The consensus clearly states that ACL reconstruction has no definitive “gold standard” graft choice. Autografts have advantages in healing capability but are limited in availability and have potential donor site morbidities; allografts reduce surgical trauma but incur additional costs, and there are concerns about slow healing, quality control issues, and a higher failure rate in young athletes; synthetic ligaments allow for early rehabilitation and fast return to sport, but the surgery is technically demanding and incurs additional costs. When choosing a graft, one should comprehensively consider the graft's characteristics, the doctor's technical ability, and the patient's needs. When evaluating clinical outcomes, it is essential to ensure an adequate sample size and follow-up rate, and the research should include patient subjective scoring, joint function and stability, complications, surgical failure, and the return to sport results. Medium and long-term follow-ups should not overlook the assessment of knee osteoarthritis.

The all-d-metal Ni–Mn–Ti Heusler alloy with its good mechanical properties and colossal caloric effects has attracted significant attention for mechanocaloric refrigeration. However, the phase stability of the B2-type disordered structure at finite temperatures and the physical origin of large phase transformation entropy change in theoretical calculation remain unclear. In view of thermal and strongly anharmonic effects, we combined the first-principles and temperature dependent effective potential calculations to systematically study the phase stability, martensitic transformation mechanism, and vibrational entropy properties of B2 partial disordered structures for Ni8Mn5Ti3 and Ni8Mn6Ti2. Our results showed the austenitic structures of Ni8Mn5Ti3 and Ni8Mn6Ti2 both exhibit antiferromagnetic interaction behaviors at targeted temperatures, resolving the contradiction between previous calculations and experiments. By the analysis of phonon dispersion relations and Helmholtz free energies at low and high temperatures, we provided a deeper explanation for the underlying mechanism of martensitic transformation. Meanwhile, the phase transformation temperatures and vibrational entropy changes were accurately predicted compared with the experiment results. Specifically, we demonstrated that the large vibrational entropy change of Ni–Mn–Ti material originates from the contributions of both the tetragonal distortion ratio and volume change, which provides important theoretical guidance and has great practical significance for designing the solid-state material with large vibrational entropy change in the application of solid-state refrigeration.

Radioisotopes tend to play important roles in many fields, such as industry, healthcare, agriculture, aerospace, etc. Radioisotope production is mainly through accelerators or research reactors, and high flux research reactor is one of the most effective approaches for radioisotope production. The physical basis of preparing radioisotope relies on nuclear reactions occurring in the reactor core, which includes fission, (n,γ), (n,α), and (n,p) reaction, etc. Among them, fission and (n,γ) reaction are most important in the nuclear reactor. For example, the 99Mo could be generated by uranium fission and extracting from the fission products, or through the radiative capture reaction from enriched 98Mo. As for the fission method, the irradiation target is gradually transitioning from high enriched uranium (HEU) target to low enriched uranium (LEU) target due to the requirement of non-proliferation. In this paper, studies on the impacts of different fission targets on radioisotope productions are conducted. Moreover, an optimized study on the radiative capture method is performed to improve the production efficiency. It is concluded that it is advantageous to use radiative capture method to generate radioisotopes in high flux reactor, which helps to improve the specific activity with environmental friendliness.

Superelasticity of shape memory alloy associated with the martensitic transformation is extremely attractive for applications in sensors and biomedical. This application requires narrow stress hysteresis to reduce energy dissipation and a stable superelasticity cycle is an important factor in their practical applications. Co–V–Al alloys have inimitable advantages due to their narrow stress hysteresis, low-cost, and corrosion resistance, but the low number of superelasticity cycles restricts its development. Here, we report an intrinsic Co58V29Al13 polycrystalline alloy with a superelasticity stress hysteresis of 30 MPa at room temperature, the lowest among the alloys in this system, and a superelasticity strain of 3.6%. In addition, the sample shows no significant decay trend after 500 loading and unloading cycles. The high number of superelasticity cycles is mainly due to the elastic stress field generated around the dislocation during the cycle, which provides internal stress for martensite nucleation and reduces energy dissipation during martensitic transformation. This work provides essential guiding significance for the design of high-performance superelasticity alloys.

Malaria remains a major public health concern. The rapid spread of resistance to antimalarial drugs is a major challenge for malaria eradication. Timely and accurate molecular monitoring based on practical detection methods is a critical step toward malaria control and elimination. In this study, two rapid detection techniques, allele-specific PCR (AS‒PCR) and recombinase-aided amplification (RAA) combined with CRISPR/Cas12a, were established, optimized and assessed to detect single nucleotide polymorphisms in the Plasmodium falciparum exonuclease (Pfexo) gene related to suspected piperaquine resistance. Moreover, phosphorothioate and artificial mismatches were introduced into the allele-specific primers for AS‒PCR, and crRNA-mismatched bases were introduced into the RAA‒CRISPR/Cas12a assay because crRNAs designed according to conventional rules fail to discriminate genotypes. As a result, the detection limits of the AS‒PCR and RAA‒CRISPR/Cas12a assays were 104 copies/μL and 103 copies/μL, respectively. The detection threshold for dried blood spots was 100‒150 parasites/μL, with no cross-reactivity against other genotypes. The average cost of AS‒PCR is approximately $1 per test and takes 2–3 h, whereas that of the RAA‒CRISPR/Cas12a system is approximately $7 per test and takes 1 h or less. Therefore, we provide more options for testing single nucleotide polymorphisms in the Pfexo gene, considering economic conditions and the availability of instruments, equipment, and reagents, which can contribute to the molecular monitoring of antimalarial resistance.

Chickpea protein isolate (CPI) is a promising dietary protein with the advantages of low allergenicity, easy digestion and balanced composition of essential amino acids. However, due to the thick skin of chickpeas, the extraction of CPI is challenging, resulting in lower efficiency of the alkaline extraction-isoelectric precipitation (AE-IEP) method. Therefore, the present study investigated the effect of pulsed electric field combined with ultrasound (PEF-US) treatment on the extraction efficiency of CPI and the functional properties was characterized. Parameter optimization was carried out using response surface methodology (RSM), with the following optimized conditions: pulse duration of 87 s, electric field intensity of 0.9 kV/cm, ultrasonic time of 15 min, and ultrasonic power of 325 W. Under the optimized conditions, the yield of CPI after combined (PEF-US) treatment was 13.52 ± 0.13 %, which was a 47.28 % improvement over the AE-IEP method. This yield was better than that obtained with either individual PEF or US treatment. Additionally, the functional properties (solubility, emulsification, and foaming) of CPI were significantly enhanced compared to AE-IEP. However, the stability of emulsification and foaming did not show significant differences among the four methods. The PEF-US method efficiently extracts CPI with excellent functional properties, enabling the production of proteins as desired functional additives in the food industry.

