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-rw-r--r--build/main.fdb_latexmk20
-rw-r--r--build/main.fls15
-rw-r--r--build/main.log104
-rw-r--r--build/main.pdfbin5600893 -> 5596084 bytes
-rw-r--r--build/main.synctex.gzbin58223 -> 57087 bytes
-rw-r--r--images/predictive_analytics.drawio6
-rw-r--r--images/predictive_analytics.pdfbin335934 -> 335776 bytes
-rw-r--r--images/predictive_analyticsv2.drawio120
-rw-r--r--images/predictive_analyticsv3.pdfbin0 -> 95062 bytes
-rw-r--r--indent.log2
-rw-r--r--main.tex35
11 files changed, 137 insertions, 165 deletions
diff --git a/build/main.fdb_latexmk b/build/main.fdb_latexmk
index 486e32d..1bbba74 100644
--- a/build/main.fdb_latexmk
+++ b/build/main.fdb_latexmk
@@ -1,13 +1,13 @@
# Fdb version 4
-["bibtex build/main"] 1782208852.95742 "build/main.aux" "build/main.bbl" "build/main" 1782225000.60861 0
+["bibtex build/main"] 1782227924.64445 "build/main.aux" "build/main.bbl" "build/main" 1782305532.3312 0
"./main.bib" 1781119362.6891 32876 5e1eedec56d981b65e768a05f0692d62 ""
"/usr/share/texmf-dist/bibtex/bst/is-bst/is-plain.bst" 1775415801 37711 8712640e4301c9b53f91a39ab688edfe ""
- "build/main.aux" 1782225000.41152 5050 46cb649df6ca2aab63d41795a8ac9c19 "pdflatex"
+ "build/main.aux" 1782305532.13776 5050 46cb649df6ca2aab63d41795a8ac9c19 "pdflatex"
(generated)
"build/main.bbl"
"build/main.blg"
(rewritten before read)
-["pdflatex"] 1782224997.75436 "main.tex" "build/main.pdf" "main" 1782225000.6088 0
+["pdflatex"] 1782305529.5948 "main.tex" "build/main.pdf" "main" 1782305532.3314 2
"/usr/share/texmf-dist/fonts/enc/dvips/base/8r.enc" 1775415801 4850 80dc9bab7f31fb78a000ccfed0e27cab ""
"/usr/share/texmf-dist/fonts/enc/dvips/fontawesome5/fa5free1.enc" 1775415801 3042 0e2b14b9be7d01075a4c4591d5d1781b ""
"/usr/share/texmf-dist/fonts/enc/dvips/inconsolata/i4-t1-0.enc" 1775415801 7631 5169ff1acd97ff1c4ab83563c99f96f4 ""
@@ -302,22 +302,22 @@
"/usr/share/texmf-dist/web2c/texmf.cnf" 1775415801 43569 fd570f2fa160877d211e859f687312ba ""
"/var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map" 1780237389 5385779 47c0c393a77fd4a098bacfd57d66b88a ""
"/var/lib/texmf/web2c/pdftex/pdflatex.fmt" 1780237370 2328183 557d2fa5c1c83b5f04dceecc4ca457bf ""
- "build/main.aux" 1782225000.41152 5050 46cb649df6ca2aab63d41795a8ac9c19 "pdflatex"
- "build/main.bbl" 1782208853.00252 7385 ebb376ed26be34664c64306358b7ab86 "bibtex build/main"
- "build/main.nav" 1782225000.41252 1853 736fbaf0126bafd9e7445f1462372559 "pdflatex"
- "build/main.out" 1782224998.47993 0 d41d8cd98f00b204e9800998ecf8427e "pdflatex"
+ "build/main.aux" 1782305532.13776 5050 46cb649df6ca2aab63d41795a8ac9c19 "pdflatex"
+ "build/main.bbl" 1782227924.69537 7385 ebb376ed26be34664c64306358b7ab86 "bibtex build/main"
+ "build/main.nav" 1782305532.13928 1853 736fbaf0126bafd9e7445f1462372559 "pdflatex"
+ "build/main.out" 1782305530.20664 0 d41d8cd98f00b204e9800998ecf8427e "pdflatex"
"images/23_Jun_2026_102028.pdf" 1782210125.33549 12607 a159742aca575be4b361dcd11784f215 ""
"images/datacenter_complexity.pdf" 1782047719.43552 3667720 d5ea274735f595adf176d3ce5526798d ""
"images/digital_twin_ms.pdf" 1781078756.05606 174463 377f3c625c4f63c8c509df84e9b2bf36 ""
"images/dt_timeline.pdf" 1781033378.83544 277735 13f78509d63b3e800ed0101349139483 ""
"images/manageability.pdf" 1781026281.55976 275244 e8fcf5d84108e954279a1e538263aab4 ""
- "images/predictive_analytics.pdf" 1781801281.18553 335934 9ed4cbe7a0fa00b0e8265123f6fa6cfb ""
- "images/predictive_analyticsv2.pdf" 1782058674.91488 99507 199631cabfde9c0846c053d7bd90a5b9 ""
+ "images/predictive_analytics.pdf" 1782305413.07306 335776 12df13eddddec6f331f31a0089b2bfa0 ""
+ "images/predictive_analyticsv3.pdf" 1782305294.55355 95062 f26da3d63ba0abdccded60740738ca34 ""
