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"Liu, Xingyi"
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The Idea of justice in literature
The theme arises from the legal-academic movement \"Law and Literature\". This newly developed field should aim at two major goals, first, to investigate the meaning of law in a social context by questioning how the characters appearing in literary works understand and behave themselves to the law (law in literature), and second, to find out a theoretical solution of the methodological question whether and to what extent the legal text can be interpreted objectively in comparison with the question how literary works should be interpreted (law as literature). The subject of justice and injustice has been covered not only in treatises of law and philosophy, but also in many works of literature: On the one hand, poets and writers have been outraged at the social conditions of their time. On the other hand, some of them have also contributed fundamental reflections on the idea of justice itself.
Book
Calibration and analysis of discrete element simulation parameters of Chinese cabbage seeds
To improve the accuracy of parameters used in discrete element simulation test of Chinese cabbage seeds harvesting process. Firstly, the key physical parameters of Chinese cabbage seeds were measured. According to the results, the discrete element simulation model was established and the value range of simulation test parameters was determined. Then, the actual repose angle of Chinese cabbage seeds was obtained by physical accumulation test using bottomless conical cylinder lifting method. Plackett-Burman test, steepest climb test, Box-Behnken test and parameter optimization test were carried out in sequence with the actual angle of repose as the response value. Finally, the obtained parameters are verified. 1. The Plackett-Burman test showed that the seed-seed rolling friction coefficient, the seed-steel rolling friction coefficient, the seed-seed static friction coefficient, and the seed-steel static friction coefficient had significant effects on the repose angle of Chinese cabbage seeds (P<0.05). 2. The optimization test showed that the seed-seed rolling friction coefficient was 0.08, the seed-steel rolling friction coefficient was 0.109, the seed-seed static friction coefficient was 0.496, and the seed-steel static friction coefficient was 0.415. 3. The validation test showed that the repose angle of Chinese cabbage seeds under such parameter was 23.62°, and the error with the repose angle of the physical test was 0.73%. The study show that the discrete element simulation parameters of Chinese cabbage seeds model and calibration are reliable, which can provide reference for the discrete element simulation of Chinese cabbage seeds.
Journal Article
In Situ Test and Numerical Analysis of the Subway-Induced Vibration Influence in Historical and Cultural Reserves
Although the rapid expansion of urban rail transit offers convenience to citizens, the issue of subway vibration cannot be overlooked. This study investigates the spatial distribution characteristics of vibration in the Fayuan Temple historic and cultural reserve. It involves using a V001 magnetoelectric acceleration sensor capable of monitoring low amplitudes with a sensitivity of 0.298 V/(m/s2), a measuring range of up to 20 m/s2, and a frequency range span from 0.5 to 100 Hz for in situ testing, analyzing the law of vibration propagation in this area, evaluating the impact on buildings, and determining the vibration reduction scheme. The reserve is divided into three zones based on the vertical vibration level measured during the in situ test as follows: severely excessive, generally excessive, and non-excessive vibration. Furthermore, the research develops a dynamic coupling model of vehicle–track–tunnel–stratum–structure to verify the damping effect of the wire spring floating plate track and periodic pile row. It compares the characteristics of three vibration reduction schemes, namely, internal vibration reduction reconstruction, periodic pile row, and anti-vibration reinforcement or reconstruction of buildings, proposing a comprehensive solution. Considering the construction conditions, difficulty, cost, and other factors, a periodic pile row is recommended as the primary treatment measure. If necessary, anti-vibration reinforcement or reconstruction of buildings can serve as supplemental measures.
Journal Article
Mobility functional status ascertainment in electronic health records using large language models
With global aging, assessing functional status is vital for precision medicine. Electronic Health Records (EHRs), particularly unstructured data, hold abundant information on patient mobility. This study explores using Large Language Models (LLMs) to extract and standardize mobility status from unstructured EHR data (i.e., clinical notes). We annotated 600 clinical notes from three healthcare institutions located in southeastern Minnesota and west-central Wisconsin, focusing on expressions of mobility and associated impairment. Leveraging the open-source Llama 3 model, we tested various prompting strategies, including zero-shot, few-shot, and task decomposition, and evaluated their performance. Error analysis showed that while the model sometimes inferred impairments without explicit evidence, most errors were clinically reasonable, often reflecting borderline or ambiguous cases. Our final model achieved a patient-level micro-average F1-score of 0.876 [95% CI 0.858–0.894] for Mobility Extraction and 0.897 [95% CI 0.878–0.917] for Impairment Classification. A secondary analysis counting “clinically reasonable inferences” as correct, performed to assess clinical plausibility, yielded F1-scores of 0.962 [95% CI 0.952–0.971] and 0.948 [95% CI 0.936–0.960], respectively. A local, deterministic setup improved trustworthiness by ensuring consistent outputs, safeguarding privacy, and demonstrating cross-institution generalizability. These findings highlight the feasibility of LLM-based solutions for extracting mobility functional status from unstructured EHR data, supporting both clinical applications and research.
