Search

Summary: We delve into the distinctive color gamut characteristics resulting from color dispersion of surface relief grating (SRG) and wavelength degeneracy of volume holographic optical element (VHOE) in a diffractive light guide. While a laser-like spectrum achieves an impressive 194% sRGB color gamut for both cases, it proves unsuitable for VHOE light guides due to limitations in breaking the field of view (FOV) of the display. Conversely, a broad-band light source, such as LEDs, offers continuous FOV but reduces the common color gamut to 50% sRGB. We then present a newly designed VHOE light guide capable of achieving the common color gamut of 130% sRGB using two multiplexed holograms of each color, closely matching the 133% sRGB achieved by an SRG light guide. This article presents the first theoretical methodology to elucidate color performance of diffractive light guides utilizing VHOEs with holographic multiplexing, affirming their suitability for crafting high-quality near-eye display.

Abstract We investigate the representation of individual supercells and intriguing tornado‐like vortices in a simplified, locally refined global atmosphere model. The model, featuring grid stretching, can locally enhance the model resolution and reach cloud‐resolving scales with modest computational resources. Given a conditionally unstable sheared environment, the model can simulate supercells realistically, with a near‐ground vortex and funnel cloud at the center of a rotating updraft reminiscent of a tornado. An analysis of the Eulerian vertical vorticity budget suggests that the updraft core of the supercell tilts horizontal vorticity into the tornado‐like vortex, which is then amplified through vertical stretching by the updraft. Results suggest that the simulated vortex is dynamically similar to observed tornadoes, as well as those simulated in modeling studies at much higher horizontal resolution. Lastly, we discuss the prospects for the study of cross‐scale interactions involving supercells.

Abstract Background and Aims Immune checkpoint inhibitors (ICIs) across multiple treatment lines have not yet been evaluated comprehensively. The purpose of this research was to investigate whether or not continuous cross‐line ICIs therapy is effective in treating non‐small cell lung cancer (NSCLC). Methods We conducted a retrospective investigation into the medical histories of 47 patients diagnosed with advanced NSCLC and treated with ICIs at the Peking University First Hospital between January 2018 and June 2022. Results Due to the progression of their disease, 14 patients were given the same ICIs, 5 patients were given different ICIs, and 6 patients discontinued taking ICIs altogether. The objective response rates were 7.140% in the ICIs cross‐line treatment group, 0% in the replacement of ICIs treatment group, and 0% in the discontinuation of ICIs treatment group. The disease control rates were 64.260% in the ICIs cross‐line treatment group, 60% in the replacement of ICIs treatment group, and 0% in the discontinuation of ICIs treatment group. The average overall survival durations of the three groups were 24.020 (95% confidence interval [CI]: 17.061–30.979), 31.643 (95% CI: 23.513–39.774), and 7.997 (95% CI: 3.746–12.247) months, respectively (p = 0.003). The median second progression‐free survival (PFS2) durations of the three groups were 4.570 (95% CI: 3.276–5.864), 3.530 (95% CI: 0.674–6.386), and 1.570 (95% CI: 0–4.091) months, respectively (p = 0.091). Conclusions Cross‐line ICIs cannot improve the prognosis and PFS2 of patients with NSCLC, but compared to discontinuing ICIs, OS may be prolonged. A few patients may benefit from prolonged ICIs therapy.

Tropical cyclone (TC) intensity forecasting poses challenges due to complex dynamical processes and data inadequacies during model initialization. This paper describes efforts to improve TC intensity prediction in the Geophysical Fluid Dynamics Laboratory (GFDL) System for High-resolution prediction on Earth-to-Local Domains (SHiELD) model by implementing a Vortex Initialization (VI) technique. The GFDL SHiELD model, relying on the Global Forecast System (GFS) analysis for initialization, faces deficiencies in initial TC structure and intensity. The VI method involves adjusting the TC vortex inherited from the GFS analysis and merging it back into the environment at the observed location, enhancing the analyzed representation of storm structure. We made modifications to the VI package implemented in the operational Hurricane Analysis and Forecast System, including handling initial condition data, reducing input domain size, and improving storm intensity enhancement. Experiments using the T-SHiELD configuration demonstrate that using VI significantly improves the representation of initial TC intensity and size, enhancing TC predictions, particularly in storm intensity and outer wind forecasts within the first 48 h.

