1.Investigating the Effect of the Backlight Angle on the Aerodynamic Drag Experienced by Notchbacks in the Presence of Flow Separation

2.Application of Twin Type Ia supernovae to reduce Hubble diagram dispersion

3.Long-Range Wireless Energy Transmission through Stimulated Emission in Atmospheric Molecular Oxygen

Math and Computer Science

1.The Effect of Topological Parameters on the Predictive Performance of Long Short-Term Memory for Financial Forecasting


3.Modelling The Best Hospital

A Mathematical Approach with Calculus and Analytic Geometry to the Projecting Process of a Planar Image onto a Sphere

Class 12(1A), Hongyuan Yan, 2018/1, High School

4.How will a figure distort

5.An Asymptotic Approach to the Analysis of Swings


1.Multi-purpose Foldable Crutch

2.An Integrated Intelligent Medical Infusion Device Based on PLC

3.The Design and Construction of an Intelligent Selfie Robot

4.Household water-saving system



Biology and Environmental Science

1.Pathogen Identification and Environmental Effects Analysis of Black Rot Disease of Imported Vietnamese ‘Red’ Pitaya

2.The Effect of Oral Administered Grape-Seed Extract on Cerebral Hypoperfusion Dementia in Mice

3.Bacterium Improves the Efficiency of Root Regeneration in A. thaliana

4.Molecular Tool to Improve the Root System for Stress Resistance

5.EEG Results Indicate Quality of Sleep and Mood in the Elderly

6.The Effect of Excretory Factor EREG Released by Stromal Cells during Chemotherapy on the Malignant Phenotype of Prostate Cancer

7.An Organoid Culture Based Investigation: The Prevention Mechanism of Tea Polyphenols on Prostate Cancer

8.Decay of Urban Rail Transit-induced Ground-borne Vibration and Rapid Prediction Methods

9.Evaluation of Avian Species Diversity at Microforests of Nanhui Dongtan Wetlands in Terms of Human Disturbance and Edge Effect

10.Effects of Sleep Intervention and Herb Medication Ganwei on Behavioral and Biochemical Responses in Drosophila Alzheimer’s Disease Model

11.The Effect of Vitamin C on SW480 Colon Cancer Cells In Vitro

12.The Inhibitory Effect of Chemical and Biological Food Preservatives on growth of Escherichia coli and Rhizopus stolonifer

13.EGFR Mutation Testing

14.Mitigating Biodiversity Loss

15.Investigate the effect of e-liquid, high temperature stress and UV-C radiation exposure on the growth of Saccharomyces cerevisiae (yeast).

16.Surface Electromyogram Analysis of Muscle Reactivity During Tennis Top-spin Serve

Investigating the Effect of the Backlight Angle on the Aerodynamic Drag Experienced by Notchbacks in the Presence of Flow Separation

Class 12(1B), Tsz Shun Cheung, 2019/1, High School


1. “What is Aerodynamics?”. NASA. NASA. Web. 3 July 2018. 

2. Hucho, W. H., & Sovran, G. (1993). “Aerodynamics of road vehicles. Annual review of fluid mechanics”. 25(1), 485-537.

3. Mayer, W., & Wickern, G. (2011). “The New Audi A6/A7 Family-Aerodynamic Development of Different Body Types on One Platform”. SAE International Journal of Passenger Cars-Mechanical Systems, 4(1), 197-206.

4. Cooper, K. R. (1993). “Bluff body aerodynamics as applied to vehicles”. Journal of Wind Engineering and Industrial Aerodynamics, 49, pp. 1-22.

5. “Aerodynamic Drag Reduction of a Square-Back Car Model Using Linear Genetic Programming and Physic-Based Control” - Scientific Figure on ResearchGate. <http://www.researchgate.net/figure/Sketch-illustrating-the-drag-origin-for-road-vehicles-a-aerodynamic-drag-skin_fig2_322640200> [accessed 15 Feb, 2019]

6. S. R. Ahmed, G. Ramm, and G. Faltin. (1984). “Some salient features of the time averaged ground vehicle wake”. SAE Paper 840300.

7. “Drag and lift reduction of a 3D bluff-body using active vortex generators” - Scientific Figure on ResearchGate. <http://www.researchgate.net/figure/a-Side-view-and-upper-view-of-the-original-Ahmed-bo dy-with-a-30-rear-slant-b-Schematic_fig1_226408776> [accessed 14 Feb, 2019]

8. R. Gilhome, Brendan & W. Saunders, Jeffrey & Sheridan, John. (2001). “Time Averaged and Unsteady Near-Wake Analysis of Cars”. 10.4271/2001-01-1040.

9. M. K. A. B. Salleh, “Simulation and analsys drag and lift coefficent between sedan and hatchback car”. Bachelor thesis, PAHANG: University Malaysia Pahang, 2009

10. Buresti, Guido. (2000) “Bluff-Body Aerodynamics Lecture Notes”. Department of Aerospace Engineering University of Pisa, Italy.

11. Hucho, Wolf-Heinrich (1981). Aerodynamics of Road Vehicles: From Fluid Mechanics  Vehicle Engineering. English Edition.

12. Butterworth-Heinemann Ltd, 1987.Anagnost, A., Alajbegovic, A., Chen, H., Hill, D. et al., "DIGITAL PHYSICS? Analysis of the Morel Body in Ground Proximity," SAE Technical Paper 970139, 1997

13. Wickern, G., Wagner, A., and Zoerner, C., "Induced Drag of Ground Vehicles and Its Interaction with Ground Simulation," SAE Technical Paper 2005-01-0872, 2005

14. Marklund, J. and Chalmers tekniska h?gskola and Chalmers tekniska h?gskola. Institutionen f?r till?mpad mekanik. “Under-body and Diffuser Flows of Passenger Vehicles”. Chalmers University of Technology, 2013.

15. Cockrell DJ,Markland E. “Diffuser behavior, a review of past experimental work, relevant today”. Aircr Engng.1974;46:16.

16. R. Ramkissoon and K. Manohar. “Design and Calibration of a Low Speed Wind Tunnel”. British Journal of Applied Science & Technology. SCIENCEDOMAIN international. 4 (20): 2878-2890, 2014. Retrieved 7 July 2018.

17. Mehta RD, Bradshaw P. “Design Rules for Small Low Speed Wind Tunnels”. Aeronautical Journal.1979;443-449.

18. “Air - Density, Specific Weight and Thermal Expansion Coefficient at Varying Temperature and Constant Pressures Online calculator”. The Engineering ToolBox. 

19. Carr, G. W., Influence of Rear Body Shape on the Aerodynamic Characteristics of Saloon Cars, MIRA Report 1974/2, 1974.

20. Nouzawa, T., Hiasa, K., Nakamura, T., Kawamoto, A., and Sato, H., Unsteady-Wake Analysis of the Aerodynamic Drag of a Notchback Model with Critical Afterbody, “Vehicle Aerodynamics: Wake Flows, Computational Fluid Dynamics, and Aerodynamic Testing”, SP-908, SAE, Pennsylvania, pp. 1-12.

21. Hucho, W. H., Aerodynamic Drag of Passenger Cars, Aerodynamics of Road Vehicles, edited by W. H. Hucho, SAE, Pennsylvania, 1989, pp. 131-238.

Application of Twin Type Ia supernovae to reduce Hubble diagram dispersion

Class 11(3), Matthew Rui Zhang, 2016/1, High School


[1]  HUBBLE SITE., 2004. The progenitor of a type Ia supernova. Available at: .

[2] Paolo A. Mazzali., Friedrich K. R?pke., Stefano Benetti., & Wolfgang Hillebrandt. (2007). A Common Explosion Mechanism For Type Ia Supernovae. Science, 315 (5813), 825-828. [doi: 10.1126/science.1136259].

[3]  Riess AG et al. (1998) Observational Evidence from Supernovae for An Accelerating Universe And A Cosmological Constant. The Astronomical Journal, 116: 1009-1038.

[4]  A. G. Kim et al. Standardizing Type Ia Supernova Absolute Magnitudes Using Gaussian Process Data Regression. The Astrophysical Journal, 766:84 (22pp) (2013)

[5]  McCully, C., Jha, S. W., Foley, R. J., Bildsten, L., Fong, W. F., Kirshner, R. P., & Stritzinger, M. D. (2014). A luminous, blue progenitor system for the type Iax supernova 2012Z. Nature, 512(7512), 54-56.

[6]  Fakhouri, H. K., Boone, K., Aldering, G., Antilogus, P., Aragon, C., Bailey, S., & Buton, C. (2015). Improving Cosmological Distance Measurements Using Twin Type Ia Supernovae. The Astrophysical Journal,815(1), 58.

[7]  Stephane Blondin, 2016. Supernovae Identification. Stephane Blondin. Available at: . Accessed on 7-18-2016.

