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Co-free high-entropy alloys (HEAs) are promising, cost-effective candidates for structural applications, but their inherently low strength has hindered widespread industrial adoption. In this study, a series of Cu20Cr10Fe35-0.5xNi35-0.5xTix (x = 0, 2, 6, 8, and 10) HEAs were synthesized through mechanical alloying (MA) and spark plasma sintering (SPS). Microstructural analysis revealed a predominantly FCC-structured matrix with minor secondary phases strongly dependent on Ti content. Alloys with low Ti contents (Ti < 6 at%) contained Cr7C3 phase, while the Ti6 alloy (x = 6) showed TiC and eta phases. At higher Ti contents, TiC particles formed alongside eta and L1(2) precipitation phases. Notably, this work demonstrates for the first time that Ti additions can transform detrimental Cr7C3 contamination from milling media into beneficial TiC particles, leading to significant grain refinement. The Ti6 alloy achieved a yield strength (YS) of 683 MPa with 30.0 % elongation, while the Ti8 alloy attained a YS of 1085 MPa and an elongation of 9.5 %. In particular, the Ti8 alloy demonstrates one of the best strength-ductility combinations reported for Cu-rich HEAs, despite the inherent tendency of Cu to segregate and degrade mechanical strength. This exceptional performance is attributed to grain refinement, dispersion strengthening by TiC particles and L1(2) nanoprecipitates, and a distinctive three-stage work-hardening behavior associated with hierarchical precipitation and deformation twinning. This work presents an effective strategy for overcoming the strength-ductility trade-off in MAed/SPSed Co-free HEAs through Ti alloying.
Rare earth-containing magnesium alloys are critical materials in biomedical applications, yet their corrosion performance directly determines service safety. To overcome the time-consuming limitations of traditional experiments and the difficulty in quantifying complex corrosion mechanisms, this study established a machine learning prediction framework using literature-derived alloy compositions and environmental data. Six algorithms, including Random Forest Regressor, Extreme Gradient Boosting, and Support Vector Machine, were rigorously evaluated. Beyond standard grid search, an advanced optimization strategy integrating the Local Outlier Factor method for noise reduction and learning curve analysis was employed to effectively mitigate overfitting. The results indicate that the optimized Random Forest Regressor model achieved the highest accuracy for corrosion potential prediction (coefficient of determination R^2 of 0.98 for training and 0.93 for testing), while the Extreme Gradient Boosting model excelled in predicting corrosion current density (coefficient of determination R^2 of 0.97 for training and 0.94 for testing). Notably, validation through independent electrochemical experiments demonstrated the models’ excellent generalization ability, with prediction errors for corrosion potential and current density within 2
INTRODUCTION:This study examined treatment disparities for colorectal cancer among patients diagnosed with schizophrenia spectrum disorders (SSD), focusing on invasive treatments and stage-appropriate systemic therapy within a universal healthcare system. METHOD:In this nationwide retrospective cohort study (2018-2021), we identified 248,966 colorectal cancer patients, including 2337 diagnosed with SSD, using linked cancer registry and insurance claims data in Japan. The presence of SSD was classified according to ICD-10 codes F20-29. We used multivariable logistic regression to compare the odds of receiving stage-appropriate adjuvant chemotherapy and systemic therapy, as well as the odds of receiving surgical or endoscopic treatments, between the two groups. The analysis adjusted for age, sex, clinical stage, and scores on the Charlson Comorbidity Index and Barthel Index. RESULTS:The clinical stage distribution at diagnosis for colorectal cancer differed significantly between patients with SSD and those without psychiatric disorders (p < 0.001). After adjusting for clinical stage and other covariates, patients with SSD demonstrated significantly lower odds of receiving surgical or endoscopic treatment (adjusted odds ratio [aOR], 0.83; 95% CI, 0.73-0.94). The disparities were more pronounced for systemic therapy; patients with SSD had substantially lower odds of receiving adjuvant chemotherapy for stage III disease (aOR, 0.33; 95% CI, 0.26-0.41) and systemic therapy for stage IV disease (aOR, 0.23; 95% CI, 0.17-0.31). CONCLUSION:Patients with SSD encounter substantial disparities in accessing standard colorectal cancer care, particularly systemic therapies. These findings highlight the urgent need for interventions to ensure equitable cancer treatment for this vulnerable population.
Statistical mechanics explains the properties of macroscopic phenomena based on the movements of microscopic particles such as atoms and molecules. Movements of microscopic particles can be represented by large-scale interacting systems. In this article, we systematically study combinatorial objects which we call interactions, given as symmetric directed graphs representing the possible transitions of states on adjacent sites of large-scale interacting systems. Such interactions underlie various standard stochastic processes such as the exclusion processes, generalized exclusion processes, multi-species exclusion processes, lattice gas with energy processes, and the multi-lane exclusion processes. We introduce the notion of equivalences of interactions using their space of conserved quantities. This allows for the classification of interactions reflecting the expected macroscopic properties. In particular, we prove that when the set of local states consists of two, three or four elements, then the number of equivalence classes of separable interactions are respectively one, two and five. We also define the wedge sums and box products of interactions, which give systematic methods for constructing new interactions from existing ones. Furthermore, we prove that the irreducibly quantified condition for interactions, which implicitly plays an important role in the theory of hydrodynamic limits, is preserved by wedge sums and box products. Our results provide a systematic method to construct and classify interactions, offering abundant examples suitable for considering hydrodynamic limits.
Lake Nakaumi, Japan, a brackish enclosed lagoon, has been significantly modified since the 20th century. We investigated spatiotemporal changes in meiobenthic Ostracoda, total organic carbon (TOC), and total sulfur (TS) from five sedimentary cores, reconstructing climatic and anthropogenic impacts since the Little Ice Age (LIA). Novel environmental ranks from S to F in the order of the higher degree of salinity and/or dissolved oxygen, were established using a modern analog technique on ostracod assemblages. TOC profiles showed similar vertical trends with chronologically correlated minima. Prior to 1600, ostracod assemblages possibly reflected the Sporer Minimum solar activity decline. During the mid-17th century cooling to the LIA's end (mid-19th century), reduced ostracod abundance and diversity suggest increased water stagnation and stratification driven by high precipitation and low surface salinity. Lake circulation was weakest during the Maunder Minimum, corresponding to the lowest environmental rank. Then, ostracod diversity and abundance increased, peaking in 1850-1860, reaching the highest environmental rank by similar to 1920 because of the increased seawater inflow from the Sea of Japan due to global sea-level rise. An artificial dike at the seawater entrance (1922-1930) caused rapid increase in TOC and TS, indicating intensified eutrophication and organic pollution, which peaked in the eastern lake during the 1960s-1970s. Later interventions (water barrier gate, dikes, dredging, land reclamation; 1968-1981) accelerated eutrophication and stagnation in western/southern sites. Despite improved water and bottom conditions in the east due to altered seawater inflow, the environmental rank became extremely low in all the sites. Post-1920, anthropogenic influences superseded natural climatic changes in shaping the lake's water, bottom, and ostracod conditions.
