DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data

Data preprocessing is a crucial step in the machine learning process that transforms raw data into a more usable format for downstream ML models. However, it can be costly and time-consuming, often requiring the expertise of domain experts. Existing automated machine learning (AutoML) frameworks claim to automate data preprocessing. However, they often use a restricted search space of data preprocessing pipelines which limits the potential performance gains, and they are often too slow as they require training the ML model multiple times. In this paper, we propose DiffPrep, a method that can automatically and efficiently search for a data preprocessing pipeline for a given tabular dataset and a differentiable ML model such that the performance of the ML model is maximized. We formalize the problem of data preprocessing pipeline search as a bi-level optimization problem. To solve this problem efficiently, we transform and relax the discrete, non-differential search space into a continuous and differentiable one, which allows us to perform the pipeline search using gradient descent with training the ML model only once. Our experiments show that DiffPrep achieves the best test accuracy on 15 out of the 18 real-world datasets evaluated and improves the model's test accuracy by up to 6.6 percentage points.Comment: Published at SIGMOD 202

TikTok video as a health education source of information on heart failure in China: a content analysis

BackgroundHeart failure (HF) is a complex and life-threatening syndrome associated with significant morbidity and mortality. While TikTok has gained popularity as a social media platform for sharing HF-related information, the quality of such content on TikTok remains unexplored.MethodsA cross-sectional analysis was conducted on TikTok videos related to HF in China. The sources of the videos were identified and analyzed. The content comprehensiveness of the videos was evaluated using six questions that covered definition, signs and symptoms, risk factors, evaluation, management, and outcomes. The reliability and quality of the videos were assessed using three standardized evaluation instruments: DISCERN, JAMA benchmarks, and the Global Quality Scale. Additionally, the correlation between video quality and video characteristics was further investigated.ResultsAmong the video sources, 92.2% were attributed to health professionals, while news agencies and non-profit organizations accounted for 5.7% and 2.1%, respectively. The content comprehensiveness score for the videos was 3.36 (SD 3.56), with news agencies receiving the highest scores of 4.06 (SD 3.31). The median DISCERN, JAMA, and GQS scores for all 141 videos were 26.50 (IQR 25.00–28.750), 2.00 (IQR 2.00–2.00), and 2.00 (IQR 2.00–2.00), respectively. Videos from health professionals had significantly higher JAMA scores compared to those from non-profit organizations (P < 0.01). Correlation analysis between video quality and video characteristics showed positive correlations between content comprehensiveness scores and video duration (r = 0.420, P < 0.001), number of comments (r = 0.195, P < 0.05), and number of shares (r = 0.174, P < 0.05). GQS scores were negatively or positively correlated with the number of days since upload (r = −0.212, P < 0.05) and video duration (r = 0.442, P < 0.001).ConclusionThe overall quality of the videos was found to be unsatisfactory, with variations in quality scores observed across different video sources. Content comprehensiveness was inadequate, the reliability and quality of the information presented in the videos was questionable. As TikTok continues to grow as a platform for health information, it is essential to prioritize accuracy and reliability to enhance patients’ self-care abilities and promote public health

High Self-Control Reduces Risk Preference: The Role of Connectivity Between Right Orbitofrontal Cortex and Right Anterior Cingulate Cortex

Risk preference, the preference for risky choices over safe alternatives, has a great impact on many fields, such as physical health, sexual safety and financial decision making. Ample behavioral research has attested that inadequate self-control can give rise to high risk preference. However, little is known about the neural substrates underlying the effect of self-control on risk preference. To address this issue, we combined voxel-based morphometry (VBM) with resting-state functional connectivity (RSFC) analyses to explore the neural basis underlying the effect of self-control on risk preference across two independent samples. In sample 1 (99 participants; 47 males; 20.37 ± 1.63 years), the behavioral results indicated that the scores of self-control were significantly and negatively correlated with risk preference (indexed by gambling rate). The VBM analyses demonstrated that the higher risk preference was correlated with smaller gray matter volumes in right orbitofrontal cortex (rOFC) and right posterior parietal cortex. In the independent sample 2 (80 participants; 33 males; 20.33 ± 1.83 years), the RSFC analyses ascertained that the functional connectivity of rOFC and right anterior cingulate cortex (rACC) was positively associated with risk preference. Furthermore, the mediation analysis identified that self-control mediated the impact of functional connectivity of rOFC-rACC on risk preference. These findings suggest the functional coupling between the rOFC and rACC might account for the association between self-control and risk preference. The present study extends our understanding on the relationship between self-control and risk preference, and reveals possible neural underpinnings underlying this association

The triple psychological and neural bases underlying procrastination: Evidence based on a two-year longitudinal study

