Smart Materials Prediction: Applying Machine Learning to Lithium Solid-State Electrolyte

Traditionally, the discovery of new materials has often depended on scholars’ computational and experimental experience. The traditional trial-and-error methods require many resources and computing time. Due to new materials’ properties becoming more complex, it is difficult to predict and identify new materials only by general knowledge and experience. Material prediction tools based on machine learning (ML) have been successfully applied to various materials fields; they are beneficial for modeling and accelerating the prediction process for materials that cannot be accurately predicted. However, the obstacles of disciplinary span led to many scholars in materials not having complete knowledge of data-driven materials science methods. This paper provides an overview of the general process of ML applied to materials prediction and uses solid-state electrolytes (SSE) as an example. Recent approaches and specific applications to ML in the materials field and the requirements for building ML models for predicting lithium SSE are reviewed. Finally, some current obstacles to applying ML in materials prediction and prospects are described with the expectation that more materials scholars will be aware of the application of ML in materials prediction.     

Identifying epilepsy based on machine‐learning technique with diffusion kurtosis tensor

IntroductionEpilepsy is a serious hazard to human health. Minimally invasive surgery is an extremely effective treatment to refractory epilepsy currently if the location of epileptic foci is given. However, it is challenging to locate the epileptic foci since a multitude of patients are MRI‐negative. It is well known that DKI (diffusion kurtosis imaging) can analyze the pathological changes of local tissues and other regions of epileptic foci at the molecular level. In this article, we propose a new localization way for epileptic foci based on machine‐learning method with kurtosis tensor in DKI.MethodsWe recruited 59 children with hippocampus epilepsy and 70 age‐ and sex‐matched normal controls; their T1‐weighted images and DKI were collected simultaneously. Then, the hippocampus in DKI is segmented based on a mask as a local brain region, and DKE is utilized to estimate the kurtosis tensor of each subject''s hippocampus. Finally, the kurtosis tensor is fed into SVM (support vector machine) to identify epilepsy.ResultsThe classifier produced 95.24% accuracy for patient versus normal controls, which is higher than that obtained with FA (fractional anisotropy) and MK (mean kurtosis). Experimental results show that the kurtosis tensor is a kind of remarkable feature to identify epilepsy, which indicates that DKI images can act as an important biomarker for epilepsy from the view of clinical diagnosis.ConclusionAlthough the classification task for epileptic patients and normal controls discussed in this article did not directly achieve the location of epileptic foci and only identified epilepsy on certain brain region, the epileptic foci can be located with the results of identifying results on other brain regions.     

六味地黄汤干预抑郁大鼠学习记忆的作用机制

目的:探讨六味地黄汤对慢性抑郁大鼠记忆障碍的改善作用,并探讨其可能的作用机制。方法:Wistar雌性大鼠随机分为正常组(生理盐水)、慢性不可预见性温和应激(CUMS)模型组(生理盐水)、六味地黄汤低、中、高剂量组(2. 60,7. 81,23. 50 g·kg~(-1)·d~(-1))。除正常组外,其余各组造成CUMS模型。每周称体质量,观察其行为学指标变化;实时荧光定量聚合酶链式反应(Real-time PCR)检测其海马G蛋白偶联雌激素受体(GPR30),胞内磷脂酰肌醇激酶(PI3K),环磷酸腺苷反应元件结合蛋白(CREB),脑源性神经营养因子(BDNF) mRNA的表达;酶联免疫吸附测定(ELISA)检测血清中雌激素含量。结果:与正常组比较,模型组体质量、活动能力、兴趣等明显降低(P 0. 05,P 0. 01);与模型组比较,六味地黄汤2. 60,7. 81,23. 50 g·kg~(-1)可明显提高CUMS大鼠糖水偏好度(P 0. 01)和旷场实验的站立次数(P 0. 01);7. 81,23. 50 g·kg~(-1)明显提高旷场实验的总距离(P 0. 05,P 0. 01);2. 60,7. 81 g·kg~(-1)可缩短水迷宫实验寻台潜伏期(P 0. 01);7. 81 g·kg~(-1)可增加血清中雌激素含量(P 0. 05);CUMS模型组大鼠海马组织内的GPR30,PI3K,CREB,BDNF mRNA表达明显下降(P 0. 05,P 0. 01),六味地黄汤2. 60 g·kg~(-1)显著增加海马组织内的GPR30,CREB mRNA表达(P 0. 05,P 0. 01),7. 81 g·kg~(-1)明显增加海马组织内的GPR30,PI3K,CREB,BDNF mRNA表达量(P 0. 05,P 0. 01)。结论:六味地黄汤具有抗抑郁作用,逆转CUMS大鼠抑郁样行为及学习记忆障碍,其中中剂量组药效最显著。其作用机制可能与增加血清中雌激素和提高大鼠海马GPR30,PI3K,CREB,BDNF mRNA表达有关。     