[8]  Tim Pearson, 2002. PGPLOT Graphic Subroutine Library. California Institute of Technology. Available at: . Accessed on 7-19-2016.

[9]  Graham, M. L., Foley, R. J., Zheng, W., Kelly, P. L., Shivvers, I., Silverman, J. M., & Ganeshalingam, M. (2015). Twins for life? A comparative analysis of the Type Ia supernovae 2011fe and 2011by.Monthly Notices of the Royal Astronomical Society, 446(2), 2073-2088.

[10] Stephane Blondin, 2016. Homepage of Stephane Blondin. Available at: . Accessed on 7-18-2016.

[11] Samantha L. Hoffmann et al. (2015) Optical Identification of Ceipheid in 19 Host Galaxies of Type Ia Supernovae and NGC 4258 with the HUBBLE SPACE TELESCOPE. Astrophysics-SR, arXiv:1607.08658v2.

[12] Riess et al. (2016) A 2.4% DETERMINATION OF THE LOCAL VALUE OF THE HUBBLE CONSTANT. The Astrophysical Journal, 826:56 (31pp).

Long-Range Wireless Energy Transmission through Stimulated Emission in Atmospheric Molecular Oxygen

Class 12(1A), Victor Shichen Yu, 2017/1, High School


[1] N. Tesla, Apparatus for transmitting electrical energy, US patent number 1,1 19,732, Dec 1914

[2] J.M. Fernandez, and J.A. Borras, Contactless battery charger with wireless control link, US patent number 6,184,651, Feb 2001

[3] A. Esser, H.-C. Skudelny, IEEE Trans. Industry Appl. 27 (1991) 872.

[4] J. Hirai, T.-W. Kim, A. Kawamura, IEEE Trans. Power Electron. 15 (2000) 21.

[5] Karalis, Aristeidis, J. D. Joannopoulos, and Marin Soljacic. "Efficient Wireless Non-radiative Mid-range Energy Transfer." Annals of Physics (2007): n. pag. Print.

[6]. Nasa.gov. 7 May 2008.

[7] Dickinson, Richard M. (1976). (PDF). MTT-S Int'l Microwave Symposium Digest:139–141.:.

[8] Strandberg, M. W. P.; Meng, C. Y.; Ingersoll, J. G. (1949). "The Microwave Absorption Spectrum of Oxygen". Phys.Rev. 75 (10)

[9] Cosmovici, C. B.; Montebugnoli, S.; Pogrebenko, S.; Colom, P. ,

[10] Chen, Szu-yuan; Maksimchuk, Anatoly; Umstadter, Donald (December 17, 1998).


[12] Einstein, A (1916). "Strahlungs-emission und -absorption nach der Quantentheorie". Verhandlungen der Deutschen Physikalischen Gesellschaft.

[13] Wikimedia, User: Borb

[14] A. E. Siegman (1986). . University Science Books.

[15] Lide, David R. Handbook of Chemistry and Physics. Boca Raton, FL: CRC, 1996: 14-7

[16] “Solar Arrays” Nasa.gov. NASA, n.d. Web.


The Effect of Topological Parameters on the Predictive Performance of Long Short-Term Memory for Financial Forecasting

Class 12(1A), Angle Qian, 2018/11, High School


[1] S. Siami-Namini and A. Saimi Namin, "Forecasting economics and financial time series: Arima vs. lstm," Jul. 2017. doi: 10.1371/journal.pone.0180944.

[2] M. Hansson, "On stock return prediction with LSTM networks," 2017. [Online]. Avail-able: http://lup.lub.lu.se/student-papers/search/publication/8911069.

[3] W. Bao, J. Yue, and Y. L. Rao, "A deep learning framework for financial time series using stacked autoencoders and long-short term memory," Jul. 2017. doi: 10.1371/ journal.pone.0180944.

[4] S. Selvin, R. Vinayakumar, E. A. Gopalakrishnan, V. K. Menon, and K. P. Soman, "Stock price prediction using LSTM, RNN and CNN-sliding window model," pp. 1643{ 1647, Sep. 2017. doi: 10.1109/ICACCI.2017.8126078.

[5] H. Y. Kim and C. H. Won, "Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models," Expert Systems with Applications, vol. 103, pp. 25{37, 2018, issn: 0957-4174. doi: http://doi.org/10. 1016/j.eswa.2018.03.002. [Online]. Available: http://www.sciencedirect.com/ science/article/pii/S0957417418301416.

[6] W. S. McCulloch and W. Pitts, "A logical calculus of the ideas immanent in nervous activity," The bulletin of mathematical biophysics, vol. 5, no. 4, pp. 115{133, Dec. 1943, issn: 1522-9602. doi: 10.1007/BF02478259. [Online]. Available: http://doi. org/10.1007/BF02478259.

[7] F. Rosenblat, "The perceptron: A probabilistic model for information storage and organization in the brain," Psychological Review, pp. 65{386, 1958.

[8] K. Hornik, "Approximation capabilities of multilayer feedforward networks," Neural Networks, vol. 4, no. 2, pp. 251{257, 1991, issn: 0893-6080. doi: http://doi.org/ 10.1016/0893-6080(91)90009-T. [Online]. Available: http://www.sciencedirect. com/science/article/pii/089360809190009T.

[9] B. C. Csaji, "Approximation with arti cial neural networks," 2001.

[10] C. Szegedy, A. Toshev, and D. Erhan, "Deep Neural Networks for object detection," C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger, Eds., pp. 2553{2561, 2013. [Online]. Available: http://papers.nips.cc/paper/5207-deep-neural-networks-for-object-detection.pdf.

[11] Y. Bengio, "Learning deep architectures for AI," Foundations and Trends in Ma-chine Learning, vol. 2, no. 1, pp. 1{127, Jan. 2009, issn: 1935-8237. doi: 10.1561/ 2200000006. [Online]. Available: http://dx.doi.org/10.1561/2200000006.

[12] Y. Bengio, P. Frasconi, and P. Simard, "The problem of learning long-term dependen-cies in recurrent networks," 1183{1188 vol.3, 1993. doi: 10.1109/ICNN.1993.298725.

[13] S. Hochreiter, "The vanishing gradient problem during learning recurrent neural nets and problem solutions," Int. J. Uncertain. Fuzziness Knowl.-Based Syst., vol. 6, no. 2, pp. 107{116, Apr. 1998, issn: 0218-4885. doi: 10.1142/S0218488598000094. [Online]. Available: http://dx.doi.org/10.1142/S0218488598000094.

[14] S. Hochreiter and J. Schmidhuber, "Long Short-Term Memory," Neural Comput., vol. 9, no. 8, pp. 1735{1780, Nov. 1997, issn: 0899-7667. doi: 10.1162/neco.1997. 9.8.1735. [Online]. Available: http://dx.doi.org/10.1162/neco.1997.9.8.1735.

[15] F. Gers, J. Schmidhuber, and F. Cummins, "Learning to forget: Continual prediction with LSTM," Neural Computation, vol. 12, pp. 2451{2471, 1999.

[16] F. Gers, "Long Short-Term Memory in Recurrent Neural Networks," 2001.

[17] Yahoo Finance, Historical data for the S&P 500. [Online]. Available: https : / / finance.yahoo.com/quote/%5EGSPC/history/.

[18] J. Chou and T. Nguyen, "Forward forecast of stock price using sliding-window metaheuristic-optimized machine-learning regression," IEEE Transactions on Industrial Informatics, vol. 14, no. 7, pp. 3132{3142, Jul. 2018, issn: 1551-3203. doi: 10.1109/TII.2018. 2794389.

Modelling the Best Hospital

Class 11(1A), James Tyler Liu, Class 11(7), Yuxuan Wang, Class 11(1B), John Xiaoshu Zhou, and Class 11(6), Lizhi Li, 2019/5, High School


[1] Health Forum LLC. "Fast Facts on U.S. Hospitals, 2018 | AHA." American Hospital Association, Feb. 2018, www.aha.org/statistics/fast-facts-us-hospitals. Accessed 18 Mar. 2018.

[2]Ableau. "China: Number of Hospitals in 2017 | Statistic." Statista, 2018, www.statista.com/statistics/279322/number-of-hospitals-in-china/. Accessed 18 Mar. 2018.

[3](equotemd, 2018) "Different Types of Hospitals and Hospital Medical Malpractice Insurance." EQuoteMD,18 Oct. 2011,www.equotemd.com/blog/different-types-of-hospitals-and-hospital-medical-malpractice-insurance/. Accessed 18 Mar. 2018.

[4] 秩名. NCI:差別年段的癌癥危險數據[N]. 生物資訊, 2015-08-06(1).

[5] "Cancer Mortality by Age." Cancer Research UK, 27 Sept. 2017, www.cancerresearchuk.org/health-professional/cancer-statistics/mortality/age#collapseZero. Accessed 16 Mar. 2018.