The triple brain anatomical network model of procrastination theorized procrastination as the result of psychological and neural dysfunction implicated in self-control, emotion regulation and episodic prospection. However, no studies have provided empirical evidence for such model. To address this issue, we designed a two-wave longitudinal study where participants underwent the resting-state scanning and completed the questionnaires at two time-points that spanned 2-year apart (T1, n = 457; T2, n = 457). Using the cross-lagged panel network modeling (CLPN), we found that triple psychological components at T1, including self-control, emotion regulation (i.e., reappraisal) and episodic prospection, negatively predicted procrastination at T2 in the temporal network. Moreover, the CLPN modeling found that functional connectivity between networks accounting for episodic prospection (EP) and emotion regulation (ER) positively predicted future procrastination in the temporal network. The centrality analyzes further showed that procrastination was greatly affected by other nodes, whilst the psychological component (i.e., episodic prospection), and the functional network connectivity (FNC) of EP- ER exerted strongest impacts on other nodes in the networks, which indicated that treatments targeting episodic prospection might largely help reduce procrastination. Collectively, these findings firstly provide evidence for testifying the triple brain anatomical network model of procrastination, and highlights the contribution of triple psychological and neural components implicated in self-control, emotion regulation and episodic prospection to procrastination that enhances our understanding of causes of procrastination

Table_1_TikTok video as a health education source of information on heart failure in China: a content analysis.DOCX

BackgroundHeart failure (HF) is a complex and life-threatening syndrome associated with significant morbidity and mortality. While TikTok has gained popularity as a social media platform for sharing HF-related information, the quality of such content on TikTok remains unexplored.MethodsA cross-sectional analysis was conducted on TikTok videos related to HF in China. The sources of the videos were identified and analyzed. The content comprehensiveness of the videos was evaluated using six questions that covered definition, signs and symptoms, risk factors, evaluation, management, and outcomes. The reliability and quality of the videos were assessed using three standardized evaluation instruments: DISCERN, JAMA benchmarks, and the Global Quality Scale. Additionally, the correlation between video quality and video characteristics was further investigated.ResultsAmong the video sources, 92.2% were attributed to health professionals, while news agencies and non-profit organizations accounted for 5.7% and 2.1%, respectively. The content comprehensiveness score for the videos was 3.36 (SD 3.56), with news agencies receiving the highest scores of 4.06 (SD 3.31). The median DISCERN, JAMA, and GQS scores for all 141 videos were 26.50 (IQR 25.00–28.750), 2.00 (IQR 2.00–2.00), and 2.00 (IQR 2.00–2.00), respectively. Videos from health professionals had significantly higher JAMA scores compared to those from non-profit organizations (P ConclusionThe overall quality of the videos was found to be unsatisfactory, with variations in quality scores observed across different video sources. Content comprehensiveness was inadequate, the reliability and quality of the information presented in the videos was questionable. As TikTok continues to grow as a platform for health information, it is essential to prioritize accuracy and reliability to enhance patients’ self-care abilities and promote public health.</p

A Pyridazine-Containing Phthalonitrile Resin for Heat-Resistant and Flame-Retardant Polymer Materials

In this study, a novel phthalonitrile monomer containing a pyridazine ring, 3,6-bis[3-(3,4-dicyanophenoxy)phenoxy]pyridazine (BCPD) with a low melting point (74 °C) and wide processing window (178 °C), was prepared by a nucleophilic substitution reaction. The molecular structure of the BCPD monomer was identified by Fourier transform infrared spectroscopy (FTIR), and nuclear magnetic resonance spectroscopy (NMR). Poly(BCPD) resins were derived from the formulations by curing at 350 and 370 °C. The thermoset that was post-cured at 370 °C demonstrated outstanding high heat-resistant (glass transition temperature (Tg) > 400 °C, 5% weight loss temperature (T5%) = 501 °C, Yc at 900 °C > 74%) and was flame-retardant (limiting oxygen index (LOI) = 48)). Further, the poly(BCPD) resin simultaneously exhibited a superior storage modulus, which could reach up to 3.8 Gpa at room temperature. Excellent processability and heat resistance were found for phthalonitrile thermosets containing the pyridazine ring, indicating poly(BCPD) resin could be potentially applied as high-temperature structural composite matrices

Strengthening and ductilization of laminate dual-phase steels with high martensite content

The steels with excellent strength and ductility are expected to be achieved by tailoring the microstructural features. In this work, laminate dual-phase (DP) steels with high martensite content (laminate HMDP steels) were produced by a combination of warm rolling and intercritical annealing. Influence of rolling strain and annealing temperature on the microstructural evolution and mechanical properties of laminate HMDP steels were systematically studied. The strength of HMDP steels was significantly improved to similar to 1.6 GPa associated with a high uniform elongation of 7%, as long as the laminate structure is maintained. The strengthening and ductilizing mechanisms of laminate HMDP steels are discussed based on the influence of laminate structure and the high martensite content, which promote the development of internal stresses and can be correlated to the Bauschinger effect as measured by the cyclic loading-unloading-reloading experiments. Detailed transmission electron microscopy (TEM) observation was applied to characterize the dislocation structure in the deformed ferrite. (C) 2021 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology