2022小美赛赛题的移动云盘下载地址 7 U6 B: ~1 O: k( M
https://caiyun.139.com/m/i?0F5CJAMhGgSJx3 V# E3 P, C# ?% r2 U4 J8 Z
7 N/ b# l* b; W( t" T2022 $ a1 r7 k5 f3 U1 o! ^/ _- ECertifificate Authority Cup International Mathematical Contest Modeling ) C3 F# q) ~: Whttp://mcm.tzmcm.cn" d+ }0 K. K, J& T: e( x, C* J7 e
Problem A (MCM) ) T; b8 D. q/ u1 [How Pterosaurs Fly" I G) u/ q' J8 p! l
Pterosaurs is an extinct clade of flflying reptiles in the order, Pterosauria. They8 m: t$ b8 D8 [$ X7 U
existed during most of the Mesozoic: from the Late Triassic to the end of, t3 \' c, ` l1 ^0 Y
the Cretaceous. Pterosaurs are the earliest vertebrates known to have evolved - r$ G# n4 T( ]: E4 t6 r; {9 d3 Upowered flflight. Their wings were formed by a membrane of skin, muscle, and) w- ~, B: a' W. p5 j
other tissues stretching from the ankles to a dramatically lengthened fourth5 A" m. G& @* Z9 J3 k/ w
fifinger[1]. $ Z( V$ C$ m& ^; p+ cThere were two major types of pterosaurs. Basal pterosaurs were smaller ; G% G+ D, I6 \! h+ janimals with fully toothed jaws and long tails usually. Their wide wing mem" B I' o/ E% h! E2 F1 X5 J
branes probably included and connected the hind legs. On the ground, they 5 p/ G' x p0 [' Zwould have had an awkward sprawling posture, but their joint anatomy and0 c1 M- K4 Q) v0 u5 Q
strong claws would have made them effffective climbers, and they may have lived" x$ i, h) G" D+ H: y. {
in trees. Basal pterosaurs were insectivores or predators of small vertebrates.7 |9 Z: M. \9 ]; ]
Later pterosaurs (pterodactyloids) evolved many sizes, shapes, and lifestyles. ( E: d% w4 T5 j$ s/ y: _6 tPterodactyloids had narrower wings with free hind limbs, highly reduced tails,: K# s6 @$ |9 D3 }5 t3 c. ?+ ]
and long necks with large heads. On the ground, pterodactyloids walked well on / L4 H0 s6 ?! z2 V" mall four limbs with an upright posture, standing plantigrade on the hind feet and% f9 ~/ N, N5 ?% k, d9 E2 i
folding the wing fifinger upward to walk on the three-fifingered “hand”. The fossil8 ` m/ g# K% X
trackways show at least some species were able to run and wade or swim[2]./ C; V z$ C! Y; c; V+ H, v$ {
Pterosaurs sported coats of hair-like fifilaments known as pycnofifibers, which $ R$ T$ f+ V! n, N3 Icovered their bodies and parts of their wings[3]. In life, pterosaurs would have5 C1 h, V' q( H. V( R
had smooth or flfluffffy coats that did not resemble bird feathers. Earlier sug- s6 X# ^3 A$ D9 h* G5 ]3 Z
gestions were that pterosaurs were largely cold-blooded gliding animals, de , G4 q7 k6 b8 g& @: O' Nriving warmth from the environment like modern lizards, rather than burning1 o5 ]6 h# v; | U, V" _3 O
calories. However, later studies have shown that they may be warm-blooded % ]' \9 y3 c: ~& g/ j- B2 f(endothermic), active animals. The respiratory system had effiffifficient unidirec9 v3 P }! m' j
tional “flflow-through” breathing using air sacs, which hollowed out their bones6 B/ D% R9 b' Z! S' f& m5 w+ K
to an extreme extent. Pterosaurs spanned a wide range of adult sizes, from , H% O; \& [- m+ j* cthe very small anurognathids to the largest known flflying creatures, including , N- [0 p# Q5 L: LQuetzalcoatlus and Hatzegopteryx[4][5], which reached wingspans of at least% A- y+ T$ Q+ I3 r; U; {% @/ {! K& X
nine metres. The combination of endothermy, a good oxygen supply and strong$ I1 `# q3 y# y8 ^" c9 q0 H
1muscles made pterosaurs powerful and capable flflyers. ' s6 [" b8 G3 Q' q1 Z& p5 aThe mechanics of pterosaur flflight are not completely understood or modeled6 Y2 Y' j, S( z7 M3 s9 B
at this time. Katsufumi Sato did calculations using modern birds and concluded " }7 z! l+ H, v0 ethat it was impossible for a pterosaur to stay aloft[6]. In the book Posture, " u6 N; U4 x7 K+ jLocomotion, and Paleoecology of Pterosaurs it is theorized that they were able) e- V; s4 m3 c
to flfly due to the oxygen-rich, dense atmosphere of the Late Cretaceous period[7]. 7 q+ S/ b9 h! b- t6 `! pHowever, both Sato and the authors of Posture, Locomotion, and Paleoecology c4 J2 Q; B+ M0 s9 U
of Pterosaurs based their research on the now-outdated theories of pterosaurs 3 p6 Y" U4 W6 l% R( c- I4 @being seabird-like, and the size limit does not apply to terrestrial pterosaurs, 3 l: C2 w6 x6 m( T/ b6 b' x% ?* wsuch as azhdarchids and tapejarids. Furthermore, Darren Naish concluded that V2 P( h9 G7 _. O! u! _
atmospheric difffferences between the present and the Mesozoic were not needed6 o& H: v9 L1 ]0 n ?" \9 Y- k
for the giant size of pterosaurs[8].7 f/ f& W( E# z, a/ X4 u
Another issue that has been diffiffifficult to understand is how they took offff.8 \/ F$ U4 l" c9 _, `: k
If pterosaurs were cold-blooded animals, it was unclear how the larger ones: |- X! R4 ~0 c0 \
of enormous size, with an ineffiffifficient cold-blooded metabolism, could manage 6 o8 |+ F) S0 za bird-like takeoffff strategy, using only the hind limbs to generate thrust for ; B" j7 e+ W" ]# Dgetting airborne. Later research shows them instead as being warm-blooded . H' U, l( e+ o3 L, e! Wand having powerful flflight muscles, and using the flflight muscles for walking as% o* ^2 ?2 X; o0 t: q/ k
quadrupeds[9]. Mark Witton of the University of Portsmouth and Mike Habib of7 i0 \- \9 \* \* V5 O
Johns Hopkins University suggested that pterosaurs used a vaulting mechanism) [0 N( B, @7 Y; o0 |; | j
to obtain flflight[10]. The tremendous power of their winged forelimbs would z* v7 @- r: L9 V- w9 Qenable them to take offff with ease[9]. Once aloft, pterosaurs could reach speeds8 v( E, @. I. b# i+ ~1 s
of up to 120 km/h and travel thousands of kilometres[10].9 F0 q8 Z& C; _$ f
Your team are asked to develop a reasonable mathematical model of the 3 ]1 X2 c. m9 g" [7 X$ aflflight process of at least one large pterosaur based on fossil measurements and& T" r$ m6 a5 T9 v) ^# i
to answer the following questions. 2 E/ J; f! w7 k6 ^' _2 W1. For your selected pterosaur species, estimate its average speed during nor; `9 O' y! o) d3 U
mal flflight.4 w: {, ]6 m& X
