Hydrological response of drought impacts across catchments worldwide.

Drought will inevitably affect linkages between different water components, which have previously been investigated across different spatiotemporal scales. Elucidating drought-induced precipitation (P) partition effects remain uncertain because they involve drought propagation, even inducing streamflow (Q) non-stationarity. This study collected data on 1069 catchments worldwide to investigate Q and evapotranspiration (ET) impacts from P deficit-derived reductions in drought propagation. Results show that P deficits trigger soil moisture drought, subsequently inducing negative Q and ET anomalies that vary under different climate regimes. Generally, drought-induced hydrological legacies indicate that breaks in hydrological linkages cause a relatively rapid Q response (i.e., negative Q anomaly), amplified by drought strength and duration. Compared with the Q response, the ET response to drought stress involves a more complex, associative vegetation response and an associative evaporative state controlled by water and energy, which lags behind the Q response and can also intensify with increasing drought severity and duration. This is confirmed by the ET response under different climate regimes. Namely, in drier climates, a positive ET anomaly can be detected in its early stages, this is unusual in wetter climate. Additionally, Q and ET sensitivity to drought strength can be mechanistically explained by the water and energy status. This implies that ET is mainly controlled by water and energy, resulting in higher and lower drought sensitivity within water- and energy-limited regions, respectively. Understanding the impacts of drought on Q and ET response is essential for identifying key linkages in drought propagation across different climate regimes. Our findings will also be useful for developing early warning and adaptation systems that support both human and ecosystem requirements.

TPP-Based Microfluidic Chip Design and Fabrication Method for Optimized Nerve Cells Directed Growth.

Microfluidic chips offer high customizability and excellent biocompatibility, holding important promise for the precise control of biological growth at the microscale. However, the microfluidic chips employed in the studies of regulating cell growth are typically fabricated through 2D photolithography. This approach partially restricts the diversity of cell growth platform designs and manufacturing efficiency. This paper presents a method for designing and manufacturing neural cell culture microfluidic chips (NCMC) using two-photon polymerization (TPP), where the discrete and directional cell growth is optimized through studying the associated geometric parameters of on-chip microchannels. This study involves simulations and discussions regarding the effects of different hatching distances on the mold surface topography and printing time in the Describe print preview module, which determines the appropriate printing accuracy corresponding to the desired mold structure. With the assistance of the 3D maskless lithography system, micron-level rapid printing of target molds with different dimensions were achieved. For NCMC with different geometric parameters, COMSOL software was used to simulate the local flow velocity and shear stress characteristics within the microchannels. SH-SY5Y cells were selected for directional differentiation experiments on NCMC with different geometric parameters. The results demonstrate that the TPP-based manufacturing method efficiently constructs neural microfluidic chips with high precision, optimizing the discrete and directional cell growth. We anticipate that our method for designing and manufacturing NCMC will hold great promise in construction and application of microscale 3D drug models.

General reversal of N-decomposition relationship during long-term decomposition in boreal and temperate forests.

Decomposition of dead organic matter is fundamental to carbon (C) and nutrient cycling in terrestrial ecosystems, influencing C fluxes from the biosphere to the atmosphere. Theory predicts and evidence strongly supports that the availability of nitrogen (N) limits litter decomposition. Positive relationships between substrate N concentrations and decomposition have been embedded into ecosystem models. This decomposition paradigm, however, relies on data mostly from short-term studies analyzing controls on early-stage decomposition. We present evidence from three independent long-term decomposition investigations demonstrating that the positive N-decomposition relationship is reversed and becomes negative during later stages of decomposition. First, in a 10-y decomposition experiment across 62 woody species in a temperate forest, leaf litter with higher N concentrations exhibited faster initial decomposition rates but ended up a larger recalcitrant fraction decomposing at a near-zero rate. Second, in a 5-y N-enrichment experiment of two tree species, leaves with experimentally enriched N concentrations had faster decomposition initial rates but ultimately accumulated large slowly decomposing fractions. Measures of amino sugars on harvested litter in two experiments indicated that greater accumulation of microbial residues in N-rich substrates likely contributed to larger slowly decomposing fractions. Finally, a database of 437 measurements from 120 species in 45 boreal and temperate forest sites confirmed that higher N concentrations were associated with a larger slowly decomposing fraction. These results challenge the current treatment of interactions between N and decomposition in many ecosystems and Earth system models and suggest that even the best-supported short-term controls of biogeochemical processes might not predict long-term controls.