Abstract Global storm‐resolving models (GSRMs) that can explicitly resolve some of deep convection are now being integrated for climate timescales. GSRMs are able to simulate more realistic precipitation distributions relative to traditional Coupled Model Intercomparison Project 6 (CMIP6) models. In this study, we present results from two‐year‐long integrations of a GSRM developed at Geophysical Fluid Dynamics Laboratory, eXperimental System for High‐resolution prediction on Earth‐to‐Local Domains (X‐SHiELD), for the response of precipitation to sea surface temperature warming and an isolated increase in CO2 and compare it to CMIP6 models. At leading order, X‐SHiELD's response is within the range of the CMIP6 models. However, a close examination of the precipitation distribution response reveals that X‐SHiELD has a different response at lower percentiles and the response of the extreme events are at the lower end of the range of CMIP6 models. A regional decomposition reveals that the difference is most pronounced for midlatitude land, where X‐SHiELD shows a lower increase at intermediate percentiles and drying at lower percentiles.

BackgroundGlioblastoma (GBM) is a highly malignant brain tumor, and immune cells play a crucial role in its initiation and progression. The immune system's cellular components, including various types of lymphocytes, macrophages, and dendritic cells, among others, engage in intricate interactions with GBM. However, the precise nature of these interactions remains to be conclusively determined.MethodIn this study, a comprehensive two-sample Mendelian Randomization (MR) analysis was conducted to elucidate the causal relationship between immune cell features and the incidence of GBM. Utilizing publicly available genetic data, we investigated the causal associations between 731 immune cell signatures and the risk of GBM. Subsequently, we conducted a reverse Mendelian randomization analysis to rule out reverse causation. Finally, it was concluded that there is a unidirectional causal relationship between three subtypes of immune cells and GBM. Comprehensive sensitivity analyses were employed to validate the results robustness, heterogeneity, and presence of horizontal pleiotropy. To enhance the accuracy of our results, we concurrently subjected them to Bayesian analysis.ResultsAfter conducting MR analyses, we identified 10 immune phenotypes that counteract glioblastoma, with the most protective being FSC-A on Natural Killer T cells (OR = 0.688, CI = 0.515–0.918, P = 0.011). Additionally, we found 11 immune cell subtypes that promote GBM incidence, including CD62L– HLA DR++ monocyte % monocyte (OR = 1.522, CI = 1.004–2.307, P = 0.048), CD4+CD8+ T cell % leukocyte (OR = 1.387, CI = 1.031–1.866, P = 0.031). Following the implementation of reverse MR analysis, where glioblastoma served as the exposure variable and the outcomes included 21 target immune cell subtypes, we discerned that only three cell subtypes (CD45 on CD33+ HLA DR+ CD14dim, CD33+ HLA DR+ Absolute Count, and IgD+ CD24+ B cell Absolute Count) exhibited a unidirectional causal association with glioblastoma.ConclusionOur study has genetically demonstrated the close relationship between immune cells and GBM, guiding future clinical research.

Modular Multilevel Converter (MMC) is widely used in applications such as High Voltage Direct Current (HVDC) transmission, AC/DC power conversion centers, and large-scale power quality management in electrical grids due to its highly modular structure, strong redundancy and low harmonic content in AC output. The application of the traditional deadbeat predictive current control to MMC enhances the fast tracking ability of the output current, but it still has the problems of low output current accuracy and high dependence on bridge arm inductor. Based on this, this paper proposes an improved two-beat deadbeat synchronous predictive current control based on Newton interpolation method. By improving the two-beat deadbeat synchronous predictive current control strategy, the accuracy of the output current can be further improved and its fast tracking ability can be enhanced. Newton interpolation is introduced to improve the accuracy of the output current while reducing the dependence on the bridge arm inductor. The results show that the control strategy proposed in this paper reduces the output current THD by 2.88% compared with the two-beat deadbeat predictive current control, thus improving the accuracy; the bridge arm inductor value is reduced by 1.28%, thus reducing the dependence; and under the transient environment, the output current can be tracked to its predicted reference value 843 μs in advance, which enhances the fast tracking capability.

