What To Do (and Not to Do) with Causal Panel Analysis under Parallel Trends: Lessons from A Large Reanalysis Study

Two-way fixed effects (TWFE) models are ubiquitous in causal panel analysis in political science. However, recent methodological discussions challenge their validity in the presence of heterogeneous treatment effects (HTE) and violations of the parallel trends assumption (PTA). This burgeoning literature has introduced multiple estimators and diagnostics, leading to confusion among empirical researchers on two fronts: the reliability of existing results based on TWFE models and the current best practices. To address these concerns, we examined, replicated, and reanalyzed 37 articles from three leading political science journals that employed observational panel data with binary treatments. Using six newly introduced HTE-robust estimators, we find that although precision may be affected, the core conclusions derived from TWFE estimates largely remain unchanged. PTA violations and insufficient statistical power, however, continue to be significant obstacles to credible inferences. Based on these findings, we offer recommendations for improving practice in empirical research

The abundance of homoeologue transcripts is disrupted by hybridization and is partially restored by genome doubling in synthetic hexaploid wheat

Dataset S7. List of nonadditively expressed genes in F1 hybrids derived from AS2255 × AS60. (XLSX 72 kb

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Large scale preparation of surface enhanced Raman spectroscopy substrates based on silver nanowires for trace chemical detection

In this paper, a facile large-scale preparation of surface enhanced Raman spectroscopy (SERS) substrates based on silver nanowires has been developed. The SERS substrates can be easily and precisely obtained by filtering bulky amounts of silver nanostructures through hydrophilic filter membranes one time. The developed membranes can be expanded to commercial wafer-style filter membranes of large size (>47 mm in diameter). The as-prepared SERS substrates presented good uniformity and good performance for the detection of crystal violet (CV) and 1,2-di(4-pyridyl)ethylene (BPE). The relative standard deviations (RSD) were less than 5.5% (n = 11) and 5.2% (n = 11) for CV and BPE, respectively. The logarithm of characteristic SERS intensity plotted against CV and BPE concentrations presented a linear relationship over the ranges from 1.0 x 10(-4) to 1.0 x 10(-8) mol L-1 and from 5.0 x 10(-4) to 5.0 x 10(-9) mol L-1, respectively. In the detection of natural water samples of river water, Membrane Bio-Reactor (MBR) effluent and sewage disposal plant effluent, spiked with CV and BPE, the as-prepared SERS substrates also presented good performance, suggesting that such substrates possessed great potential in a broad range of analytical applications

Revealing the apparent and local mechanical properties of heterogeneous lattice: a multi-scale study of functionally graded scaffold

Functionally graded scaffold (FGS) can flexibly regulate the mechanical properties of bone scaffold and holds great promise for offering multifunctional responses of orthopaedic implants. Heterogeneous FGSs constructed by skeletal and sheet triply periodic minimal surfaces (TPMSs) have been proposed in this study. The diversified deformation mechanisms of TPMS-FGSs showed superior mechanical stability, and energy absorption efficiency was enhanced by 3.0–79.0% and 2.6–16.8% compared to uniform skeletal and sheet TPMS, respectively. The graded structure of TPMS-FGSs altered the large-scale 45° shear failure to layer-wise or zigzag failure mode. Moreover, the comprehensive reformation of strain distribution and crack propagation in transition region under small compressive strain was experimentally and numerically studied. The results shed light on the global and local mechanical regulation mechanism of TPMS-FGS

A 2.5-GS/s Four-Way-Interleaved Ringamp-Based Pipelined-SAR ADC with Digital Background Calibration in 28-nm CMOS

A 2.5-GS/s 12-bit four-way time-interleaved pipelined-SAR ADC is presented in 28-nm CMOS. A bias-enhanced ring amplifier is utilized as the residue amplifier to achieve high bandwidth and excellent power efficiency compared with a traditional operational amplifier. A high linearity front-end is proposed to alleviate the non-linearity of the diode for ESD protection in the input PAD. The embedded input buffer can suppress the kickback noise at high input frequencies. A blind background calibration based on digital-mixing is used to correct the mismatches between channels. Additionally, an optional neural network calibration is also provided. The prototype ADC achieves a low-frequency SNDR/SFDR of 51.0/68.0 dB, translating a competitive FoMw of 0.48 pJ/conv.-step at 250 MHz input running at 2.5 GS/s

Changes and significance of α kinase 1 expression in cartilage tisssueof patients with knee osteoarthritis

Objective: To investigate the expression changes and significance of α kinase 1 （ALPK1）, a member of the α kinase family, in cartilage tissue of knee osteoarthritis (OA). Methods: Twenty-five patients who underwent knee OA surgery in Pizhou Hospital affiliated to Xuzhou Medical University from July 2018 to October 2022 were retrospectively selected, and cartilage tissue samples of the patients’ knee joints were collected. In addition, the tibial plateau cartilage of 10 patients who underwent lower limb amputation due to trauma in the biological sample of the hospital was selected as the control. Immunohistochemical (IHC) staining, Western blotting and real-time quantitative PCR （RT-qPCR） were used to detect the expression of ALPK1 in cartilage. Results: The results of IHC staining, Western blotting and RT-qPCR showed that compared with the control group, the mRNA expression level of ALPK1 （2.126±0.930 vs 0.995±0.049, t=4.112, P＜0.01）, protein expression level （1.880±0.722 vs 1.025±0.062, t=3.706, P＜0.01） and IHC-positive cell rate （P＜0.01） in the cartilage of knee OA patients were significantly increased. Conclusion: The high expression of ALPK1 in cartilage of patients with kee OA may be one of the reasons for the increase of inflammation and destruction of articular cartilage. ALPK1 is expected to be a diagnostic marker and therapeutic target of kee OA