EGC enhances tumor antigen presentation and CD8+ T cell-mediated antitumor immunity via targeting oncoprotein SND1.

The Staphylococcal nuclease and Tudor domain containing 1 (SND1) has been identified as an oncoprotein. Our previous study demonstrated that SND1 impedes the major histocompatibility complex class I (MHC-I) assembly by hijacking the nascent heavy chain of MHC-I to endoplasmic reticulum-associated degradation. Herein, we aimed to identify inhibitors to block SND1-MHC-I binding, to facilitate the MHC-I presentation and tumor immunotherapy. Our findings validated the importance of the K490-containing sites in SND1-MHC-I complex. Through structure-based virtual screening and docking analysis, (-)-Epigallocatechin (EGC) exhibited the highest docking score to prevent the binding of MHC-I to SND1 by altering the spatial conformation of SND1. Additionally, EGC treatment resulted in increased expression levels of membrane-presented MHC-I in tumor cells. The C57BL/6J murine orthotopic melanoma model validated that EGC increases infiltration and activity of CD8+ T cells in both the tumor and spleen. Furthermore, the combination of EGC with programmed death-1 (PD-1) antibody demonstrated a superior antitumor effect. In summary, we identified EGC as a novel inhibitor of SND1-MHC-I interaction, prompting MHC-I presentation to improve CD8+ T cell response within the tumor microenvironment. This discovery presents a promising immunotherapeutic candidate for tumors.

The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutations.

OBJECTIVES: 18F-fluorodeoxyglucose (FDG) PET/CT has been widely used for the differential diagnosis of cancer. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may make it difficult to differentiate between benign and malignant lesions. It is crucial to find reliable quantitative metabolic parameters to further support the diagnosis. This study aims to evaluate the value of the quantitative metabolic parameters derived from dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting epidermal growth factor receptor (EGFR) mutation status. METHODS: We included 147 patients with lung lesions to perform FDG PET/CT dynamic plus static imaging with informed consent. Based on the results of the postoperative pathology, the patients were divided into benign/malignant groups, adenocarcinoma (AC)/squamous carcinoma (SCC) groups, and EGFR-positive (EGFR+)/EGFR-negative (EGFR-) groups. Quantitative parameters including K1, k2, k3, and Ki of each lesion were obtained by applying the irreversible two-tissue compartmental modeling using an in-house Matlab software. The SUV analysis was performed based on conventional static scan data. Differences in each metabolic parameter among the group were analyzed. Wilcoxon rank-sum test, independent-samples T-test, and receiver-operating characteristic (ROC) analysis were performed to compare the diagnostic effects among the differentiated groups. P < 0.05 were considered statistically significant for all statistical tests. RESULTS: In the malignant group (N = 124), the SUVmax, k2, k3, and Ki were higher than the benign group (N = 23), and all had-better performance in the differential diagnosis (P < 0.05, respectively). In the AC group (N = 88), the SUVmax, k3, and Ki were lower than in the SCC group, and such differences were statistically significant (P < 0.05, respectively). For ROC analysis, Ki with cut-off value of 0.0250 ml/g/min has better diagnostic specificity than SUVmax (AUC = 0.999 vs. 0.70). In AC group, 48 patients further underwent EGFR testing. In the EGFR (+) group (N = 31), the average Ki (0.0279 ± 0.0153 ml/g/min) was lower than EGFR (-) group (N = 17, 0.0405 ± 0.0199 ml/g/min), and the difference was significant (P < 0.05). However, SUVmax and k3 did not show such a difference between EGFR (+) and EGFR (-) groups (P>0.05, respectively). For ROC analysis, the Ki had a cut-off value of 0.0350 ml/g/min when predicting EGFR status, with a sensitivity of 0.710, a specificity of 0.588, and an AUC of 0.674 [0.523-0.802]. CONCLUSION: Although both techniques were specific, Ki had a greater specificity than SUVmax when the cut-off value was set at 0.0250 ml/g/min for the differential diagnosis of lung cancer. At a cut-off value of 0.0350 ml/g/min, there was a 0.710 sensitivity for EGFR status prediction. If EGFR testing is not available for a patient, dynamic imaging could be a valuable non-invasive screening method.

AKIMLpred: An interpretable machine learning model for predicting acute kidney injury within seven days in critically ill patients based on a prospective cohort study.

BACKGROUND: Early recognition and timely intervention for AKI in critically ill patients were crucial to reduce morbidity and mortality. This study aimed to use biomarkers to construct a optimal machine learning model for early prediction of AKI in critically ill patients within seven days. METHODS: The prospective cohort study enrolled 929 patients altogether who were admitted in ICU including 680 patients in training set (Jiefang Campus) and 249 patients in external testing set (Binjiang Campus). After performing strict inclusion and exclusion criteria, 421 patients were selected in training set for constructing predictive model and 167 patients were selected in external testing for evaluating the predictive performance of resulting model. Urine and blood samples were collected for kidney injury associated biomarkers detection. Baseline clinical information and laboratory data of the study participants were collected. We determined the average prediction efficiency of six machine learning models through 10-fold cross validation. RESULTS: In total, 78 variables were collected when admission in ICU and 43 variables were statistically significant between AKI and non-AKI cohort. Then, 35 variables were selected as independent features for AKI by univariate logistic regression. Spearman correlation analysis was used to remove two highly correlated variables. Three ranking methods were used to explore the influence of 33 variables for further determining the best combination of variables. The gini importance ranking method was found to be applicable for variables filtering. The predictive performance of AKIMLpred which constructed by the XGBoost algorithm was the best among six machine learning models. When the AKIMLpred included the nine features (NGAL, IGFBP7, sCysC, CAF22, KIM-1, NT-proBNP, IL-6, IL-18 and L-FABP) with the highest influence ranking, its model had the best prediction performance, with an AUC of 0.881 and an accuracy of 0.815 in training set, similarly, with an AUC of 0.889 and an accuracy of 0.846 in validation set. Moreover, the performace was slightly outperformed in testing set with an AUC of 0.902 and an accuracy of 0.846. The SHAP algorithm was used to interpret the prediction results of AKIMLpred. The web-calculator of AKIMLpred was shown for predicting AKI with more convenient(https://www.xsmartanalysis.com/model/list/predict/model/html?mid=8065&symbol=11gk693982SU6AE1ms21). AKIMLpred was better than the optimal model built with only routine tests for predicting AKI in critically ill patients within 7 days. CONCLUSION: The model AKIMLpred constructed by the XGBoost algorithm with selecting the nine most influential biomarkers in the gini importance ranking method had the best performance in predicting AKI in critically ill patients within 7 days. This data-driven predictive model will help clinicians to make quick and accurate diagnosis.

Metabolic phenotyping reveals an emerging role of ammonia abnormality in Alzheimer's disease.

The metabolic implications in Alzheimer's disease (AD) remain poorly understood. Here, we conducted a metabolomics study on a moderately aging Chinese Han cohort (n = 1397; mean age 66 years). Conjugated bile acids, branch-chain amino acids (BCAAs), and glutamate-related features exhibited strong correlations with cognitive impairment, clinical stage, and brain amyloid-ß deposition (n = 421). These features demonstrated synergistic performances across clinical stages and subpopulations and enhanced the differentiation of AD stages beyond demographics and Apolipoprotein E ε4 allele (APOE-ε4). We validated their performances in eight data sets (total n = 7685) obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Memory and Aging Project (ROSMAP). Importantly, identified features are linked to blood ammonia homeostasis. We further confirmed the elevated ammonia level through AD development (n = 1060). Our findings highlight AD as a metabolic disease and emphasize the metabolite-mediated ammonia disturbance in AD and its potential as a signature and therapeutic target for AD.

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies.