[6] Hall, Margaret, et al. "Trends in Inpatient Hospital Deaths: National Hospital Discharge Survey, 2000–2010." Centers for Disease Control and Prevention, National Center for Health Statistics, 24 May 2017, www.cdc.gov/nchs/products/databriefs/db118.htm. Accessed 16 Mar. 2018.

[7] Bernstein AB, Hing E, Moss AJ, Allen KF, Siller AB, Tiggle RB. Health care in America: Trends in utilization. Hyattsville, Maryland: National Center for Health Statistics. 2003.

[8]"Population Pyramids of the World: 2018." PopulationPyramid.net, 2018, www.populationpyramid.net/world/2018/. Accessed 17 Mar. 2018.

[9]"Cancer Incidence by Age." Cancer Research UK, 13 Feb. 2018, www.cancerresearchuk.org/healthprofessional/cancer-statistics/incidence/age#collapseZero.Accessed 16 Mar. 2018. [10] Niska, Richard, et al. "National Hospital Ambulatory Medical Care Survey: 2007 Emergency Department Summary." Centers for Disease Control and Prevention, 6 Aug. 2010, www.cdc.gov/nchs/data/nhsr/nhsr026.pdf. Accessed 16 Mar. 2018.

[11] Greenwood, Beth. "The Average Length of Doctors' Careers." Work - Chron.com, 19 Nov. 2012, work.chron.com/average-length-doctors-careers-13376.html. Accessed 18 Mar. 2018.

[12] "Physicians and Surgeons: Occupational Outlook Handbook." U.S. Bureau of Labor Statistics, 30 Jan. 2018, www.bls.gov/ooh/healthcare/physicians-and-surgeons.htm#tab-4. Accessed 18 Mar. 2018.

[13] Ryan, Camille L., and Kurt Bauman. "Educational Attainment in the United States: 2015." Census.gov, Mar. 2016,www.census.gov/content/dam/Census/library/publications/2016/demo/p20-578.pdf. Accessed 18 Mar. 2018.

[14] Buchmueller, Thomas, et al. "How far to the hospital? The effect of hospital closures on access to care." The National Bureau of Economic Research, 13 Dec. 2005, users.nber.org/~jacobson/Buchmuelleretal2006.pdf. Accessed 19 Mar. 2018.

[15] “Compare Hospitals.” Centers for Medicare & Medicaid Services, 31 Dec. 2016, .

Coding Results


General model Exp1:

f(x) = a*exp(b*x)

Coefficients (with 95% confidence bounds):

a = 0.4022 (0.03357, 0.7709)

b = 0.05434 (0.04035, 0.06834)

Goodness of fit:

SSE: 7.304

R-square: 0.9751

Adjusted R-square: 0.9709

RMSE: 1.103




Linear model Poly4:

f(x) = p1*x^4 + p2*x^3 + p3*x^2 + p4*x + p5

Coefficients (with 95% confidence bounds):

p1 = 0.00924 (-0.002183, 0.02066)

p2 = -1.743 (-3.695, 0.2092)

p3 = 94.22 (-12.19, 200.6)

p4 = -1054 (-3059, 951.4)

p5 = 1.356e+04 (2962, 2.416e+04)

Goodness of fit:

SSE: 6.131e+07

R-square: 0.9218

Adjusted R-square: 0.8437

RMSE: 3915

Part 3: Coding






function [ y ] =probability_of_incurable_desease( x )

y = 2.695*exp(1.331*x)



syms x












function [ y ] = percentage( x )

y=(231*x^4)/25000 - (1743*x^3)/1000 + (4711*x^2)/50 - 1054*x + 13560



syms x







C-3 (Visual Basic Code of the Hospital Evaluation Program):

Public Class frmMain

Const integralPrecision = 0.01

Dim compMortalityMatrix = {0.0097, 0.0451, 0.0627, 0.2345, 0.148}

Private Sub frmMain_Load(sender As Object, e As EventArgs) Handles MyBase.Load


End Sub

Private Sub rdbNetMortality_CheckedChanged(sender As Object, e As EventArgs) Handles rdbNetMortality.CheckedChanged

If rdbNetMortality.Checked Then

txtNetMortality.Enabled = True

txtMortality0_3.Enabled = False

txtMortality3_18.Enabled = False

txtMortality18_30.Enabled = False

txtMortality30_60.Enabled = False

 txtMortality60.Enabled = False


txtNetMortality.Enabled = False

txtMortality0_3.Enabled = True

txtMortality3_18.Enabled = True

txtMortality18_30.Enabled = True

txtMortality30_60.Enabled = True

txtMortality60.Enabled = True

End If

End Sub

Private Sub btnCalScore_Click(sender As Object, e As EventArgs) Handles btnCalScore.Click

Dim dist As Single = txtDist.Text

Dim mortalityScore As Single

If rdbNetMortality.Checked Then

mortalityScore = txtNetMortality.Text * 0.01


Dim compMortalities = {Val(txtMortality0_3.Text), Val(txtMortality3_18.Text), Val(txtMortality18_30.Text),

Val(txtMortality30_60.Text), Val(txtMortality60.Text)}

For i As Byte = 0 To 4

compMortalities(i) *= compMortalityMatrix(i) * 0.01

mortalityScore += compMortalities(i) ^ 2


mortalityScore ^= 0.5

End If

mortalityScore = 2.5 * (1 - mortalityScore)

Dim doctorAgeOffset As Byte = txtDoctorAvgAge.Text - 28

Dim doctorExperienceScore As Single = calTotalDoctorExp(doctorAgeOffset) * txtPatientPerDay.Text / txtDoctorNum.Text

doctorExperienceScore = 2.5 - 1 / doctorExperienceScore

Dim doctorCareScore As Single = calTotalDoctorExp(0.2 * doctorAgeOffset) - calTotalDoctorExp(0.2 * doctorAgeOffset - 8.5)

doctorCareScore *= (2.5 / 1.5) ^ 2

Dim distScore As Single

If txtDist.Text <= 3.78 Then

distScore = 2.5

ElseIf txtDist.Text <= 6.68 Then

distScore = 2.5 - 0.86 * (txtDist.Text - 3.78)

End If

lblScore.Text = distScore + mortalityScore + doctorCareScore + doctorExperienceScore

End Sub

Function calTotalDoctorExp(ByVal doctorAgeOffset As Single)

Dim a As Single

For i As Single = 0 To 0.7 * doctorAgeOffset Step integralPrecision

a += integralPrecision * Math.E ^ (-i ^ 2)


Return a

End Function

End Class

An Asymptotic Approach to the Analysis of Swings

Class 12(1B), John Xiaoshu Zhou, 2019/10, High School


King, A., Billingham, J., & Otto, S. (2003). Asymptotic Methods: Differential Equations. In Differential Equations: Linear, Nonlinear, Ordinary, Partial (pp. 303-371). Cambridge: Cambridge University Press. doi:10.1017/CBO9780511755293.013

Multi-purpose Foldable Crutch

Class 8(5), Guo HaoHui, 2017/12, Middle School






An Integrated Intelligent Medical Infusion Device Based on PLC

Class 7(1), Raymond Zheng Tang, Max Liu, Yuxiang Wu, 2017/12, Middle School



孔雪卉,張慧芬,焦婷婷. 一種智能輸液節制系統的設想[J]. 外洋電子丈量手藝,2014,33(06):73-77.




徐光憲,郭琳,陸偉. 智能輸液監控系統的設想與完成[J].激光雜志.2014,35(09):119-121.

楊光偉. 一種新型智能輸液監護系統的研制[D].南京航空航天大學,2012.



