<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
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
针对园区综合能源系统中存在多利益主体且收益分配不均的实际情况,提出一种基于混合博弈的双层能量管理模型。首先,建立园区综合能源系统的运行框架,分析上层微网运营商与下层用户聚合商的利益关系。其次,为使园区各主体利益最大化,构...针对园区综合能源系统中存在多利益主体且收益分配不均的实际情况,提出一种基于混合博弈的双层能量管理模型。首先,建立园区综合能源系统的运行框架,分析上层微网运营商与下层用户聚合商的利益关系。其次,为使园区各主体利益最大化,构建了多用户与微网运营商多方参与的混合博弈模型。其中,运营商通过主从博弈制定向用户的售能价格,用户聚合商在接收价格后基于纳什-海萨尼理论进行利益分配。然后,针对储能设备前期投入较高的实际情况,充分挖掘电动汽车的集群可调度潜力,通过卷积神经网络-双向长短期记忆网络(convolutional neural networks and Bi-directional long short-term memory,CNN-BiLSTM)法处理电动汽车的历史数据以降低不确定性,并制定了利用电动汽车共享储能特性作为储能设备的运行策略。最后,以某市园区综合能源系统为研究对象进行分析。结果表明,所建立的模型可以有效减少碳排放,实现运营商与多用户共赢。展开更多
分布式点对点(peer to peer,P2P)电能交易能促进能源就近达到供需平衡,在保证公平性的同时提高电网利用效率。该文提出P2P电能交易模型,并基于非对称纳什谈判(asymmetric nash bargaining,ANB)理论研究合作收益分配机制。首先,建立P2P...分布式点对点(peer to peer,P2P)电能交易能促进能源就近达到供需平衡,在保证公平性的同时提高电网利用效率。该文提出P2P电能交易模型,并基于非对称纳什谈判(asymmetric nash bargaining,ANB)理论研究合作收益分配机制。首先,建立P2P电能交易双方合作模型,二者通过合作产生合作剩余,然后基于非对称纳什谈判理论构建交易双方的收益分配模型,使得合作收益能在买卖双方间得到合理分配,最后通过算例验证所提合作博弈模型的有效性。仿真结果表明,交易双方通过合作,可以较大幅度提高各主体的运行效益以及合作联盟的整体效益,也能体现P2P电能交易卖方和买方在联盟中贡献大小的差异,可以更合理地分配合作收益。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.
文摘针对园区综合能源系统中存在多利益主体且收益分配不均的实际情况,提出一种基于混合博弈的双层能量管理模型。首先,建立园区综合能源系统的运行框架,分析上层微网运营商与下层用户聚合商的利益关系。其次,为使园区各主体利益最大化,构建了多用户与微网运营商多方参与的混合博弈模型。其中,运营商通过主从博弈制定向用户的售能价格,用户聚合商在接收价格后基于纳什-海萨尼理论进行利益分配。然后,针对储能设备前期投入较高的实际情况,充分挖掘电动汽车的集群可调度潜力,通过卷积神经网络-双向长短期记忆网络(convolutional neural networks and Bi-directional long short-term memory,CNN-BiLSTM)法处理电动汽车的历史数据以降低不确定性,并制定了利用电动汽车共享储能特性作为储能设备的运行策略。最后,以某市园区综合能源系统为研究对象进行分析。结果表明,所建立的模型可以有效减少碳排放,实现运营商与多用户共赢。
文摘分布式点对点(peer to peer,P2P)电能交易能促进能源就近达到供需平衡,在保证公平性的同时提高电网利用效率。该文提出P2P电能交易模型,并基于非对称纳什谈判(asymmetric nash bargaining,ANB)理论研究合作收益分配机制。首先,建立P2P电能交易双方合作模型,二者通过合作产生合作剩余,然后基于非对称纳什谈判理论构建交易双方的收益分配模型,使得合作收益能在买卖双方间得到合理分配,最后通过算例验证所提合作博弈模型的有效性。仿真结果表明,交易双方通过合作,可以较大幅度提高各主体的运行效益以及合作联盟的整体效益,也能体现P2P电能交易卖方和买方在联盟中贡献大小的差异,可以更合理地分配合作收益。