Journal Article
Hypergraph clustering for analyzing chronic disease patterns in mild cognitive impairment reversion and progression
Identifying the sequential patterns of chronic conditions that precede the onset of mild cognitive impairment (MCI) is essential for understanding both the progression and the potential reversal of MCI. This study identifies common sequences of chronic conditions preceding MCI and introduces a novel, network-based clustering framework for characterizing patients with similar progression patterns linked to cognitive trajectories. We used the Mayo Clinic Study of Aging (MCSA) cohort and categorized participants of MCSA into two groups (i) stay at MCI or progressed to dementia, or (ii) reversion to normal within 5 years after the first onset of MCI. We curate the
state transition network
(patient level) for identifying and introduced
hypergraph clustering
(patient group level) to characterize participants with similar sequences. We identified generic key indicators (e.g., chronic kidney disease) and highlighted sex-specific potential indicators (e.g., arthritis, hypertension) associated with MCI reversal, opening new research directions to explore potential differences between males and females. There are certain ssequences of chronic conditions (e.g., originating from arthritis) that are more commonly observed in females. However, these observations warrant further validation. The proposed framework – hypergraph clustering – offers a promising method for uncovering similarities in patients through unique trajectories of chronic conditions that precede MCI.
Journal Article
Effects of grazing exclusion on soil microbial diversity and its functionality in grasslands: a meta-analysis
Grazing exclusion (GE) is considered an effective strategy for restoring the degradation of overgrazed grasslands on the global scale. Soil microbial diversity plays a crucial role in supporting multiple ecosystem functions (multifunctionality) in grassland ecosystems. However, the impact of grazing exclusion on soil microbial diversity remains uncertain. Here, we conducted a meta-analysis using a dataset comprising 246 paired observations from 46 peer-reviewed papers to estimate how GE affects microbial diversity and how these effects vary with climatic regions, grassland types, and GE duration ranging from 1 to 64 years. Meanwhile, we explored the relationship between microbial diversity and its functionality under grazing exclusion. Overall, grazing exclusion significantly increased microbial Shannon (1.9%) and microbial richness (4.9%) compared to grazing group. For microbial groups, GE significantly increased fungal richness (8.6%) and bacterial richness (5.3%), but decreased specific microbial richness (-11.9%). The responses of microbial Shannon to GE varied among climatic regions, grassland types, and GE duration. Specifically, GE increased microbial diversity in in arid, semi-arid, and dry sub-humid regions, but decreased it in humid regions. Moreover, GE significantly increased microbial Shannon in semidesert grasslands (5.9%) and alpine grasslands (3.0%), but not in temperate grasslands. Long-term (>20 year) GE had greater effects on microbial diversity (8.0% for Shannon and 6.7% for richness) compared to short-term (<10 year) GE (-0.8% and 2.4%). Furthermore, grazing exclusion significantly increased multifunctionality, and both microbial and plant Shannon positively correlated with multifunctionality. Overall, our findings emphasize the importance of considering climate, GE duration, and grassland type for biodiversity conservation and sustainable grassland ecosystem functions.
Journal Article
Intelligent regional subsurface prediction based on limited borehole data and interpretability stacking technique of ensemble learning
This study introduces an intelligent method for regional subsurface prediction using a Stacking ensemble learning approach, which incorporates K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), Gradient Boosted Decision Trees (GBDT), and Xgboost as base classifiers, with Logistic Regression (LR) serving as the meta-classifier. Leveraging data from 1119 boreholes in Zigong City, China, this method achieves a prediction accuracy of 93%, and notably improves the prediction of weak layers, with accuracy rates ranging from 71.4% to 81.5%. This enhancement is particularly significant in areas with a random distribution of excavation and backfill. Furthermore, this study employs the SHAP method (SHapley Additive explanations) to interpret the Stacking ensemble learning model, revealing that the outputs of the base classifiers enhance the feature set for the meta-classifier, effectively addressing the insensitivity of the spatial coordinates x, y, and z as input features for lithology prediction. The findings demonstrate that the expansion of effective feature dimensions is key to the superior performance of the Stacking ensemble learning method in regional subsurface lithology prediction.