2. For your selected pterosaur species, estimate its wing-flflap frequency during% `3 V; h% Z% t* O0 F
normal flflight. * C! H& r6 n! y! S. T7 T5 ?3. Study how large pterosaurs take offff; is it possible for them to take offff like# v$ i$ S% G& p4 c6 E2 }, V
birds on flflat ground or on water? Explain the reasons quantitatively." Q0 ~$ N: M; i& [1 B
References7 p2 A( w: N A4 D( b0 [, _
[1] Elgin RA, Hone DW, Frey E (2011). The Extent of the Pterosaur Flight . X9 Z7 x7 M+ K* uMembrane. Acta Palaeontologica Polonica. 56 (1): 99-111. : A) j/ Z% a, g/ J2[2] Mark Witton. Terrestrial Locomotion. ( \1 Y: k8 }; T# shttps://pterosaur.net/terrestrial locomotion.php! `! D' e. l: \8 I
[3] Laura Geggel. It’s Offiffifficial: Those Flying Reptiles Called Pterosaurs 6 }+ P) U) l# A6 G1 K* E7 \Were Covered in Fluffffy Feathers. https://www.livescience.com/64324-8 t/ \/ p! _) q3 H: h; W5 b, u1 ]
pterosaurs-had-feathers.html. p4 f' m& M+ W
[4] Wang, X.; Kellner, A.W.A.; Zhou, Z.; Campos, D.A. (2008). Discovery of a # N6 u7 i Q' c2 K# arare arboreal forest-dwelling flflying reptile (Pterosauria, Pterodactyloidea) + ]7 G( N7 x0 E7 R" p. f. i! afrom China. Proceedings of the National Academy of Sciences. 105 (6):" n2 k4 X3 N6 y3 P6 K7 \3 r
1983-87. A3 i/ P* r( ^3 _% x! I% P[5] Buffffetaut E, Grigorescu D, Csiki Z. A new giant pterosaur with a robust , B( W3 M3 ]4 T, g, u/ Y1 p/ oskull from the latest cretaceous of Romania. Naturwissenschaften. 89 (4):8 p6 ]2 h3 L! w& ^. e
180-84. 7 `% ?2 T% @, H, c1 d! E( j( s[6] Devin Powell. Were pterosaurs too big to flfly? 3 a1 e/ o" H4 R. H& A& ^/ ]* nhttps://www.newscientist.com/article/mg20026763-800-were-pterosaurs! [' C L( B6 i0 U7 c
too-big-to-flfly/+ W% ^3 K' I6 y3 \1 h) ]" Z
[7] Templin, R. J.; Chatterjee, Sankar. Posture, locomotion, and paleoecology% s' ^0 M s7 f9 n
of pterosaurs. Boulder, Colo: Geological Society of America. p. 60. & \* m0 L& v" X- i7 X. y2 s[8] Naish, Darren. Pterosaurs breathed in bird-like fashion and had inflflatable5 R" w2 K2 F; Q# J4 I
air sacs in their wings.# W$ P4 H- c" ]/ B. X- i6 H' ~9 o
https://scienceblogs.com/tetrapodzoology/2009/02/18/pterosaur2 J$ E! C* ]7 h! N) w5 j
breathing-air-sacs' A% Q- Z' n* n, t$ N
[9] Mark Witton. Why pterosaurs weren’t so scary after all.; _1 o- o. }9 K: T
https://www.theguardian.com/science/2013/aug/11/pterosaurs-fossils 9 g1 B+ ^! w) L+ Nresearch-mark-witton " J4 U( f* n& h[10] Jeffff Hecht. Did giant pterosaurs vault aloft like vampire bats? 1 A' O/ U) e! o$ C$ ?5 `/ k1 C ^https://www.newscientist.com/article/dn19724-did-giant-pterosaurs & r3 A5 f" |5 A4 \0 v0 [9 v! F1 Qvault-aloft-like-vampire-bats/ " \! R$ c5 s' P 6 ~5 i* x3 a: p3 O5 R2022 # Z2 x) I [+ DCertifificate Authority Cup International Mathematical Contest Modeling # g+ I0 f! l* l h1 khttp://mcm.tzmcm.cn& W/ \7 J5 q4 T6 z6 E( T
Problem B (MCM)2 h( x& c" {* k0 {, ~
The Genetic Process of Sequences 6 o' X# p/ W% SSequence homology is the biological homology between DNA, RNA, or protein# v$ u) S. s* r# o3 d: i
sequences, defifined in terms of shared ancestry in the evolutionary history of4 f3 A. Y* _1 g' \ s% o; u# {
