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Abstract

We introduce a novel method for map registration and apply it to transformation of the river Ister from Strabo’s map of the World to the current map in the World Geodetic System. This transformation leads to the surprising but convincing result that Strabo’s river Ister best coincides with the nowadays Tauernbach-Isel-Drava-Danube course and not with the Danube river what is commonly assumed. Such a result is supported by carefully designed mathematical measurements and it resolves all related controversies otherwise appearing in understanding and translation of Strabo’s original text. Based on this result, we also show that Strabo’s Suevi in the Hercynian Forest corresponds to the Slavic people in the Carpathian-Alpine basin and thus that the compact Slavic settlement was there already at the beginning of the first millennium AD.
Στράβωνος Γεωγραφικά
῎Ιστρος
῎Ιστρος ῥέων πρὸς νότον κατ᾿ ἀρχάς εἶτ᾿ ἐπιστρέφων εὐθὺς ἀπὸ
τῆς δύσεως ἐπὶ τὴν ἀνατολὴν καὶ τὸν Πόντον ἄρχεται μὲν οὖν ἀπὸ
τῶν Γερμανικῶν ἄκρων τῶν ἑσπερίων πλησίον δὲ καὶ τοῦ μυχοῦ τοῦ
᾿Αδριατικοῦ διέχων αὐτοῦ περὶ χιλίους σταδίους
χιλίους σταδίους
ἄκρων
γνησίους
γνήσιοι γὰρ οἱ Γερμανοὶ κατὰ τὴν ῾Ρωμαίων διάλεκτον
῾Ρῆνος
Σαβάτα
῎Οκρ῎Αλπεις
῎Αλπεια ῎Αλβια
᾿Ισάρας ῎Αταγι ς
῎Ιστρος
M1M2
y=Ax+b,
x=(x1,x
2)M1y=(y1,y
2)
M2
A=a1a2
a3a4
2×2
b=b1
b2
y1=a1x1+a2x2+b1,
y2=a3x1+a4x2+b2.
Ab
|y(Ax+b)|2
xM1yM2
x1,...,xny1,...,yn
n
i=1 (yi1a1xi1a2xi2b1)2+(yi2a3xi1a4xi2b2)2
a1,a
2,b
1,a
3,a
4b2
0
a1
n
i=1
2(yi1a1xi1a2xi2b1)(xi1)=0
a1
n
i=1
xi1xi1+a2
n
i=1
xi2xi1+b1
n
i=1
xi1=
n
i=1
yi1xi1
n
i=1
x2
i1
n
i=1
xi1xi2
n
i=1
xi1000
n
i=1
xi1xi2
n
i=1
x2
i2
n
i=1
xi2000
n
i=1
xi1
n
i=1
xi2n000
000
n
i=1
x2
i1
n
i=1
xi1xi2
n
i=1
xi1
000
n
i=1
xi1xi2
n
i=1
x2
i2
n
i=1
xi2
000
n
i=1
xi1
n
i=1
xi2n
a1
a2
b1
a3
a4
b2
=
n
i=1
yi1xi1
n
i=1
yi1xi2
n
i=1
yi1
n
i=1
yi2xi1
n
i=1
yi2xi2
n
i=1
yi2
Tpkpk,k =1,2,3
k=1
k=2 k=3
Tpk
pj={xi,yi;i=1,...,n
pj}
εpj
mean (Tpk)=1
npj
xipj
DEyi,Tpk(xi)2,
DEyi,Tpk(xi)yi
Tpk(xi)
εpj
max (Tpk)= max
xipj
DEyi,Tpk(xi).