Enhancing photosynthesis is a pivotal strategy for achieving sustainable plant production. Blue and red light facilitate plant growth since these wavelengths are readily absorbed by chlorophyll pigments and power crucial photosynthetic processes. In this investigation, double light conversion films were prepared by incorporating biomass-derived carbon dots into a polyvinyl alcohol matrix (CDs@PVAs). The study conclusively demonstrated that CDs@PVAs can convert ultraviolet and green light from sunlight into blue and red light. Using 2-week-old Athaliana plants as the model organism, the Athaliana plants were covered with CDs@PVAs and then exposed to simulated sunlight (0.57 mW cm−2) for 1 hour. The Fv/Fm value in the presence of the CDs@PVAs was approximately 12% higher than without the film, indicating a significant boost in photosynthesis. Analysis of gene expression showed that the CDs@PVAs cause significant upregulation of genes associated with photosynthesis. These double light conversion films thus emerge as promising contenders for eco-friendly plant cultivation methods that circumvent reliance on electric power. Their potential applications in agriculture are substantial, underscoring their significance in promoting sustainable practices.

The oil-paper insulation system in eco-friendly fire-retardant transformers depends on hydrophilic natural ester insulating oil. Moisture within the system synergistically interacts with aging, worsening oil-paper insulation degradation and hastening overall system aging. Chemical vapor deposition was used to create parylene surface-modified insulating paper as a strategy to inhibit moisture-induced aging in natural ester oil-paper insulation. The effectiveness of the approach was identified by a comprehensive assessment of the physicochemical and electrical properties of the parylene surface-modified insulating paper. The findings from accelerated thermal aging at 130 °C for 90 days on the natural ester oil-paper insulation system reveal the outstanding lipophilic and hydrophobic properties while maintaining electrical characteristics of the parylene surface-modified insulating paper. After 90 days of aging, the parylene surface-modified insulating paper exhibited a 56.76 % higher degree of polymerization and a 19.36 % significantly lower moisture content than conventional cellulose insulating paper. In the natural ester oil-paper insulation system, the parylene surface-modified insulating paper led to a notable 63 % reduction in insulating oil acid value, a 60.50 % decrease in dielectric loss, and a substantial 20.35 % increase in AC breakdown voltage. Molecular-level investigations revealed the inhibitory mechanism of the parylene film, offering a promising solution to enhance the thermal stability and aging resistance of natural ester oil-paper insulation systems.

Deoxynivalenol (DON), a prevalent and highly toxic mycotoxin in animal feed, poses significant risks to livestock health and productivity. This study evaluates the effectiveness of iron-manganese oxide (Fe/Mn oxides) in degrading DON. The DON degradation rate of Fe/Mn oxide reached 98.46 % in a controlled solution under specific conditions (0.2 % concentration, 37–85 °C, pH 6–7, 1-minute reaction time). When applied to actual feed, it reduced DON levels by approximately 49.3 % and remained stable in simulated gastrointestinal environments of weaned piglets. A 28-day trial involving 48 weaned piglets assessed the impacts of Fe/Mn oxides on health and growth. Results indicated that piglets consuming contaminated feed without the treatment exhibited reduced growth and compromised gut integrity, which were significantly mitigated by the addition of Fe/Mn oxides. Therefore, Fe/Mn oxides effectively reduce DON in feed and alleviate adverse health effects in piglets, making them a viable option to enhance safety and performance in mycotoxin-prone environments.

Summary: Artificial intelligence (AI) is rarely directly used in patent foramen ovale (PFO) diagnosis. In this study, an AI model was developed to detect the presence of PFO automatically in both contrast transthoracic echocardiography (cTTE) images and videos. The whole intelligent diagnosis neural network framework consists of two functional modules of image segmentation (Unet, n = 1866) and image classification (ResNet 101, n = 9152). Finally, another test databases, including 20 cTTE videos (4609 cTTE images), was used to compare the RLS classification model accuracy between AI model and different levels of physicians. The Dice similarity coefficient of left chamber segmentation model of cTTE images was 91.41%, the accuracy of PFO-RLS classification model of cTTE images was 83.55%, the accuracy of PFO-RLS classification model of cTTE videos was 90%. Besides, the AI diagnosis time was significantly shorter than doctors (at only 1.3 s).

Endometrial cancer (EC) is one of the most common gynecologic malignancies, which lacking effective drugs for intractable conditions or patients unsuitable for surgeries. Recently, the patient-derived organoids (PDOs) are found feasible for cancer research and drug discoveries. Here, we have successfully established a panel of PDOs from EC and conducted drug repurposing screening and mechanism analysis for cancer treatment. We confirmed that the regulatory β subunit of methionine adenosyltransferase (MAT2B) is highly correlated with malignant progression in endometrial cancer. Through drug screening on PDOs, we identify JX24120, chlorpromazine derivative, as a specific inhibitor for MAT2B, which directly binds to MAT2B (Kd = 4.724 μM) and inhibits the viability of EC PDOs and canonical cell lines. Correspondingly, gene editing assessment demonstrates that JX24120 suppresses tumor growth depending on the presence of MAT2B in vivo and in vitro. Mechanistically, JX24120 induces inhibition of S-adenosylmethionine (SAMe) synthesis, leading to suppressed mTORC1 signaling, abnormal energy metabolism and protein synthesis, and eventually apoptosis. Taken together, our study offers a novel approach for drug discovery and efficacy assessment by using the PDOs models. These findings suggest that JX24120 may be a potent MAT2B inhibitor and will hopefully serve as a prospective compound for endometrial cancer therapy.

Objective: An alternative to conventional posterior lumbar interbody fusion (PLIF) is a PLIF with transpedicular oblique screw fixation system. An assessment of new fixation system's viability and efficacy is conducted through a comparison of its biomechanical properties with those of conventional PLIF. Method: A comprehensive finite element model (FEM) of the lumbar regions L1-L5 was developed and the surgical segment L3-L4 was chosen to comprise the surgical models of both traditional PLIF and new PLIF. In new PLIF model, an analysis was conducted on segmental range of motion (RoM), cage stress, inferior endplates stress, vertebral stress, and internal fixation stress. Three-dimensional printers are utilized to fabricate and assemble the fusion cage and vertebrae, and compression test machines are employed to execute physiological load and extreme load experiments on new PLIF, so as to verify the accuracy of the FEM analysis and the mode of fatigue exhibited by new PLIF. Results: In new PLIF, the maximum stress on the inferior endplates under physiological loads was reduced in comparison to conventional PLIF. While the maximum stress on the cage, vertebral body, and screw increased, it remained within an acceptable range. The experimental data indicates that new fixation system can endure a vertical load exceeding 2800 N and an ultimate bending moment of 77 Nm. Conclusion: The new PLIF exhibits a comparable RoM to its predecessor, simultaneously mitigating inferior endplate stress and accommodating physiological loads, which reduce the amount of surgical incision and fusion fixation instruments. Consequently, it emerges as a sanguine surgical approach to fuse the degenerative lumbar spine.