The Design and Construction of an Intelligent Selfie Robot

Class 7(8), Leo Lu2018/12, Middle School




OpenCV-Python Tutorials,

Supplementary materials

Codes in Python:

l Controlling the Servo:

import RPi.GPIO as GPIO

from time import sleep

def rotate_to(angle):


GPIO. setup(3, GPIO.OUT)

pwm = GPIO. PWM(3, 50) #Set input to pin 3

pwm.start(0) # Set movement to zero

duty = angle / 18 + 2.5 #Turn degrees (0-180) into signals (2.5~12.5)

pwm.ChangeDutyCycle(duty) # Set the Duty Cycle (Rotation)

GPIO.output(3, True)


GPIO.output(3, False)



GPIO.cleanup() # End

l Controlling the Vehicle:

import RPi.GPIO as g

import time

import sys

dirm = 4

dirnm = 25

powerm = 10

powernm = 17

#m is the labeled side, nm is the unlabeled side

cc = 1/100 #Convert Constant, convert degrees into turning time




#set basic parameters

def forward(t):


g.output(dirnm,g.HIGH) #control “direction”

g.output([powerm,powernm],g.HIGH) #control “enabled”


g.output([powerm,powernm],g.LOW) #stop the rotation

def backward(t):






def turnright(d):

t = d * cc





def turnleft(d):

t = d * cc





l Code for Face Detection:

import time

import io  #”Input and Output” Module

import picamera

import numpy as np

import cv2

if __name__ == '__main__': #Determine whether the program is running individually

#Use the preset face detection model

face_cascade = cv2.CascadeClassifier  ('/usr/local/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml')

# Use the preset eye detection model

eye_cascade = cv2.CascadeClassifier  ('/usr/local/share/OpenCV/haarcascades/haarcascade_eye.xml')

# Use the preset mouth detection model

eye_cascade = cv2.CascadeClassifier  ('/usr/local/share/OpenCV/haarcascades/haarcascade_mouth.xml')

with picamera.PiCamera() as camera:

 camera.rotation = 180

 camera.resolution = (640, 480)

 camera.framerate = 90

 camera.video_stabilization = True #Set basic parameters


stream = io.BytesIO() #Store “stream” into a buffer

for foo in camera.capture_continuous(stream,format='jpeg',use_video_port=True):

data = np.fromstring(stream.getvalue(), dtype=np.uint8) #Retrieve data

# Process the image so that it can be analyzed

image = cv2.imdecode(data, cv2.IMREAD_COLOR)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) #Save power with grayscale

 faces = face_cascade.detectMultiScale(gray, 1.3, 5) #Detect Faces

 cap = bool(len(faces))

for (x,y,w,h) in faces:


roi_gray = gray[y:y+h, x:x+w]

 roi_color = image[y:y+h, x:x+w]

eyes = eye_cascade.detectMultiScale(roi_gray) #Detect Eyes

 mouths = mouth_cascade.detectMultiscale(roi_gray) #Detect Mouths

if len(eyes) != 2 or len(mouths) != 1:

 cap = False

for (ex,ey,ew,eh) in eyes:


 for (mx,my,mw,mh) in eyes:


 if cap:

#If there’re any faces, with two eyes and a mouth per face, save the picture

 facesize = faces[0][2] * faces[0][3]

 _name = str(len(faces)) + “*” + str(facesize) #Name picture by its quality

 cv2.imwrite(“/home/pi/Desktop/” + _name + “. jpg”)  

cv2.imshow("img", image) #Show the picture

if cv2.waitKey(1) & 0xFF == ord('q'):

break #break when Ctrl+Q is pressed



cv2.destroyAllWindows() #Clear the program

l Filtering the Pictures:

def takefirst(elem):

return elem[0] #Order only according to the quality of the picture

def update():

import os, os.path

DIR = '/home/pi/Desktop/Pictures'

listofnames = []

q = []

for name in os.listdir(DIR):

if os.path.isfile(os.path.join(DIR,name)):

listofnames.append(name) #List all the names

if len(listofnames) > 10: #If there are too many pictures:

i = 0

for name in listofnames:

nq = name.split("*")

nq[1] = int(nq[1].replace(".jpg",""))

qe = int(int(nq[0]) * nq[1]) #Process name into (integer) quality

q.append((qe,i)) #Package data in the form of (Quality, Index)

i += 1

q = sorted(q,key = takefirst) #Sort the pictures from lowest to highest quality

last = q[0][1]

os.remove(os.path.join(DIR,listofnames[last])) #Remove the first picture

Pathogen Identification and Environmental Effects Analysis of Black Rot Disease of Imported Vietnamese ‘Red’ Pitaya

Class 7(11) Ashley Fan, Class 7(3) Yolanda Xing, Class 7(6) Ho Alicia, 2014/12, Middle School


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李敏, 胡美姣, 薛丁榕, 楊冬平, 楊波, 張正科, 趙超, 高兆銀(2013). 火龍果黑斑病菌 Bipolaris cactivora (Petrak) Alcorn 生物學特征研討. 寒帶作物學報, 34 (9): 1770~1775.

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章四平(2010) 效益看好, 火龍果另有擴種空間. 南邊鄉村報, 8~17.

鄭良永(2004). 海南島火龍果豐登種植手藝. 寒帶農業迷信, 24 (4): 36~41.

周真, 杜妍嫻, 李希清(2011). 玄色素與罕見病原真菌致病性的干系. 中國真菌學雜志, (6): 23.

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The Effect of Oral Administered Grape-Seed Extract on Cerebral Hypoperfusion Dementia in Mice

Class 8(10) Jiaxiao Gabriel Zhang, Class 8(1) Emily Jiang, Class 9(4) Qingyi Zhou

2016/12, Middle School


李齊歡. 補陽還五湯改良慢性腦缺血大鼠進修影象才能的研討[D].南邊醫科大學,2010.


Ahn, S.H., et al., Grape seed proanthocyanidin extract inhibits glutamate-induced cell death through inhibition of calcium signals and nitric oxide formation in cultured rat hippocampal neurons. BMC Neurosci, 2011. 12: p. 78.

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Chen, C., et al., Oral administration of grape seed polyphenol extract restores memory deficits in chronic cerebral hypoperfusion rats. Behav Pharmacol, 2016.

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Ferruzzi, M.G., et al., Bioavailability of gallic acid and catechins from grape seed polyphenol extract is improved by repeated dosing in rats: implications for treatment in Alzheimer's disease. J Alzheimers Dis, 2009. 18(1): p. 113-24.

Gu, Y., et al., Potassium Aspartate Attenuates Brain Injury Induced by Controlled Cortical Impact in Rats Through Increasing Adenosine Triphosphate (ATP) Levels, Na+/K+-ATPase Activity and Reducing Brain Edema. Med Sci Monit, 2016. 22: p. 4894-4901.

Lian, Q., et al., Effects of grape seed proanthocyanidin on Alzheimer's disease in vitro and in vivo. Exp Ther Med, 2016. 12(3): p. 1681-1692.

Liang, Y., et al., Beneficial effects of grape seed proanthocyanidin extract on arterial remodeling in spontaneously hypertensive rats via protecting against oxidative stress. Mol Med Rep, 2016. 14(4): p. 3711-8.

Long, M., et al., The Protective Effect of Grape-Seed Proanthocyanidin Extract on Oxidative Damage Induced by Zearalenone in Kunming Mice Liver. Int J Mol Sci, 2016. 17(6).

Narita, K, et al. Differential nueroprotective activity of two different grape seed extracts. 2011. 6(1)

Ren, Q., et al., Effects of erythropoietin on neonatal hypoxia-ischemia brain injury in rat model. Physiol Behav, 2016. 169: p. 74-81.

Sarkaki, A., et al., Improvement in Memory and Brain Long-term Potentiation Deficits Due to Permanent Hypoperfusion/Ischemia by Grape Seed Extract in Rats. Iran J Basic Med Sci, 2013. 16(9): p. 1004-10.

Wang, Y.J., et al., Consumption of grape seed extract prevents amyloid-beta deposition and attenuates inflammation in brain of an Alzheimer's disease mouse. Neurotox Res, 2009. 15(1): p. 3-14.

Zhang, Z., Y. Li and Y. Li, Grape seed proanthocyanidin extracts prevent hyperglycemia-induced monocyte adhesion to aortic endothelial cells and ameliorates vascular inflammation in high-carbohydrate/high-fat diet and streptozotocin-induced diabetic rats. Int J Food Sci Nutr, 2015. 67(5): p. 524-34.

Bacterium Improves the Efficiency of Root Regeneration in A. thaliana

Class 8(1), Yi-Ting Chen, 2017/12, Middle School


Birnbaum, K. D., and Sanchez Alvarado, A. (2008). Slicing across kingdoms: regeneration in plants and animals. Cell 132, 697–710.

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Molecular Tool to Improve the Root System for Stress Resistance

Liang Kaiqing, Tan, Jiaxin, 2017/12, Class 8(3), Middle School


范智勇, et al., 鹽勒迫和干旱勒迫對藍花子種子萌生和幼苗發展的影響. 南方園藝, 2011. 2: p. 7-10.

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EEG Results Indicate Quality of Sleep and Mood in the Elderly

Class 8(9) Christopher Cao, Class 8(5) Yusuke Atsuta, 2018/12, Middle School


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Appendix I. Profiles of Mood State (POMS) Questionnaire


Sex:  M F


Below is a list of words that describe feelings people have. Please CIRCLE THE NUMBER THAT BEST DESCRIBES HOW YOU FEEL DURING THE PAST WEEK (INCLUDING TODAY).

Not at all

A little


Quite a lot

















Worn Out


































































































Unable to concentrate























































































































Full of Pep




























Uncertain about things





















Scores for each item is recorded as follows: 0 for “not at all”, 1 for “a little”, 2 for “moderately”, 3 for “quite a lot” and 4 for “extremely”.

