Illuminating innovations: leveraging the optoelectronic capabilities of carbon dots for advanced displays, sensors, and renewable energy solutions [0.03%]
发光新发明：利用碳点的光电性能用于高级显示、传感器和可再生能源解决方案
Azkah Shehzadi,Tanzeela Fazal,Mazloom Shah et al.
Azkah Shehzadi et al.
Carbon dots (CDs) are a fascinating area of research. Carbon nanodots (CDs), also known as carbon quantum dots (CQDs), carbon nanodots (CNDs), and graphene quantum dots (GQDs), have garnered increasing attention in recent times due to their...
Improved visible photocatalytic CO oxidation of CoTiO3 nanotubes by surface engineering and Au nanoparticle loading [0.03%]
通过表面工程和Au纳米粒子负载提高CoTiO3纳米管的可见光催化CO氧化性能
Zhanyu Chu,Tianwei Dou,Zhuo Li et al.
Zhanyu Chu et al.
The tubular structure photocatalyst, known for its excellent light absorption and mass diffusion properties, represents an attractive class of photocatalytic materials for the removal of toxic gaseous pollutants. However, the availability o...
Detection of drugs of abuse: evolving analytical strategies and emerging challenges [0.03%]
药物滥用检测：日益发展的分析策略及新兴挑战
Nagwa Eliw,Manal A Alhefeiti,Ahmed A Shamroukh et al.
Nagwa Eliw et al.
The detection of drugs of abuse in biological and non-biological matrices remains a cornerstone of forensic, clinical, and public health investigations. Traditional matrices such as urine and blood provide short-term evidence of drug intake...
Utilization of machine learning models and grey wolf optimization method in estimation of pharmaceutical solubility in supercritical CO2 [0.03%]
机器学习模型和灰狼优化方法在制药溶解度估计中的应用：超临界CO2中的溶剂化作用
Nidal H Abu-Hamdeh,Abdulmalik A Aljinaidi,Ahmed B Khoshaim
Nidal H Abu-Hamdeh
Accurate prediction of solubility and solvent density in supercritical fluids is essential for the efficient design and optimization of pharmaceutical and chemical processes. In this study, three machine learning regression models-Elastic N...
Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production [0.03%]
机器学习在水分解电催化剂设计中的应用：绿色制氢技术综述
Vamsi Krishna Kudapa,Shoaib Mohd,Vijayakumar Sivasundar et al.
Vamsi Krishna Kudapa et al.
The production of green hydrogen through water splitting requires highly efficient electrocatalysts, but the current trial-and-error-based synthesis or discovery is time-consuming, costly and resource-intensive. Machine learning (ML) provid...
Identification and quantification of putative active constituents of huangqin decoction for ulcerative colitis treatment through the integration of chemical profiling, network pharmacology, and bioinformatics [0.03%]
基于化学谱图、网络药理学和生物信息学的黄芩汤治疗溃疡性结肠炎潜在活性成分的鉴定与量化研究
Seol Jang,Yu Jin Kim,Youn-Hwan Hwang
Seol Jang
Introduction: Huangqin decoction (HQD), a traditional Chinese medicine prescription, is used to treat gastrointestinal diseases, including ulcerative colitis (UC). However, systematic research on the components of HQD rem...
Recent advances in ultrasound microbubble-mediated gold-based nanomaterials for cancer theranostics [0.03%]
用于癌症诊疗的超声微泡介导的金基纳米材料最新研究进展
Xinyi Ma,Xiaobing Chen,He Li et al.
Xinyi Ma et al.
In the realm of oncology, precision cancer diagnosis and treatment is a current research emphasis and development trend. Its main objective is to accomplish closed-loop management of "early diagnosis - precise treatment - real-time monitori...
Progress on novel compounds for the treatment of bone metabolism-related disorders: focus on osteoporosis and beyond [0.03%]
骨代谢紊乱疾病治疗药物研发进展：以骨质疏松症为例
Yeqiong Song,Ruixing Zhang,Xinyue Zhang et al.
Yeqiong Song et al.
Bone metabolism-related disorders represent a significant global health burden, due to their high prevalence and substantial socioeconomic costs, particularly osteoporosis. Conventional antiresorptive and anabolic agents have well-establish...
Machine learning-driven identification of key chemical determinants of tobacco leaf sensory irritation [0.03%]
基于机器学习的烟草叶片感官刺激关键化学指标识别模型研究
Wenting Li,Xuehui Sun,Zhe Jin et al.
Wenting Li et al.
Introduction: To identify the key chemical components affecting the sensory irritation of tobacco leaves, a binary classification model for high and low irritation was constructed based on 78 chemical components and senso...
Machine learning-driven identification of key chemical determinants of tobacco leaf sensory irritation [0.03%]
基于机器学习的烟草叶片感官刺激关键化学指标识别
Wenting Li,Xuehui Sun,Zhe Jin et al.
Wenting Li et al.
Introduction: To identify the key chemical components affecting the sensory irritation of tobacco leaves, a binary classification model for high and low irritation was constructed based on 78 chemical components and senso...