Tpk
pj
pkεp1
mean (Tpk)εp2
mean (Tpk)εp3
mean (Tpk)
7.527 256.856 723.619
197.655 24.259 126.697
155.672 189.790 22.981
Tpk
pj
pkεp1
max (Tpk)εp2
max (Tpk)εp3
max (Tpk)
12.201 383.310 917.010
235.104 32.042 178.451
198.112 232.691 35.989
TpG
pG=p1p2p3
TpG
pk,k =1,2,3
TpG
pG
pkεpk
mean (TpG)εpk
max (TpG)
45.730 65.453
62.224 92.509
43.519 79.303
52.543 92.509
pk
Tpk
pG=p1p2p3
TpG
TpG
εpk
mean (TpG)εpk
max (TpG)k=1,2,3
xipk
pkk=1,...,n
pnp
M1pk
Tpk
pkM1
M1
Δu(x)=0,
u
a1,a
2,b
1,a
3,a
4,b
2
pk
Ω
Ω Ω M1
Ω
Tp1
p1
p1
p2p3
Tp2
p2
p2
p1p3
Tp3
p3
p3
p1p2
TpG
pG=p1p2p3
Ω
xi,j,i =1,...,N
1,j =1,...,N
2
M1E(pk)
pk
Δu(x)= 2u
∂x12(x)+ 2u
∂x22(x)
ui1,j 2ui,j +ui+1,j +ui,j12ui,j +ui,j+1
=ui1,j +ui+1,j 4ui,j +ui,j1+ui,j+1,
ui,j uxi,j
Ω
ui1,j =ui+1,j
Δu(x)ui+1,j 2ui,j +ui+1,j +ui,j12ui,j +ui,j+1
=2ui+1,j 4ui,j +ui,j1+ui,j +1
xi,j E(pk):ui,j =v(pk)
vAb
Tpk
xi,j ∈ E(pk)xi,j ∈ Ω:ui1,j ui,j1+4ui,j ui+1,j ui,j+1 =0
xi,j ∈ E(pk)i=1,j =1:4ui,j 2ui+1,j 2ui,j+1 =0
xi,j ∈ E(pk)i=1,j =N2:2ui,j1+4ui,j 2ui+1,j =0
xi,j ∈ E(pk)i=N1,j =1:2ui1,j +4ui,j 2ui,j +1 =0
xi,j ∈ E(pk)i=N1,j =N2:2ui1,j 2ui,j1+4ui,j =0
xi,j ∈ E(pk)i=N1,j =2,...,N
21:2ui1,j ui,j1+4ui,j ui,j+1 =0
xi,j ∈ E(pk)i=2,...,N
11,j =N2:ui1,j 2ui,j1+4ui,j ui+1,j =0
xi,j ∈ E(pk)i=2,...,N
11,j =1:ui1,j +4ui,j ui+1,j 2ui,j +1 =0
xi,j ∈ E(pk)i=1,j =2,...,N
21:ui,j1+4ui,j 2ui+1,j ui,j+1 =0
pkM1
pk
M1
M1M2
Ω A J
E(pk)
pk
CJΩ
p1p2p3
Tp1Tp2Tp3
῎Ιστρος
Λούγδουνον
῾Ροδανὸς
᾿Αδούλας
Λημέννα λίμνη
A={a1,...,anA}.
ai,i=1,...,n
A
A={
a1,...,
anA}
a1=a1,a1+a2
2,
ai=ai1+ai
2,aiai,ai+ai+1
2,i=2,...,n
A1,
anA=anA1+anA
2,anA,
u,v u v ai=|
ai|
LA
A
δH(A, B)
A={a1,...,anA}B={b1,...,bnB}
A={
a1,...,
anA}
B=
b1,...,
bnB
δH(A, B)= 1
LA
nA
i=1aimin
bj
B
DE(ai,
bj),
DE(ai,
bj)ai
bj
B
H(A, B)
H(A, B)= LAδH(A, B)+LBδH(B, A)
LA+LB
.
δH(A, B)
δH(A, B)= sup
aiA
inf
bj
B
DEai,
bj
H(A, B)
H(A, B)=max{δH(A, B)
H(B, A)}.
ai
A
dtB
Lm(A, B, dt)
Lm(A, B, dt)=
ai
Aai,
min
bj
B
DE(ai,
bj)<d
t.
x=1,2,3
300 km
ABδH(A, B)H(A, B)δH(A, B )H(A, B)
317.781 112.802
206.829 79.573
154.611 44.903
149.693 39.621
154.611 44.717
149.693 39.484
317.781 177.243
206.829 130.218
39.020 21.831
38.809 20.547
39.020 21.383
40.628 20.173
154.611 65.344
149.693 59.130
Lm(A, B, dt)
LAdt=10 dt=50 dt= 100
228.127 (8.4 ) 633.263 (23.3 ) 1114.154 (41.0 )
185.952 (13.0 ) 493.414 (34.7 ) 782.470 (55.0 )
207.040 (10.0 ) 563.339 (27.2 ) 948.312 (45.8 )
299.190 (14.7 ) 1285.049 (63.5 ) 1693.837 (83.7 )
267.783 (18.8 ) 1011.383 (71.1 ) 1247.252 (87.7 )
283.486 (16.4 ) 1148.216 (66.6 ) 1470.545 (85.4 )
320.930 (15.8 ) 1289.600 (63.6 ) 1698.389 (83.8 )
287.667 (20.2 ) 1011.383 (71.1 ) 1247.252 (87.7 )
304.299 (17.6 ) 1150.492 (66.7 ) 1472.821 (85.4 )
16.857 (1.1 ) 85.824 (5.9 ) 157.926 (11.0 )
24.146 (3.9 ) 99.998 (16.1 ) 153.185 (24.7 )
20.501 (2.0 ) 92.911 (9.0 ) 155.555 (15.1 )
87.920 (11.9 ) 737.609 (100.0 ) 737.609 (100.0 )
105.976 (17.1 ) 617.966 (100.0 ) 617.966 (100.0 )
96.948 (14.3 ) 677.788 (100.0 ) 677.788 (100.0 )
109.660 (14.7 ) 742.161 (100.0 ) 742.161 (100.0 )
125.860 (20.3 ) 617.966 (100.0 ) 617.966 (100.0 )
117.760 (17.3 ) 680.063 (100.0 ) 680.063 (100.0 )