Background: Firearms are the leading cause of victimization of abused women by intimate partner homicide and intimate partner homicide-suicides in the US. This calls for evidence-based intervention strategies to prevent firearm-related injuries or mortality and address the firearms-related safety needs of women in abusive relationships. My Safety Steps (MySteps) was designed to comprehensively assess women's firearm-related risks, and current safety needs and to prevent women's harm from their abuser's access or ownership of a firearm through a digitally delivered firearm-focused safety planning intervention. This paper describes the development, feasibility, acceptability, and preliminary evaluation of the digital BSHAPE intervention among women survivors of intimate partner violence (IPV). Methods: Using a pretest post-test control group design, the study was conducted with 103 participants with 55 women randomly assigned to the MySteps arm and 48 women to the standard of care control arm. The feasibility and acceptability outcomes assessed were enrollment, adherence, and perceptions of the intervention. Preliminary evaluation outcomes included the partner's access to a firearm, women's self-efficacy beliefs, and empowerment. Further, qualitative follow-up interviews were conducted with 30 survivors of IPV in the MySteps arm to follow up on the use and helpfulness of safety strategies provided in MySteps. Results and conclusion: The intervention was found to be feasible, and acceptable and demonstrated improved outcomes for survivors of IPV at risk from their partner's firearm. Women provided feedback for further refinement. The findings of this study will be useful in further refining MySteps and testing it in a full-scale randomized controlled trial.

Heavy metals (HMs) pollution is a globally emerging concern. It is difficult to cost-effectively combat such HMs polluted soil environments. The efficient remediation of HMs polluted soil is crucial to protect human health and ecological security that could be carried out by several methods. Amidst, biological remediation is the most affordable and ecological. This review focused on the principles, mechanisms, performances, and influential factors in bioremediation of HMs polluted soil. In microbial remediation, microbes can alter metallic compounds in soils. They transform these compounds into their metabolism through biosorption and bioprecipitation. The secreted microbial enzymes act as transformers and assist in HMs immobilization. The synergistic microbial effect can further improve HMs removal. In bioleaching, the microbial activity can simultaneously produce H2SO4 or organic acids and leach HMs. The production of acids and the metabolism of bacteria and fungi transform metallic compounds to soluble and extractable form. The key bioleaching mechanisms are acidolysis, complexolysis, redoxolysis and bioaccumulation. In phytoremediation, hyperaccumulator plants and their rhizospheric microbes absorb HMs by roots through absorption, cation exchange, filtration, and chemical changes. Then they exert different detoxification mechanisms. The detoxified HMs are then transferred and accumulated in their harvestable tissues. Plant growth-promoting bacteria can promote phytoremediation efficiency; however, use of chelants have adverse effects. There are some other biological methods for the remediation of HMs polluted soil environment that are not extensively practiced. Finally, the findings of this review will assist the practitioners and researchers to select the appropriate bioremediation approach for a specific soil environment.

Chinese bayberry residue (CBR) is a by-product of processing, which can be used as an auxiliary material during the processing of quinoa rice wine. In this study, the effects of CBR on the chemical profile, bioactive function, taste traits, and flavor of Chinese quinoa rice wine (CQRW) were investigated. The results showed that adding CBR increased the total phenolics, the total flavonoids, and antioxidant capacity. Malic acid content was the highest in Chinese rice wine (CRW), while the total content of components detected in HPLC-MS/MS was the highest in 10%CBR + CQRW. The CQRW exhibited the highest amino acid content, followed by 20%CBR + CQRW. E-tongue analysis results showed that 10%CBR + CQRW, 20%CBR + CQRW, and CQRW had the closest taste traits. Moreover, GC–MS analysis identified 72 aroma compounds in 10%CBR + CQRW sample, more than other samples. In summary, adding 10% CBR significantly improved the quality of CQRW.

Transparent photoresists with a high refractive index (RI) and high transmittance in visible wavelengths have promising functionalities in optical fields. This work reports a kind of tunable optical material composed of titanium dioxide nanoparticles embedded in acrylic resin with a high RI for ultraviolet (UV)-imprint lithography. The hybrid film exhibits a tunable RI of up to 1.67 (589 nm) after being cured by UV light, while maintaining both a high transparency of over 98% in the visible light range and a low haze of less than 0.05%. The precision machining of optical microstructures can be imprinted easily and efficiently using the hybrid resin, which acts as a light guide plate (LGP) to guide the light from the side to the top in order to conserve the energy of the display device. These preliminary studies based on both laboratory and commercial experiments pave the way for exploiting the unparalleled optical properties of nanocomposite resins and promoting their industrial application.

Introduction and Objectives: With rising prevalence of pre-sarcopenia in metabolic dysfunction-associated steatotic liver disease (MASLD), this study aimed to develop and validate machine learning-based model to identify pre-sarcopenia in MASLD population. Materials and Methods: A total of 571 MASLD subjects were screened from the National Health and Nutrition Examination Survey 2017–2018. This cohort was randomly divided into training set and internal testing set with a ratio of 7:3. Sixty-six MASLD subjects were collected from our institution as external validation set. Four binary classifiers, including Random Forest (RF), support vector machine, and extreme gradient boosting and logistic regression, were fitted to identify pre-sarcopenia. The best-performing model was further validated in external validation set. Model performance was assessed in terms of discrimination and calibration. Shapley Additive explanations were used for model interpretability. Results: The pre-sarcopenia rate was 17.51 % and 15.16 % in NHANES cohort and external validation set, respectively. RF outperformed other models with area under receiver operating characteristic curve (AUROC) of 0.819 (95 %CI: 0.749, 0.889). When six top-ranking features were retained as per variable importance, including weight-adjusted waist, sex, race, creatinine, education and alkaline phosphatase, a final RF model reached an AUROC being 0.824 (0.737, 0.910) and 0.732 (95 %CI: 0.529, 0.936) in internal and external validation sets, respectively. The model robustness was proved in sensitivity analysis. The calibration curve and decision curve analysis confirmed a good calibration capacity and good clinical usage. Conclusions: This study proposed a user-friendly model using explainable machine learning algorithm to predict pre-sarcopenia in MASLD population. A web-based tool was provided to screening pre-sarcopenia in community and hospitalization settings.

Compressed Air Energy Storage (CAES) is an effective solution to the problems of the intermittency and volatility of renewable energy. However, the process of compressing air consumes energy and converts it into low-temperature waste heat, limiting the improvement of round-trip efficiency. This paper introduces the dual-pressure evaporation organic Rankine cycle (ORC) to recover the waste heat from the CAES system compression process, which enhances the round-trip efficiency. Optimal working fluids and design schemes of parallel and series dual-pressure evaporation ORCs are analyzed. The thermodynamic performance of two cycle types is compared. The exergy loss distribution characteristics of the dual-pressure evaporation ORC are explored, and the impact on the round-trip efficiency of the CAES system is evaluated. Results show that the parallel dual-pressure evaporation ORC has better performance with an optimum working fluid of R1234yf and a maximum waste heat conversion efficiency of 9.3 %. The round-trip efficiency of the CAES system will be relatively increased by 5.2 % by introducing the parallel dual-pressure evaporation ORC. The maximum exergy efficiency of the parallel dual-pressure evaporation ORC is 52.8 %, and the condenser and low-pressure stage expander have larger exergy losses, accounting for 33.8 % and 22.0 % of the total losses, respectively.