OBJECTIVES: Older people are more likely to have digital exclusion, which is associated with poor health. This study investigated the relationship between digital exclusion and cognitive impairment in older adults from 23 countries across five longitudinal surveys. DESIGN AND MEASUREMENTS: Digital exclusion is defined as self-reported non-use of the Internet. We assessed cognitive impairment on three dimensions: orientation, memory, and executive function. We used generalized estimation equations fitting binary logistic regression with exchangeable correlations to study the relationship between digital exclusion and cognitive impairment, and apply the minimum sufficiently adjusted set of causally directed acyclic graphs as the adjusted variable. SETTING AND PARTICIPANTS: We pooled a nationally representative sample of older adults from five longitudinal studies, including the China Health and Retirement Longitudinal study (CHARLS), the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Study (HRS), the Mexican Health and Ageing Study (MHAS) and the Survey of Health, Ageing and Retirement in European (SHARE). RESULTS: We included 62,413 participants from five longitudinal studies. Digital exclusion varied by country, ranging from 21.69% (SHARE) in Denmark to 97.15% (CHARLS) in China. In the original model, digital exclusion was significantly associated with cognitive impairment in all five studies. In the adjusted model, these associations remained statistically significant: CHARLS (Odds ratio [OR] = 2.81, 95% confidence interval [CI] 1.84-4.28, ELSA (1.92 [1.70-2.18]), HRS(2.48[2.28-2.71), MHAS (1.92 [1.74-2.12]), and SHARE (2.60 [2.34-2.88]). CONCLUSION: Our research shows that a significant proportion of older people suffer from digital exclusion, especially in China. Digital exclusion was positively correlated with cognitive impairment. These findings suggest that digital inclusion could be an important strategy to improve cognitive function and reduce the risk of cognitive impairment in older adults.

MSC microvesicles loaded G-quadruplex-enhanced circular single-stranded DNA-9 inhibits tumor growth by targeting MDSCs.

BACKGROUND: Myeloid-derived suppressor cells (MDSCs) promote tumor growth, metastasis, and lead to immunotherapy resistance. Studies revealed that miRNAs are also expressed in MDSCs and promote the immunosuppressive function of MDSCs. Currently, few studies have been reported on inducible cellular microvesicle delivery of nucleic acid drugs targeting miRNA in MDSCs for the treatment of malignant tumors. RESULTS AND CONCLUSION: In this study, we designed an artificial DNA named G-quadruplex-enhanced circular single-stranded DNA-9 (G4-CSSD9), that specifically adsorbs the miR-9 sequence. Its advanced DNA folding structure, rich in tandem repeat guanine (G-quadruplex), also provides good stability. Mesenchymal stem cells (MSCs) were prepared into nanostructured vesicles by membrane extrusion. The MSC microvesicles-encapsulated G4-CSSD9 (MVs@G4-CSSD9) was delivered into MDSCs, which affected the downstream transcription and translation process, and reduced the immunosuppressive function of MDSCs, so as to achieve the purpose of treating melanoma. In particular, it provides an idea for the malignant tumor treatment.

Application of poly(L-lactic acid)-based films for equilibrium modified atmosphere packaging of "Kyoho" grapes and its favorable protection for anthocyanins.

Grapes were packaged by different Poly (L-lactic acid)-based packaging films (PLTL-PLEL) and stored at 5 °C for 35 days to investigate the effects of equilibrium modified atmosphere packaging on the quality of "Kyoho" grapes during storage. Changes in physiochemical quality, antioxidant content and senescence of grapes were studied. Furthermore, UPLC-Q-TOF-MS/MS was used to observe and identify key factors influencing the variation of grape anthocyanins under different atmosphere conditions. Alterations in gas components and enzyme activities significantly impacted anthocyanin levels, highlighting oxygen concentration as the primary influence on total anthocyanin levels. The PLTL-PLEL50 packaging resulted in an approximate 5.7% lower weight loss and increased soluble solids by approximately 14.4%, vitamin C, total phenols and flavonoids reaching 60.2 mg/100 g, 8.4 mg/100 g and 7.2 mg/100 g, respectively. This packaging also preserved higher anthocyanin levels, with malvidin-3-glucoside and peonidin-3-glucoside at 0.55 µg/mL and 1.62 µg/mL, respectively, on the 35th day of storage.