211.270 (16.4 ) 547.439 (42.6 ) 956.228 (74.4 )
161.806 (20.1 ) 393.416 (48.9 ) 629.285 (78.3 )
186.538 (17.8 ) 470.428 (45.0 ) 792.757 (75.9 )
ABδH(A, B)H(A, B)δH(A, B )H(A, B)
278.962 116.695
194.446 92.584
198.848 66.131
189.915 57.998
198.848 65.625
189.915 56.683
278.962 157.633
194.446 125.898
54.656 35.270
66.735 35.623
54.656 33.857
70.863 32.194
198.848 96.661
189.915 88.555
Lm(A, B, dt)
LAdt=10 dt=50 dt= 100
61.260 (2.2 ) 481.784 (17.7 ) 948.962 (34.9 )
55.447 (3.8 ) 323.687 (22.4 ) 641.770 (44.5 )
58.353 (2.8 ) 402.736 (19.3 ) 795.366 (38.2 )
26.097 (1.2 ) 1082.523 (53.5 ) 1508.358 (74.5 )
26.768 (1.8 ) 852.692 (59.1 ) 1144.834 (79.4 )
26.433 (1.5 ) 967.608 (55.8 ) 1326.596 (76.6 )
41.406 (2.0 ) 1087.075 (53.6 ) 1512.910 (74.6 )
50.989 (3.5 ) 855.911 (59.3 ) 1144.834 (79.4 )
46.197 (2.6 ) 971.493 (56.0 ) 1328.872 (76.6 )
34.437 (2.4 ) 112.681 (7.8 ) 178.212 (12.4 )
25.465 (3.9 ) 90.754 (14.0 ) 143.805 (22.2 )
29.951 (2.8 ) 101.717 (9.7 ) 161.008 (15.5 )
0.000 (0.0 ) 713.419 (96.7 ) 737.609 (100.0 )
0.000 (0.0 ) 619.759 (95.8 ) 646.869 (100.0 )
0.000 (0.0 ) 666.589 (96.2 ) 692.239 (100.0 )
15.308 (2.0 ) 717.971 (96.7 ) 742.161 (100.0 )
24.221 (3.7 ) 622.978 (96.3 ) 646.869 (100.0 )
19.764 (2.8 ) 670.474 (96.5 ) 694.515 (100.0 )
26.097 (2.0 ) 369.103 (28.7 ) 770.749 (60.0 )
26.768 (3.3 ) 232.933 (29.3 ) 497.964 (62.6 )
26.433 (2.5 ) 301.018 (28.9 ) 634.357 (61.0 )
ABδH(A, B)H(A, B)δH(A, B )H(A, B)
296.586 117.455
205.818 92.198
219.255 84.164
205.818 74.903
219.255 83.610
205.818 74.175
296.586 145.940
194.015 115.984
101.197 65.823
94.308 60.811
101.197 64.181
94.308 58.773
219.255 112.879
205.818 99.975
Lm(A, B, dt)
LAdt=10 dt=50 dt= 100
46.134 (1.6 ) 327.386 (12.0 ) 911.606 (33.5 )
40.573 (2.7 ) 248.261 (16.9 ) 674.137 (45.9 )
43.354 (2.0 ) 287.824 (13.7 ) 792.871 (37.9 )
22.798 (1.1 ) 374.882 (18.5 ) 1390.515 (68.7 )
20.561 (1.4 ) 301.285 (20.5 ) 1130.088 (76.9 )
21.679 (1.2 ) 338.083 (19.3 ) 1260.301 (72.2 )
48.427 (2.3 ) 379.434 (18.7 ) 1395.067 (68.8 )
48.975 (3.3 ) 296.829 (20.2 ) 1130.088 (76.9 )
48.701 (2.7 ) 338.131 (19.3 ) 1262.577 (72.2 )
19.581 (1.3 ) 122.200 (8.5 ) 257.106 (17.9 )
10.404 (1.7 ) 57.143 (9.5 ) 144.355 (24.0 )
14.992 (1.4 ) 89.671 (8.8 ) 200.730 (19.7 )
0.000 (0.0 ) 191.060 (25.9 ) 727.479 (98.6 )
0.000 (0.0 ) 178.483 (29.7 ) 600.305 (100.0 )
0.000 (0.0 ) 184.771 (27.6 ) 663.892 (99.2 )
25.628 (3.4 ) 195.612 (26.3 ) 732.031 (98.6 )
28.413 (4.7 ) 174.027 (28.9 ) 600.305 (100.0 )
27.021 (4.0 ) 184.819 (27.5 ) 666.168 (99.2 )
22.798 (1.7 ) 183.821 (14.3 ) 652.906 (50.8 )
20.561 (2.3 ) 122.801 (14.1 ) 529.782 (61.0 )
21.679 (2.0 ) 153.311 (14.2 ) 591.344 (54.9 )
῾Ερκυνίου δρυμος
Σοήβων
ὅπου αἱ τοῦ ῎Ιστρου πηγαὶ πλησίον Σοήβων καὶ τοῦ ῾Ερκυνίου δρυμοῦ
ὥστ᾿ ἀνάγκη τῷ ἐκ τῆς Κελτικῆς ἐπὶ τὸν ῾Ερκύνιον δρυμὸν ἰόντι
πρῶτον μὲν διαπερᾶσαι τὴν λίμνην ἔπειτα τὸν ῎Ιστρον εἶτ᾿ ἤδη δι᾿
εὐπετεστέρων χωρίων ἐπὶ τὸν δρυμὸν τὰς προβάσεις ποιεῖσθαι δι᾿ ὀροπε-
δίων
ἔστι δὲ καὶ ἄλλη ὕλη μεγάλη Γαβρῆτα ἐπὶ τάδε τῶν Σοήβων ἐπέκεινα
δ᾿ ὁ ῾Ερκύνιος δρυμός ἔχεται δὲ κἀκεῖνος ὑπ᾿ αὐτῶν
Γαβρῆτα