Long-range air striking is an important trend in the modern air operations. This paper focuses on the development of equipment, technology, and operation concepts in long-range air strike domain in foreign countries, analyzes the main research status in this field and summarizes the development trends in operation concepts, weapon platforms, and kill chains. Three typical operation modes of long-range air striking, which are collaborative target detection guided long-range striking, collaborative target indication guided long-range striking and networked relayed guided long-range striking, are proposed from the perspective of how guidance information is generated. Based on the development situation in foreign countries, key technologies supporting long-range air striking are summarized and discussed.

Abstract Changes in tropical deep convection with global warming are a leading source of uncertainty for future climate projections. A comparison of the responses of active sensor measurements of cloud ice to interannual variability and next-generation global storm-resolving model (also known as k-scale models) simulations to global warming shows similar changes for events with the highest column-integrated ice. The changes reveal that the ice loading decreases outside the most active convection but increases at a rate of several percent per Kelvin surface warming in the most active convection. Disentangling thermodynamic and vertical velocity changes shows that the ice signal is strongly modulated by structural changes of the vertical wind field towards an intensification of strong convective updrafts with warming, suggesting that changes in ice loading are strongly influenced by changes in convective velocities, as well as a path toward extracting information about convective velocities from observations.

Abstract Background The global prevalence of diabetes mellitus (DM) continues to rise and 70% of diabetic individuals have dry eye disease (DED) that leads to subsequent abnormalities of the corneal epithelium, corneal nerves, tear film, or corneal endothelium. In addition, persons with diabetes produce fewer tear secretions than healthy individuals. While several anti-inflammatory drug-based therapies for dry eye in diabetic individuals are currently being administered, their efficacy has not been studied in detail. Therefore, the aim of this study was to compare the effectiveness of 3% diquafosol (DQS) vs 0.1% hyaluronic acid (HA) eye drops in diabetic dry eye patients. Methods This triple-blind randomized, control trial will include 202 diabetic-related DED and will be assigned to DQS (n = 101) and HA (n = 101) one drop, six times per day for 8 weeks. Tear film lipid layer, non-invasive breakup time, conjunctivocorneal staining score, corneal sensitivity, tear MMP-9 levels, meibomian gland expression and quality, tear meniscus height, corneal nerves, immune/inflammatory cell change, conjunctival hyperemia, and ocular surface disease index questionnaire score will be assessed and compared at baseline, week 4, and week 8. Discussion This study will be a standardized, scientific, clinical trial designed to evaluate the therapeutic effects and safety of DQS and HA for diabetic dry eye treatment. Trial registration ClinicalTrials.govNCT05682547. Registered on December 05, 2022.

Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two transformative technologies that offer distinct benefits. SDN virtualizes the control plane by separating it from the data plane, while NFV virtualizes the data plane by moving network functions from hardware and implementing them in software. Therefore, combining SDN and NFV can fully exploit the benefits of both technologies. As Programming Protocol-independent Packet Processors (P4) become popular due to its flexibility, traditional SDN switches are being replaced by P4 switches. In the P4+NFV architecture, network functions can be provided in both P4 switches (PNF) and NFV servers (VNF). However, to minimize packet delay, the offloading problem between P4 switches and NFV needs to be addressed. The novelty of our paper lies in investigating the offloading problem and evaluating the impact of employing multiple VNFs with varying computing capacities within the P4+NFV architecture. We also use M/M/1 queuing theory to derive the average packet delay and propose an optimization solution based on gradient descent to find out the optimal offloading probabilities of various VNF servers. Results show that optimal offloading from P4 switch to multiple VNFs can reduce the average packet delay from 4.76% to 40.02%.

