Publications by authors named "Tian Tan"

The lack of low temperature processable, high-performance p-type oxide thin-film transistors (TFTs) limits their implementation in monolithically integrated back-end-of-line (BEOL) CMOS circuitries. In this work, we demonstrate a reactive magnetron-sputtered SnO TFT with unprecedented hole field-effect mobility (μ) of 38.7 cm/V·s, as well as an on/off current ratio () of 2.

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Step width is vital for gait stability, postural balance control, and fall risk reduction. However, estimating step width typically requires either fixed cameras or a full kinematic body suit of wearable inertial measurement units (IMUs), both of which are often too expensive and time-consuming for clinical application. We thus propose a novel data-augmented deep learning model for estimating step width in individuals with and without neurodegenerative disease using a minimal set of wearable IMUs.

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Background: Pianists often suffered from postural related problems due to prolonged sitting and awkward postures. Despite that postural related problems are common among pianists, there is only one study found by the authors, which applied RULA to assess pianists' postures, without any modification to the original RULA worksheet. None of the other existing literature has applied this postural assessment tool to assess the pianists' overall posture.

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Chinese farmers, especially small ones, always sell their food at low prices during harvest season rather than storing it for a better price. Based on a theoretical framework of expected utility, this paper examines the mechanism by which risk perception affects farmers' timing choices of food sales and the role played by risk preference, utilizing data from the 2019 China Family Database and the China Household Finance Survey of farmers in six provinces of the main wheat-producing regions. This study shows that farmers with a high risk perception are more likely to choose current sales compared with intertemporal sales.

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Friedel-Crafts acylation is usually promoted by Lewis acids or Brønsted acids. In this work, a novel acylation of arenes with a highly electrophilic acylphosphonium salt was developed. The alkylation of the phosphorus atom in acylphosphines generated a neutral trivalent phosphine as a good leaving group and triggered the high electrophilicity of the acylphosphonium salt.

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Accurate prediction of drug-target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual interactions between protein binding sites and key drug substructures. To address these challenges, we propose a MSFFDTA (Multi-scale feature fusion for predicting drug target affinity) model, in which multi-scale encoders effectively capture multi-level structural information of drugs and proteins are designed.

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Piezoelectric atomization is becoming mainstream in the field of inhalation therapy due to its significant advantages. With the rapid development of high-viscosity gene therapy drugs, the demand for piezoelectric atomization devices is increasing. However, conventional piezoelectric atomizers with a single-dimensional energy supply are unable to provide the energy required to atomize high-viscosity liquids.

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Urolithin families are gut-microbial metabolites of ellagic acid (EA). Although urolithin A (UA) and urolithin B (UB) were reported to have antiproliferative activities in cancer cells, the role and related mechanisms of urolithin C (UC) in colorectal cancer (CRC) have not yet been clarified. In this study, we assess the antitumor activities of UC in vitro and in vivo and further explore the underlying mechanisms in CRC cell lines.

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In contemporary autonomous driving systems relying on sensor fusion, traditional digital processors encounter challenges associated with analogue-to-digital conversion and iterative vector-matrix operations, which are encumbered by limitations in terms of response time and energy consumption. In this study, we present an analogue Kalman filter circuit based on molybdenum disulfide (MoS) memtransistor, designed to accelerate sensor fusion for precise localization in autonomous vehicle applications. The nonvolatile memory characteristics of the memtransistor allow for the storage of a fixed Kalman gain, which eliminates the data convergence and thus accelerates the processing speeds.

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Detection of leaks of flammable methane (CH) gas in a timely manner can mitigate health, safety, and environmental risks. Zinc oxide (ZnO), a polar semiconductor with controllable surface defects, is a promising material for gas sensing. In this study, Ag-Ru co-doped into self-assembled ZnO nanorod arrays (ZnO NRs) was prepared by a one-step hydrothermal method.

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Background: Many studies have investigated the efficacy of acupuncture in treating depression, but the mechanism of acupuncture for depression is still controversial and there is a lack of meta-analysis of mechanisms. Consequently, we investigated acupuncture's efficacy and mechanism of depression.

Methods: We searched the Cochrane Library, PubMed, EMBASE, Web of Science.

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Falls represent a significant cause of injury among the elderly population. Extensive research has been devoted to the utilization of wearable IMU sensors in conjunction with machine learning techniques for fall detection. To address the challenge of acquiring costly training data, this paper presents a novel method that generates a substantial volume of synthetic IMU data with minimal actual fall experiments.

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The escalating incidence of kidney biopsies providing insufficient tissue for diagnosis poses a dual challenge, straining the healthcare system and jeopardizing patients who may require rebiopsy or face the prospect of an inaccurate diagnosis due to an unsampled disease. Here, we introduce a web-based tool that can provide real-time, quantitative assessment of kidney biopsy adequacy directly from photographs taken with a smartphone camera. The software tool was developed using a deep learning-driven automated segmentation technique, trained on a dataset comprising nephropathologist-confirmed annotations of the kidney cortex on digital biopsy images.

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Through facilitating DNA homologous recombination repair, PPIP5K2 has been proven to be essential for improving colorectal cancer survival in our previous research. However, its function in the tumorigenesis of NSCLC, the most common cancer and the primary cause of cancer-related death globally, is still unknown. Here, we initially discovered that PPIP5K2 had significant effects on proliferation of NSCLC cells through loss- and gain-of-function assays in vitro and in vivo.

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Article Synopsis
  • Recent deep learning techniques can enhance kinetic assessments using IMU data, but they usually need a lot of labeled ground reaction force (GRF) data, which is often scarce.
  • The researchers propose using self-supervised learning (SSL) to pre-train deep learning models with large IMU datasets, improving GRF estimation accuracy and making better use of available data.
  • The study shows that SSL pre-training can significantly boost GRF estimation accuracy with minimal labeled data, suggesting that it can make IMU-driven assessments more practical and accessible.*
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Article Synopsis
  • Recent advancements in deep learning techniques can enhance IMU-driven kinetic assessment but require substantial amounts of ground reaction force (GRF) data for training; self-supervised learning (SSL) can help utilize large IMU datasets for pre-training models, improving accuracy and data efficiency in GRF estimation.* -
  • The study involved masking parts of IMU data and training a transformer model to predict the masked sections, comparing various masking ratios across different datasets (real, synthetic, and combined) to optimize performance.* -
  • Results showed that SSL pre-training significantly increased the accuracy of GRF estimation during walking tasks, allowing models to achieve similar accuracy with much less labeled data, and suggesting an optimal masking ratio of 6.25-
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Background: More than half of cancer patients develop severe chemotherapy-induced peripheral neuropathy (CIPN), resulting in low quality of life, negative effects on function, and challenges in treatment compliance. Most recent studies have shown that exercise therapy has a positive impact on reducing CIPN symptoms and can also improve quality of life, balance, and activity levels. The aim of this meta-analysis was to evaluate the effect of exercise therapy on the efficacy of CIPN.

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Piezoelectric pumps play an important role in modern medical technology. To improve the flow rate of valveless piezoelectric pumps with flow tube structures and promote the miniaturization and integration of their designs, a cardioid flow tube valveless piezoelectric pump (CFTVPP) is proposed in this study. The symmetric dual-bend tube design of CFTVPP holds great potential in applications such as fluid mixing and heat dissipation systems.

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Mercury ions (Hg) primarily target mitochondria in the cells. Therefore, the development of novel probes that specifically target mitochondria in the presence of Hg is of immense importance. Most previously reported probes that utilize the softness of S, Te, O, and/or N atoms for Hg binding often face problems such as fluorescence quenching and off-target signals.

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