life[1]. Homology among DNA, RNA, or proteins is typically inferred from their! V ?& o. U% I$ _) F; x P
nucleotide or amino acid sequence similarity. Signifificant similarity is strong 7 w2 T; J; W1 ^/ \" xevidence that two sequences are related by evolutionary changes from a common ; e) z2 O |! r% D. N+ k4 n& e. ~ancestral sequence[2]. ' ?. S7 o8 o; w3 k; P5 mConsider the genetic process of a RNA sequence, in which mutations in nu 9 A# q6 P- A3 K: S0 pcleotide bases occur by chance. For simplicity, we assume the sequence mutation # d9 f3 z* I( O6 ^* }& iarise due to the presence of change (transition or transversion), insertion and9 u: w. U9 ?" n/ ?( X8 v
deletion of a single base. So we can measure the distance of two sequences by( O) I0 |5 [& h0 r. R
the amount of mutation points. Multiple base sequences that are close together % O7 f& m2 b( V: ~: Y# U' K- F) ?; Zcan form a family, and they are considered homologous. ' Z1 N) F& a9 V: }8 E+ `Your team are asked to develop a reasonable mathematical model to com" C: S8 e& _) N" a; z4 O8 W( H
plete the following problems.5 U/ H4 ]& K3 t2 M
1. Please design an algorithm that quickly measures the distance between & R3 I* `( D, p* Y! ctwo suffiffifficiently long(> 103 bases) base sequences. ! ?, i$ L6 X& w% H+ g2. Please evaluate the complexity and accuracy of the algorithm reliably, and {8 f4 Z% Y; m$ R- Z
design suitable examples to illustrate it.* h$ v+ L' d9 c: x4 V5 C
3. If multiple base sequences in a family have evolved from a common an, P+ j) p6 g. J; U0 @
cestral sequence, design an effiffifficient algorithm to determine the ancestral3 A9 |3 z6 P# c! ?* S7 G$ D! x k, `
sequence, and map the genealogical tree. / {; j1 H; [3 Y- K& K- e3 `% `References ) m% t1 ] B) j; }- z& c[1] Koonin EV. “Orthologs, paralogs, and evolutionary genomics”. Annual Re2 T* Q( b& ?+ k" h' N1 `6 h
view of Genetics. 39: 30938, 2005. & V+ r: n# N2 a/ }# j[2] Reeck GR, de Han C, Teller DC, Doolittle RF, Fitch WM, Dickerson RE," S1 [2 k0 N. W0 e+ d# t$ J
et al. “Homology” in proteins and nucleic acids: a terminology muddle and; X1 m, @% I& P, O7 y' H; r2 a
a way out of it. Cell. 50 (5): 667, 1987.* n1 V* r7 ~, X7 Y
( t; x$ N* Z" Y. A* y5 }20226 Z; Y3 ?1 Q, l" `( v' J; D1 Y
Certifificate Authority Cup International Mathematical Contest Modeling 6 e0 F( o$ L- L, w ^http://mcm.tzmcm.cn' r2 ~& K9 |2 L+ p7 n
Problem C (ICM) ! r" x1 F( \: `Classify Human Activities , |: G3 O- R+ U+ w9 {/ POne important aspect of human behavior understanding is the recognition and o1 Z3 |4 k1 [3 W4 L5 R/ y. d
monitoring of daily activities. A wearable activity recognition system can im ! ?% d: L/ |& c6 e& mprove the quality of life in many critical areas, such as ambulatory monitor 1 O# {+ @" Z+ _ing, home-based rehabilitation, and fall detection. Inertial sensor based activ . _$ [3 K4 K: r8 a7 N, k- [' |' Qity recognition systems are used in monitoring and observation of the elderly" _1 W& A# F$ @# a/ n& l& j) C