Purpose: To identify brain regions affected by Hypoxic-Ischemic Encephalopathy (HIE) in neonates using Amide Proton Transfer (APT) imaging and Apparent Diffusion Coefficient (ADC). Materials and methods: Twenty neonates were divided into HIE and control groups. All neonates were undergoing MRI, including APT and DWI. Imaging analysis was performed using SPM12. The independent-samples t-test was used to analyze the difference in APTw values and ADC values between the mild HIE neonates and the control group. The receiver operating characteristic (ROC) curves were established to assess the diagnostic values of APTw and ADC values in different brain regions for HIE. Pearson's correlation analysis was used to analyze the correlation between APTw values and ADC values for each region. Results: APTw values were significantly higher in 26 regions of the HIE group. ADC values were lower in the right anterior temporal lobe and higher in bilateral Subthalamic nucleus in HIE. The APTw values of 22 regions showed very high area under the curve (AUC), whereas the AUC of ADC values in right anterior temporal lobe and right subthalamic nucleus were both 0.802. Notably, the right anterior temporal lobe exhibited significant differences in both APTw and ADC values between the HIE and control groups, additionally, APTw value was significant positive correlated with ADC values in right anterior temporal lobe. Conclusion: APTw and ADC are effective in detecting HIE, with APTw being more sensitive. The right anterior temporal lobe is particularly affected by HIE, with significant changes in APTw and ADC values and a positive correlation between them. This suggests that temporal lobe damage may be critical in the long-term neurological consequences of HIE.

Background: Sivelestat, a neutrophil elastase inhibitor, is postulated to mitigate acute lung injury in patients following emergency surgery. However, its efficacy in patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) induced by coronavirus disease 2019 (COVID-19) remains uncertain. This study aims to evaluate the pulmonary protective effects of sivelestat in COVID-19 patients with ALI/ARDS. Methods: A retrospective study was conducted involving 2454 COVID-19 patients between October 5, 2022, and February 1, 2023. Of these, 102 patients received sivelestat (0.2 mg/kg/h), while 2352 age- and sex-matched controls were identified. Propensity score matching (PSM) analysis was used to match sivelestat and non-sivelestat subgroups in ratios of 1:1 and 1:3 for sensitivity analysis. The primary outcome was a composite of effective outcomes, including 30-day mortality. Secondary outcomes included changes in partial pressure of arterial oxygen (PaO2), the ratio of PaO2 to the fraction of inspired oxygen (PaO2/FiO2), and various cytokine levels. Safety evaluations included assessments of liver function, kidney function, and leukopenia. Results: In the propensity score-matched analysis, the sivelestat group had a higher proportion of severe/critical patients (87.26 % vs. 51.02 %, P

Background: Ferroptosis is a new type of programmed cell death. Although ferroptosis has been studied in various aspects, there has been no visual analysis of ferroptosis in coronavirus disease 2019 (COVID-19) to date. It is still a global health concern of the COVID-19 pandemic worldwide, three years after its outbreak. Yet the emergence of the mutant strain Omicron has caused a fourth wave of infections in many countries. The pathogenesis of COVID-19 is still undergoing extensive exploration, which holds paramount importance in mitigating future epidemics. Methods: For this study, CiteSpace 6.2 R4 software was used for bibliometric and visual atlas analysis of ferroptosis-related research, and the Genecards database was used to mine ferroptosis and COVID-19-related genes. Results: We found increasing studies about ferroptosis. China and the United States have demonstrated robust scientific innovation over recent years, with extensive collaboration between their institutions and authors. Ferroptosis and COVID-19 were seen to have 13 shared genes, which may be new targets for the treatment of COVID-19 in the future. Most of the shared genes are enriched in tumor necrosis factor (TNF) pathways. The majority of those genes are up-regulated under the cellular response to oxidative stress. Genes including Tumour necrosis factor (TNF), RELA proto-oncogene (RELA), Activating transcription factor 4 (ATF4), Cytochrome b-245 beta chain (CYBB), Jun proto-oncogene (JUN), Mitogen-activated protein kinase 1 (MAPK1) and Heme oxygenase 1 (HMOX1), maybe a breakthrough for ferroptosis and COVID‐19. Whilst previous research has shown there to be a relationship between ferroptosis and COVID‐19, the specific role of ferroptosis remained unclear. Our study aimed to analyze the research status of ferroptosis and its relationship with COVID-19, to provide a useful reference for further prevention and treatment of COVID-19. Overall, uncovering the role of ferroptosis in SARS-CoV-2 infection is important for the development of new treatment strategies for COVID-19.

Obesity management can effectively reduce the risks and complications associated with obesity and improve the quality of life of patients. After assessing the advantages and limitations of various obesity management approaches, self-management has been strongly recommended due to the advantages of minimal side effects and lower costs compared to treatment via drugs and surgery. However, successfully implementing lifestyle intervention strategies requires scientific guidance and strong determination. With the development of electronic and information technology, lifestyle intervention has transformed considerably. A new concept, called Gamified Digital Therapeutics (GDTx), represents a gaming format with Digital Therapeutics (DTx). It can effectively enhance patient compliance and accessibility to chronic disease management. Here, we review recent studies on the application of GDTx for the self-management of obesity and discuss three aspects surrounding its completion rates, satisfaction levels, and effectiveness. In contrast to traditional approaches to obesity self-management, implementing GDTx effectively corrects unhealthy dietary and lifestyle habits, markedly enhancing the dissemination of nutritional and exercise-related health knowledge. Of particular significance is the evident improvement in the adherence of obese patients to weight loss programs. Despite numerous studies indicating that GDTx may offer an effective solution for obesity self-management, there are still several limitations in the medicalization of GDTx for self-management of obesity. This review aimed to provide a reference for subsequent studies and promote the widespread application of GDTx in obesity self-management to help reduce the obesity rate and alleviate the burden on obese patients.

The sustainability and additive manufacturing of dielectric insulators are the development direction of the power system. Introducing dynamic covalent bonds in light-based 3D printing have attracted considerable attention as the reversible crosslinks allow for the reprocessing of printed objects. However, there generally exists a trade-off between mechanical strength, glass transition temperature (Tg), and reconfigurability for dynamic covalent networks. The reconfiguring process of the dynamic covalent network often requires high mobility of molecular chains and large free volumes, which in turn decreases the mechanical strength, Tg, and electrical insulating performance. Herein, we demonstrate a novel strategy for developing a kind of mechanically robust and sustainable vitrimer by building a rigid-flexible coupling inter-penetration network (IPN). Specifically, a two-stage curing approach was used to prepare high-performance 3D-printing vitrimers by using the plant oil-epoxy hybrid resin, which brings a lot of ester bonds and β-hydroxyl ester for the crosslinking network. Computational techniques with molecular dynamics calculation are used for the design and optimization of the crosslinking network, and then the optimized IPN is prepared by digital light processing 3D printing and subsequent heat curing. In the IPN, the epoxy backbone is rigid to enhance the Tg and tensile strength, while the plant-based methacrylate is flexible to guarantee topological rearrangement at elevated temperatures. Compared to reported epoxy vitrimers, the resultant IPN exhibits simultaneous high Tg (111 °C), outstanding tensile strength and toughness (tensile strength of 70 MPa, elongation at break of 17.58 %), good topological rearrangement, and excellent dielectric properties (permittivity less than 4, breakdown strength of 49.3 kV/mm). This work provides a new strategy for balancing the strength, toughness, electrical insulating and sustainability of 3D-printed thermosets.

The utilization of ultrasonic guided wave technology for detecting cracks in railway tracks involves analyzing echo signals produced by the interaction of cracks with guided wave modes to achieve precise crack localization, which is extremely important in a real-time railway crack robotic detection system. Addressing the challenge of selecting the optimal detection mode for cracks in various regions of railway tracks, this paper presents a method for optimal crack detection mode selection. This method is based on the sensitivity of guided wave modes to cracks. By examining the frequency dispersion characteristics and mode shapes of guided wave modes, we establish indicators for crack zone energy and crack reflection intensity. Our focus is on the railhead of the railway track, selecting guided wave modes characterized by specific cracks for detection purposes. Experimental findings validate the accuracy of our proposed mode selection method in detecting cracks in railway tracks. This research not only enhances crack detection but also lays the groundwork for exploring advanced detection and localization techniques for cracks in railway tracks.

Background: For locally advanced cervical cancer (LACC), treatment response to radiotherapy (RT) can vary significantly even among those with the same stage classification of International Federation of Gynecology and Obstetrics (FIGO). This study investigated the value of ADC metric for forecasting end-of-treatment outcomes in LACC patients referred for RT. Methods: Eighty patients with pathologically confirmed cervical squamous cell carcinoma with (SCC) were included in the research. Abdominal or pelvic MRI scans were conducted at least three times for all participants: before RT, three weeks after beginning of RT and approximately two months after RT was finalized. Calculated apparent diffusion coefficient (ADC) values of the LACC include: pre-ADC, interim-ADC, ΔADC and Δ%ADC. Based on Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, subjects were calculated and subsequently categorized into good responders group (complete response) and poor responders group (progressive disease, stable disease or partial response). Results: Compared to good-responders, subjects of poor-responder group showed significantly lower values of interim-ADC, ΔADC, and Δ%ADC (all P

In this study, a systematic analysis was conducted to investigate the efficiency and mechanism of methylene blue (MB) removal from water using blue coke-based activated carbon (AC) as an adsorbent. The investigation encompassed several critical parameters, including adsorbent dosage, contact time, pH, temperature, initial MB concentration, and the regeneration capacity of the adsorbent. The adsorption mechanism of MB by AC was elucidated through instrumental analysis and theoretical models such as adsorption kinetics, isotherm models, and thermodynamic analysis. The experimental results demonstrated several key findings: the removal efficiency of MB increased with the adsorbent dosage, although the unit adsorption capacity decreased; the removal rate of MB rose rapidly with increasing contact time and reached equilibrium after 90 min; the highest removal efficiency was achieved at pH 6; the adsorption capacity increased with higher initial MB concentrations. The adsorption kinetics conformed to the pseudo-second-order model, indicating that chemical adsorption was the predominant control step. The adsorption process was identified as a spontaneous reaction, with the Langmuir model suggesting a maximum adsorption capacity of 2040.696 mg/g at 318 K. Furthermore, AC exhibited an abundant mesoporous structure and surface functional groups, contributing to the efficient removal of MB. The adsorption mechanism involved pore-filling, hydrogen bonding, π-π interactions, and electrostatic attraction. Additionally, AC demonstrated excellent regeneration performance. These findings suggest that AC prepared from blue coke holds significant potential for industrial applications in MB removal, owing to its high removal efficiency, low cost, and good regenerative properties, making it highly valuable for practical use.

Objective: This study aimed to clarify the mechanism by which Krüppel-like factor 12 (KLF12) affects progesterone sensitivity in endometrial cancer (EC) through the progesterone receptor PGR signaling pathway. Methods: The relationship of KLF12 with PGR in EC patients was examined by immunohistochemistry, and the expression of KLF12 and PGR in EC cell lines was detected by real-time PCR and western blotting. Cell proliferation assay, plate clone formation, cell apoptosis assay, and cell cycle analysis were conducted to determine the impact of KLF12 intervention on progesterone therapy. CUT&Tag analysis and the dual-luciferase reporter experiment were used to determine the underlying regulatory effect of KLF12 on the PGR DNA sequence. A subcutaneous xenograft nude mouse model was established to validate the in vivo effect of KLF12 on progesterone sensitivity via PGR expression modulation. Results: KLF12 demonstrated decreased progesterone sensitivity and a negative correlation with PGR expression in EC tissues. Progesterone sensitivity was increased by KLF12 deficiency through PGR overexpression, a result that could be significantly reversed by PGR downregulation. PGR was identified as a target gene of KLF12, which could directly bind to the PGR promotor region and inhibit its expression. Conclusion: This study is the first to investigate the effect of KLF12 expression on EC cell resistance to progesterone. Our results offer important mechanistic insight into the direct regulation of the PGR promoter region, demonstrating that KLF12 expression strongly suppressed the PGR signaling pathway and, as a result, reduced progesterone sensitivity in EC patients.

Driven by rapid advancements in technology and data science, a revolutionary transformation is sweeping across environmentally friendly cities worldwide. This surge stems from a pressing need to tackle the intricate complexities of urban sustainability, encompassing everything from infrastructure and governance to fragmented design and technological solutions. To effectively manage these complexities and accurately measure, assess, and optimize their sustainability performance, sustainable communities are increasingly tapping into the potential of smart city technologies, particularly big data and its fictionalized applications. This trend culminates in the emergence of smart cities. This article delves into the current state of research surrounding data-driven, environmentally conscious smart cities, aiming to assess the extent to which these two concepts are currently being integrated and identify potential gaps in this field. Through a strong emphasis on evidence-based research, the study underscores the potential of big data technologies to offer innovative approaches for monitoring, comprehending, evaluating, and ultimately managing sustainable urban development. It further highlights the crucial role of data-driven advancements in formulating strategic development policies and operational management procedures, ensuring that environmentally conscious cities can continue to contribute to sustainability goals even amidst rapid urbanization.