Gut microbial alterations in arginine metabolism determine bone mechanical adaptation.

Although mechanical loading is essential for maintaining bone health and combating osteoporosis, its practical application is limited to a large extent by the high variability in bone mechanoresponsiveness. Here, we found that gut microbial depletion promoted a significant reduction in skeletal adaptation to mechanical loading. Among experimental mice, we observed differences between those with high and low responses to exercise with respect to the gut microbial composition, in which the differential abundance of Lachnospiraceae contributed to the differences in bone mechanoresponsiveness. Microbial production of L-citrulline and its conversion into L-arginine were identified as key regulators of bone mechanoadaptation, and administration of these metabolites enhanced bone mechanoresponsiveness in normal, aged, and ovariectomized mice. Mechanistically, L-arginine-mediated enhancement of bone mechanoadaptation was primarily attributable to the activation of a nitric-oxide-calcium positive feedback loop in osteocytes. This study identifies a promising anti-osteoporotic strategy for maximizing mechanical loading-induced skeletal benefits via the microbiota-metabolite axis.

Clinical Implementation of Total-Body PET in China.

Total-body (TB) PET/CT is a groundbreaking tool that has brought about a revolution in both clinical application and scientific research. The transformative impact of TB PET/CT in the realms of clinical practice and scientific exploration has been steadily unfolding since its introduction in 2018, with implications for its implementation within the health care landscape of China. TB PET/CT's exceptional sensitivity enables the acquisition of high-quality images in significantly reduced time frames. Clinical applications have underscored its effectiveness across various scenarios, emphasizing the capacity to personalize dosage, scan duration, and image quality to optimize patient outcomes. TB PET/CT's ability to perform dynamic scans with high temporal and spatial resolution and to perform parametric imaging facilitates the exploration of radiotracer biodistribution and kinetic parameters throughout the body. The comprehensive TB coverage offers opportunities to study interconnections among organs, enhancing our understanding of human physiology and pathology. These insights have the potential to benefit applications requiring holistic TB assessments. The standard topics outlined in The Journal of Nuclear Medicine were used to categorized the reviewed articles into 3 sections: current clinical applications, scan protocol design, and advanced topics. This article delves into the bottleneck that impedes the full use of TB PET in China, accompanied by suggested solutions.

Sorafenib plus TACE with or without camrelizumab for the treatment of intermediate and advanced hepatocellular carcinoma.

OBJECTIVES: To compare the efficacy and safety of transcatheter arterial chemoembolization (TACE) combined with sorafenib and camrelizumab or with sorafenib alone in patients with intermediate or advanced hepatocellular carcinoma (HCC). METHODS: We retrospectively analyzed 78 patients with intermediate or advanced HCC who were treated at our centers between January 2018 and December 2021. 26 of them received sorafenib and camrelizumab plus TACE (the TACE + Sor + C group), while 52 received TACE and sorafenib (the TACE + Sor group). Overall survival (OS), progression-free survival (PFS), and adverse events (AEs) were evaluated. Univariate and multivariate analyses were used to determine the factors affecting survival. RESULTS: The mOS (22 vs. 10 months, P < 0.001) and mPFS (11 vs. 6 months, P = 0.008) of the TACE + Sor + C group were significantly higher than those of the TACE + Sor group. Multivariate analysis showed that compared with TACE + Sor + C, TACE + Sor increased the risk of all-cause mortality and tumor progression. For grade I and II adverse events (AEs), the incidence of skin capillary hyperplasia and hypothyroidism in the TACE + Sor + C group was significantly higher than that in the TACE + Sor group. For serious AEs (grade III or IV), there was no significant difference in any adverse reaction between the two groups (P > 0.05). CONCLUSION: Patients with intermediate or advanced HCC appeared to benefit more in terms of survival from TACE + Sor + C than from TACE + Sor, and the AEs were tolerable. ADVANCES IN KNOWLEDGE: 1.Subgroup analysis demonstrated TACE+ Sorafenib+ Camrelizumab could benefit HCC patients regardless of whether they had PVTT, BCLC B or C, or CHILD A or B；2.We reported the immunotherapy related adverse events (irAEs) occurred with a significant higher incidence in triple treatment, but all the adverse events are tolerable.