Abstract The gut microbiome and its metabolites are increasingly implicated in several cardiovascular diseases, but their role in human myocardial infarction (MI) injury responses have yet to be established. To address this, we examined stool samples from 77 ST-elevation MI (STEMI) patients using 16 S V3-V4 next-generation sequencing, metagenomics and machine learning. Our analysis identified an enriched population of butyrate-producing bacteria. These findings were then validated using a controlled ischemia/reperfusion model using eight nonhuman primates. To elucidate mechanisms, we inoculated gnotobiotic mice with these bacteria and found that they can produce beta-hydroxybutyrate, supporting cardiac function post-MI. This was further confirmed using HMGCS2-deficient mice which lack endogenous ketogenesis and have poor outcomes after MI. Inoculation increased plasma ketone levels and provided significant improvements in cardiac function post-MI. Together, this demonstrates a previously unknown role of gut butyrate-producers in the post-MI response.

Abstract Background The aim of this article is to establish an external quality assessment (EQA) scheme for sperm Deoxyribonucleic acid (DNA) fragmentation (SDF) detection, and to assess the feasibility of the scheme. In addition, this article provides some case analysis of abnormal results in order to really help improve the performance of the laboratory. Results In 2021 and 2022, 10 and 28 laboratories in China volunteered to participate in the EQA program respectively. Two samples were selected for EQA each year, a large spread of results was obtained for the four samples, and the highest values were 13.7, 4.2, 8.0 and 4.0 times the lowest respectively. The coefficients of variation (CVs) were very high for the four samples, at 46.6%, 30.1%, 26.7% and 30.3%, respectively. The CVs of the samples with high SDF values were lower than those of the samples with low SDF values. There was no significant difference between the results of sperm chromatin structure assay (SCSA) and sperm chromatin dispersion (SCD). For the 10 laboratories that participated in EQA in 2021 and 2022, the CVs of low SDF value samples and high SDF value samples decreased from 46.6% and 30.1% in 2021 to 32.5% and 22.7% in 2022, respectively. Conclusion This is the first study to evaluate the EQA program on SDF, which involved a number of laboratories and was demonstrated to be feasible. It is recommended that all laboratories participate in the EQA of SDF to ensure the accuracy of the results.

In this paper, a high-yield Hf-modified SiHfBOC ceramic precursor was developed, and a high-pressure assisted impregnation pyrolysis method was proposed to achieve the preparation of 3D PyC–Cf/SiHfBOC composites. This high-pressure assisted impregnation method significantly improves impregnation filling effect of the precursor in and between fiber bundles compared to dozens of traditional impregnation cycles. After undergoing just 9 precursor infiltration pyrolysis (PIP) cycles, the composites achieved relative density of approximately 90% and density of 1.64 g/cm3. The critical temperature difference of the 3D PyC–Cf/SiHfBOC composites after the shock of room temperature (RT)–1000 ℃ is as high as 650 ℃, which is twice that of traditional ceramic materials, showing good thermal shock resistance. Under the effect of Hf modification, a dense HfO2–SiO2 oxide layer (thickness of 93 μm) was formed in situ on the surface of the 3D PyC–Cf/SiHfBOC composites, effectively preventing further erosion of the composite matrix by high-temperature oxidation gas. Even in the ultra-high-temperature oxygen-containing environment at 1800 ℃, it still exhibits an excellent non-ablative result (with a linear ablation rate of 0.83×10−4 mm/s). This work not only enriches the basic research on lightweight ultra-high-temperature ceramic composites converted from Hf ceramic precursors, but also provides strong technical support for their applications in ultra-high-temperature non-ablative thermal protection materials for high-speed aircraft.

Abstract Stannous fluoride (SnF2) is an effective fluoride source and antimicrobial agent that is widely used in commercial toothpaste formulations. The antimicrobial activity of SnF2 is partly attributed to the presence of Sn(II) ions. However, it is challenging to directly determine the Sn speciation and oxidation state within commercially available toothpaste products due to the low weight loading of SnF2 (0.454 wt% SnF2, 0.34 wt% Sn) and the amorphous, semi-solid nature of the toothpaste. Here, we show that dynamic nuclear polarization (DNP) enables 119Sn solid-state NMR experiments that can probe the Sn speciation within commercially available toothpaste. Solid-state NMR experiments on SnF2 and SnF4 show that 19F isotropic chemical shift and 119Sn chemical shift anisotropy (CSA) are highly sensitive to the Sn oxidation state. DNP-enhanced 119Sn magic-angle turning (MAT) 2D NMR spectra of toothpastes resolve Sn(II) and Sn(IV) by their 119Sn chemical shift tensor parameters. Fits of DNP-enhanced 1D 1H → 119Sn solid-state NMR spectra allow the populations of Sn(II) and Sn(IV) within the toothpastes to be estimated. This analysis reveals that three of the four commercially available toothpastes contained at least 80% Sn(II), whereas one of the toothpaste contained a significantly higher amount of Sn(IV).

