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#Carmel 紅葉。 #NorCal #17miles #winter (at Carmel, California)
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#時間煮雨 📑📝🔫🔫💉💉 說life science major的痛 每日都對自己說,無論前面會多難行,有幾多坎坷,既然已經走到這一步,就要堅持落去,不要等以後的某一天,因為今日既「未完成」而後悔。其實每一個人都比自己想像中堅強。
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玫瑰美得耐不住時間的推敲,一天便開始凋謝。 遇見你是最美麗的巧合,那麼真實卻又想夢境般虛無 怕是醒來只剩下感動,卻無你在身旁 與我共賞山下的一片燈海。原諒我不敢,原諒我膽小,不敢相信有這般運氣遇上和擁有這樣的美好,又怕被再次奪走現在的擁有。「擁有,就是失去的開始,你不知道嗎」 但係,很多東西錯過了就不再了。等了又等,一分一秒也似太短,不願再被恐懼奪走更多分秒,放開雙手接受你的擁抱,等到一天你說「你太癡纏」 花會凋零,夢會醒來,身邊會有你,一切都好。鐵觀音的淡淡幽香,希望可以慢慢dep落去
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An Amazing Invention.
Researchers develop novel Brain Training Device to reconnect the brain and paralyzed limb after stroke
The world’s first Brain Training Device has given a ray of new hope to the recovery of survivors after stroke. Developed by researchers of The Hong Kong Polytechnic University (PolyU)’s Interdisciplinary Division of Biomedical Engineering (BME), this novel device which can detect brainwave, and thereby control the movement of paralyzed limbs, or go even further to control a robotic hand based on its sophisticated algorithm.
The research was led by Prof. Raymond Tong Kai-yu, Professor of PolyU’s Interdisciplinary Division of Biomedical Engineering, who is also the Principal Investigator of the award-winning Exoskeleton Hand Robotic Training Device or the “Hand of Hope”. His team members include the BME research team (Newmen Ho, Xiaoling Hu, Ching-hang Fong, Xinxin Lou, Lawrence Chong and Nathan Lam) and the Industrial Centre team of PolyU (Robert Tam, Bun Yu, Shu-to Ng and Peter Pang).
The latest breakthrough “Brain Training Device” can be coupled with the use of the “Hand of Hope” to achieve higher degree of recovery for stroke patients. While effective motor recovery after stroke depends on early rehabilitation program and intensive voluntary practice of the paretic limbs, current rehabilitation products have not use brainwave to guide the stroke survivors to identify voluntary intention and to relearn how to reconnect to their paralyzed limb again.
Prof. Raymond Tong and his team therefore developed the Brain Training Device with a new coherence algorithm for hand function training. The new algorithm is based on frequency coherence on surface electroencephalography (EEG, brainwave) and electromyography (EMG, muscle activities) to identify voluntary intention and their connection.
“The Brain Training Device is able to guide the stroke patients to relearn the reconnection between the brain and the limb, with a new design on the EEG headset and the EMG forearm brace to transmit data for controlling a hand robotic system interfaced by a telecare software platform using iPad app.” Prof. Raymond Tong explained.
The patented Brain Training System, which looks like a helmet for cyclist and can read brainwaves, also has new features to find the specific EEG electrode locations for each individual stroke patient and reduce the number of EEG electrodes, which can reduce the system cost and the preparation time for brain training, added by Prof. Tong.
To find a minimal set of electrodes to control the device with accuracy higher than 90%, five chronic stroke patients were recruited to be trained for 20 sessions in the study. The researchers found that, in general, 32 electrodes are needed to maintain accuracy higher than 90%.
The high accuracy and low number of channels needed means that the Brain Training Device is a viable tool for assistive aid and rehabilitation training. The futuristic system will be made portable and easy-to-use at hospital and home settings.
PolyU researchers have already filed patents for this Brain Training Device in both the United States and China. This project is funded by the HKSAR Government’s Innovation and Technology Fund (ITF). The findings of this brain control algorithm have been published as the cover story in top international journal IEEE Transactions on Neural Systems and Rehabilitation Engineering (2011.12).
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That Moment, I wish I could go back to my old times. I wish I could stay in Atchison, for at least one more year.
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As a Poikilotherm.
1. I need external sources of heat
2. Only when I am exposed to the sunshine I have enough heat supply
3. I stay in the shade when it's hot.
4. I still have to store enough heat in the sun when it's already 75 Fahrenheit in L.A.
5. I move a lot to stay warm.
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How Multitasking Can Improve Judgments
Research has revealed that multitasking impedes performance across a variety of tasks. Emergency room nurses that are interrupted multiple times while treating a patient can be more likely to make medication errors. Driving while speaking on a mobile phone significantly increases the probability of an automobile accident. At the same time, however, experienced golfers putt better when distracted than experienced golfers who are focusing on performance. Distractions resulting from the presence of other people can increase an individual’s performance, too. Why?
Addressing the Contradictions In a forthcoming issue of Psychological Science, one of the world’s top-ranked empirical journals in psychology, a team of researchers from the University of Basel helps to clarify these apparent contradictions. Lead author Janina Hoffmann, a Ph.D. student in Economic Psychology, and her co-authors Dr. Bettina von Helversen and Prof. Dr. Jörg Rieskamp, find that the type of judgment strategy that an individual employs strongly conditions how the “cognitive load” induced by multitasking affects performance. Higher cognitive load can actually improve performance when the task can be best completed using a less demanding, similarity-based strategy that informs judgments by retrieving past instances from memory.
The study is supported by the findings of two experiments conducted at the University of Basel. The first study exposed 90 participants to variable cognitive loads as they were asked to solve a judgment task whose solution was best achieved through the use of a similarity-based strategy (predicting how many cartoon characters another cartoon character could catch). Most participants switched to using a similarity-based strategy and produced more accurate judgments. The second study then exposed 60 participants to a linear task whose solution was not conducive to similarity-based strategies but rather rule- based strategies. Those participants who employed a similarity-based strategy made poorer judgments. The experiments were conducted with financial support from the Swiss National Science Foundation.
Moving Forward Cognitive load does not per se lead to worse performance, but rather it can, dependent on strategy choice, lead to better performance. The researchers believe that it is important to decipher cognitive strategies that people choose under given levels of cognitive load. Hoffmann claims, “A better understanding of these cognitive strategies may permit future studies to predict the precise circumstances under which people can solve a problem particularly well.”
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In love with Duet with Boba. what a weird combination #bobalover#coffeentea #boba #sunshine#insta#excitement
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Architecture is a mirror of history, culture and politics.
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Something must exist without physical explanation. This is what have been supporting me through all the failures and difficulties. Such support is impossible to be generated by any kinds of electrical signals in the brain.
We are all Loved Creatures.
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