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The establishment of the Free Trade (Pilot) Zone (FTZ) is a new attempt by China to embark on modern sustainable urban planning and governmental territorial management at the development stage of a high-quality economy. As urban lands serve as the limited resource foundation for civic production and livelihoods, enhancing land use efficiency becomes a key measure to facilitate metropolitan economies of high quality. Utilizing panel data from prefecture-level cities spanning from 2005 to 2021, this study constructs a multi-period difference-in-differences model to explore the impact of FTZs on urban land use efficiency (ULUE). The results indicate that FTZs can significantly enhance urban land use efficiency, with a more pronounced policy effect observed in central cities, inland cities, and cities with higher urbanization rates. Furthermore, the FTZs also demonstrate spatial spillover effects on urban land use efficiency. This study holds great significance for relevant government departments in formulating policies to optimize land resource allocation, promote FTZ development, and foster high-quality urban planning and territorial management. [ABSTRACT FROM AUTHOR]

Background: Macrotrabecular‐massive hepatocellular carcinoma (MTM‐HCC) is highly aggressive. Comparing the diagnosis ability of CT and gadoxetate disodium (Gd‐EOB‐DTPA) MRI for MTM‐HCC are lacking. Purpose: To compare the performance of Gd‐EOB‐DTPA MRI and CT for differentiating MTM‐HCC from non‐MTM‐HCC, and determine the prognostic indicator. Study Type: Retrospective. Subjects: Post‐surgery HCC patients, divided into the training (N = 272) and external validation (N = 44) cohorts. Field Strength/Sequence: 3.0 T, T1‐weighted imaging, in‐opp phase, and T1‐weighted volumetric interpolated breath‐hold examination/liver acquisition with volume acceleration; enhanced CT. Assessment: Three radiologists evaluated clinical characteristics (sex, age, liver disease, liver function, blood routine, alpha‐fetoprotein [AFP] and prothrombin time international normalization ratio [PT‐INR]) and imaging features (tumor length, intratumor fat, hemorrhage, arterial phase peritumoral enhancement, intratumor necrosis or ischemia, capsule, and peritumoral hepatobiliary phase [HBP] hypointensity). Compared the performance of CT and MRI for diagnosing MTM‐HCC. Follow‐up occurred every 3–6 months, and nomogram demonstrated the probability of MTM‐HCC. Statistical Tests: Fisher test, t‐test or Wilcoxon rank‐sum test, area under the curve (AUC), 95% confidence interval (CI), multivariable logistic regression, Kaplan–Meier curve, and Cox proportional hazards. Significance level: P < 0.05. Results: Gd‐EOB‐DTPA MRI (AUC: 0.793; 95% CI, 0.740–0.839) outperformed CT (AUC: 0.747; 95% CI, 0.691–0.797) in the training cohort. The nomogram, incorporating AFP, PT‐INR, and MRI features (non‐intratumor fat, incomplete capsule, intratumor necrosis or ischemia, and peritumoral HBP hypointensity) demonstrated powerful performance for diagnosing MTM‐HCC with an AUC of 0.826 (95% CI, 0.631–1.000) in the external validation cohort. Median follow‐up was 347 days (interquartile range [IQR], 606 days) for the training cohort and 222 days (IQR, 441 days) for external validation cohort. Intratumor necrosis or ischemia was an independent indicator for poor prognosis. Data Conclusion: Gd‐EOB‐DTPA MRI might assist in preoperative diagnosis of MTM‐HCC, and intratumor necrosis or ischemia was associated with poor prognosis. Evidence Level: 4 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Trunk borers are among the most destructive forest pests. The larvae of some species living and feeding in the trunk, relying solely on the tree's appearance to judge infestation is challenging. Currently, one of the most effective methods to detect the larvae of some trunk-boring beetles is by analyzing the vibration signals generated by the larvae while they feed inside the tree trunk. However, this method faces a problem: the field environment is filled with various noises that get collected alongside the vibration signals, thus affecting the accuracy of pest detection. To address this issue, vibration signal enhancement is necessary. Moreover, deploying sophisticated technology in the wild is restricted due to limited hardware resources. In this study, a lightweight vibration signal enhancement was developed using EAB (Emerald Ash Borer) and SCM (Small Carpenter Moth) as insect example. Our model combines CRN (Convolutional Recurrent Network) and Transformer. We use a multi-head mechanism instead of RNN (Recurrent Neural Network) for intra-block processing and retain inter-block RNN. Furthermore, we utilize a dynamic pruning algorithm based on sparsity to further compress the model. As a result, our model achieves excellent enhancement with just 0.34M parameters. We significantly improve the accuracy rate by utilizing the vibration signals enhanced by our model for pest detection. Our results demonstrate that our method achieves superior enhancement performance using fewer computing and storage resources, facilitating more effective use of vibration signals for pest detection. [ABSTRACT FROM AUTHOR]