Abstract Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has led to state-of-the-art ML models that have superior performance compared to the European Centre for Medium-Range Weather Forecasts (ECMWF)’s high-resolution forecast (HRES), which is widely considered as the world’s best physics-based weather forecasting system. Specifically, ML models have outperformed HRES in 10-day forecasts with a spatial resolution of 0.25∘. However, the challenge remains in mitigating the accumulation of forecast errors for longer effective forecasts, such as achieving comparable performance to the ECMWF ensemble in 15-day forecasts. Despite various efforts to reduce accumulation errors, such as implementing autoregressive multi-time step loss, relying on a single model has been found to be insufficient for achieving optimal performance in both short and long lead times. Therefore, we present FuXi, a cascaded ML weather forecasting system that provides 15-day global forecasts at a temporal resolution of 6 hours and a spatial resolution of 0.25∘. FuXi is developed using 39 years of the ECMWF ERA5 reanalysis dataset. The performance evaluation demonstrates that FuXi has forecast performance comparable to ECMWF ensemble mean (EM) in 15-day forecasts. FuXi surpasses the skillful forecast lead time achieved by ECMWF HRES by extending the lead time for Z500 from 9.25 to 10.5 days and for T2M from 10 to 14.5 days. Moreover, the FuXi ensemble is created by perturbing initial conditions and model parameters, enabling it to provide forecast uncertainty and demonstrating promising results when compared to the ECMWF ensemble.

Here we investigated the nucleation of the Re, Ru-rich δ phase affected by stacking faults in the γ phase in a 4th generation Ni-based single crystal superalloy during the service at 800°C. The stacking faults in the γ phase were rich in Re and Ru, similar to the observed δ phase. And the stacking fault regions possessed a similar structure to the δ phase, promoting the transformation from γ phase to δ phase. Furthermore, the calculation results indicated that Ru had more significant promoting effects on the δ phase precipitation than Re, providing a reference for the alloy design.

Abstract Although the gut microbiota has been reported to influence osteoporosis risk, the individual species involved, and underlying mechanisms, remain largely unknown. We performed integrative analyses in a Chinese cohort of peri-/post-menopausal women with metagenomics/targeted metabolomics/whole-genome sequencing to identify novel microbiome-related biomarkers for bone health. Bacteroides vulgatus was found to be negatively associated with bone mineral density (BMD), which was validated in US white people. Serum valeric acid (VA), a microbiota derived metabolite, was positively associated with BMD and causally downregulated by B. vulgatus. Ovariectomized mice fed B. vulgatus demonstrated increased bone resorption and poorer bone micro-structure, while those fed VA demonstrated reduced bone resorption and better bone micro-structure. VA suppressed RELA protein production (pro-inflammatory), and enhanced IL10 mRNA expression (anti-inflammatory), leading to suppressed maturation of osteoclast-like cells and enhanced maturation of osteoblasts in vitro. The findings suggest that B. vulgatus and VA may represent promising targets for osteoporosis prevention/treatment.