Time Is Ripe for Targeting Per- and Polyfluoroalkyl Substances-Induced Hormesis: Global Aquatic Hotspots and Implications for Ecological Risk Assessment.

Globally implemented ecological risk assessment (ERA) guidelines marginalize hormesis, a biphasic dose-response relationship characterized by low-dose stimulation and high-dose inhibition. The present study illuminated the promise of hormesis as a scientific dose-response model for ERA of per- and polyfluoroalkyl substances (PFAS) represented by perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS). A total of 266 hormetic dose-response relationships were recompiled from 1237 observations, covering 30 species from nine representative taxonomic groups. The standardized hormetic amplitudes followed the log-normal probability distribution, being subject to the limits of biological plasticity but independent of stress inducers. The SHapley Additive exPlanations algorithm revealed that the target endpoint was the most important variable explaining the hormetic amplitudes. Subsequently, quantitative frameworks were established to incorporate hormesis into the predicted no-effect concentration levels, with a lower induction dose and a zero-equivalent point but a broader hormetic zone for PFOS. Realistically, 10,117 observed concentrations of PFOA and PFOS were gathered worldwide, 4% of which fell within hormetic zones, highlighting the environmental relevance of hormesis. Additionally, the hormesis induction potential was identified in other legacy and emerging PFAS as well as their alternatives and mixtures. Collectively, it is time to incorporate the hormesis concept into PFAS studies to facilitate more realistic risk characterizations.

Increased intestinal bile acid absorption contributes to age-related cognitive impairment.

Cognitive impairment in the elderly is associated with alterations in bile acid (BA) metabolism. In this study, we observe elevated levels of serum conjugated primary bile acids (CPBAs) and ammonia in elderly individuals, mild cognitive impairment, Alzheimer's disease, and aging rodents, with a more pronounced change in females. These changes are correlated with increased expression of the ileal apical sodium-bile acid transporter (ASBT), hippocampal synapse loss, and elevated brain CPBA and ammonia levels in rodents. In vitro experiments confirm that a CPBA, taurocholic acid, and ammonia induced synaptic loss. Manipulating intestinal BA transport using ASBT activators or inhibitors demonstrates the impact on brain CPBA and ammonia levels as well as cognitive decline in rodents. Additionally, administration of an intestinal BA sequestrant, cholestyramine, alleviates cognitive impairment, normalizing CPBAs and ammonia in aging mice. These findings highlight the potential of targeting intestinal BA absorption as a therapeutic strategy for age-related cognitive impairment.

Westerlies-driven transboundary transport of atmospheric mercury to the north-central Tibetan Plateau.

The transboundary mercury (Hg) pollution has caused adverse effects on fragile ecosystems of the Tibetan Plateau (TP). Yet, knowledge of transport paths and source regions of atmospheric Hg on the inland TP remains poor. Continuous measurements of atmospheric total gaseous mercury (TGM) were conducted in the central TP (Tanggula station, 5100 m a.s.l., June-October). Atmospheric TGM level at Tanggula station (1.90 ± 0.30 ng m-3) was higher than the background level in the Northern Hemisphere. The identified high-potential source regions of atmospheric TGM were primarily located in the northern South Asia region. TGM concentrations were lower during the Indian summer monsoon (ISM)-dominant period (1.81 ± 0.25 ng m-3) than those of the westerly-receding period (2.18 ± 0.40 ng m-3) and westerly-intensifying period (1.91 ± 0.26 ng m-3), contrary to the seasonal pattern in southern TP. The distinct TGM minima during the ISM-dominant period indicated lesser importance of ISM-transported Hg to Tanggula station located in the northern boundary of ISM intrusion, compared to stations in proximity to South and Southeast Asia source regions. Instead, from the ISM-dominant period to the westerly-intensifying period, TGM concentrations showed an increasing trend as westerlies intensified, indicating the key role of westerlies in transboundary transport of atmospheric Hg to the inland TP.

The Effect of Laser Remelting during SLM on Microstructure and Mechanical Properties of CoCrFeNiNb0.25.