Summary: Background: The long-term survival and perioperative outcomes of robotic-assisted lobectomy (RAL) and video-assisted lobectomy (VAL) in resectable non-small-cell lung cancer (NSCLC) were found to be comparable in retrospective studies, but they have not been investigated in a randomized trial setting. We conducted the RVlob trial to investigate if RAL was non-inferior to VAL in patients with resectable NSCLC. Methods: In this single-center, open-label, and parallel-arm randomized controlled trial conducted in Ruijin Hospital (Shanghai, China) between May 2017 and May 2020, we randomly assigned patients with resectable NSCLC in a 1:1 ratio to receive either RAL or VAL. One of the primary endpoints was 3-year overall survival. Secondary endpoints included 3-year disease-free survival. The Kaplan–Meier approach was used to calculate overall survival and disease-free survival at 3 years. This study was registered with ClinicalTrials.gov, NCT03134534. Findings: A total of 320 patients were randomized to receive RAL (n = 157) or VAL (n = 163). The baseline characteristics of patients were well balanced between the two groups. After a median follow-up of 58.0 months, the 3-year overall survival was 94.6% (95% confidence interval [CI], 91.0–98.3) in the RAL group and 91.5% (95% CI, 87.2–96.0) in the VAL group (hazard ratio [HR] for death, 0.65; 95% CI, 0.33–1.28; P = 0.21); noninferiority of RAL was confirmed according to the predefined margin of −5% (absolute difference, 2.96%; a one-sided 90% CI, −1.39% to ∞; P = 0.0029 for noninferiority). The 3-year disease-free survival was 88.7% (95% CI, 83.6–94.1) in the RAL group and 85.4% (95% CI, 80.0–91.2) in the VAL group (HR for disease recurrence or death, 0.87; 95% CI, 0.50–1.52; P = 0.62). Interpretation: This study is the first randomized trial to show that RAL resulted in non-inferior overall survival compared with VAL in patients with resectable NSCLC. Based on our results, RAL is an equally oncologically effective treatment and can be considered as an alternative to VAL for resectable NSCLC. Funding: National Natural Science Foundation of China (82072557), National Key Research and Development Program of China (2021YFC2500900), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (20172005, the 2nd round of disbursement), program of Shanghai Academic Research Leader from Science and Technology Commission of Shanghai Municipality (20XD1402300), Novel Interdisciplinary Research Project from Shanghai Municipal Health Commission (2022JC023), and Interdisciplinary Program of Shanghai Jiao Tong University (YG2023ZD04).

Major depression is a complex psychiatric disorder that includes genetic, neurological, and cognitive factors. Early detection and intervention can prevent progression, and help select the best treatment. Traditional clinical diagnosis tends to be subjective and misdiagnosed. Based on this, this study leverages clinical scale assessments and sequencing data to construct disease prediction models. Firstly, data undergoes preprocessing involving normalization and other requisite procedures. Feature engineering is then applied to curate subsets of features, culminating in the construction of a model through the implementation of machine learning and deep learning algorithms. In this study, 18 features with significant differences between patients and healthy controls were selected. The depression recognition model was constructed by deep learning with an accuracy of 87.26 % and an AUC of 91.56 %, which can effectively distinguish patients with depression from healthy controls. In addition, 33 features selected by recursive feature elimination method were used to construct a prognostic effect model of patients after 2 weeks of treatment, with an accuracy of 75.94 % and an AUC of 83.33 %. The results show that the deep learning algorithm based on clinical and sequencing data has good accuracy and provides an objective and accurate method for the diagnosis and pharmacodynamic prediction of depression. Furthermore, the selected differential features can serve as candidate biomarkers to provide valuable clues for diagnosis and efficacy prediction.

The corrosion performance of martensitic steel remains a matter of dispute, with no consensus on whether it exhibits heightened or diminished corrosion resistance. In this study, the corrosion behavior and mechanism of martensitic steel were systematically investigated by simulating a cargo oil tank environment. The results indicate that under strong acidic conditions, the corrosion rate of martensite (1.1404 mm/y) is significantly higher than that of ferrite-pearlite (0.7430 mm/y) due to its increased dislocation density and internal stress. Additionally, the presence of high-energy defects provides abundant active sites for the redeposition of Cu-bearing particles, while their uneven distribution further exacerbates corrosion. Therefore, we propose a competitive mechanism that governs the corrosion behavior of martensite, complementing the understanding of its behavior and mechanism.

Summary: Polymyxins are often the only effective antibiotics against the “Critical” pathogen Acinetobacter baumannii. Worryingly, highly polymyxin-resistant A. baumannii displaying dependence on polymyxins has emerged in the clinic, leading to diagnosis and treatment failures. Here, we report that arginine metabolism is essential for polymyxin-dependent A. baumannii. Specifically, the arginine degradation pathway was significantly altered in polymyxin-dependent strains compared to wild-type strains, with critical metabolites (e.g., L-arginine and L-glutamate) severely depleted and expression of the astABCDE operon significantly increased. Supplementation of arginine increased bacterial metabolic activity and suppressed polymyxin dependence. Deletion of astA, the first gene in the arginine degradation pathway, decreased phosphatidylglycerol and increased phosphatidylethanolamine levels in the outer membrane, thereby reducing the interaction with polymyxins. This study elucidates the molecular mechanism by which arginine metabolism impacts polymyxin dependence in A. baumannii, underscoring its critical role in improving diagnosis and treatment of life-threatening infections caused by “undetectable” polymyxin-dependent A. baumannii.

Deep learning, which has exhibited considerable potential and effectiveness in forest resource assessment, is vital for comprehending and managing forest resources and ecosystems. However, extensive assessment of forest resources is highly challenging due to the complex and varied nature of forest types sourced from diverse remote sensing platforms, which include images, point clouds, and fusion data. To facilitate further study, we systematically review the current status, applications and prospects of deep learning technologies for different types of forest remote sensing data. After considering more than two hundred forest-related papers published over the past decade, we introduce sensors and devices for forest data acquisition, classify deep learning methods based on their data processing methods and operational principles, and categorize diverse instances of these methods with various forest applications. Moreover, we summarize available datasets related primarily to forest data and examine the global geographic distribution of the relevant literature. Comprehensive insights into the advantages and limitations of each method are described, offering a forward-looking perspective on the trend of applying deep learning technology to forest research. In this paper, we aim to provide an overview of the current trends and challenges of deep learning techniques applied to forest research, creating a comprehensive picture for use as a reference by both academia and industry professionals.

This work addresses a novel technique for selecting the best process parameters for the 4H–SiC epitaxial layer in a horizontal hot-wall chemical vapor reactor using a transient multi-physical (thermal-fluid-chemical) simulation model and combined with a machine-learning model. An experiment was performed to validate the feasibility of the numerical model. Secondly, a single-factor analysis was conducted to investigate the effects of process parameters, including the deposition temperature, inlet-flow volume, rotational speed of the susceptor, and cavity pressure, on the quality of the 4H–SiC epitaxial layer. Finally, a machine learning algorithm, the ant colony optimization-back propagation neural network (ACO–BPNN), was employed to develop the input/output model and optimize process parameters for obtaining a high-quality epitaxial layer and reducing the optimization cycle and costs. Notably, the optimized process was validated by real experiments, where the error between calculation and experiment is 4.03 % for deposition rate and 0.49 % for coefficient of variation, respectively. The results highlight the model as reliable and lay the foundation for the CVD growth of the 4H–SiC epitaxial layer.