Neuroinflammation is a recognized complication of immunotherapeutic approaches such as immune checkpoint inhibitor treatment, chimeric antigen receptor therapy, and graft versus host disease (GVHD) occurring after allogeneic hematopoietic stem cell transplantation. While T cells and inflammatory cytokines play a role in this process, the precise interplay between the adaptive and innate arms of the immune system that propagates inflammation in the central nervous system remains incompletely understood. Using a murine model of GVHD, we demonstrate that type 2 cannabinoid receptor (CB2R) signaling plays a critical role in the pathophysiology of neuroinflammation. In these studies, we identify that CB2R expression on microglial cells induces an activated inflammatory phenotype that potentiates the accumulation of donor-derived proinflammatory T cells, regulates chemokine gene regulatory networks, and promotes neuronal cell death. Pharmacological targeting of this receptor with a brain penetrant CB2R inverse agonist/antagonist selectively reduces neuroinflammation without deleteriously affecting systemic GVHD severity. Thus, these findings delineate a therapeutically targetable neuroinflammatory pathway and have implications for the attenuation of neurotoxicity after GVHD and potentially other T cell-based immunotherapeutic approaches., Introduction Neurological inflammation and cognitive dysfunction are increasingly recognized complications of cancer immunotherapeutic approaches such as immune checkpoint inhibitor treatment (1, 2), chimeric antigen receptor therapy (3, 4), and graft [...]

Objective: This study provided a quantitative prediction of best-corrected visual acuity (BCVA) for cataract patients using the inverse problem algorithm (IPA) technique earlier proposed by the authors. Methods: To this end, seven risk factors (age, BMI, MAP, IOP, HbA1c, LDL-C, and gender) were linked by a semi-empirical formula by normalizing each factor into a dimensionless range of −1.0 to +1.0. The adopted inverse problem algorithm (IPA) technique was run via a self-developed program in STATISTICA 7.0, featuring a 29-term nonlinear equation considering seven risk factors, cross-interaction between various pairs of factors, and one constant term [7 + (7 × 6)/2 + 1 = 29]. The IPA neglected quadratic, triple, or quadruple factors′ cross-interactions. This study used a dataset of 632 cataract patients to attain a reliable BCVA prediction with a variance of 0.929. A verification dataset of 160 patients with similar symptoms was used to verify this approach′s feasibility, reaching a good correlation with R2 = 0.909. Results: The verification group′s derived average AT (agreement) (9.12 ± 27.00%) indicated a slight deviation between the theoretical prediction and practical BCVA. The significant factors were age, body mass index (BMI), and intraocular pressure (IOP), whereas mean arterial pressure (MAP), hemoglobin A1c (HbA1c), low-density-lipoprotein cholesterol (LDL-C), and gender insignificantly contributed to BCVA. Conclusions: The proposed approach is instrumental in AI-assisted clinical diagnosis, yielding robust BCVA predictions for individual cataract patients based on their biological indices before the ophthalmological examination procedure.

Purpose: In the present study, we aimed to assess the effectiveness and safety of immune-targeted therapy (IT) with or without transarterial chemoembolization (TACE) for advanced hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT). Patients and methods: This was a multicenter retrospective study that included 265 HCC patients with PVTT (IT + TACE: 82, IT: 183). Overall survival (OS) and progression-free survival (PFS), as well as tumor responses and adverse events, were evaluated. Results: Patients in the IT + TACE group experienced significantly longer overall survival (OS) and progression-free survival (PFS) periods, compared with those in the IT group (OS 19.0 vs. 13.0 months, p < 0.001; PFS 12.0 vs. 7.3 months, p < 0.001). Multivariable analysis confirmed IT + TACE as an independent predictor for improved OS and PFS. Subgroup analysis demonstrated the benefits of IT + TACE in patients with rich PVTT blood supply. Preoperative imaging and DSA offered predictive value. Conclusions: TACE combined with IT provides a safe and effective treatment option for advanced-HCC patients with PVTT, particularly those with abundant PVTT blood supply.

Enterovirus A71 (EV-A71) causes hand, foot, and mouth disease in infants and children with potential for fatal complications such as encephalitis and acute flaccid myelitis. This study examined the long-term immunity conferred by EV71vac, an inactivated EV-A71 vaccine adjuvanted with aluminum phosphate, in children from the age of 2 months to

