Precise Measurement of the e^{+}e^{-}→D_{s}^{+}D_{s}^{-} Cross Section at Center-of-Mass Energies from Threshold to 4.95 GeV.

Using the e^{+}e^{-} collision data collected with the BESIII detector operating at the BEPCII collider, at center-of-mass energies from the threshold to 4.95 GeV, we present precise measurements of the cross section for the process e^{+}e^{-}→D_{s}^{+}D_{s}^{-} using a single-tag method. The resulting cross section line shape exhibits several new structures, thereby offering an input for a future coupled-channel analysis and model tests, which are critical to understand vector charmonium-like states with masses between 4 and 5 GeV.

Machine learning prediction of hepatic encephalopathy for long-term survival after transjugular intrahepatic portosystemic shunt in acute variceal bleeding.

Background: Transjugular intrahepatic portosystemic shunt (TIPS) is an effective intervention for managing complications of portal hypertension, particularly acute variceal bleeding (AVB). While effective in reducing portal pressure and preventing rebleeding, TIPS is associated with a considerable risk of overt hepatic encephalopathy (OHE), a complication that significantly elevates mortality rates.

Aim: To develop a machine learning (ML) model to predict OHE occurrence post-TIPS in patients with AVB using a 5-year dataset.

A novel MADM model integrating hybrid information for evaluating the development prospects of urban new energy vehicles.

As an effective approach to mitigating urban environmental issues, New Energy Vehicles (NEVs) have become a focal point of research regarding their current development status and future prospects in China. Addressing the significant disparities in the development of the NEVs industry across different cities, this study focuses on ten typical Chinese cities and develops a novel multi-attribute decision-making (MADM) framework to evaluate the prospects of NEVs promotion in these cities. The study first establishes a comprehensive indicator system that covers key dimensions such as economy, policy support, infrastructure, technological innovation, and environment, encompassing five different types of evaluation information.

Constructing an Organic-Inorganic Hybrid Solid-Electrolyte Interface In Situ via an Organo-Polysulfide Electrolyte Additive for Lithium-Sulfur Batteries.

Lithium (Li) metal's extremely high specific energy and low potential make it critical for high-performance batteries. However, uncontrolled dendrite growth and an unstable solid-electrolyte interphase (SEI) during repeated cycling still seriously hinder its practical application in Li metal batteries. Herein, we demonstrate a facile and effective approach to fabricate a flexible and robust hybrid SEI layer using two kinds of organo-polysulfides with different sulfur chain lengths [bis(3-(triethoxysilyl)propyl)disulfide (Si-O-2S) and bis(3-(triethoxysilyl)propyl)tetrasulfide (Si-O-4S)] as the additives in the electrolyte.