Advancements, Challenges, and Future Directions in Rainfall-Induced Landslide Prediction: A Comprehensive Review

Rainfall-induced landslides threaten lives and properties globally. To address this, researchers have developed various methods and models that forecast the likelihood and behavior of rainfall-induced landslides. These methodologies and models can be broadly classified into three categories: empirical, physical-based, and machine-learning approaches. However, these methods have limitations in terms of data availability, accuracy, and applicability. This paper reviews the current state-of-the-art of rainfall-induced landslide prediction methods, focusing on the methods, models, and challenges involved. The novelty of this study lies in its comprehensive analysis of existing prediction techniques and the identification of their limitations. By synthesizing a vast body of research, it highlights emerging trends and advancements, providing a holistic perspective on the subject matter. The analysis points out that future research opportunities lie in interdisciplinary collaborations, advanced data integration, remote sensing, climate change impact analysis, numerical modeling, real-time monitoring, and machine learning improvements. In conclusion, the prediction of rainfall-induced landslides is a complex and multifaceted challenge, and no single approach is universally superior. Integrating different methods and leveraging emerging technologies offer the best way forward for improving accuracy and reliability in landslide prediction, ultimately enhancing our ability to manage and mitigate this geohazard

Threshold level of Peptest in diagnosing gastroesophageal reflux disease with extraesophageal symptoms: Evidence from Vietnam

Abstract Background and Aim We aimed to evaluate the application of Peptest, a novel technique to detect pepsin in the saliva, and identify its threshold level for the diagnosis of gastroesophageal reflux disease (GERD) with extraesophageal symptoms. Methods A cross‐sectional study was conducted in two groups: patients with extraesophageal GERD symptoms (symptomatic group divided into GERD and non‐GERD groups according to 24‐h esophageal pH‐impedance monitoring [pH‐I] results) and healthy controls. For the symptomatic group, endoscopy, pH 24 h, high‐resolution manometry (HRM), and salivary Peptest were performed. For the healthy control group, only Peptest was done. The accuracy of Peptest was compared with that of pH‐I by the Lyon consensus criteria. Results Chronic laryngitis was the most frequent extraesophageal symptom. On saliva testing, the GERD group had a higher prevalence of positive samples and pepsin concentration than the control group. Between GERD and non‐GERD groups, the optimal threshold level was 31.2 ng/mL, with a sensitivity of 86.7% and specificity of 27.5%. The optimal threshold level was 31.4 ng/mL to differentiate GERD from healthy controls, with a sensitivity of 86.7% and specificity of 66.0%. Age, number of total refluxes, DeMeester score, post‐reflux swallow‐induced peristaltic wave (PSPW) index, and mean nocturnal baseline impedence (MNBI) were associated with pepsin concentration. Regarding HRM metrics, there was no significant difference of pepsin concentration between low/normal upper esophageal sphincter (UES) resting pressure, low/normal lower esophageal sphincter (LES) resting pressure, low/normal 4‐s integrated relaxation pressure (IRP4s), and hypomotility/normal motility. Conclusion Patients with extraesophageal symptoms had a higher prevalence of positive Peptest. The optimum threshold level of 31.4 ng/mL had high sensitivity and moderate specificity to differentiate between patients with GERD and healthy controls

New dianthramide and cinnamic ester glucosides from the roots of <i>Aconitum carmichaelii</i>

<p>Four new compounds <i>N</i>-salicyl-3-hydroxyanthranilic acid methyl ester (<b>1</b>), <i>N</i>-(2′-dehydroxysalicyl)-3-hydroxyanthranilic acid methyl ester (<b>2</b>), methyl-4-β-D-allopyranosyl-ferulate <b>(3</b>), and methyl-4-β-D-gulopyranosyl-cinnamate (<b>4</b>), along with six known compounds (<b>5</b>–<b>10</b>), were isolated from the roots of <i>Aconitum carmichelii</i> Debx. Their structures were elucidated on the basis of spectral data analysis, including 1D, 2D-NMR, and HR-ESI-MS. Compounds <b>1</b> and <b>2</b> showed the inhibition of nitric oxide (NO) production with IC₅₀ values of 9.13 and 19.94 μM, respectively.</p

New dianthramide and cinnamic ester glucosides from the roots of <i>Aconitum carmichaelii</i>

<p>Four new compounds <i>N</i>-salicyl-3-hydroxyanthranilic acid methyl ester (<b>1</b>), <i>N</i>-(2′-dehydroxysalicyl)-3-hydroxyanthranilic acid methyl ester (<b>2</b>), methyl-4-β-D-allopyranosyl-ferulate <b>(3</b>), and methyl-4-β-D-gulopyranosyl-cinnamate (<b>4</b>), along with six known compounds (<b>5</b>–<b>10</b>), were isolated from the roots of <i>Aconitum carmichelii</i> Debx. Their structures were elucidated on the basis of spectral data analysis, including 1D, 2D-NMR, and HR-ESI-MS. Compounds <b>1</b> and <b>2</b> showed the inhibition of nitric oxide (NO) production with IC₅₀ values of 9.13 and 19.94 μM, respectively.</p