Background: Different job strain formulations based on the Job Demand-Control model have been developed. This study evaluated longitudinal associations between job strain and psychological distress and whether associations were influenced by six formulations of job strain, including quadrant (original and simplified), subtraction, quotient, logarithm quotient, and quartile based on quotient, in randomly selected Japanese workers. Methods: Data were from waves I and II of the Survey of Midlife in Japan (MIDJA), with a 4-year follow-up period. The study sample consisted of 412 participants working at baseline and had complete data on variables of interest. Associations between job strain at baseline and psychological distress at follow-up were assessed via multivariable linear regression, and results were expressed as β coefficients and 95% confidence intervals including R2 and Akaike information criterion (AIC) evaluation. Results: Crude models revealed that job strain formulations explained 6.93–10.30% of variance. The AIC ranged from 1475.87 to 1489.12. After accounting for sociodemographic and behavioral factors and psychological distress at baseline, fully-adjusted models indicated significant associations between all job strain formulations at baseline and psychological distress at follow-up: original quadrant (β: 1.16, 95% CI: 0.12, 2.21), simplified quadrant (β: 1.01, 95% CI: 0.18, 1.85), subtraction (β: 0.39, 95% CI: 0.09, 0.70), quotient (β: 0.37, 95% CI: 0.08, 0.67), logarithm quotient (β: 0.42, 95% CI: 0.12, 0.72), and quartile based on quotient (β: 1.22, 95% CI: 0.36, 2.08). Conclusion: Six job strain formulations showed robust predictive power regarding psychological distress over 4 years among Japanese workers.

Chemotherapy-induced complications, particularly lethal cardiovascular diseases, pose significant challenges for cancer survivors. The intertwined adverse effects, brought by cancer and its complication, further complicate anticancer therapy and lead to diminished clinical outcomes. Simple supplementation of cardioprotective agents falls short in addressing these challenges. Developing bi-functional co-therapy agents provided another potential solution to consolidate the chemotherapy and reduce cardiac events simultaneously. Drug repurposing was naturally endowed with co-therapeutic potential of two indications, implying a unique chance in the development of bi-functional agents. Herein, we further proposed a novel “trilogy of drug repurposing” strategy that comprises function-based, target-focused, and scaffold-driven repurposing approaches, aiming to systematically elucidate the advantages of repurposed drugs in rationally developing bi-functional agent. Through function-based repurposing, a cardioprotective agent, carvedilol (CAR), was identified as a potential neddylation inhibitor to suppress lung cancer growth. Employing target-focused SAR studies and scaffold-driven drug design, we synthesized 44 CAR derivatives to achieve a balance between anticancer and cardioprotection. Remarkably, optimal derivative 43 displayed promising bi-functional effects, especially in various self-established heart failure mice models with and without tumor-bearing. Collectively, the present study validated the practicability of the “trilogy of drug repurposing” strategy in the development of bi-functional co-therapy agents.

Plutonium-238 has always been considered as the one of the promising radioisotopes for space nuclear power supply, which has long half-life, low radiation protection level, high power density, and stable fuel form at high temperatures. The industrial-scale production of 238Pu mainly depends on irradiating solid 237NpO2 target in high flux reactors, however the production process faces problems such as large fission loss and high requirements for product quality control. In this paper, a conceptual design study of producing 238Pu in a multi-purpose high flux reactor was evaluated and analyzed, which includes a sensitivity analysis on 238Pu production and a further study on the irradiation scheme. It demonstrated that the target structure and its location in the reactor, as well as the operation scheme has an impact on 238Pu amount and product quality. Furthermore, the production efficiency could be improved by optimizing target material concentration, target locations in the core and reflector. This work provides technical support for irradiation production of 238Pu in high flux reactors.

With the rapid development of solid-state refrigeration technology, elastocaloric materials face higher requirements, such as a higher elastocaloric effect (eCE), better mechanical properties, and simpler and faster large-scale preparation. In this work, we propose a composition design strategy for Mn-doped Co–V-Ga shape memory alloys, which can enhance both the eCE and the mechanical properties. We combine first-principles calculations and experiments to demonstrate this strategy. Our results reveal that the lattice distortion caused by the difference in atomic radii produces a solid-solution-strengthening effect within the alloy, impeding dislocation motion and significantly improving the mechanical properties. Through composition optimization, the low-cost Co51.7V31.3Ga14.75Mn2.25 as-cast polycrystalline alloy exhibits a large adiabatic temperature change (ΔTad) of −11.2 K at room temperature, while its maximum compressive strength and strain can reach up to 1859 MPa and 26% at room temperature, respectively. Importantly, the alloy exhibits excellent cycle stability, and its ΔTad does not decay after 100 loading and unloading cycles, indicating that it has the potential for practical application. Further comparison with the annealed sample shows that the secondary defects deteriorate the ΔTad of the alloy. Our research provides an effective strategy for the simple, rapid and large-scale production of as-cast eCE alloys.

Taking a caisson foundation engineering of a railway across-river bridge as the case, the technical characteristics and key challenges of over-deep inclined caisson were described firstly. Subsequently, the main controlling factors of the uneven settlement were analyzed. In view of the difficulty in obtaining the parameters of disturbed grouting soil, as well as the large adjustment of subsequent construction loads, an uneven settlement method based on over-deep underwater lateral pressure test and high-pressure consolidation test was proposed. The proposed method was simulated by finite element method to analyze the variations of total settlement, differential settlement and inclined attitude of caisson foundation under different loading stages. The results showed that the difference in the thickness of the disturbed layer was the dominant factor of uneven settlement, finally controlling the inclination shape. Grouting reinforcement was conductive to improving the settlement of caisson foundation. The maximum total settlement, differential settlement and offset after reinforcement were reduced to 249.53 mm, 19.54 mm and 29.20 mm, respectively. The deformation mainly occurred in the loading stage before the platform construction, accounting for about 60 %. If it is considered to level the top surface, adjust the elevation and load center during the construction of platform, the incremental settlement, the north–south differential settlement and the offset of top surface corresponded to 94.26 mm, 10.31 mm and 17.52 mm, respectively. Finally, the reliability of above method was fully verified by comparing the measured data with calculated value. The results will provide certain ideas and methods for relevant engineering problems.

Photocatalytic reactions, achieving chemical synthesis in a more sustainable manner than thermal reactions, have been demonstrated to become more efficient, greener and easier to scale up when combined with continuous microflow technology. Nevertheless, the report on the kinetics measurement for photocatalytic reactions in continuous microflow, especially in a fully automated way, is very rare. In this work, two challenging parameters, i.e., the reaction order with respect to oxygen (2.48) and photoreaction activation energy (-16.83 kJ/mol) of the photocatalytic oxidation of 9,10-diphenylanthracene, were acquired in an automated continuous flow platform using the Steady-state Method. Moreover, the Ramping Method was also successfully implemented in the automated continuous flow photoreaction platform, exhibiting a predictive accuracy of 4.42 %, with 64.3 % less time and 58.0 % less material consumption than the Steady-state Method. And it was found that the improvement in the residence time distribution of the microreactor could improve the accuracy of the Ramping Method. The automated continuous flow process developed in this work could offer an efficient and accurate way to attain the reaction kinetics information for homogeneous photocatalytic reactions.