Journal Article
Retention of high-pressure solution-processable metastable phase to ambience via differential sublattice rigidity for broadband photodetectors
Materials science exploits only properties that are available at ambience. Therefore, although high-pressure changes the physical state of all condensed matter, most of the extraordinary properties discovered vanish after decompression and cannot be utilized. Here, we demonstrate sublattice decoupling in a mixed-anion chalcohalide Rb
6
Re
6
S
8
I
8
upon compression, in which the [Rb
6
I
2
]
4+
framework is soft and plastic, while the [Re
6
S
8
I
6
]
4-
clusters are hard and elastic. This discrepancy in the rigidity allows the applied pressure to selectively amorphize the framework while maintaining the ordered state in the cluster, leading to intriguing photocurrent generation and enhancement upon compression. These high-pressure properties are retained at ambience, permitting scalable synthesis of the decompressed samples using a large-volume press, followed by further fabrication into self-powered broadband photodetectors with a response time of ~ 10
2
μs and a specific detectivity of ~ 10
11
Jones. This study subverts the stereotype that pressure engineering is hardly to be employed for device applications.
Li et al. report the sublattice decoupling in Rb
6
Re
6
S
8
I
8
upon compression, in which [Rb
6
I
2
]
4+
framework can be selectively amorphized while the [Re
6
S
8
I
6
]
4-
clusters keep in ordered state, leading to emission-to-photocurrent switching at 15 GPa, which can retain when back to ambient condition.
Journal Article
MiR-200/183 family-mediated module biomarker for gastric cancer progression: an AI-assisted bioinformatics method with experimental functional survey
Background
Gastric cancer (GC) is a major cancer burden throughout the world with a high mortality rate. The performance of current predictive and prognostic factors is still limited. Integrated analysis is required for accurate cancer progression predictive biomarker and prognostic biomarkers that help to guide therapy.
Methods
An AI-assisted bioinformatics method that combines transcriptomic data and microRNA regulations were used to identify a key miRNA-mediated network module in GC progression. To reveal the module’s function, we performed the gene expression analysis in 20 clinical samples by qRT-PCR, prognosis analysis by multi-variable Cox regression model, progression prediction by support vector machine, and in vitro studies to elaborate the roles in GC cells migration and invasion.
Results
A robust microRNA regulated network module was identified to characterize GC progression, which consisted of seven miR-200/183 family members, five mRNAs and two long non-coding RNAs H19 and CLLU1. Their expression patterns and expression correlation patterns were consistent in public dataset and our cohort. Our findings suggest a two-fold biological potential of the module: GC patients with high-risk score exhibited a poor prognosis (
p-value
< 0.05) and the model achieved AUCs of 0.90 to predict GC progression in our cohort. In vitro cellular analyses shown that the module could influence the invasion and migration of GC cells.
Conclusions
Our strategy which combines AI-assisted bioinformatics method with experimental and clinical validation suggested that the miR-200/183 family-mediated network module as a “pluripotent module”, which could be potential marker for GC progression.
Journal Article
A‐site coordinating cation engineering in zero‐dimensional antimony halide perovskites for strong self‐trapped exciton emission
Low‐dimensional hybrid halide perovskites represent a promising class of materials in optoelectronic applications because of strong broad self‐trapped exciton (STE) emissions. However, there exists a limitation in designing the ideal A‐site cation that makes the material satisfy the structure tolerance and exhibit STE emission raised by the appropriate electron–phonon coupling effect. To overcome this dilemma, we developed an inorganic metal‐organic dimethyl sulfoxide (DMSO) coordinating strategy to synthesize a series of zero‐dimensional (0D) Sb‐based halide perovskites including Na3SbBr6·DMSO6 (1), AlSbBr6·DMSO6 (2), AlSbCl6·DMSO6 (3), GaSbCl6·DMSO6 (4), Mn2Sb2Br10·DMSO13 (5) and MgSbBr5·DMSO7 (6), in which the distinctive coordinating A‐site cation [Am‐DMSO6]n+ efficiently separate the [SbXz] polyhedrons. Advantageously, these materials all exhibit broadband‐emissions with full widths at half maxima (FWHM) of 95–184 nm, and the highest photoluminescent quantum yield (PLQY) of 3 reaches 92%. Notably, compounds 2–4 are able to remain stable after storage of more than 120 d. First‐principles calculations indicate that the origin of the efficient STE emission can be attributed to the localized distortion in [SbXz] polyhedron upon optical excitation. Experimental and calculational results demonstrate that the proposed coordinating strategy provides a way to efficiently expand the variety of novel high‐performance STE emitters and continuously regulate their emission behaviors. For low‐dimensional perovskites exhibiting broad‐band emission by self‐trapped excitons (STEs), satisfying the structure tolerance while exhibiting strong emission is a roadblock. By designing a unique cation [Am‐DMSO6]n+, a series of zero‐dimensional perovskites as AmSbXz·DMSOi has been synthesized, boosting the variety of antimony‐based STE‐emitting perovskites with excellent photoluminescent properties such as high photoluminescent quantum yields and adjustable correlated color temperature range.
Journal Article