PBL联合CBL教学法在中医院校影像教学中应用的优势

随着影像技术的快速发展,影像检查已发展为临床诊断疾病的主要手段之一。所以作为未来医疗工作者的医学生,学好影像学变得越来越重要。目前影像教学大多采用传统的“满堂灌”的授课方式,学生处于学习的被动状态,效果并不尽人意。如何才能让学生真正掌握影像学知识,是值得每位任教老师深思的问题。作者结合多年的教学经验与实践,并针对中医院校医学生西医知识相对薄弱,课时少这一特点,认为PBL联合CBL教学法不但可以激发学生学习的主观能动性,培养学生的自学能力,增强学生解决问题的能力,提升临床思维能力,还可以提高课堂效率,有利于学生更好地学习、掌握影像知识,并学会将所学理论知识应用于临床实践。     

学习困难儿童社会认知发展研究

目的 探讨学习困难儿童社会认知发展的研究现状,重点阐释学习困难儿童自我概念发展的特点及其社会认知发展的过程——社会信息加工各阶段的特点。方法 利用文献法整合国内外的相关研宛。结果 学习困难儿童社会认知发展中的某些方面存在缺陷。结论 学习困难儿童的自我概念存在明显的消极倾向,且在接纳与理解社会信息以及运用社会技能方面存在障碍。     

基于CT平扫的影像组学模型鉴别肺炎性肌纤维母细胞瘤和周围型肺癌的研究

目的 探讨基于CT平扫的影像组学在鉴别肺炎性肌纤维母细胞瘤(IMT)和周围型肺癌(PLC)的价值.方法 回顾性收集经我院及外院手术后病理证实的72例肺IMT及79例PLC的资料.使用A.K(Artificial Intelligence Kit)软件从CT平扫图像中提取高通量数据,对其进行特征筛选及降维,去除了重复性差...     

CBL联合TBL教学法同步培养口腔正畸专业研究生临床和科研能力的效果研究

目的 研究以案例为基础的学习(CBL)联合基于团队的学习(TBL)教学法同步培养口腔正畸专业研究生临床和科研能力的教学效果.方法 选取中山大学光华口腔医学院口腔正畸专业2018级与2019级研究生共24人为研究对象,按随机数字表法分为两组,实验组采用CBL联合TBL教学法;对照组采用以讲授为基础的学习(LBL)传统教学...     

Civic Learning,Science, and Structural Racism

Vaccine hesitancy is a major public health challenge, and racial disparities in the acceptance of vaccines is a particular concern. In this essay, we draw on interviews with mothers of Black male adolescents to offer insights into the reasons for the low rate of vaccination against the human papillomavirus among this group of adolescents. Based on these conversations, we argue that increasing the acceptance of HPV and other vaccines cannot be accomplished merely by providing people with more facts. Instead, we must address the pervasive racial discrimination in the United States that undermines trust in social institutions, including the health care system. In the short term, it may be helpful to increase the number of clinicians of color working in the health system, but more fundamental changes are required. The U.S. must adopt and implement policies that dismantle structural racism if it hopes to produce greater trust and community‐oriented thinking on behalf of people who have been exploited for centuries.     

固定比率食物强化法建立大鼠可卡因药物辨别模型

目的 建立固定比率为10(FR10)的大鼠可卡因药物辨别模型,进行可卡因辨别效应和剂量关系的测试及半数有效量(ED50)测定.方法 采用FR值逐渐递增1和每获得5次奖励FR值自动增加1的两种实验程序对32只SD大鼠进行食物训练,食物训练成功的大鼠给予可卡因10 mg·kg-1或氯化钠注射液进行辨别训练;将辨别训练成功的...     

基于迁移学习的2型糖尿病风险预测方案设计

提出了一种基于迁移学习的2型糖尿病风险预测方案,使用2型糖尿病发病相关危险因素作为原始糖尿病预测建模特征,对原有的糖尿病风险预测模型进行了优化,帮助医疗欠发达地区通过该模型实现对2型糖尿病的有效监测和防护.