The phyllosphere, particularly the leaf surface of plants, harbors a diverse range of microbiomes that play a vital role in the functioning of terrestrial ecosystems. However, our understanding of microbial successions and their impact on functional genes during plant community development is limited. In this study, considering core and satellite microbial taxa, we characterized the phyllosphere microbiome and functional genes in various microhabitats (i.e., leaf litter, moss and plant leaves) across the succession of a plant community in a low-altitude glacier foreland. Our findings indicate that phyllosphere microbiomes and associated ecosystem stability increase during the succession of the plant community. The abundance of core taxa increased with plant community succession and was primarily governed by deterministic processes. In contrast, satellite taxa abundance decreased during plant community succession and was mainly governed by stochastic processes. The abundance of microbial functional genes (such as C, N, and P hydrolysis and fixation) in plant leaves generally increased during the plant community succession. However, in leaf litter and moss leaves, only a subset of functional genes (e.g., C fixation and degradation, and P mineralization) showed a tendency to increase with plant community succession. Ultimately, the community of both core and satellite taxa collaboratively influenced the characteristics of phyllosphere nutrient-cycling genes, leading to the diverse profiles and fluctuating abundance of various functional genes during plant community succession. These findings offer valuable insights into the phyllosphere microbiome and plant–microbe interactions during plant community development, advancing our understanding of the succession and functional significance of the phyllosphere microbial community.

This paper presents a difference interior penalty discontinuous Galerkin method for the 3D elliptic boundary-value problem. The main idea of this method is to combine the finite difference discretization in the z-direction with the interior penalty discontinuous Galerkin discretization in the (x,y)-plane. One of the advantages of this method is that the solution of 3D problem is transformed into a series of 2D problems, thereby overcoming the computational complexity of traditional interior penalty discontinuous Galerkin method for solving high-dimensional problems and allowing for code reuse. Additionally, we use the interior penalty discontinuous Galerkin method to solve each 2D problem, therefore, this method retains the advantage of the interior penalty discontinuous Galerkin method in dealing with non-matching grids and non-uniform, even anisotropic, polynomial approximation degrees. Then, the error estimates are given for difference interior penalty discontinuous Galerkin method. Finally, numerical experiments demonstrate the accuracy and effectiveness of the difference interior penalty discontinuous Galerkin method.

In order to investigate the effects of a flag rugby game programs on the development of gross motor skills and physical fitness in 5–6 year old preschool children. An overall random sampling method was adopted to select 56 preschoolers aged 5–6 years from class A and class B,class A was the ExG (28) implemented a flag rugby games intervention program,and class B was the ConG (28) implemented a regular physical education program,with a 12-week intervention period.The content and requirements of the experimental intervention program were determined through a systematic analysis method, and the subjects' gross motor skills level was tested using the TGMD-3, and their physical fitness level was measured using China's fifth national physical fitness monitoring of early childhood (3–6 years) component.Experimental data were statistically analyzed using independent samples t-test, paired samples t-test, and repeated measures ANOVA test.After 12 weeks of practice, 1）We found that the ExG outperformed the ConG in Skip,One hand stationary dribble, Overhand throw, Underhand throw, Forehand strike of self-bounced,Kick a stationary ball, Total object control subject score, Total gross motor score test results with significant differences (p

Transforming growth factor-β1 (TGF-β1) is essential for cartilage regeneration, but its susceptibility to enzymatic denaturation and high cost limit its application. Herein, we report Ac-LIANAKGFEFEFKFK-NH2 (LKP), a self-assembled peptide nanofiber hydrogel that can mimic the function of TGF-β1. The LKP hydrogel is simple to synthesize, and in vitro experiments confirmed its good biocompatibility and cartilage-promoting ability. However, LKP hydrogels suffer from poor mechanical properties and are prone to fragmentation; therefore, we prepared a series of injectable hydrogel composite scaffolds (SF-GMA/LKP) by combining LKP with glycidyl methacrylate (GMA)-modified silk fibroin (SF). SF-GMA/LKP composite scaffolds instantaneously induced in-situ filling of cartilage defects and, at the same time, relied on the interaction between LKP and SF-GMA interaction to prolong the duration of action of LKP. The SF-GMA/LKP10 and SF-GMA/LKP20 composite scaffolds had the best effect on neocartilage and subchondral bone reconstruction. This composite hydrogel scaffold can be used for high-quality cartilage repair.

The corrosion behavior of ship steel with different microstructure in a simulated tropical marine atmosphere was systematically investigated. Results show that homogeneous martensite structure obtained by water-quenching process was much more resistant to corrosion than that of ferrite-pearlite. Furthermore, the precipitation of carbide resulting from tempering process promoted the formation of corrosive microcells within the matrix and further intensified the corrosion. Rapid cooling rate led to the enrichment of chromium, which formed protective corrosion products such as FeCr2O4 and Cr(OH)3. This also facilitated the conversion of α-FeOOH and significantly enhanced the corrosion resistance.

The onsite surveillance plays an important role in the smart substation since the smart substation is unattended. All the sites and operation staff should be supervised throughout the process since a series of risks exist on the working sites. KCF (Kernel Correlation Filter) is an effective method to track a moving object for safety surveillance. However, the occlusion and shape changes worsen the performance of KCF, especially on the occasion of multi-objective detection. This paper proposes a comprehensive method for improving the precision and robustness of detection. Firstly, all the moving objects are detected by the YOLO method. In the tracking part, an AKCF (Augmented Kernel Correlation Filter) is proposed for the heavily occluded object, and the Kalman Filter (KF) serves as a supplementary output. Moreover, in the target association section, based on priority matching and rematching based on motion estimation, a two-stage target association method is proposed. Test outcomes indicate that the proposed algorithm is accurate and robust for tracking workers’ trajectories and conducting surveillance.

Non-technical losses (NTL) refer to unrecorded power consumption generated by dishonest customers, which is a substantial issue affecting the power system stability and economic efficiency of the power grid. The detection of dishonest customers is hindered by the complexity of NTL such as data feature selection, retention time feature, and power consumption pattern judgment. This work addresses these issues using meter recording data, proposing an NTL detection approach with Gram’s angle field (GAF) and deep residual network (ResNet). Principal component analysis (PCA) method is applied to compress multiple electricity detection indexes, which aims to obtain multi-dimensional power consumption data characteristics without changing its timing characteristics. The GAF method is used to convert the time-series power features of individual users into a two-dimensional image, achieving the purpose of maintaining the user’s time-series features and user-based units. The images generated by the GAF method, which contain information about the electricity consumption characteristics of many customers, are classified by ResNet to highlight customers with NTL. The claimed algorithm was tested on a dataset consisting of both fraudulent and non-fraudulent subscriber data. The results demonstrated that the NTL detection method based on GAF and ResNet is superior to the traditional NTL detection method and has high accuracy.

Sub-synchronous oscillations (SSO) caused by large-scale wind farm integrated systems have become an important issue threatening the security and stability of power systems. Some practical cases have shown that SSO can propagate through multiple voltage levels to more than hundreds kilometers. Many studies have focused on this problem, but there is a lack of research on the power propagation characteristics of SSO. In this paper, a measurement-based method for sub synchronous oscillation (SSO) propagation path criterion in SSO events is proposed. The method is based on the concept of sub synchronous power (SSP). By monitoring the sign of SSP generated by different wind farms or turbines, the propagation path can be identified. The method gives an effective way to quantitatively analyze the power propagation path of sub synchronous oscillations from the power perspective. Experimental cases demonstrate the practicality of the method.