remotely by personal alarm systems[1], detection and classifification of falls[2],/ O! l3 p0 v% ^6 ~! ~
medical diagnosis and treatment[3], monitoring children remotely at home or in# u$ N1 j: w, v! E3 o
school, rehabilitation and physical therapy , biomechanics research, ergonomics,3 U! `1 c/ R8 r6 m- w! A9 J
sports science, ballet and dance, animation, fifilm making, TV, live entertain6 l' r! x& W2 T0 |1 }
ment, virtual reality, and computer games[4]. We try to use miniature inertial 4 s# P) f) k5 o' |# ~* [" Nsensors and magnetometers positioned on difffferent parts of the body to classify1 x4 `( [* S9 f- Z+ w. Z5 Z1 K
human activities, the following data were obtained.' e5 F+ j0 \7 [( f$ m
Each of the 19 activities is performed by eight subjects (4 female, 4 male, ) X+ S) |8 L! c) k/ d1 X% s3 Rbetween the ages 20 and 30) for 5 minutes. Total signal duration is 5 minutes 8 n& M) G/ y) l+ d5 E! Gfor each activity of each subject. The subjects are asked to perform the activ % I' {- ?5 Q! ^( u: l5 }, kities in their own style and were not restricted on how the activities should be 8 l/ Z( `# C! ]- M; Nperformed. For this reason, there are inter-subject variations in the speeds and s* L0 a* X+ y$ w
amplitudes of some activities. 2 g- }8 s8 y+ X! t1 X- G" f" xSensor units are calibrated to acquire data at 25 Hz sampling frequency." n, p) [/ t' o7 P7 c
The 5-min signals are divided into 5-sec segments so that 480(= 60 × 8) signal 2 \: W5 O7 {4 }7 Y2 J3 h( Usegments are obtained for each activity. : l( Z! N( R9 V0 T# SThe 19 activities are: $ _1 R4 `1 [" u: z7 t1. Sitting (A1);/ X! Q! C5 |/ d7 Y
2. Standing (A2); 3 d6 q+ k V7 n" i+ r3. Lying on back (A3); 7 R- }& Y0 o. M4 k8 O4. Lying on right side (A4);# ~# g$ s( U8 J8 e) o+ q
5. Ascending stairs (A5); # N G4 O+ U3 Q4 t J16. Descending stairs (A6);3 \ u# D4 o2 }0 n
7. Standing in an elevator still (A7); + V$ |( j+ c6 }" m! c* }8. Moving around in an elevator (A8);) h* I9 t0 d# t* h$ y' X! L4 y4 R- o
9. Walking in a parking lot (A9); , \3 }0 t# S( a8 V) J7 j, e10. Walking on a treadmill with a speed of 4 km/h in flflat position and 15 deg, @" E, Z6 O6 D0 \2 s E
inclined positions (A10); # Z, N5 N& v# \: x/ c11. Walking on a treadmill with a speed of 4 km/h in 15 deg inclined positions+ V, Z. U( g: o0 J+ o
(A11);, m. W# F; n1 b/ S0 ~) N0 Q+ i5 q
12. Running on a treadmill with a speed of 8 km/h (A12); 0 l* U- y7 I! ?3 Z6 b! i13. Exercising on a stepper (A13); - {) l4 y6 g7 `) A+ T y- O2 W14. Exercising on a cross trainer (A14); N& T" \' V6 q0 e9 D7 L; E
15. Cycling on an exercise bike in horizontal position (A15); / _( I3 \( \, M7 Z16. Cycling on an exercise bike in vertical position (A16);# W6 c k4 B# r; V( o; E
17. Rowing (A17);; X p, H* \6 X) x5 S9 ^7 n
18. Jumping (A18); & @3 K2 ~% b( Q1 |19. Playing basketball (A19). 3 O) V. N! e$ P6 M: P! K X5 |/ NYour team are asked to develop a reasonable mathematical model to solve - a& \. A/ r: Pthe following problems. # }2 G. d& n! n9 e! {. c( t& V1. Please design a set of features and an effiffifficient algorithm in order to classify + j$ A4 f- {( n6 T% Q% ^4 m" athe 19 types of human actions from the data of these body-worn sensors. a9 a6 d. H4 |. W K# n. m* R- t' J
