<strong>Introduction:</strong> Tonsillectomy is described as one of the oldest surgical procedures according to the authors of the surgical treatise (Aulus Amida and Paul of Aegina in the 6th and 7th centu...<strong>Introduction:</strong> Tonsillectomy is described as one of the oldest surgical procedures according to the authors of the surgical treatise (Aulus Amida and Paul of Aegina in the 6th and 7th centuries) found in the Vatican library. The contraindication of codeine in children has changed the management of post tonsillectomy pain. The aim of this study was to assess the management of post tonsillectomy pain in our developing country context. <strong>Methods:</strong> This was a prospective, analytical study lasting 6 months (September 2019-February 2020), carried out in the ENT/CFS department of the Ignace Deen National Hospital. We included in this study all patients who underwent a tonsillectomy in the department during the study period and who agreed to participate in the survey. <strong>Results:</strong> 34 patients were included in our study, i.e. a frequency of 25% of surgical interventions. The mean age of our patients was 18.06 ± 12 years with extremes of 03 years and 45 years. Recurrent hypertrophic tonsillitis with sleep disturbances was the most frequent indication for surgery in our study, at 47.06% (n = 16). We performed an isolated tonsillectomy in 52.9% (n = 18) of cases. Analgesia was multimodal using the WHO Step I and II analgesics in 44.1% (n = 15) and 55.9% (n = 19), respectively. Pain control was satisfactory in all patients. <strong>Conclusion:</strong> The evaluation of post tonsillectomy pain is essential for optimal management. In this indication, multimodal analgesia, involving several levels I and II analgesics, provided satisfactory pain control.展开更多
面向无人机智能巡检的桥梁数字孪生系统需要集成与处理增量式的多模态数据,以支撑面向现实场景动态决策的高精度仿真需求。然而,现有数字孪生平台时空数据管理割裂、多模态数据融合不足、决策交互机制缺失,并未形成真正意义上的面向无...面向无人机智能巡检的桥梁数字孪生系统需要集成与处理增量式的多模态数据,以支撑面向现实场景动态决策的高精度仿真需求。然而,现有数字孪生平台时空数据管理割裂、多模态数据融合不足、决策交互机制缺失,并未形成真正意义上的面向无人机智能巡检的桥梁数字孪生系统。基于此,提出了一种融合IFC (Industry Foundation Classes)、知识图谱和游戏引擎的桥梁数字孪生系统。系统以基于IFC构建的知识图谱(IFC-graph)为核心的数据管理引擎,统一整合桥梁设计建造信息、无人机巡检规划所需的结构语义,以及巡检过程中获取的多模态感知数据(如点云、图像等),构建覆盖构件-子结构-区域等多空间尺度、支持全生命周期演化的增量式语义管理体系,并实现语义驱动下的高效信息检索与动态数据关联。在虚拟仿真层面,系统引入虚幻引擎构建高保真三维桥梁环境,精准复刻物理场景中的几何结构与环境要素,并通过与IFC知识图谱的双向联动机制,支持无人机路径规划、飞行策略模拟与多轮次巡检任务的交互式推演,能够真实还原飞行过程中的转向、避障与碰撞等复杂行为。基于上述系统框架,进一步提出一种融合构件语义的无人机巡检路径优化算法,有效提升路径规划的适应性与精度,实现面向关键构件的高分辨率检测。系统已在实际桥梁案例中完成部署与验证,结果表明:该方案具备良好的可扩展性与工程适用性,可为桥梁运维过程中的智能化分析与全生命周期管理提供新型解决思路与技术支撑。展开更多
Advanced oxidation processes(AOPs)that utilize the highly potent hydroxyl radical(·OH)are a cornerstone of modern environmental remediation.Among these,the Fenton reaction is renowned for its effectiveness[1].How...Advanced oxidation processes(AOPs)that utilize the highly potent hydroxyl radical(·OH)are a cornerstone of modern environmental remediation.Among these,the Fenton reaction is renowned for its effectiveness[1].However,its practical application has been persistently hampered by two fundamental constraints:a strict reliance on acidic conditions(typically pH 2-4)and the need to be continuously supplied,costly externally generated hydrogen peroxide(H_(2)O_(2))[2-4].展开更多
The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently...The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently,the protection of sensitive data has become increasingly critical.Regardless of the complexity of the encryption algorithm used,a robust and highly secure encryption key is essential,with randomness and key space being crucial factors.This paper proposes a new Robust Deoxyribonucleic Acid(RDNA)nucleotide-based encryption method.The RDNA encryption method leverages the unique properties of DNA nucleotides,including their inherent randomness and extensive key space,to generate a highly secure encryption