果蠅(Drosophila melanogaster)的習得性無助表現之研究
習得性無助是個體經多次追求獎賞或逃離困境失敗後產生的一種消極行為表現。習得性無助的行為研究雖多,但對其神經機制的研究卻甚少。 本研究發現273,cha-Gal80>CsC-mCh是適合光遺傳學訓練的果蠅殖系。在白光點獎賞記憶訓練中,使273,cha-Gal80>CsC-mCh果蠅學會白光點視覺訊號代表著獎賞,並發現其白光獎賞記憶能持續7分鐘以上但未達10分鐘。藉已建立白光視覺訊號與獎賞連結的273,cha-Gal80>CsC-mCh,發現重複追求獎賞失敗的實驗組,相較於持續接受獎賞與完成獎賞記憶訓練而無任何操作的對照組,明顯表現習得性無助,本研究亦發現習得性無助個體也表現了活動力、覓食表現及攝食動機的下降。 本研究成功建立高成效的果蠅成蟲光遺傳學習得性無助訓練,並針對果蠅成蟲的習得性無助行為表現進行完整的研究,未來期望本於此訓練方式進行特定腦區、神經群和神經傳遞物之探究,建構果蠅習得性無助的神經網路機制。
Conscious Brain Mind-Controlled Cybonthitic Cyborg Bionic-Leg - V2
Lower limb amputations affect about 28.9 million people worldwide, influencing normal human functions, we are developing a conscious brain mind-controlled Cybonthitic cyborg bionic-leg to provide a professional solution for this problem, which is classified as restricted knee movement, short-term solution, limited pressure bearing, unspecific analog reading of EMG; Because the output voltage measured in nano-volts, resulting in unspecific knee movement. The functionality of these modern gadgets is still limited due to a lack of neuromuscular control (i.e. For movement creation, control relies on human efferent neural signals to peripheral muscles). Electromyographic (EMG) or myoelectric signals are neuromuscular control signals that can be recorded from muscles for our engineering goals. We worked on a sophisticated prosthetic knee design with a 100-degree angle of motion. We also used a specific type of coiled spring to absorb abrupt or unexpected motion force. In addition, we amplified the EMG output from (Nano-Voltage) to (Milli-Voltage) using customized instrumentation amplifiers (operational amplifiers). We used a full-wave rectifier to convert AC to DC, as a consequence of these procedures, sine-wave output voltage measures in millivolts, and the spring constant indicates the most force for every 1cm. Von mises Stress analysis shows bearing as 3000N is the maximum load for the design. Detecting the edge of a stairwell using the first derivative. The benefit of a system that controls the prosthetic limb is activated by the patient’s own EMG impulses, rather than sensors linked to the body.
探討多子連線的最小阻隔數
2021年國際科展中,有作品探討鉛直與水平排列的支配數,而本研究從五子棋的想法出發,將前述研究進行重要的延伸與改變,探討在a×b棋盤中,「米」字方向無p子連線時,所需的阻隔數最小值。由於有界棋盤比無界棋盤複雜許多,因此我們先在無界棋盤中找出符合阻隔限制的「完美型態」,並找出存在至少一種「完美型態」的p值集合Ω。研究發現,只要是可以表示為p=6k-1或p=6k+1(k∈N)的正整數p,皆可以型態DT(p,d)阻隔。接著我們推廣至有界棋盤,先探討所有p值的f(a,b;p)上界與下界,再針對Ω中的p值做討論,利用「任意1×p區域至少有1個阻隔」的性質導出「完美型態」下長或寬為kp(k∈N)的下界,並找出非常接近f(a,b;p)的上界。我們也將二維的探討方式與結果延伸至三維,找出所有p值的f(a,b,c;p)上下界與可使阻隔型態DT(p,d_R,d_h)為完美型態的p值集合。另外我們也找出嚴格對角拉丁方陣可對應成「完美型態」之必要條件。