2. Because of the high cost of the data, we need to make the model have ! c. e2 @( i, [a good generalization ability with a limited data set. We need to study5 M, f5 O9 V% b
and evaluate this problem specififically. Please design a feasible method to 1 T2 V/ L1 P4 D) Oevaluate the generalization ability of your model.' p6 a3 ~2 Z' L/ Q2 L& T
3. Please study and overcome the overfifitting problem so that your classififi-9 Y7 G, R! H7 p3 z! e
cation algorithm can be widely used on the problem of people’s action . ]8 V0 {0 b, E9 }; Jclassifification. " z5 B* }: H- O) eThe complete data can be downloaded through the following link:' f% }4 C7 S5 Q) T' m- W4 g
https://caiyun.139.com/m/i?0F5CJUOrpy8oq# _4 _# }/ m# ]3 R4 Q
2Appendix: File structure$ Y D! O7 G, O, c. Y, ?& N% U( \4 E
• 19 activities (a)4 d) O# g" l, B7 j1 \- u
• 8 subjects (p)% B( v' ^0 _$ h( A3 i
• 60 segments (s) 4 k3 w+ c5 \# w( L2 U$ H• 5 units on torso (T), right arm (RA), left arm (LA), right leg (RL), left3 {6 j) l2 R! N+ c6 ~- m. {# z
leg (LL) , W' I/ d* }- {• 9 sensors on each unit (x, y, z accelerometers, x, y, z gyroscopes, x, y, z Z9 \1 r# q* R1 u2 {
magnetometers)) }! r9 ^$ z# s: L5 y- g$ z& l
Folders a01, a02, ..., a19 contain data recorded from the 19 activities.. n; y* w5 h/ Z& W+ G' F2 M
For each activity, the subfolders p1, p2, ..., p8 contain data from each of the8 g% b$ `4 B3 ? F+ J4 A
8 subjects. # G" g6 d; h* Z' T2 MIn each subfolder, there are 60 text fifiles s01, s02, ..., s60, one for each : x7 Y5 [ v2 ?# w/ Q$ lsegment. 7 \1 B* |5 P; ^, B9 \& R2 mIn each text fifile, there are 5 units × 9 sensors = 45 columns and 5 sec × 25/ S* N: F/ k* M4 q& |* j0 F
Hz = 125 rows.9 W7 N( M8 c" w( q
Each column contains the 125 samples of data acquired from one of the" ~* {7 X7 S8 i- r0 c. q
sensors of one of the units over a period of 5 sec.' }. O$ Q/ B4 S# c8 v, h6 ]
Each row contains data acquired from all of the 45 sensor axes at a particular 1 e4 F I6 o- \% G4 d( Zsampling instant separated by commas. " ]- m q. P8 p* Y' e- Y# S' I" \Columns 1-45 correspond to:0 {* K4 q8 s- t5 G% m
• T_xacc, T_yacc, T_zacc, T_xgyro, ..., T_ymag, T_zmag, , h, S$ n3 O2 F1 `" Q. X• RA_xacc, RA_yacc, RA_zacc, RA_xgyro, ..., RA_ymag, RA_zmag, / o2 ], V8 Z7 m0 E4 r• LA_xacc, LA_yacc, LA_zacc, LA_xgyro, ..., LA_ymag, LA_zmag, * h6 f- A1 S* ]• RL_xacc, RL_yacc, RL_zacc, RL_xgyro, ..., RL_ymag, RL_zmag,5 k' P/ \' b5 c6 j
• LL_xacc, LL_yacc, LL_zacc, LL_xgyro, ..., LL_ymag, LL_zmag.4 l! b* t0 C8 [% ?- `0 ^
Therefore,( t+ X8 S& y) A# ^, D3 M' J) m' k7 d
• columns 1-9 correspond to the sensors in unit 1 (T), $ _* z; s/ d" l• columns 10-18 correspond to the sensors in unit 2 (RA),0 C+ j0 ]. Q6 K/ W8 b' l$ _8 |# K
• columns 19-27 correspond to the sensors in unit 3 (LA),, {7 O% P- E& j: r. s1 y/ ~: K