Tension; items 1, 8, 15, 21, 28, 35

Anger: items 2, 9, 16, 22, 29, 36, 37

Fatigue: items 3, 10, 17, 23, 30

Depression: items 4, 11, 18, 24, 31, 38

Vigor: items 5, 12, 19, 25, 32, 39

Confuse: items 6, 13, 20, 26, 33

Esteem-related affect: items 7, 14, 27, 34, 40

A Total Mood Disturbance (TMD) score = sum of the 5 negative subscales (tension, depression, fatigue, confuse, anger) – sum of the 2 positive subscales (vigor and esteem-related affect) + 100

Appendix IIThe Pittsburgh Sleep Quality Index (PSQI)

Instructions: The following questions relate to your usual sleep habits during the past week only. Your answers should indicate the most accurate reply for the majority of days and nights in the past week. Please answer all questions. During the past week,

1. When have you usually gone to bed? ______________

2. How long (in minutes) has it taken you to fall asleep each night? ______________

3. When have you usually gotten up in the morning? ______________

4. How many hours of actual sleep do you get at night? (This may be different than the number of hours you spend in bed) ______________

Please elect the best fit answer for the following questions:

5. During the past week, , how often have you had trouble sleeping   because you….

Not during the past week (0)

Less than once a week (1)

Once or twice a week (2)

Three or more times a week (3)

a. Cannot get to sleep within 30 minutes

b. Wake up in the middle of the night or early   morning

c. Have to get up to use the bathroom

d. Cannot breathe comfortably

e. Cough or snore loudly

f. Feel too cold

g. Feel too hot

h. Have bad dreams

i. Have pain

j. Other reason(s), please describe, including   how often you have had trouble sleeping because of this reason(s):

Very good (0)

Fairly good (1)

Fairly bad (2)

Very bad (3)

6. During the past week, how would you rate your sleep quality overall?

Not during the past week (0)

Less than once a week (1)

Once or twice a week (2)

Three or more times a week (3)

7. During the past week, how often have you taken medicine (prescribed or   “over the counter”) to help you sleep?

8. During the past week, how often have you had trouble staying awake   while driving, eating meals, or engaging in social activity?

No problem at all (0)

Only a very slight problem (1)

Somewhat of a problem (2)

A very big problem (3)

9. During the past week, how much of a problem has it been for you to   keep up enthusiasm to get things done?

The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire and was used to assess the subject’s sleep quality and disturbances over a one-week interval. Nineteen individual items generate seven component scores. The sum of these component scores yields one global PSQI score, with a range of 0 to 20 points. The higher the PSQI scores, the worse the sleep quality.

Scoring proceed as follows:

Component 1: Sleep quality

Examine question 6, and assign the scores as follows:

Response   Score

Very good 0

Fairly good 1

Fairly bad 2

Very bad 3

Component 2: Sleep latency

1. Examine question 2, and assign the scores as follows:

Response  Score

≤ 15min 0

16 – 30 min 1

31 – 60 min 2

> 60 min   3

2. Examine question 5a, and assign the scores as follows:

Response   Score

Not during the past week 0

Less than once a week 1

Once or twice a week 2

Three or more times a week 3

3. Assign component 2 score as follows:

Sum of 2 and 5a Score

0   0

1 – 2   1

3 – 4   2

5 – 6   3

Component 3: Sleep duration

Examine question 4, and assign the scores as follows:

Response   Score

> 7 hours  0

6 – 7 hours 1

5 – 6 hours 2

< 5 hours  3

Component 4: Habitual sleep efficiency

1. Calculate the number of hours spent in bed:

getting up time (Q3) – bed time (Q1)

2. Calculate habitual sleep efficiency (%):

(number of hours slept/number of hours spent in bed) × 100

3. Assign component 4 score as follows:

Habitual sleep efficiency Score

>85%  0

75 – 84%  1

65 – 74%   2

<65%   3

Component 5: Sleep disturbance

1. Examine question 5b – 5j, and assign scores for each question as follows:

Response   Score

Not during the past week 0

Less than once a week 1

Once or twice a week 2

Three or more times a week 3

2. Assign component 5 score as follows:

Sum of scores of 5b – 5j Score

0  0

1 – 9   1

10 – 18   2

19 – 27   3

Component 6: Use of sleep medication

Examine question 4, and assign the scores as follows:

Response  Score

Not during the past week 0

Less than once a week 1

Once or twice a week 2

Three or more times a week 3

Component 7: Daytime dysfunction

1. Examine question 8, and assign the scores as follows:

Response  Score

Not during the past week 0

Less than once a week 1

Once or twice a week 2

Three or more times a week 3

2. Examine question 9, and assign the scores as follows:

Response  Score

No problem at all 0

Only a very slight problem 1

Somewhat of a problem 2

A very big problem  3

3. Assign component 7 score as follows:

Sum of 8 and 9 Score

0  0

1 – 2   1

3 – 4   2

5 – 6   3

Global PSQI score = sum of scores of 1 - 7

Appendix III. The Brain Networks Differed Among Subjects

The four circles represent the four brain regions. We used arrows to indicate that the phases of EEG activity between the two brain regions are significantly synchronous (p<0.05). The top three indicate the brain networks of the first day during the 1st-3rd recordings, and the below three indicate the brain networks of the second day in the corresponding time periods.

The Effect of Excretory Factor EREG Released by Stromal Cells during Chemotherapy on the Malignant Phenotype of Prostate Cancer

Class 8(8) Run Yi Liu, Class 8(3) Helen Xiong, Middle School


董志偉 ,喬友林 ,李連弟 ,陳育德 ,王潤田 ,雷通海 ,饒克勤 ,王汝寬 ,趙平 ,游偉程 ,魯鳳珠 ,戴旭東 ,王國清 ,羅賢懋 ,周海城.中國癌癥節制戰略研討報告[J].中國醫學迷信院學報,2002(03):334.

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Baade, Peter D., et al. "Epidemiology of prostate cancer in the Asia-Pacific region." Prostate international 1.2 (2013): 47-58.

Boelens, Mirjam C., et al. "Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways." Cell 159.3 (2014): 499-513.

Chen, Wanqing, et al. "Cancer statistics in China, 2015." CA: a cancer journal for clinicians 66.2 (2016): 115-132.

Khodarev, Nikolai N., et al. "STAT1 is overexpressed in tumors selected for radioresistance and confers protection from radiation in transduced sensitive cells." Proceedings of the National Academy of Sciences 101.6 (2004): 1714-1719.

Mandair, Dalvinder, et al. "Prostate cancer and the influence of dietary factors and supplements: a systematic review." Nutrition & metabolism 11.1 (2014): 30.

Mitsudomi, Tetsuya, and Yasushi Yatabe. "Mutations of the epidermal growth factor receptor gene and related genes as determinants of epidermal growth factor receptor tyrosine kinase inhibitors sensitivity in lung cancer." Cancer science 98.12 (2007): 1817-1824.

Pines, Gur, Wolfgang J. K?stler, and Yosef Yarden. "Oncogenic mutant forms of EGFR: lessons in signal transduction and targets for cancer therapy." FEBS letters584.12 (2010): 2699-2706.

Ren, Shan-Cheng, Rui Chen, and Ying-Hao Sun. "Prostate cancer research in China." Asian journal of andrology 15.3 (2013): 350.

Revillion, F., et al. "ErbB/HER ligands in human breast cancer, and relationships with their receptors, the bio-pathological features and prognosis." Annals of oncology 19.1 (2007): 73-80.

Siegel, Rebecca L., Kimberly D. Miller, and Ahmedin Jemal. "Cancer statistics, 2017." CA: a cancer journal for clinicians 67.1 (2017): 7-30.

Sun, Yu, et al. "Treatment-induced damage to the tumor microenvironment promotes prostate cancer therapy resistance through WNT16B." Nature medicine 18.9 (2012): 1359.

Weichselbaum, Ralph R., et al. "An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer." Proceedings of the National Academy of Sciences 105.47 (2008): 18490-18495.

An Organoid Culture Based Investigation: The Prevention Mechanism of Tea Polyphenols on Prostate Cancer

Class 8(2), Ivan Yuan Junior, 2019/12, Middle School


崔濤, 高晶, 曾勇, 李薇, 伊秀林, 司端運,... 李大鵬. (2017). 薏苡仁油對人前線腺癌PC-3細胞的按捺感化. 中草藥, 48(21), 4460-4464

毛小強, 那萬里, 趙丹, 施朝齡, 于洋, 姜福全,... 王偉華. (2010). 茶多酚對前線腺癌PC-3M細胞增殖與凋亡的影響. 中國嘗試診斷學, 14(02), 170-173

張星海, & 楊賢強. (2003). 茶多酚及兒茶素對前線腺癌細胞發展的按捺感化. 茶葉(03), 142-144

Balk, S. P., & Knudsen, K. E. (2018). AR, the cell cycle, and prostate cancer. Nuclear Receptor Signaling, 6(1), 6001.

Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A. Jemal, A. (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians, 68(6), 394-424.

Chen, W., Zheng, R., Baade, P. D., Zhang, S., Zeng, H., Bray, F. He, J. (2016). Cancer statistics in China, 2015. CA: A Cancer Journal for Clinicians, 66(2), 115-132.

Gao, D., Vela, I., Sboner, A., Iaquinta, P. J., Karthaus, W. R., Gopalan, A.,... Arora, V. K. (2014). Organoid cultures derived from patients with advanced prostate cancer. Cell, 159(1), 176-187

Johnson, J. J., Bailey, H. H., & Mukhtar, H. (2010). Green tea polyphenols for prostate cancer chemoprevention: A translational perspective. Phytomedicine, 17(1), 3-13.

Khan, N., & Mukhtar, H. (2007). Tea polyphenols for health promotion. Life Sciences, 81(7), 519-533.

Magee, J. A., Chang, L., Stormo, G. D., & Milbrandt, J. (2006). Direct, Androgen Receptor-Mediated Regulation of the FKBP5 Gene via a Distal Enhancer Element. Endocrinology, 147(1), 590-598.

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Puca, L., Bareja, R., Prandi, D., Shaw, R., Benelli, M., Karthaus, W. R. Beltran, H. (2018). Patient derived organoids to model rare prostate cancer phenotypes. Nature Communications, 9(1).

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Xia, X., Li, F., He, J., Aji, R., & Gao, D. (2019). Organoid technology in cancer precision medicine. [Journal Article]. Cancer Lett, 457, 20-27.

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Decay of Urban Rail Transit-induced Ground-borne Vibration and Rapid Prediction Methods

Class 7(2), Ivan Yuan Junior, 2018/12, Middle School










王媛. 軌道交通計劃情況影響評估目標系統研討及其操縱[D].吉林大學, 2008

F. T. A. Office Of Planning And Environment, "Transit noise and vibration impact assessment. 2006.

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M. Sanayei, P. Maurya and J. A. Moore, "Measurement of building foundation and ground-borne vibrations due to surface trains and subways," Engineering Structures, vol. 53, pp. 2013, 102-111.

An Evaluation of Avian Species Diversity at Microforests of Nanhui Dongtan Wetlands in Terms of Human Disturbance and Edge Effect

Class 12(1A), Yasuhiko Komatsu Senior, 2018/12, High School


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[3] Gregory, R.D., Noble, D.G., Custance, J. (2004). The state of play of farmland birds: population trends and conservation status of lowland farmland birds in the United Kingdom.

[4] “Nanhui Dongtan.” ebird.org. The Cornell Lab of Ornithology. Web. 18 January 2019.


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Effects of Sleep Intervention and Herb Medication Ganwei on Behavioral and Biochemical Responses in Drosophila Alzheimer’s Disease Model

Class 11(1B), Lily Peng and Tina Mengting Liu, 2018/11, High School


1. Williams, J. A., Sathyanarayanan, S., Hendricks, J. C., & Sehgal, A. (2007). Interaction Between Sleep and the Immune Response in Drosophila: A Role for the NFκB Relish. Sleep, 30(4), 389–400. doi:10.1093/sleep/30.4.389

2. Ju YE, Lucey BP, Holtzman DM. Sleep and Alzheimer disease pathology—a bidirectional relationship. Nat Rev Neurol. 2014 Feb;10(2):115–9.

3. Mitolo, M., Tonon, C., La Morgia, C., Testa, C., Carelli, V., & Lodi, R. (2018). Effects of Light Treatment on Sleep, Cognition, Mood, and Behavior in Alzheimer’s Disease: A Systematic Review. Dementia and Geriatric Cognitive Disorders, 371–384. doi:10.1159/000494921

4. Ancoli-Israel S, Gehrman P, Martin JL, Shochat T, Marler M, Corey-Bloom J, et al. Increased light exposure consolidates sleep and strengthens circadian rhythms in severe Alzheimer’s disease patients. Behav Sleep Med. 2003a;1(1):22–36.

5. Ancoli-Israel S, Martin JL, Kripke DF, Marler M, Klauber MR. Effect of light treatment on sleep and circadian rhythms in demented nursing home patients. J Am Geriatr Soc. 2002 Feb;50(2):282–9.

6. Dowling GA, Hubbard EM, Mastick J, Luxenberg JS, Burr RL, Van Someren EJ. Effect of morning bright light treatment for rest-activity disruption in institutionalized patients with severe Alzheimer’s disease. Int Psychogeriatr. 2005a Jun;17(2):221–36

7. Satlin A, Volicer L, Ross V, Herz L, Campbell S. Bright light treatment of behavioral and sleep disturbances in patients with Alzheimer’s disease. Am J Psychiatry. 1992 Aug;149(8):1028–32.

8. Yamadera H, Ito T, Suzuki H, Asayama K, Ito R, Endo S. Effects of bright light on cognitive and sleep-wake (circadian) rhythm disturbances in Alzheimer-type dementia. Psychiatry Clin Neurosci. 2000 Jun;54(3): 352–3

9. Iaccarino, H. F., Singer, A. C., Martorell, A. J., Rudenko, A., Gao, F., Gillingham, T. Z., … Tsai, L. H. (2016). Gamma frequency entrainment attenuates amyloid load and modifies microglia. Nature, 540(7632), 230–235. doi:10.1038/nature20587

10. Onega LL, Pierce TW, Epperly L. Effect of Bright Light Exposure on Depression and Agitation in Older Adults with Dementia. Issues Ment Health Nurs. 2016 Sep;37(9):660–7.

11. Botanov, Yevgeny, and Stephen S Ilardi. “The acute side effects of bright light therapy: a placebo-controlled investigation.” PloS one vol. 8,9 e75893. 24 Sep. 2013, doi:10.1371/journal.pone.0075893

12. Terman, M., & Terman, J. S. (2005). Light Therapy for Seasonal and Nonseasonal Depression: Efficacy, Protocol, Safety, and Side Effects. CNS Spectrums, 10(8), 647–663. doi: 10.1017/s1092852900019611

13. Hanus J., Zhang H., Wang Z., Liu Q., Zhou Q., Wang S. Induction of necrotic cell death by oxidative stress in retinal pigment epithelial cells. Cell Death & Disease. 2013;4(12):p. e965. doi: 10.1038/cddis.2013.478.

14. Peng IF. 2018 GanWei, a hepatic lipidosis medication, improves sleep loss via alleviating oxidative stress. Personal Communications.

15. Collin F, Cheignon C, & Hureau C. (2018) Oxidative stress as a biomarker for Alzheimer’s disease. Biomarkers in Medicine, 12(3). doi: 10.2217/bmm-2017-0456.

16. Markesbery, W. R. (1999). The Role of Oxidative Stress in Alzheimer Disease. Archives of Neurology, 56(12), 1449. doi: 10.1001/archneur.56.12.1449

17. Pohanka, M. (2013). Alzheimer′s Disease and Oxidative Stress: A Review. Current Medicinal Chemistry, 21(3), 356–364. doi: 10.2174/09298673113206660258

18. Iijima K, Liu HP, Chiang AS, Hearn SA, Konsolaki M, Zhong Y. Dissecting the pathological effects of human Abeta40 and Abeta42 in Drosophila: a potential model for Alzheimer's disease. Proc Natl Acad Sci U S A. 2004 Apr 27;101(17):6623-8. Epub 2004 Apr 6. PMID: 15069204

19. Sehgal, A., Joiner, W., Crocker, A., Koh, K., Sathyanarayanan, S., Fang, Y., … Zheng, X. (2007). Molecular Analysis of Sleep: Wake Cycles in Drosophila. Cold Spring Harbor Symposia on Quantitative Biology, 72(1), 557–564. doi:10.1101/sqb.2007.72.018

20. Joan C. Hendricks,* Stefanie M. Finn, Karen A. Panckeri, Jessica Chavkin, Julie A. Williams, Amita Sehgal, and Allan I. Pack. Rest in Drosophila Is a Sleep-like State. Neuron, Vol.

21. Thimgan, M. S., Gottschalk, L., Toedebusch, C., McLeland, J., Rechtschaffen, A., Gilliland-Roberts, M., … Shaw, P. J. (2013). Cross-Translational Studies in Human and Drosophila Identify Markers of Sleep Loss. PLoS ONE, 8(4), e61016. doi:10.1371/journal.pone.0061016

22. Sheetal Potdar, Danita K. Daniel, Femi A. Thomas, Shraddha Lall, Vasu Sheeba, Behavioural Neurogenetics Laboratory, Evolutionary and Organismal Biology Unit, Neuroscience Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore, INDIA. Sleep deprivation negatively impacts reproductive output in Drosophila melanogaster. Journal of Experimental Biology. 4 January 2018. doi: 10.1242/jeb.174771.