οἱ τοίνυν ῞Ελληνες τοὺς Γέτας Θρᾷκας ὑπελάμβανον
εἶτ᾿ εὐθὺς ἡ τῶν Γετῶν συνάπτει γῆ κατ᾿ ἀρχὰς μὲν στενή παρατε-
ταμένη τῷ ῎Ιστρῳ κατὰ τὸ νότιον μέρος κατὰ δὲ τοὐναντίον τῇ παρωρείᾳ
τοῦ ῾Ερκυνίου δρυμοῦ
137 ×1.62 km = 222,24
Δίερνα
ΔΔίερνα
+
... Finally, we computed the velocities on the smoothed curves and used them as sparse samples to reconstruct the wound attractant field. Many different computational contexts require the reconstruction of vector fields from sparse samples: the applications of such a process include fluid dynamics visualization, texture synthesis, non-photorealistic rendering, optical flow fields, and map registration [10,20,25]. In [20], the authors proposed local piecewise polynomial approximations using least squares methods. ...
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In this paper, we propose a new workflow to analyze macrophage motion during wound healing. These immune cells are attracted to the wound after an injury and they move showing both directional and random motion. Thus, first, we smooth the trajectories and we separate the random from the directional parts of the motion. The smoothing model is based on curve evolution where the curve motion is influenced by the smoothing term and the attracting term. Once we obtain the random sub-trajectories, we analyze them using the mean squared displacement to characterize the type of diffusion. Finally, we compute the velocities on the smoothed trajectories and use them as sparse samples to reconstruct the wound attractant field. To do that, we consider a minimization problem for the vector components and lengths, which leads to solving the Laplace equation with Dirichlet conditions for the sparse samples and zero Neumann boundary conditions on the domain boundary.
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The genetic composition of the medieval populations of Central Europe has been poorly investigated to date. In particular, the region of modern-day Slovakia is a blank spot in archaeogenetic research. This paper reports the study of mitochondrial DNA (mtDNA) in ancient samples from the 9th–12th centuries originating from the cemeteries discovered in Nitra-Šindolka and Čakajovce, located in western Slovakia (Central Europe). This geographical region is interesting to study because its medieval multi-ethnic population lived in the so-called contact zone of the territory of the Great Moravian and later Hungarian state formations. We described 16 different mtDNA haplotypes in 19 individuals, which belong to the most widespread European mtDNA haplogroups: H, J, T, U and R0. Using comparative statistical and population genetic analyses, we showed the differentiation of the European gene pool in the medieval period. We also demonstrated the heterogeneous genetic characteristics of the investigated population and its affinity to the populations of modern Europe.
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Tufts University, based on Dio’s Roman History. Cassius Dio Cocceianus, Earnest Cary
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