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Bi2Te3-based compounds are currently the most commercially relevant thermoelectric materials near room temperature. They are prepared via hot pressing, hot deformation, spark plasma sintering, and other consolidation processes, which are typically performed at 400–500 °C. Such high-temperature processes are energy-intensive and generate unnecessary waste heat, making them undesirable for a large-scale production. In this study, a low-temperature liquid-phase-assisted sintering (or so-called cold-sintering) process was employed to fabricate p-type Bi0.5Sb1.5Te3 bulk materials at temperatures below 150 °C. At the optimal sintering temperature (130 °C), a ZT value as high as 0.56 at 450 K can be achieved, competitive to that of a commercial Bi0.5Sb1.5Te3 ingot (ZT 0.8–1.0). The addition of a small amount of transient liquid facilitates grain reorientation and expedites a mass transfer process under axial compaction and liquid evaporation conditions, thus resulting in nearly fully densified Bi0.5Sb1.5Te3 pellet samples (>97% theoretical density). Furthermore, the low-temperature sintering process results in the reduction of grain size and promotes twin boundaries, resulting in a low lattice thermal conductivity of 0.57 W m–1 K–1 at 380 K due to phonon scattering. The strategy reported in this work can be used not only as a substitute for high-temperature sintering of other thermoelectric materials but also to engineer phonon scattering for high-performance thermoelectrics.

Couple-based interventions may be an adjunctive method for cancer patients and their spouses to improve HRQoL. Further study concerning couple-based skill training and blending intervention are needed to better understand intervention effects.

Aberrant HOXA9 expression is a hallmark of most aggressive acute leukemias, including human acute myeloid leukemia (AML) and subtypes of acute lymphoblastic leukemia (ALL). HOXA9 overexpression not only predicts poor diagnosis and outcome but also plays a critical role in leukemia transformation and maintenance. However, our current understanding of HOXA9 regulation in leukemia is limited, hindering development of therapeutic strategies to treat HOXA9-driven leukemia. To mitigate these challenges, we generated the first HOXA9-mCherry knock-in reporter in an MLL-rearranged (MLLr) B-ALL cell line to dissect HOXA9 regulation. By utilizing the reporter and CRISPR/Cas9 mediated screens, we identified transcription factors controlling HOXA9 expression, including a novel regulator, USF2 and its homolog USF1. USF1/USF2 depletion significantly down-regulated HOXA9 expression and impaired MLLr leukemia cell proliferation. Ectopic expression of HOXA9-MEIS1 fusion protein rescued the impaired leukemia cell proliferation upon USF2 loss. Cut&Run analysis revealed the direct occupancy of USF2 onto HOXA9 promoter in MLLr leukemia cells. Collectively, the HOXA9 reporter facilitated the functional interrogation of the HOXA9 regulome and has advanced our understanding of the molecular regulation network in HOXA9-driven leukemia.

ive document summarization is a comprehensive task including document understanding and summary generation, in which area Transformer-based models have achieved the state-of-the-art performance. Compared with Transformers, topic models are better at learning explicit document semantics, and hence could be integrated into Transformers to further boost their performance. To this end, we rearrange and explore the semantics learned by a topic model, and then propose a topic assistant (TA) including three modules. TA is compatible with various Transformerbased models and user-friendly since i) TA is a plug-and-play model that does not break any structure of the original Transformer network, making users easily fine-tune Transformer+TA based on a well pre-trained model; ii) TA only introduces a small number of extra parameters. Experimental results on three datasets demonstrate that TA is able to improve the performance of several Transformer-based models.

BACKGROUND: In this study, we aimed to validate the agreement between pulmonary function measurements obtained with a portable spirometer and measurements obtained with conventional spirometry in Chinese pediatric and adult populations. METHODS: Pulmonary function testing was performed to evaluate subjects enrolled at Shanghai Zhongshan Hospital (n 5 104) and Shanghai Children's Medical Center (n 5 103). The portable spirometers and conventional devices were applied to each subject with a 20-min quiescent period between each measurement. Pulmonary function parameters of FVC, FEV 1 , peak expiratory flow, maximum expiratory flow at 25%, 50%, and 75% of FVC (MEF 25 , MEF 50 , and MEF 75 , respectively), and FEV 1 /FVC% were compared with intraclass correlation and Bland-Altman methods. RESULTS: A satisfactory concordance of pulmonary function was observed between spirometry measurements obtained with portable versus conventional spirometers. Intraclass correlation indicated excellent reliability (>0.75) for all pulmonary function indicators in pediatric and adult subjects. Significant positive correlations of all variables measured with different spirometers were observed (all P < .001). No significant bias was observed in either group, although limits of agreement varied. Funnel effects were observed for peak expiratory flow in pediatric subjects and for FVC, FEV 1 , MEF 50 , and MEF 25 in adult subjects. CONCLUSIONS: The portable spirometer is an alternative to the conventional device for the measurement of pulmonary function.

We present Semantic WordRank (SWR), an unsupervised method for generating an extractive summary of a single document. Built on a weighted word graph with semantic and co-occurrence edges, SWR scores sentences using an article-structure-biased PageRank algorithm with a Softplus function adjustment, and promotes topic diversity using spectral subtopic clustering under the Word-Movers-Distance metric. We evaluate SWR on the DUC-02 and SummBank datasets and show that SWR produces better summaries than the state-of-the-art algorithms over DUC-02 under common ROUGE measures. We then show that, under the same measures over SummBank, SWR outperforms each of the three human annotators (aka. judges) and compares favorably with the combined performance of all judges.