PBL与思维导图相结合教学模式在临床教学中的应用

目的探讨PBL与思维导图相结合教学模式在临床教学中的应用。方法本文研究对象为在我院见习的临床本科生,为大理大学2015级一个班级,共55名学生,数据收集时间为2019年1月;按照授课方式的差异将学生分为实验班与对照班,实验班27名学生,对照班28名学生;对照班实施常规教学法,实验班实施PBL与思维导图相结合教学法。结果实验班教学结束测试得分为(85.60±3.46)分,对照班教学结束测试得分为(77.48±3.12)分,差异具有统计学意义(P<0.05);实验班教学方式满意度评分为(90.35±4.12)分,对照班教学方式满意度评分为(80.25±4.05)分,差异具有统计学意义(P<0.05)。结论在临床教学中采用PBL与思维导图相结合教学模式,能够提高学生的专业知识掌握水平与对教学模式的认可度。     

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solving the differential equations associated with conservation laws is a major branch in computational mathematics. The recent success of machine learning, especially deep learning in areas such as computer vision and natural language processing, has attracted a lot of attention from the community of computational mathematics and inspired many intriguing works in combining machine learning with traditional methods. In this paper, we are the first to view numerical PDE solvers as an MDP and to use (deep) RL to learn new solvers. As proof of concept, we focus on 1-dimensional scalar conservation laws. We deploy the machinery of deep reinforcement learning to train a policy network that can decide on how the numerical solutions should be approximated in a sequential and spatial-temporal adaptive manner. We will show that the problem of solving conservation laws can be naturally viewed as a sequential decision-making process, and the numerical schemes learned in such a way can easily enforce long-term accuracy. Furthermore, the learned policy network is carefully designed to determine a good local discrete approximation based on the current state of the solution, which essentially makes the proposed method a meta-learning approach. In other words, the proposed method is capable of learning how to discretize for a given situation mimicking human experts. Finally, we will provide details on how the policy network is trained, how well it performs compared with some state-of-the-art numerical solvers such as WENO schemes, and supervised learning based approach L3D and PINN, and how well it generalizes.     

Easy Words: Reference Resolution in a Malevolent Referent World

This article describes early stages in the acquisition of a first vocabulary by infants and young children. It distinguishes two major stages, the first of which operates by a stand‐alone word‐to‐world pairing procedure and the second of which, using the evidence so acquired, builds a domain‐specific syntax‐sensitive structure‐to‐world pairing procedure. As we show, the first stage of learning is slow, restricted in character, and to some extent errorful, whereas the second procedure is determinative, rapid, and essentially errorless. Our central claim here is that the early, referentially based learning procedure succeeds at all because it is reined in by attention‐focusing properties of word‐to‐world timing and related indicants of referential intent.     

Kinetic modeling of PET-FDG in the brain without blood sampling

The aim in this work is to report a new method to calculate parametric images from a single scan acquisition with positron emission tomography (PET) and fluorodeoxyglucose (FDG) in the human brain without blood sampling. It is usually practical for research or clinical purposes to inject the patient in an isolated room and to start the PET acquisition only for some 10–20 min, about 30 min after FDG injection. In order to calculate the cerebral metabolic rates for glucose (CMRG), usually several blood samples are required. The proposed method considers the relation between the uptake of the tracer in the cerebellum as a reference tissue and the population based input curve. Similar results were obtained for CMRG values with the present method in comparison to the usual autoradiographic and the non-linear least squares fitting of regions of interest.     

Differential role for the striatum and cerebellum in response to novel movements using a motor learning paradigm.

The aim of this pilot study was to examine the role of the striatum and cerebellum in the adaptation to a novel movement within a sequence of practiced movements using a motor learning paradigm. The performance of patients in the early or advanced stages of Parkinson's disease (PD) and of patients with damage to the cerebellum (CE) was compared, respectively to a group of aged and young matched controls on an adapted version of the Mirror-Tracing Test. In this task, subjects were required to trace a series of complex figures in two conditions: (1) a Practiced condition, in which the figures were composed of the juxtaposition of three simple designs that were extensively practiced before; and (2) a Mixed condition in which triads were created by replacing the last simple figure of the triads in the Practiced condition by a new simple figure that had never been traced individually before. Results showed that all clinical groups were slower than controls at tracing the Practiced triads. Most interestingly, however, only patients in the advanced stages of PD showed increased completion time to trace the triads in the Mixed condition. This suggests that a bilateral striatal dysfunction affects the ability to adapt to a novel motion within a sequence of practiced movements. Although exploratory, these results support a functional dissociation between the striatum and cerebellum in acquiring visuomotor skilled behaviors.     

Effects of acute administration of d-amphetamine and haloperidol on procedural learning in man

The effects of an indirect dopamine-agonist, d-amphetamine, and a non-selective dopamine receptor antagonist, haloperidol, were investigated in normal male volunteers using a between-subjects double-blind design in a procedural learning task, thought mainly to involve unconscious/automatic learning. The results showed: (1) d-amphetamine facilitated response speed, whereas haloperidol inhibited it, in comparison to placebo; (2) the linear increase in procedural learning corresponded with pharmacological manipulation of degree of dopaminergic activity, i.e. subjects given haloperidol showed the least, and subjects given d-amphetamine the greatest, procedural learning. The implications of these findings are discussed in relation to investigation of abnormalities of procedural learning processes in schizophrenia. Received: 28 June 1996/Final version: 2 October 1996     

Long-term neurotoxicity of chlorpyrifos: spatial learning impairment on repeated acquisition in a water maze.

Organophosphate compounds are cholinesterase inhibitors widely used in agriculture, industry, household products, and even as chemical weapons. Their major mechanism of acute toxic action is the inhibition of acetylcholinesterase, which is responsible for the degradation of the neurotransmitter acetylcholine. An organophosphorus ester-induced chronic neurotoxicity (OPICN) syndrome has been proposed. The OPICN syndrome could result from both long-term exposure to subclinical doses of OPs and after acute poisoning. Development of animal models for the cognitive decline are required and could later help to elucidate the mechanisms involved in this long-term effect on the central nervous system. Previously, we have found performance decrements in a four-trial repeated acquisition spatial task in a water maze. The present study includes two experiments to extend the long-term behavioral effects observed. Rats were injected either once or twice with chlorpyrifos (CPF) and then tested months after in a two-trial repeated acquisition task in a water maze. Our results confirm and extend the long-term behavioral effects of subcutaneous administration of CPF. The two treatments used produced performance decrements that suggest functional central nervous system alterations.     

石杉碱甲和乙促进小鼠的空间辨别学习和记忆

石杉碱甲和乙是从石杉科石杉属植物蛇足石杉[Huperzia scrrata(Thunb.)Trev.]中分得的二个新生物碱。“Y”迷宫实验表明,ip Hup-A 0.075～0.125 mg/kg或Hup-B 0.4～0.8mg/kg,均能明显促进小鼠的空间辨别学习,并能显著预防CO₂产生的短时识别障碍,促进记忆保持和记忆再现。ig Hup-A 0.1～0.3 mg/kg或Hup-B 0.8 mg/kg也有促进学习的作用。促进作用Hup-A>Phys>Hup-B。剂量与效应曲线呈倒U型。