A sub-eutectic high-entropy alloy composed of CoCrFeNiNb0.25 was prepared using a combination of mechanical powder mixing and selective laser melting (SLM). The mechanical properties of the alloy were enhanced by employing an interlayer laser remelting process. This study demonstrates the feasibility of using mechanical mixing and SLM to form an CoCrFeNiNb0.25 alloy. The interlayer laser remelting process can effectively promote the melting of Nb particles introduced by mechanical mixing, release the stresses near the unfused Nb particles, and reduce their degradation of the specimen properties. The results indicate that the CoCrFeNiNb0.25 alloy, prepared using the interlayer laser remelting process, had an average microhardness of 376 HV, a tensile strength of 974 MPa, and an elongation at break of 10.51%. This process offers a viable approach for rapidly adjusting the composition of high-entropy alloys for SLM forming.

Transformation of Coherent Twin Boundary into Basal-Prismatic Boundary in HCP-Ti: A Molecular Dynamics Study.

The manufacturing process for wrought Ti alloys with the hexagonal close-packed (HCP) structure introduces a complicated microstructure with abundant intra- and inter-grain boundaries, which greatly influence performance. In the hexagonal close-packed (HCP) structure, two types of grain boundaries are commonly observed between grains with ~90° misorientation: the basal/prismatic boundary (BPB) and the coherent twin boundary (CTB). The mechanical response of the BPB and CTB under external loading was studied through molecular dynamic simulations of HCP-Ti. The results revealed that CTB undergoes transformation into BPB through the accumulation of twin boundary (TB) steps and subsequent emission of Shockley partial dislocations. When the total mismatch vector is close to the Burgers vector of a Shockley partial dislocation, BPB emits partial dislocations and further grows along the stacking faults. When a pair of CTBs are close to each other, severe boundary distortion occurs, facilitating the emission and absorption of partial dislocations, which further assists the CTB-BPB transformation. The present results thus help to explain the frequent observation of coexisting CTB and BPB in HCP alloys and further contribute to the understanding of their microstructure and property regulation.

Global prevalence of microplastics in tap water systems: Abundance, characteristics, drivers and knowledge gaps.

Tap water is a main route for human direct exposure to microplastics (MPs). This study recompiled baseline data from 34 countries to assess the current status and drivers of MP contamination in global tap water systems (TWS). It was shown that MPs were detected in 87 % of 1148 samples, suggesting the widespread occurrence of MPs in TWS. The detected concentrations of MPs spanned seven orders of magnitude and followed the linearized log-normal distribution (MSE = 0.035, R2 = 0.965), with cumulative concentrations at 5th, 50th and 95th percentiles of 0.028, 4.491 and 728.105 items/L, respectively. The morphological characteristics were further investigated, indicating that particles smaller than 50 µm dominated in global TWS, with fragment, polyester and transparent as the most common shape, composition and color of MPs, respectively. Subsequently, the SHapley Additive exPlanations (SHAP) algorithm was implemented to quantify the importance of variables affecting the MP abundance in global TWS, showing that the lower particle size limit was the most important variables. Subgroup analysis revealed that the concentration of MPs counted at the size limit of 1 µm was >20 times higher than that above 1 µm. Ultimately, current knowledge gaps and future research needs were elucidated.

Decentralized stochastic sharpness-aware minimization algorithm.

In recent years, distributed stochastic algorithms have become increasingly useful in the field of machine learning. However, similar to traditional stochastic algorithms, they face a challenge where achieving high fitness on the training set does not necessarily result in good performance on the test set. To address this issue, we propose to use of a distributed network topology to improve the generalization ability of the algorithms. We specifically focus on the Sharpness-Aware Minimization (SAM) algorithm, which relies on perturbation weights to find the maximum point with better generalization ability. In this paper, we present the decentralized stochastic sharpness-aware minimization (D-SSAM) algorithm, which incorporates the distributed network topology. We also provide sublinear convergence results for non-convex targets, which is comparable to consequence of Decentralized Stochastic Gradient Descent (DSGD). Finally, we empirically demonstrate the effectiveness of these results in deep networks and discuss their relationship to the generalization behavior of SAM.