The Effects of Vitamin C on SW480 Colon Cancer Cells In Vitro

Class 11(1B), Jayden Raymond Liu, 2015/5, High School


[1] BD Biosciences. Introduction to Flow Cytometry: A Learning Guide. <>, 2000.

[2] Ferreira D, Adega F, Chaves R. “The Importance of Cancer Cell Lines as in vitro Models in Cancer Methylome Analysis and Anticancer Drugs Testing”. Oncogenomics and Cancer Proteomics - Novel Approaches in Biomarkers Discovery and Therapeutic Targets in Cancer. <>, 2013.

[3] Futschik M, Jeffs A, Pattison S, Kasabov N, Sullivan M, Merrie A, Reeve A, (2002), “Gene Expression Profiling of Metastatic and Nonmetastatic Colorectal Cancer Cell Lines”, Genome Letters, vol. 1 (1), 26-34.

[4] National Cancer Institute. Colorectal Cancer – Patient Version. <>, 2015.

[5] National Cancer Institute. High-Dose Vitamin C. <>, 2015.

[6] National Institutes of Health, Office of Dietary Supplements. Vitamin C Fact Sheet for Consumers. <>, 2011.

[7] Padayatty SJ, Sun AY, Chen Q, Espey MG, Drisko J, Levin M, (2010), Vitamin C: intravenous use by complementary and alternative medicine practitioners and adverse effects, Public Library of Science One, 5(7).

[8] Phelan MC, (1998), Basic Techniques for Mammalian Cell Tissue Culture, Current Protocols in Cell Biology.

[9] Physical Sciences-Oncology Center Network Bioresource Core Facility. Thawing, Propagating, and Cryopreserving Protocol. <>, 2012.

[10] R&D Systems. Flow Cytometry Protocol for Analysis of Cell Viability using Propidium Iodide. <>, 2012.

[11] Riss TL, Moravec RA, Niles AL, et al. Cell Viability Assays – Assay Guidance Manual, National Center for Advancing Translational Sciences. <>, 2013.

[12] Sigma. Use of Trypan Blue Stain and the Hemocytometer to Determine Total Cell Counts and Viable Cell Number. <>, 2015.

[13] Stewart BW, Wild CP, (2014), World Cancer Report, International Agency for Research on Cancer, World Health Organization Press.

[14] Valko M, Leibfritz D, Moncol J, et al, (2007), Free radicals and antioxidants in normal physiological functions and human disease, International Journal of Biochemistry & Cell Biology, vol. 39 (1), 44-84.

[15] Yun J, Mullarky E, Lu C, Bosch KN, Kavalier A, et al, (2015), Vitamin C selectively kills KRAS and BRAF mutant colorectal cancer cells by targeting GAPDH, Science, vol. 350 (6266), 1391-1396.

The Inhibitory Effect of Chemical and Biological Food Preservatives on growth of Escherichia coli and Rhizopus stolonifer

Class 12(1B), Jessica Qu, 2017/1, High School


[1] Albrecht, Julie A. “Escherichia coli O157:H7”. Institute of Agriculture and Natural Resources. University of Nebraska-Lincoln. 23 July 2016. Web. <http://food.unl.edu/documents/Escherichinia%20coli%20O157%3AH7.pdf>.

[2] Andrews, Jennifer M. “Determination of minimum inhibitory concentrations”. Journal of Antimicrobial Chemotherapy (2001) 48, Suppl. S1, 5-16. The British Society for Antimicrobial Chemotherapy. 2001. Web. <http://jac.oxfordjournals.org/content/48/suppl_1/5.abstract>.

[3] Fothergill, P.G. and M.M. Yeomen. “The Mineral Nutrition of Rhizopus stolonifer”. J. gen. Microbiol. 17. Botany Department, King's College, Newcastle upon Tyne: 1957, p631-639. 23 July 2016. Web. <http://www.microbiologyresearch.org/docserver/fulltext/micro/17/3/mic-17-3-631.pdf?eexpire=1469250417&id=id&accname=guest&checksum=90E724A93EBBA62805D6942694ABDA96>.

[4] Hsu, S.C., J.L. Lockwood. “Mechanisms of Inhibition of Fungi in Agar by Streptomycetes”. J . gen. Microbiol. 57. Great Britain (1969): 149-158. 15 May 2016. Web. <http://www.microbiologyresearch.org/docserver/fulltext/micro/57/2/mic-57-2-149.pdf?expires=1463295180&id=id&accname=guest&checksum=565B7719EBA147597DFE263F8855B94A>.

[5] Jozala, Angela Faustino, L. Novaes and A. Pessoa Jr. “Chapter 5 Nisin”. Immunology and Microbiology ? "Concepts, Compounds and the Alternatives of Antibacterials". Edited by Varaprasad Bobbarala. ISBN 978-953-51-2232-6. 9 December, 2015. 20 July 2016. Web. <http://www.intechopen.com/source/html/48931/media/image1_w.jpg>.

[6] Li, Tao. Wei Gao. “Inhibition Effect of Three Kinds of Preservatives on Bacteria Using Orthogonal Experiment”. Journal of Shaanxi Normal University (Natural Science Edition). Vol 35, p28-29. June 2007. Article.

[7] Mendonca, Aubrey Francis. “Mechanism of inhibitory action of potassium sorbate in Escherichia coli”. Retrospective Theses and Dissertations. Paper 10207. 1992. 15 May 2016. Web. <http://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=11206&context=rtd>. “CICAD26 – Benzoic Acid and Sodium Benzoate”. World Health Organization. Geneva, 2000. Web. <http://www.who.int/ipcs/publications/cicad/cicad26_rev_1.pdf>.

[8] Russell, Nicholas J, Grahame W. Gould. “Bacteriocins – Nisin.” Food Preservatives. Boston, MA: Springer US, 2003: p149-150. Web. <http://books.google.com/books?id=RE_lBwAAQBAJ&pg=PA149&lpg=PA149&dq=nisin+optimum+condition&source=bl&ots=7uNbvL_stJ&sig=M9z6rqfj6GS_qOgMnq-w4TvSU4s&hl=en&sa=X&ved=0ahUKEwiH6ev73rTRAhVCn5QKHaw2D3kQ6AEIJDAB#v=onepage&q=nisin%20optimum%20condition&f=false>.

[9] Shi, Li-san, Qing-ping Wu, Hui-qing Wu, and Ju-mei Zhang. “Present Situation and Trend of Development on Food Preservatives in China”. Guangdong Institute of Microbiology, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application. March 2008. 15 May 2016. Web. <http://www.cnki.com.cn/Article/CJFDTotal-SPYK200803054.htm>.

[10] te Welscher,Yvonne M., Hendrik H. ten Napel, Miriam Masià Balagué, etc. “Natamycin Blocks Fungal Growth by Binding Specifically to Ergosterol without Permeabilizing the Membrane”. The Journal of Biological Chemistry (283), p6393-6401. 7 March 2008. 20 July 2016. Web. <http://www.jbc.org/content/283/10/6393.long#sec-1>.

[11] Troller, J. A. “Catalase inhibition as a possible mechanism of the fungistatic action of sorbic acid.” Can. J. Microbiol. 1965, 11:611-617.

[12] Widdel, Friedrich. “Theory and Measurement of Bacterial Growth.” Grundpraktikum Mikrobiologie, 4. Sem. (B.Sc.) Universit?t Bremen. 5 June 2010. 3 October 2016. Web. < http://www.mpi-bremen.de/Binaries/Binary13037/Wachstumsversuch.pdf>.

[13] “Ergosterol”. Wikipedia.org. 26 May 2016. 20 July 2016. Web. <http://en.wikipedia.org/wiki/Ergosterol>.

[14] “Escherichia coli”. Wikipedia.org. 13 July 2016. 20 July 2016. Web. <http://en.wikipedia.org/wiki/Escherichia_coli#Role_in_disease>.

[15] “Food Spoilage.” Wikipedia.org. 26 March 2016. 20 July 2016. Web. <http://en.wikipedia.org/wiki/Food_spoilage>.

[16] “Mold.” Wikipedia.org. 15 June 2016. 20 July 2016. Web. <http://en.wikipedia.org/wiki/Mold>.

[17] “Rhizopus stolonifer”. Wikipedia.org. 5 February 2016. 20 July 2016. Web. <http://en.wikipedia.org/wiki/Black_bread_mold>.

[18] “Scientific Opinion on the Use of Natamycin (E 235) as a food additive”. The EFSA Journal (2009); 7(12): 1412. 26 November 2009. 15 May 2016. Web. <http://www.efsa.europa.eu/sites/default/files/scientific_output/files/main_documents/1412.pdf>.

[19] “Sodium Benzoate.” Emerald Kalama Chemical, LLC Customer Service. Kalama, Washington. Rev 03, Page 02, File 75500125. 9 January 2017. Web. < http://doc.ccc-group.com/spec/800910.pdf>.

[20] “The use of nisin (E 234) as a food additive”. The EFSA Journal (2006) 314, 1-16. 26 January 2006. 15 May 2016. Web. <http://www.efsa.europa.eu/sites/default/files/scientific_output/files/main_documents/afc_op_ej314_nisin_op_en1,7.pdf>.

Research on EGFR Mutation Testing

Class 11(5), Tian Yang Zhou, 2017/09, High School







[6]  Cross DA, Ashton SE, Ghiorghiu S, Eberlein C, Nebhan CA, Spitzler PJ, Orme JP, Finlay MR, Ward RA, Mellor MJ, Hughes G, Rahi A, Jacobs VN, Red Brewer M, Ichihara E, Sun J, Jin H, Ballard P, Al-Kadhimi K, Rowlinson R, Klinowska T, Richmond GH, Cantarini M, Kim DW, Ranson MR, Pao W. AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resistance to EGFR inhibitors in lung cancer. Cancer Discov. 2014;4(9):1046–1061. doi: 10.1158/2159-8290.CD-14-0337.




[10]  http://www.thermofisher.com/cn/zh/home/life-thermofisher science/dna-rna-purification-analysis/dna-extraction/genomic-dna-extraction/dna-extractions-working-with-ffpe-samples.html









[19]  http://www.bio-rad.com/zh-cn/applications-technologies/digital-pcr-next-generation-sequencing-ngs

Mitigating Biodiversity Loss

Class 11(1B), Mingyi Suo, 2017/4, High School


1. Foreman, David. Rewilding North America: A Vision for Conservation in the 21st Century”. Island Press (2004).

2. Quammen, David. Planet of Weeds: Tallying the losses of Earth’s animals and plants. Harper’s Magazine (1998).

3. Wilson, E.O. Half-Earth: Our Planet's Fight for Life. Liveright Publishing Corporation (2016)

4. Pearce, Fred. The New Wild: Why Invasive Species Will Be Nature’s Salvation. Beacon Press (2015)

5. Fraser, Caroline. Rewilding the World: Dispatches from the conservation revolution. Metropolitan Books (2009)

6. Pounds, J Alan; Fogden, Michael P L; Campbell, John H. Biological response to climate change on a tropical mountain. Nature 398, 608–610 (1999)

7. Oregon Forests and Climate Change: An OSU Forestry & Natural Resources Extension project. (2016)

8. Blumstein, Daniel T. Isolation from mammalian predators differentially affects two congeners. Behavioral Ecology Vol. 13 No. 5: 657–663 (2002) http://www.eeb.ucla.edu/Faculty/Blumstein/pdf%20reprints/Blumstein%26Daniel_2002_BE.pdf

9. The Nature Conservancy. Reforestation Project Bears Fruit for Local Communities.

10. National Park Service. Wolf Restoration. (June, 9, 2017)

11. Meachen, Julie A., and Joshua X. Samuels. "Evolution in coyotes (Canis latrans) in response to the megafaunal extinctions.." Proceedings of the National Academy of Sciences of the United States of America 109.11 (2012): 4191-4196.

12. Zimmer, Carl. Bringing them back to life. Magazine, National Geographic.

13. Dolan et al. Pleistocene Rewilding: An Optimistic Agenda for Twenty-First Century Conservation. The American Naturalist, Vol. 168, No. 5 (November 2006), pp. 660-681. The University of Chicago Press.

14. Marris, Emma. Rambunctious Garden: Saving Nature in a Post-Wild World. Bloomsbury (2011)

15. Rohland et al. Genomic DNA Sequences from Mastodon and Woolly Mammoth Reveal Deep Speciation of Forest and Savanna Elephants. (December 2010)

16. Agenbroad, Larry D. North American Proboscideans: Mammoths: The state of Knowledge. . Volumes 126–128 react-text: 71, /react-text react-text: 72 2005 /react-text react-text: 73, Pages 73-92. (2003)

17. Zimov, Sergey A.; Zimov N. S.; Chapin F. S. III. The Past and Future of the Mammoth Steppe Ecosystem. Paleontology in Ecology and Conservation pp 193-225. (2012)


Investigate the Effect of E-Liquid, High Temperature Stress and UV-C Radiation Exposure on the Growth of Saccharomyces cerevisiae (Yeast)

Class 11(1B), Karen Mei Song, 2017/11, High School

References and Bibliography

[1] Centers for Disease Control and Prevention, USA.Heat-related deaths among crop workers--United States, 1992—2006. Mortal. Wkly. Rep. 2008; 57(24): 649-653.

[2] Choi K, Lazovich D, Southwell B, Forster J, Rolnick SJ, Jackson J, Arch Dermatol. Prevalence and characteristics of indoor tanning use among men and women in the United States. 2010 Dec; 146(12):1356-61.

[3] Clontech Laboratories. Yeast Protocols Handbook. Published July 2009. E-version.

[4] Engineering Statistics Handbook Critical Values of the Chi-Square Distribution.

[5] Environmental Protection Agency. Respiratory health effects of passive smoking: lung cancer

[6] Farsalinos KE, Polosa R. Safety evaluation and risk assessment of electronic cigarettes as tobacco cigarette substitutes: a systematic review. Ther Adv Drug Saf. 2014;5(2):67– 86. doi: 10.1177/2042098614524430

[7] Halliwell B, Gutteridge J. Free Radicals in Biology and Medicine. 4th edition. Oxford, UK: Oxford University Press; 2007.

[8] Laugesen M. (2008) Safety Report on the Ruyan? e-cigarette Cartridge and Inhaled Aerosol. 2008.

[9] Lin Xiang Qian. Technical Paper, UV Lamps in Laminar Flow and Biological Safety Cabinets. Singapore. 2002 October.

[10] Rastogi RP, Richa Kumar A, Tyagi MB, Sinha RP. Molecular mechanisms of ultraviolet radiation-induced DNA damage and repair. J Nucleic Acids. 2010; 2010:592980.

[11] Scientific Review of Ultraviolet (UV) Radiation, Broad Spectrum and UVA, UVB, and UVC.  National Toxicology Program, U.S. Department of Health and Human Service. Available at:

[12] Sigmoid Population Growth Curve.

[13] Valko M, Rhodes CJ, Moncol J, Izakovic M, Mazur M.Free radicals, metals and antioxidants in oxidative stress-induced cancer. Chem Biol Interact. 2006 Mar 10; 160(1):1-40.10.

[14] Westenberger B. Evaluation of e-Cigarettes. St. Louis, MO: Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research, Division of Pharmaceutical Analysis. 2009. 

Surface Electromyogram Analysis of Muscle Reactivity During Tennis Top-spin Serve

Jiayi Zhang, Huayi Zhang, High School


[1] Matsunaga, N., Imai, A., &Kaneoka, K. (2017). Comparison of muscle synergies before and after 10 minutes of running. Journal of physical therapy science, 29(7), 1242-1246.

[2] Sorbie, G. G., Grace, F. M., Gu, Y., Baker, J. S., &Ugbolue, U. C. (2018). Electromyographic analyses of the erector spinae muscles during golf swings using four different clubs. Journal of sports sciences, 36(7), 717-723.

[3] Yanjun, Liu. Electromyogram of Table Tennis Basic Techniques. Journal of Tianjin Institute of Physical Education. 1995(03):18-21.

[4] 周萌然. 網球上旋發球手藝的生物力學闡發.東北大學,2011

[5] 郭全清. 青年男人網球活動員首要舉措的肌電闡發與操縱.北京體育大學,2006.

[6] Yongdong, Qian. Surface EMG Analysis of Tennis Players’ Service. Journal of Jilin Institute of Physical Education,2013,29(01):66-68.

[7] Hui, Liu. Sports Biomechanical Principles of Power Serve Technique in Tennis,Journal of Beijing University of Physical Education,2000(02):173-176+180.

[8] Bo-tao,YAN, &Zao, LI Tennis Serve Movement and Its Basic Technique Patterns. China Sport Science And Technology, 2001(10):37-41.

[9] 陳鍇. 網球發球手藝技能闡發.《體育科研》2004年第2期(總第94期).:甘肅省體育迷信學會,2004:3.

[10] Chun-lin,Jin,&Feng,QU. A Biomechanical Analysis of Bai Yan's Tennis Service Technique, Journal of Beijing Sport University,2008(02):271-274.

[11] Zhuoshi, Wang. Man Shot Athletes’ Main Muscle Mass Surface EMG Analysis During Sliding Stage of Shot-putting. Capital Institute of Physical Education, 2013.

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