key.By employing transposition and substitution operations,the RDNA method ensures significant diffusion and confusion in the encrypted images.Additionally,it utilises a pseudorandom generation technique based on the random sequence of nucleotides in the DNA secret key.The performance of the RDNA encryption method is evaluated through various statistical and visual tests,and compared against established encryption methods such as 3DES,AES,and a DNA-based method.Experimental results demonstrate that the RDNA encryption method outperforms its rivals in the literature,and achieves superior performance in terms of information entropy,avalanche effect,encryption execution time,and correlation reduction,while maintaining competitive values for NMAE,PSNR,NPCR,and UACI.The high degree of randomness and sensitivity to key changes inherent in the RDNA method offers enhanced security,making it highly resistant to brute force and differential attacks.展开更多
Photocatalytic transfer hydrogenation using water as the proton source has emerged as an attractive and green approach for the catalytic reduction of unsaturated bonds.Herein,we report an oxygen-defective TiO_(2)-supp...Photocatalytic transfer hydrogenation using water as the proton source has emerged as an attractive and green approach for the catalytic reduction of unsaturated bonds.Herein,we report an oxygen-defective TiO_(2)-supported palladium catalyst(Pd-TiO_(2)-Ov)for efficient photocatalytic water-donating transfer hydrogenation of anethole towards 4-n-propylanisole in a high yield of 99.9%,which is significantly higher compared to the pristine TiO_(2)-supported palladium catalyst(Pd-TiO_(2),74%).The enhanced performance is ascribed to the presence of oxygen vacancies,which facilitate light absorption and suppress the recombination of photogenerated electron-hole pairs.Furthermore,the Pd-TiO_(2)-Ov is versatile in hydrogenating various alkene substrates including those with hydroxyl,ether,fluoride,and chloride functional groups in full conversion,thus offering a green method for transfer hydrogenation of alkenes.This study provides new insights and advances in current hydrogenation technology with water as the proton source.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
文摘<strong>Introduction:</strong> Tonsillectomy is described as one of the oldest surgical procedures according to the authors of the surgical treatise (Aulus Amida and Paul of Aegina in the 6th and 7th centuries) found in the Vatican library. The contraindication of codeine in children has changed the management of post tonsillectomy pain. The aim of this study was to assess the management of post tonsillectomy pain in our developing country context. <strong>Methods:</strong> This was a prospective, analytical study lasting 6 months (September 2019-February 2020), carried out in the ENT/CFS department of the Ignace Deen National Hospital. We included in this study all patients who underwent a tonsillectomy in the department during the study period and who agreed to participate in the survey. <strong>Results:</strong> 34 patients were included in our study, i.e. a frequency of 25% of surgical interventions. The mean age of our patients was 18.06 ± 12 years with extremes of 03 years and 45 years. Recurrent hypertrophic tonsillitis with sleep disturbances was the most frequent indication for surgery in our study, at 47.06% (n = 16). We performed an isolated tonsillectomy in 52.9% (n = 18) of cases. Analgesia was multimodal using the WHO Step I and II analgesics in 44.1% (n = 15) and 55.9% (n = 19), respectively. Pain control was satisfactory in all patients. <strong>Conclusion:</strong> The evaluation of post tonsillectomy pain is essential for optimal management. In this indication, multimodal analgesia, involving several levels I and II analgesics, provided satisfactory pain control.