• columns 28-36 correspond to the sensors in unit 4 (RL),: X0 g; D5 Y& H5 ^+ n+ [6 {
• columns 37-45 correspond to the sensors in unit 5 (LL)., D% S0 a2 J/ z# Z
3References- a. N% ^7 x5 c1 }+ G/ L A4 g0 e
[1] Mathie M.J., Celler B.G., Lovell N.H., Coster A.C.F. Classifification of basic & b; f5 w/ t0 {! j7 Ndaily movements using a triaxial accelerometer. Med. Biol. Eng. Comput.6 C- c- G U. N2 p$ ]2 _ J
42(5), 679-687, 2004 # x/ Z5 W0 ^5 @4 b5 S0 B[2] Kangas M., Konttila A., Lindgren P., Winblad I., Ja¨msa¨ T. Comparison of! j, n' b) }6 ^6 g
low-complexity fall detection algorithms for body attached accelerometers.- g9 i9 j3 r( Q4 b* s: V( M
Gait Posture 28(2), 285-291, 2008 / L3 q3 ~5 J# ?1 B4 t[3] Wu W.H., Bui A.A.T., Batalin M.A., Liu D., Kaiser W.J. Incremental diag 0 E5 p8 z) o. B4 jnosis method for intelligent wearable sensor system. IEEE T. Inf. Technol. ! g8 @% {9 l; Z! ~% f# G$ F: OB. 11(5), 553-562, 2007+ B F7 ^) A* d
[4] Shiratori T., Hodgins J.K. Accelerometer-based user interfaces for the con, `2 a) F$ I7 u+ k0 d: ]: o5 O0 J
trol of a physically simulated character. ACM T. Graphic. 27(5), 2008 3 O D2 o9 I8 A- X8 a+ h; D2 e% k( e! X% B U) _3 x1 W
2022: v4 M6 T6 T1 A6 [1 T
Certifificate Authority Cup International Mathematical Contest Modeling6 ?) E7 ^6 Z7 c* l! |" K' ?
http://mcm.tzmcm.cn+ ]2 `$ e" t4 Z$ `
Problem D (ICM) ' z; ]: `* ^0 z RWhether Wildlife Trade Should Be Banned for a Long. _# @6 q0 F7 Y( l( F
Time% v$ i2 A1 ^' y' t( ]( C
Wild-animal markets are the suspected origin of the current outbreak and the3 X' S. u9 \! N) U& ~
2002 SARS outbreak, And eating wild meat is thought to have been a source , G* |( o4 o* w& D* x- ~- mof the Ebola virus in Africa. Chinas top law-making body has permanently 1 z/ {# s7 q$ R$ O# t. i& {9 ~tightened rules on trading wildlife in the wake of the coronavirus outbreak,) T6 ]- U% l1 G$ L
which is thought to have originated in a wild-animal market in Wuhan. Some. n) g2 C8 _& G/ q- e# u
scientists speculate that the emergency measure will be lifted once the outbreak 3 ~1 R1 g+ P- g5 {% y* ]+ O' p" Cends. $ J* `2 c0 x2 k- O! PHow the trade in wildlife products should be regulated in the long term? . d. ~9 r+ Q0 nSome researchers want a total ban on wildlife trade, without exceptions, whereas' r9 Q! x r, ?: B9 W
others say sustainable trade of some animals is possible and benefificial for peo 7 [2 V& b3 l/ I1 }( L- Fple who rely on it for their livelihoods. Banning wild meat consumption could . [# ^, V" ~+ c5 L7 U0 pcost the Chinese economy 50 billion yuan (US $ 7.1 billion) and put one mil% W) H5 |' N1 N3 [; q2 }, J1 X
lion people out of a job, according to estimates from the non-profifit Society of0 u+ X# {0 ~. i- t' |8 J
Entrepreneurs and Ecology in Beijing. 7 U/ b' L$ I4 C$ z X4 q R7 \A team led by Shi Zheng-Li and Cui Jie of the Wuhan Institute of Virology" {3 p/ ]0 F$ `
in China, chasing the origin of the deadly SARS virus, have fifinally found their - X5 E* s/ M. w1 L8 ^smoking gun in 2017. In a remote cave in Yunnan province, virologists have : I+ P9 J" S6 C" ?; |% Lidentifified a single population of horseshoe bats that harbours virus strains with" z6 }. h# ? \9 b0 M. x, s6 U