The propagation of antibiotic resistance in environments, particularly aquatic environments that serve as primary pathways for antibiotic resistance genes (ARGs), poses significant health risks. The impact of nutrients, as key determinants of bacterial growth and metabolism, on the propagation of ARGs, particularly extracellular ARGs (eARGs), remains poorly understood. In this study, we collected microorganisms from the Yangtze River and established a series of microcosms to investigate how variations in nutrient levels and delivery frequency affect the relative abundance of intracellular ARGs (iARGs) and eARGs in bacterial communities. Our results show that the relative abundance of 7 out of 11 representative eARGs in water exceeds that of iARGs, while 8 iARGs dominate in biofilms. Notably, iARGs and eARGs consistently exhibited opposite responses to nutrient variation. When nutrient levels increased, iARGs in the water also increased, with the polluted group (COD = 333.3 mg/L, COD:N:P = 100:3:0.6, m/m) and the eutrophic group (COD = 100 mg/L, COD:N:P = 100:25:5, m/m) showing 1.2 and 3.2 times higher levels than the normal group (COD = 100 mg/L, COD:N:P = 100:10:2, m/m), respectively. In contrast, eARGs decreased by 6.7% and 8.4% in these groups. On the other hand, in biofilms, higher nutrient levels led to an increase in eARGs by 1.5 and 1.7 times, while iARGs decreased by 17.5% and 50.1% in the polluted and eutrophic groups compared to the normal group. Moreover, while increasing the frequency of nutrient delivery (from 1 time/10 d to 20 times/10 d) generally did not favor iARGs in either water or biofilm, it selectively enhanced eARGs in both. To further understand these dynamics, we developed an ARGs-nutrient model by integrating the Lotka–Volterra and Monod equations. The results highlight the complex interplay of bacterial growth, nutrient availability, and mechanisms such as horizontal gene transfer and secretion influencing ARGs’ propagation, driving the opposite trend between these two forms of ARGs. This contrasting response between iARGs and eARGs contributes to a dynamic balance that stabilizes bacterial resistance levels amid nutrient fluctuations. This study offers helpful implications regarding the persistence of bacterial resistance in the environment.

To measure the long-range transport of PCDD/Fs, a background sampling site at Mt. Lulin station (Taiwan) was selected based on meteorological information and its location relative to burning events in Southeast Asia. During regular sampling periods, a higher concentration of PCDD/Fs was recorded in 2008 at Mt. Lulin station during La Niña events, with levels reaching 390 fg I-TEQ/m3. In contrast, a higher concentration of 483 fg I-TEQ/m3 was observed in 2013 during biomass burning events. This indicates that La Niña affects the ambient PCDD/F concentrations. The ratio of ΣPCDD/ΣPCDF was 0.59, suggesting significant long-range transport contributions from 2007 to 2023. From 2007 to 2015, the predominant species was 2,3,4,7,8-PCDF, accounting for 25.3 to 39.6% of the total PCDD/Fs. From 2018 onward, 1,2,3,7,8-PCDD became more dominant, accounting for 15.0 to 27.1%. According to the results from the receptor model PMF (n = 150), the sources of PCDD/Fs were identified as dust storms and monsoon events (19.3%), anthropogenic activity (28.5%), and biomass burning events (52.2%). The PSCF values higher than 0.7 highlighted potential PCDD/F emission source regions for Mt. Lulin during biomass burning events, indicating high PSCF values in southern Thailand, Cambodia, and southern Vietnam.

Springback error is a major obstacle in L-bending sheets via cold working. Although thermal processing can effectively reduce the springback phenomenon, it is challenging to heat the sheet globally due to the influence of working conditions. Therefore, this study applied local induction heating to reduce the springback of 45 steel sheets and investigated the effects of bending parameters on springback behavior. Initially, a thermodynamic coupling model and a static model were created utilizing the VOCE hardening model and the von Mises yield criterion in the ANSYS workbench 2022 R2 software. The springback behavior and stress distribution of the sheets were then investigated under different temperatures (room temperature and 800 °C) and bending angles (15°, 30°, 45°, 60°, 75°, and 90°). Simultaneously, the experiments were performed to investigate springback behavior and guarantee the accuracy of the model. The results indicate that the springback reached a minimum value at the 45° bending angle at room temperature while increasing with the increasing bending angle under 800 °C local heating. The springback under local heating can be decreased by 75.2% and the error of the bending angle can improve by 2–7° compared with samples processed in room temperature.