文摘面向无人机智能巡检的桥梁数字孪生系统需要集成与处理增量式的多模态数据,以支撑面向现实场景动态决策的高精度仿真需求。然而,现有数字孪生平台时空数据管理割裂、多模态数据融合不足、决策交互机制缺失,并未形成真正意义上的面向无人机智能巡检的桥梁数字孪生系统。基于此,提出了一种融合IFC (Industry Foundation Classes)、知识图谱和游戏引擎的桥梁数字孪生系统。系统以基于IFC构建的知识图谱(IFC-graph)为核心的数据管理引擎,统一整合桥梁设计建造信息、无人机巡检规划所需的结构语义,以及巡检过程中获取的多模态感知数据(如点云、图像等),构建覆盖构件-子结构-区域等多空间尺度、支持全生命周期演化的增量式语义管理体系,并实现语义驱动下的高效信息检索与动态数据关联。在虚拟仿真层面,系统引入虚幻引擎构建高保真三维桥梁环境,精准复刻物理场景中的几何结构与环境要素,并通过与IFC知识图谱的双向联动机制,支持无人机路径规划、飞行策略模拟与多轮次巡检任务的交互式推演,能够真实还原飞行过程中的转向、避障与碰撞等复杂行为。基于上述系统框架,进一步提出一种融合构件语义的无人机巡检路径优化算法,有效提升路径规划的适应性与精度,实现面向关键构件的高分辨率检测。系统已在实际桥梁案例中完成部署与验证,结果表明:该方案具备良好的可扩展性与工程适用性,可为桥梁运维过程中的智能化分析与全生命周期管理提供新型解决思路与技术支撑。
基金Cardiff University and the Max Planck Centre for Fundamental Heterogeneous Catalysis(FUNCAT)for financial supportthe Marie Skłodowska-Curie Actions Fellowship(101107009-AtomCat4Fuel)UKRI(EP/Y029305/1)。
文摘Advanced oxidation processes(AOPs)that utilize the highly potent hydroxyl radical(·OH)are a cornerstone of modern environmental remediation.Among these,the Fenton reaction is renowned for its effectiveness[1].However,its practical application has been persistently hampered by two fundamental constraints:a strict reliance on acidic conditions(typically pH 2-4)and the need to be continuously supplied,costly externally generated hydrogen peroxide(H_(2)O_(2))[2-4].
文摘The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently,the protection of sensitive data has become increasingly critical.Regardless of the complexity of the encryption algorithm used,a robust and highly secure encryption key is essential,with randomness and key space being crucial factors.This paper proposes a new Robust Deoxyribonucleic Acid(RDNA)nucleotide-based encryption method.The RDNA encryption method leverages the unique properties of DNA nucleotides,including their inherent randomness and extensive key space,to generate a highly secure encryption key.By employing transposition and substitution operations,the RDNA method ensures significant diffusion and confusion in the encrypted images.Additionally,it utilises a pseudorandom generation technique based on the random sequence of nucleotides in the DNA secret key.The performance of the RDNA encryption method is evaluated through various statistical and visual tests,and compared against established encryption methods such as 3DES,AES,and a DNA-based method.Experimental results demonstrate that the RDNA encryption method outperforms its rivals in the literature,and achieves superior performance in terms of information entropy,avalanche effect,encryption execution time,and correlation reduction,while maintaining competitive values for NMAE,PSNR,NPCR,and UACI.The high degree of randomness and sensitivity to key changes inherent in the RDNA method offers enhanced security,making it highly resistant to brute force and differential attacks.
基金supported by the National Key Research and Development Program of China(2023YFD2200505)National Natural Science Foundation of China(22202105),Natural Science Foundation of Jiangsu Higher Education Institutions of China(21KJA150003)the Innovation and Entrepreneurship Team Program of Jiangsu Province(JSSCTD202345).
文摘Photocatalytic transfer hydrogenation using water as the proton source has emerged as an attractive and green approach for the catalytic reduction of unsaturated bonds.Herein,we report an oxygen-defective TiO_(2)-supported palladium catalyst(Pd-TiO_(2)-Ov)for efficient photocatalytic water-donating transfer hydrogenation of anethole towards 4-n-propylanisole in a high yield of 99.9%,which is significantly higher compared to the pristine TiO_(2)-supported palladium catalyst(Pd-TiO_(2),74%).The enhanced performance is ascribed to the presence of oxygen vacancies,which facilitate light absorption and suppress the recombination of photogenerated electron-hole pairs.Furthermore,the Pd-TiO_(2)-Ov is versatile in hydrogenating various alkene substrates including those with hydroxyl,ether,fluoride,and chloride functional groups in full conversion,thus offering a green method for transfer hydrogenation of alkenes.This study provides new insights and advances in current hydrogenation technology with water as the proton source.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