all the genetic building blocks of the one that jumped to humans in 2002, killing 0 Q8 E7 R# i* {almost 800 people around the world. The killer strain could easily have arisen 1 N: z* O$ m- G2 E- x/ ~from such a bat population, the researchers report in PLoS Pathogens on 30 " i! D% t. I* }4 @6 D# `$ F7 C* |" m; vNovember, 2017. Another outstanding question is how a virus from bats in# Z# p9 H( v6 Q
Yunnan could travel to animals and humans around 1,000 kilometres away in . g5 E% C" ^! L+ YGuangdong, without causing any suspected cases in Yunnan itself. Wildlife 1 _4 ^# X& W$ l9 ptrade is the answer. Although wild animals are cooked at high temperature, @2 C% d2 _3 b
when eating, some viruses are diffiffifficult to survive, humans may come into contact ' d# ^& X! B0 W" R1 `5 Twith animal secretions in the wildlife market. They warn that the ingredients ( h3 r2 a* z& G2 Dare in place for a similar disease to emerge again.) h+ C9 o! z8 i* t7 {7 ?
Wildlife trade has many negative effffects, with the most important ones being: 1 o9 B* h2 E( m1Figure 1: Masked palm civets sold in markets in China were linked to the SARS ' n$ s/ l$ `7 N( Goutbreak in 2002.Credit: Matthew Maran/NPL) B3 c' @9 u' f8 q& L
• Decline and extinction of populations" S! |1 i& }3 R/ P7 G
• Introduction of invasive species ( T: s+ ]1 J/ n+ |/ T4 e& G- p• Spread of new diseases to humans 7 w! z) P$ v6 ^ g9 V( j1 c, ^We use the CITES trade database as source for my data. This database: A- n! w. p# r' L2 N& K! u
contains more than 20 million records of trade and is openly accessible. The: \9 a5 c% U7 ?$ x6 `
appendix is the data on mammal trade from 1990 to 2021, and the complete , {+ p# B* ]7 o; N) ?database can also be obtained through the following link: 1 L1 C! w6 Y5 H# D9 v/ Lhttps://caiyun.139.com/m/i?0F5CKACoDDpEJ ) J3 X( D6 C n7 pRequirements Your team are asked to build reasonable mathematical mod9 O3 t1 L, [5 k( _
els, analyze the data, and solve the following problems:. b9 G0 x6 H7 F% c6 |
1. Which wildlife groups and species are traded the most (in terms of live 6 m; w, w1 m7 ?4 E6 H* xanimals taken from the wild)?. M" e; ^' v6 D: C) t* b
2. What are the main purposes for trade of these animals? . e- w+ o9 R! r U0 V% m3. How has the trade changed over the past two decades (2003-2022)? 6 f% a( I& A( N, i" b. T9 L: M4. Whether the wildlife trade is related to the epidemic situation of major. B' A# a g6 }/ U% L: v0 H
infectious diseases?- P& o' `+ ]: Q
25. Do you agree with banning on wildlife trade for a long time? Whether it1 ~4 Y t; j+ e) ^4 p/ [9 n; D
will have a great impact on the economy and society, and why? ; M% g, D3 M7 D/ b! A# a& x2 S" A6. Write a letter to the relevant departments of the US government to explain & s+ R. m. _3 Pyour views and policy suggestions.( N' `. [! W& U- y$ H
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