"images/ref_architecture.pdf" 1782056279.75492 651099 8066ebc0edadac6de05322be6cbea9d4 ""
"images/system_model2.pdf" 1782020796.08984 43289 388db566aa1478d75b3bdfe95ef0ed4c ""
"images/table.tex" 1782054172.48395 4995 288f66be57b9a9fa764c677bad26ce37 ""
"images/vu-logo.png" 1781010929.85668 10449 ae204138961425683f3b9a1cfd88554a ""
- "main.tex" 1782224996.11158 13890 740c2874c0e2f54ee7df4c7e8f5e8882 ""
+ "main.tex" 1782305529.02561 13853 1849eefdf5c560e5542251e86d7fab9f ""
"style/style.tex" 1782210287.63049 2568 b493915cd9362cb0148ab77563da8eb4 ""
(generated)
"build/main.aux"
diff --git a/build/main.fls b/build/main.fls
index 9f3689a..6fdf722 100644
--- a/build/main.fls
+++ b/build/main.fls
@@ -741,20 +741,15 @@ INPUT ./images/vu-logo.png
INPUT ./images/vu-logo.png
INPUT ./images/vu-logo.png
INPUT ./images/vu-logo.png
-INPUT /usr/share/texmf-dist/fonts/tfm/adobe/helvetic/phvb8t.tfm
-INPUT ./images/predictive_analyticsv2.pdf
-INPUT ./images/predictive_analyticsv2.pdf
-INPUT ./images/predictive_analyticsv2.pdf
-INPUT ./images/predictive_analyticsv2.pdf
-INPUT ./images/predictive_analyticsv2.pdf
+INPUT ./images/predictive_analyticsv3.pdf
+INPUT ./images/predictive_analyticsv3.pdf
+INPUT ./images/predictive_analyticsv3.pdf
+INPUT ./images/predictive_analyticsv3.pdf
+INPUT ./images/predictive_analyticsv3.pdf
INPUT ./images/vu-logo.png
INPUT ./images/vu-logo.png
INPUT ./images/vu-logo.png
INPUT ./images/vu-logo.png
-INPUT /usr/share/texmf-dist/fonts/vf/adobe/helvetic/phvb8t.vf
-INPUT /usr/share/texmf-dist/fonts/tfm/adobe/helvetic/phvb8r.tfm
-INPUT /usr/share/texmf-dist/fonts/vf/adobe/helvetic/phvro8t.vf
-INPUT /usr/share/texmf-dist/fonts/tfm/adobe/helvetic/phvro8r.tfm
INPUT ./images/23_Jun_2026_102028.pdf
INPUT ./images/23_Jun_2026_102028.pdf
INPUT ./images/23_Jun_2026_102028.pdf
diff --git a/build/main.log b/build/main.log
index 89de703..d3502fd 100644
--- a/build/main.log
+++ b/build/main.log
@@ -1,4 +1,4 @@
-This is pdfTeX, Version 3.141592653-2.6-1.40.29 (TeX Live 2026/Arch Linux) (preloaded format=pdflatex 2026.5.31) 23 JUN 2026 16:29
+This is pdfTeX, Version 3.141592653-2.6-1.40.29 (TeX Live 2026/Arch Linux) (preloaded format=pdflatex 2026.5.31) 24 JUN 2026 14:52
entering extended mode
restricted \write18 enabled.
file:line:error style messages enabled.
@@ -1184,8 +1184,20 @@ File: images/predictive_analytics.pdf Graphic file (type pdf)
<use images/predictive_analytics.pdf>
Package pdftex.def Info: images/predictive_analytics.pdf used on input line 37.
(pdftex.def) Requested size: 306.62396pt x 114.10033pt.
+
+./main.tex:37: Undefined control sequence.
+\beamer@doifinframe ...ny Digital Twin. \textcolo
+ {Green}{\faHighlighter ~Hi...
+l.37 \end{frame}
+
+The control sequence at the end of the top line
+of your error message was never \def'ed. If you have
+misspelled it (e.g., `\hobx'), type `I' and the correct
+spelling (e.g., `I\hbox'). Otherwise just continue,
+and I'll forget about whatever was undefined.
+
LaTeX Font Info: Trying to load font information for U+fontawesomefree1 on input line 37.
- (/usr/share/texmf-dist/tex/latex/fontawesome5/ufontawesomefree1.fd)
+(/usr/share/texmf-dist/tex/latex/fontawesome5/ufontawesomefree1.fd)
File: images/vu-logo.png Graphic file (type png)
<use images/vu-logo.png>
Package pdftex.def Info: images/vu-logo.png used on input line 37.
@@ -1239,92 +1251,68 @@ Overfull \vbox (6.21732pt too high) detected at line 93
<images/ref_architecture.pdf, id=174, 309.07468pt x 302.0886pt>
File: images/ref_architecture.pdf Graphic file (type pdf)
<use images/ref_architecture.pdf>
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+Package pdftex.def Info: images/ref_architecture.pdf used on input line 117.
(pdftex.def) Requested size: 191.63997pt x 187.31142pt.
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+Overfull \hbox (38.32799pt too wide) in paragraph at lines 117--117
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File: images/vu-logo.png Graphic file (type png)
<use images/vu-logo.png>
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+Package pdftex.def Info: images/vu-logo.png used on input line 117.
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[7
<./images/ref_architecture.pdf>]
-Underfull \hbox (badness 10000) in paragraph at lines 145--145
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-
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-Underfull \hbox (badness 10000) in paragraph at lines 145--145
-
- []
-
-
-Underfull \hbox (badness 10000) in paragraph at lines 145--145
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+Underfull \hbox (badness 1983) in paragraph at lines 144--144
+[]\T1/phv/m/n/8.53581 We don't have large sys-tems at
[]
+<images/predictive_analyticsv3.pdf, id=228, 205.72859pt x 224.7597pt>
+File: images/predictive_analyticsv3.pdf Graphic file (type pdf)
+<use images/predictive_analyticsv3.pdf>
+Package pdftex.def Info: images/predictive_analyticsv3.pdf used on input line 144.
+(pdftex.def) Requested size: 183.9739pt x 200.99919pt.
-Underfull \hbox (badness 1142) in paragraph at lines 145--145
-\T1/phv/m/n/8 (phys-i-cal twin) with ex-am-ple ex-per-i-
- []
-
-
-Underfull \hbox (badness 10000) in paragraph at lines 145--145
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- []
-
-<images/predictive_analyticsv2.pdf, id=228, 239.93639pt x 270.0489pt>
-File: images/predictive_analyticsv2.pdf Graphic file (type pdf)
-<use images/predictive_analyticsv2.pdf>
-Package pdftex.def Info: images/predictive_analyticsv2.pdf used on input line 145.
-(pdftex.def) Requested size: 183.9739pt x 207.07297pt.
-
-Overfull \hbox (30.66193pt too wide) in paragraph at lines 145--145
+Overfull \hbox (30.66193pt too wide) in paragraph at lines 144--144
[]
[]
File: images/vu-logo.png Graphic file (type png)
<use images/vu-logo.png>
-Package pdftex.def Info: images/vu-logo.png used on input line 145.
+Package pdftex.def Info: images/vu-logo.png used on input line 144.
(pdftex.def) Requested size: 95.5963pt x 28.45274pt.
-
-Overfull \vbox (1.2804pt too high) detected at line 145
- []
-
[8
- <./images/predictive_analyticsv2.pdf>]
-<images/23_Jun_2026_102028.pdf, id=265, 462.52798pt x 346.89601pt>
+ <./images/predictive_analyticsv3.pdf>]
+<images/23_Jun_2026_102028.pdf, id=263, 462.52798pt x 346.89601pt>
File: images/23_Jun_2026_102028.pdf Graphic file (type pdf)
<use images/23_Jun_2026_102028.pdf>
-Package pdftex.def Info: images/23_Jun_2026_102028.pdf used on input line 172.
+Package pdftex.def Info: images/23_Jun_2026_102028.pdf used on input line 171.
(pdftex.def) Requested size: 168.6441pt x 126.481pt.
-Overfull \hbox (15.33212pt too wide) in paragraph at lines 172--172
+Overfull \hbox (15.33212pt too wide) in paragraph at lines 171--171
[]
[]
File: images/vu-logo.png Graphic file (type png)
<use images/vu-logo.png>
-Package pdftex.def Info: images/vu-logo.png used on input line 172.
+Package pdftex.def Info: images/vu-logo.png used on input line 171.
(pdftex.def) Requested size: 95.5963pt x 28.45274pt.
[9
<./images/23_Jun_2026_102028.pdf>]
File: images/vu-logo.png Graphic file (type png)
<use images/vu-logo.png>
-Package pdftex.def Info: images/vu-logo.png used on input line 179.
+Package pdftex.def Info: images/vu-logo.png used on input line 178.
(pdftex.def) Requested size: 95.5963pt x 28.45274pt.
[10
]
File: images/vu-logo.png Graphic file (type png)
<use images/vu-logo.png>
-Package pdftex.def Info: images/vu-logo.png used on input line 202.
+Package pdftex.def Info: images/vu-logo.png used on input line 201.
(pdftex.def) Requested size: 95.5963pt x 28.45274pt.
[11
@@ -1343,26 +1331,26 @@ LaTeX Font Info: Font shape `T1/zi4/m/n' will be
]
-<images/manageability.pdf, id=349, 304.869pt x 196.28331pt>
+<images/manageability.pdf, id=347, 304.869pt x 196.28331pt>
File: images/manageability.pdf Graphic file (type pdf)
<use images/manageability.pdf>
-Package pdftex.def Info: images/manageability.pdf used on input line 237.
+Package pdftex.def Info: images/manageability.pdf used on input line 236.
(pdftex.def) Requested size: 186.38383pt x 120.0pt.
[16
<./images/manageability.pdf>]
-<images/dt_timeline.pdf, id=375, 221.94919pt x 136.55014pt>
+<images/dt_timeline.pdf, id=373, 221.94919pt x 136.55014pt>
File: images/dt_timeline.pdf Graphic file (type pdf)
<use images/dt_timeline.pdf>
-Package pdftex.def Info: images/dt_timeline.pdf used on input line 254.
+Package pdftex.def Info: images/dt_timeline.pdf used on input line 253.
(pdftex.def) Requested size: 195.05171pt x 120.0pt.
[17
<./images/dt_timeline.pdf>]
-<images/digital_twin_ms.pdf, id=402, 473.27817pt x 197.89935pt>
+<images/digital_twin_ms.pdf, id=399, 473.27817pt x 197.89935pt>
File: images/digital_twin_ms.pdf Graphic file (type pdf)
<use images/digital_twin_ms.pdf>
-Package pdftex.def Info: images/digital_twin_ms.pdf used on input line 267.
+Package pdftex.def Info: images/digital_twin_ms.pdf used on input line 266.
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[18
@@ -1391,21 +1379,21 @@ Package rerunfilecheck Info: File `main.out' has not changed.
)
(\end occurred inside a group at level 1)
-### simple group (level 1) entered at line 205 ({)
+### simple group (level 1) entered at line 204 ({)
### bottom level
Here is how much of TeX's memory you used:
40114 strings out of 469515
- 817488 string characters out of 5470807
+ 817506 string characters out of 5470807
1273364 words of memory out of 5000000
- 67960 multiletter control sequences out of 15000+600000
- 753335 words of font info for 216 fonts, out of 8000000 for 9000
+ 67962 multiletter control sequences out of 15000+600000
+ 749388 words of font info for 213 fonts, out of 8000000 for 9000
14 hyphenation exceptions out of 8191
128i,16n,123p,1334b,1018s stack positions out of 10000i,1000n,20000p,200000b,200000s
</usr/share/texmf-dist/fonts/type1/public/fontawesome5/FontAwesome5Free-Solid.pfb></usr/share/texmf-dist/fonts/type1/public/inconsolata/Inconsolata-zi4r.pfb></usr/share/texmf-dist/fonts/type1/public/amsfonts/cm/cmss8.pfb></usr/share/texmf-dist/fonts/type1/public/stix/stix-mathfrak.pfb></usr/share/texmf-dist/fonts/type1/public/stix/stix-mathit.pfb></usr/share/texmf-dist/fonts/type1/public/stix/stix-mathsf.pfb></usr/share/texmf-dist/fonts/type1/public/stix/stix-mathtt.pfb></usr/share/texmf-dist/fonts/type1/urw/helvetic/uhvb8a.pfb></usr/share/texmf-dist/fonts/type1/urw/helvetic/uhvr8a.pfb></usr/share/texmf-dist/fonts/type1/urw/helvetic/uhvro8a.pfb>
-Output written on build/main.pdf (18 pages, 5600893 bytes).
+Output written on build/main.pdf (18 pages, 5596084 bytes).
PDF statistics:
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- 283 compressed objects within 3 object streams
+ 504 PDF objects out of 1000 (max. 8388607)
+ 277 compressed objects within 3 object streams
51 named destinations out of 1000 (max. 500000)
237 words of extra memory for PDF output out of 10000 (max. 10000000)
diff --git a/build/main.pdf b/build/main.pdf
index 0f56c50..28ad947 100644
--- a/build/main.pdf
+++ b/build/main.pdf
Binary files differ
diff --git a/build/main.synctex.gz b/build/main.synctex.gz
index 623a484..a6792d0 100644
--- a/build/main.synctex.gz
+++ b/build/main.synctex.gz
Binary files differ
diff --git a/images/predictive_analytics.drawio b/images/predictive_analytics.drawio
index a5dbc0b..c8ff618 100644
--- a/images/predictive_analytics.drawio
+++ b/images/predictive_analytics.drawio
@@ -1,6 +1,6 @@
<mxfile host="app.diagrams.net">
<diagram name="Page-1" id="Y5lrrR6LJWy-jUVm7I1K">
- <mxGraphModel dx="640" dy="439" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="850" pageHeight="1100" math="0" shadow="0">
+ <mxGraphModel dx="928" dy="636" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="850" pageHeight="1100" math="0" shadow="0">
<root>
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<mxCell id="1" parent="0" />
@@ -141,10 +141,10 @@
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</mxCell>
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+ <mxCell id="j6KFcfNkW-SXBffTGkYf-18" parent="1" style="ellipse;whiteSpace=wrap;html=1;fillColor=none;strokeColor=#00AB4F;strokeWidth=4;sketch=1;curveFitting=1;jiggle=2;" value="" vertex="1">
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</mxCell>
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+ <mxCell id="j6KFcfNkW-SXBffTGkYf-19" parent="1" style="ellipse;whiteSpace=wrap;html=1;fillColor=none;strokeColor=#00AB4F;strokeWidth=4;sketch=1;curveFitting=1;jiggle=2;" value="" vertex="1">
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diff --git a/images/predictive_analytics.pdf b/images/predictive_analytics.pdf
index 7bf0c20..9aa53ad 100644
--- a/images/predictive_analytics.pdf
+++ b/images/predictive_analytics.pdf
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vrf6PPRZ6GvQI9Cz0APQfPdhVHmI9D+WQYA7TOet4b0zcM5+TT039B90Kuhy+VG7Hgy+k30YFSRgAQk0BaB+1Dw8egj0WugG5Lt2Hk4egr6Z2i+yzBK3wjYMX3rkSv9uRcmf2RHYG+JTiPX46BE4zmXTUUCEpBAowTuQmn/g26FTiMJBP6TA7+O+uMECLNIF8caAHRBefo6bsOhubX/UWye72Nmkmty9FvQ66KKBCQggaYIbE5B70bnua2/O+d9AP0Yuheq9ISAAUA/OmJ73HgHmkg5yX1szi035cynoIoEJCCBpgjkmX6+WxYp7/c5+Tj07ei0dzY5tEbpps0GAN1wXqmW6/NGsmdPwj4U3dAzfnbPLI/gjKbKoihFAhKonMDDGmp/rjkpKzlLr6fM5DBhlBIE0hkl6q29zmsDIFmzZ66118I2KTtSmH9YQFAkIIGFCSS/aNeFS1m3gDyufBy7kuSc78LN2FbWEujKGAB0RfrKejbBPBZN9Jtf/vnD4mUr4i22VrBaqASqI3CDFluc78B8F+Y78dHUk+9IjNIFAQOALihfWcc9MMnsfyN2G7RtubztCixfAhKogsAlHbRyW+p4M3oi+mC0Yumu6QYA7bO+I1V8Fv0EugfalZzfVUXWIwEJjJrA92nd99AuOuwDmwAAEABJREFUJI8aMtrgM1R2e1RpkYABQHtwd6LofJC/iN0f7VJyp+GiLiu0LglIYNQE3t9x6w6ivi+h70KT04SpQ7pspQFA87RvTJGvQ7+B5lZWiWz8TCBE9YoEJCCBRgi8mlJ+jXYp+e58CBWejGbEwE2wSoMEDACag5mJMpLNmmSWv6LYlabJ5K1WJfNwZ+rgViuxcAlIoCoCeTaf+f9LNDrfpRkxkO/WQ3Eg37WYMUq3bTIAWJx3PpxPpJgM6Us263XYLiU/ouJEzCYAAkKRgAQaJZAJxjJnSaOFzlDYlhz7IvR0NAukXR2rLEDAAGB+eLk99cecnlv9r8Xm1j+mmJxDzfdGT0AVCUhAAk0T+CkF3h3NKqSYYpIZCXOXM8FIqcesrTS+60INAOYjfgCnHY2+B02yH6aYXEHNGVqYtQPiEy8VCUhAAq0QyGiAO1HyYWjXOQFUuY7kuzeJ1kkWPHCdd3wxFQEDgKkw/e6gXdjKB+4o7B3Q0vJJHNgbzfOxH2IVCUhAAm0T+DkVPBvNj44sXsZmUclwwSPxoOuh1lTZpHRflgHAdMwzcU+yUJMIk1tO053V3lFfoegMk7knNgsIYRQJSEACnRLI48/7UWO+h/rw6DGTrcWPjIK6GX4pqxAwANg4oC14O5n9p2DzK7t00kmyYJPkl8mFchcCtxQJSEACRQnkTuQ+eJDvpm9hS0quaQ/HgSQKJil7MEuj43PnElidVzqACpPZnwv+JLM/2acl3b6YynPL7bbY5B38BqtIQAIS6AuBfCfluykz+SVD/8LCji1fcG3Twv70snoDgHW7JZn9ucWfX/y55V96Rb1k3SbZZgfcjP0FVpGABCTQVwL5jnoDzuU764XY5AtgikkWMsqdgNw9zY+6nl7zyvARxlXcM7zlWF4myS8fXjaLyS+pOX9EmQIzv/x/zGtFAhKQwFAIXIqjL0Bvjea7LKOV2Cwmt6Dm/Kj7MvZuqAIBA4A1a3aHQy76eY6VjHpeFpVk1can3Eb7blFPrFwCEpDAYgTO4/R8l00eX/KyqOxL7Z9CM2JgL2wvpJQTNQcANwd6IsKvYXPbH1NUMoY/iwYlqzYJLEWdsXIJSEACDRLIY9UkCWYOgc83WO68RWXEwHGcnB9/22GrlBoDgOvT00ufCW3C65LStz+MkiysWwISGDeByQ+d+9PM0j90cv3Lj79T8SU/BrfGFpByVQZAudq7rfmaVHcImsz+DO27FtslpW+3xkqysG4JSKAuAh+guX151JlrQxIET8OnXBs2w1YhNQQAaeMkyjucXr0eWlKSHJPs2L4kx5RkYd0SkEC9BPqW7LwVXdH53WHqLCa5OBarvIOK+/ScZ/JhzwiDZMeWHh7TAX6rkIAEJLAqgb4Nd94Wj/NIILOs5scjL8cpYw0Akun5abqsD5mefZsgAyyKBCQggd4R6NuEZ7tBKEmCX8AmeRHTtJQtb2wBwC3BmXmgM1f+XdkuLRlamGAk2a/JPSjtj/VLQAIS6DuBTNqT78xMeZ5Ffkr7m4t/Ri4kGMjcLKX9aaz+sQQAk9meksSReaAzo19jkOYo6CTOyQc4i2Qcz7YiAQlIQAKzEZj8kMv3aG7Hz3Z2s0fnmpLHASdTbB4P3Bi7sJQuYOgBQN/mez6HDs2kF3tiMy82RpGABCQggQUI5E7q7Tg/P6rOwpaUyToxZ+BEEgZLrxODG/PLUAOARGMZtjHphNIrPl1GFzwXNbMfCIoEJCCBhgn8mvLyoypDB/+e7SRVY4rJZKXYzCHwGLzINQkzi5Q/dogBQCZr+AjochvmptjScgkOZG7pl2AvRxUJSEACEmiHwM8o9lD0XmhGD2CKys2o/U1opnC/IXZQMrQAIBM2/C+E0/mY4pIFLh6IF5ndCqNIQAISkEAHBD5DHY9F+yL3wZH3o7lGYVaXPhwxtADgmUDbD+2LvA5H8kHEKBKQgAQk0CGBd1LXW9C+SK5Nf9MXZ6bxY0gBQJIvnjhNozo65lfUk9v+GEUCEpCABAoQ+GfqzFwrmF5IrlG5Vq3iTD/eHlIAsBPI+vDMHzd+K5/l/++iigQkIAEJlCGQYXmZqKdM7evXmpyAndff3c89QwoA+rZk4zH97FK9koAEJFAVgS/1rLXbr+ZPX94fUgDQtxWaLupLJ+qHBCQggYoJ9O1ObOanGUR3DCkA6BvQTfvmkP5IQAISqJBA6aXdZ0Ten8MNAObvi+QkzH+2Z0pAAhKQQBME/C6ek6IBwJzgOO330U1QRQISkIAEyhDIuPu+zAszFYE+HWQAMH9vZETCH85/umdKQAISkMCCBP6E80exMA/t6FwMABZDfhinb44qEpCABCTQLYEk2/1dt1UuWlu/zjcAWKw/duT0I1AfBQBBkYAEJNARgVy7Mgugz/8XAB6IC5zuqRDIWgAfwGaRIowiAQlIQAItErg+Zb8PzfLAmOFI3zw1AGimR+5NMaegT0aTlIJRJCABCUigQQK505oFgE6izPuhyoIEDAAWBLjk9Buw/Sr0dPRxqGyBoEhAAhJogMA9KON49I3oTdABSv9c9iLVfJ/cgiJfj34ZvRuqSEACEpDAfARuz2lZcfUT2D1QpUECBgANwlxW1L68/hSaD+5eWEUCEpCABKYjkOS+d3No5vk/CDt46WMDDADa75XcujqOavJh7tuCRrilSEACEugNgRviyUvRE9EHo1dDlZYIGAC0BHZZseGcD/Op7H8lej1UkYAEJCCBKwlkPpVnsXkmGjuyZGpa1UPJhamHbo3WpXyon0LrJh9yF7EAhiIBCVRL4Bq0PEnTZ2Dzy/86WKUjAgYAHYFeVk3GsebD/k3258Of4S1sKhKQgASqIZDHo8nsT9L0qDP7+9qjBgBle+bmVJ8P/9eweUSAUSQgAQmMmsAdad1n0SRI3warFCJgAFAI/LJqd+d1kgTzB7E324oEJCCBsRHYhQble+5o7P5oJdLfZhoA9KtvckvsWFzKH8kOWEUCEpDA0AlsQwNyp3OS2c9LpQ8EDAD60Avr+pBhL3kckKmF80dzo3Xf9pUEJCCBQRDYAi+T0Z/vsuQ6XZ3X1UmfG2wAsG7v/IqXP0P7IJPs2NNwJn9Em2EVCUhAAn0nkNFOh+Dkt9EkO2+J7YP8og9O9MkHA4A1azJ3/5PplMw8dW1sxqMmS/+ubGep39IBQeYMyB9RRgw8Gp8cMQAERQIS6B2B3L18KF7lF//h2Ezqgykml1Pzu9D7onkMkR9RueYlFyEBSvzkrTal32UHRr89bM+7XNhzWyofhtdQTQKBX2IjP+S/I9FHotujr0Mn77FZRLal1jejX0XvhSoSkIAE+kIg0/UegzPvQPOdiSkmV1Bzvit3xP4p+mH0fPTX6G/Q3FXNwm23Zftv0RyPqU9qDQB+Tlcn4S4rS+VDwcsV5Xu88yQ0w1Xei80HCFNM4sdHqf2taO5WYBQJSEACRQjkOyjfo5+m9n3Q0vIhHMjaK4/BnotuTHLhz93V+3BQ7hZgmpW+l1ZrAJDbPxmKMkv/5BZ8kvPuxEkZw4opKrk7kWGDeURQ1BErl4AEqiSQ756P0/LHorn9jykmufuQ1VcPxoNvoLNI2vCMWU4Yy7E1BgBZWjIR67x9mNWpDuTk+6MnoSVlPyrPLbfSf3y4oUhAAhURyLXjnbQ3P4gwxSRTCD+E2u+A5rsdM5fkMXDDP+zm8qPTk9KJnVbYg8pe25APH6CcPdFEv+dhS8m9qfgJqCIBCUigKwJ5LFoyF+lCGvrX6G7oe9AmHs02dW3AnWFIbQFAhoG8v8GuyTOkf6e8jCB4DvZHaAk5lEpdWAgIigQk0DqBjJbK913rFW2ggp+y78VoEvxywW4yOft9lJtrBGZxGUIJtQUA36FTmvzAUNxvJSMK/pGtZL8ehr0M7VJuSmUlo3GqVyQggUoIZFhd14v3ZI6WN8D31ujz0J+gTUsu/mc3XWify6stAGj7Vv0P6Oxno7ktlWfzq40w4NDG5J6NlWRBEpCABFYm0PV3zf/DlQzZezz2ArRNaSgAaNPF5squLQBIFNkcvZVLygxYf87be6AfRLuQW3VRiXVIQALVE9iuIwJfpp4kXD8QeyrahXR1jeiiLavWUVsAsCqQhg/IKIH7UWZuz2cCHzZbk0y/2VrhFiwBCUhgLYG25/TPxf4B1DVZNpjNYclQvDUA6KanMs40k2Q8nOqSh4BpXNp+vNG4wxYoAQkMkkBb3zW5vZ/b/Lndn4S8QcIZktMGAN31VvIB/oPqMmIgH/IMY+FlY5Igo7HCLEgCEpDACgSa/q5JZn+Sp3emviT6Dfw2PK0YiBgAdN9RyTTNhzwf9pdRfaYlxiwkiZwzL8FChXiyBCQggSkIJCkvU6RPcehGD8mIrEzAk5yCJE+3kdm/UQdqf9MAoNwn4BKqzjK/CQTewnbuEGDmkqdz1qWoIgEJSKBtArlQP3OBSjJpz7s5P6OlshLrRWyPRobUEAOA8r11Di78BZpFfjKjFZszyYs4OlNyYhQJSEACnRA4glpyBxMzk2QNlgM440/QTOOLUUoRMAAoRX79ek9hV+a0ztzan2d7Ncmjg6dy0PNRRQISkEDXBHLbPgurTTPxWRboyQRC036/dd2WhuobVjEGAP3rr0mEnMWGPoJ7l6NLJVHzS9mxA/pKVJGABCRQgkBu5b+KindF8110PnapZKr0o9jxp+he6IdRpUcEDAB61BlLXMkfVpL67sO+LdBd0EyBufVa+7fYJP5hFAlIQAJFCZxF7bkbuQ32lui+aCZB2xJ7EPouNMEAZtwytNYZAPS/xzIk5jTczC//i7GKBCQggb4SyFS6x+HciWgeU2KUvhIwAOhrz+iXBCQgAQkMiMDwXDUAGF6f6bEEJCABCUhgYQIGAAsjtAAJSEACEqidwBDbbwAwxF7TZwlIQAISkMCCBAwAFgTo6RKQgAQkUDuBYbbfAGCY/abXEpCABCQggYUIGAAshM+TJSABCUigdgJDbb8BwFB7Tr8lIAEJSEACCxAwAFgAnqdKQAISkEDtBIbbfgOA4fadnktAAhKQgATmJmAAMDc6T5SABCQggdoJDLn9BgBD7j19l4AEJCABCcxJwABgTnCeJgEJSEACtRMYdvsNAIbdf3ovAQlIQAISmIuAAcBc2DxJAhKQgARqJzD09hsADL0H9V8CEpCABCQwBwEDgDmgeYoEJCABCdROYPjtNwAYfh/aAglIQAISkMDMBAwAZkbmCRKQgAQkUDuBMbTfAGAMvWgbJCABCUhAAjMSMACYEZiHS0ACEpBA7QTG0X4DgHH0o62QgAQkIAEJzETAAGAmXB4sAQlIQAK1ExhL+w0AxtKTtkMCEpCABCQwAwEDgBlgeagEJCABCdROYDztNwAYT1/aEglIQAISkMDUBAwApkblgRKQgAQkUDuBMbXfAGBMvWlbJCABCUhAAlMSMACYEpSHSUACEpBA7QTG1X4DgMeEFeEAABAASURBVHH1p62RgAQkIAEJTEVgSAHAr6ZqkQdJQAISkIAE5iNwxcZOG9t7QwoALm4A/uUNlGEREpCABCQwTgLfb6BZg7nODCkA+CYd8xt0ETlvkZM9tyoCN6G190D/En0EeiC6Gar0m8CWuHcQ+lj0ceh90K1RRQLTEDht5YOmfmcw15khBQDfA/9J6CJy/CIne24VBO5MK/8HPQf9BPoG9G3okej56KvRW6FKvwhshzuvR7+LfgZ9I5rXH8JegL4f3QdVJLAxAvnsbOz91d67jANOQQchQwoAAvTf89+cmhyCfLHPebqnjZxA/hb+iTZ+Dn0AenV0uVyPHX+Nnor+C3oDVClL4IZU/wo0fZJf/Ndme7lswo77oV9CD0UVCaxE4Iu8scELOPunkY9y0E/QQUi+9Abh6FonEwCcu3Z7VvM6TrgIVSSwIQL5Zf8M3rgauppsygFPR89An4X6aAAIHUsu9H9LnemDp2Kvia4mCepexEF/jyoS2BCBPGZ+8YbemGLfrznmH9DByNACgERWj4duQGOmltM58nmoIoENEfhjdj4RnVVyR+ClnJTPV3595pcmL5UWCeQ768GUn8eBL8FeF51VnsMJf4AqEtgQgf9iZx4ZYSYylX05Rx2LDkbyxzQYZ9c6+mHsk9Fpg4CzODbJXD/CKhJYTiC/+Bf9RbgNheZ584nYXJwwSgsE8nd8AuW+G10kDyN9/s+UEYtRJLAegT9nTx4ZYaaSt3JU7gZihiNDDABCN7fz80wviVp5vSFNgJDkrdvx5tmoIoENEbg7O3dGm5BdKSQXpyQM3p5tpRkCd6SYo9AkZe6BbUJ2p5A7oIoENkTgUnbeFf1X9Ap0JckPy4wU+gsOyDUHMxwZagAQwrkTcGs2MkTrHdgkbx2H/V/0BWjeexT2ElSRwEoEDljpjQX2Z8jglzn/A2g+hxhlDgI7cU4CqiRmtdFP+1O+IoGVCCSjP48GEywmL+CTHJiRZLkL9U62c+HfFvsmNLkDmGHJkAOAkM6EC29nI7dr8gWxL9t/hL4Q/RaqSGA1AjuudsAC7x/MuXlW/RrsjVBlOgI35rDXot9A80ilrVv1BmcAVlYjsCZzAySH7J4cmaGke2MfiubCnzsFbA5Thh4ADJO6XveJQFsXl0kbr8HGk9Bkq+dLZHO2lQ0T2ILdz0fDKr+8wo6XigQk0AYBA4A2qFrmkAh0lR+SGepyZypJqUkWmmbY2pA4LuJrLvQZRZHZPvP4LoHAIuVNe25XfT+tPx7XQwJjdskAYMy9a9umIXD0NAc1eEwmrsnQwa9T5gPRmiV3Xx4EgNzqzyiKm7LdpSRPo8v6rEsCvSJgANCr7tCZAgSSTHphgXoz8uC/qTcXoSQNslmVTDL730urk+yH6VQygujTndZoZQMkMG6XDQDG3b+2bnUCv+CQzA6HKSIZLphhg00OcSvSkCkr3YXjktmfOy8ls/D/Dj+uQBUJVEvAAKDarrfhSwhkrG8WjVmyq/PNTHKTYaxZfOhmndfefoWZLClZ07ndn8z+9mtcuYb38NYRqCKBjRIY+5sGAGPvYds3DYFM4JGL0genObjFYzJXfcYWZ2rhzE54nRbr6qroTNWbKXuT4PcYKi09XXIu/g/DD0UC1RMwAKj+IyCAtQR+jr0/+gT0B2hJyUI3z8WBM9GnoEMcMRCfs0hPhvRl0Z60iaYUkywEltnaHoIHeeyDUSSwMQLjf88AYPx9bAunJ5DZvJKNfktOyZC9BAVsFpOMGHglteeOQIbJDeHvNZn9uZtyMn6/Ak0bMMXkZ9R8GJpJf96CVSQggbUEhvCFstZVjQQ6I5DZvTIePReNPJMvnSx2C1qewOQr2LuhfZWsq3AMziXJbwdsScljncwSmj58No5kznaMIoHpCNRwlAFADb1sG+clcB4nPh69LZpnx5iikmlIP4UHGTGQRa7Y7IXshhe56Geu9PjIy6ISP/bCg6wTcj5WkYAENkDAAGADUNwlgWUETuF1nh3fCft5tLRkxEDWHc9Fd/uCztycunNnIpMa5bY/L4tK5lQ4CA8yZ3uWZmZTkcA8BOo4xwCgjn62lc0QmIxdT7Jgnss3U+p8peRvNxfdBCe5CG89XzFznbUVZ2U2w2T2JzehdGZ/FmtJgLYffh2FKhKQwBQE8iUyxWEeIgEJLCGQZX6zRGgeD3x3yf4Sm8m2z0U4F8GsMbBZi06krkMoP6MTUte12C4pF1N5RhrcBptHNEniZFORwGIEajnbAKCWnradTRP4JQUmQXBHbJLMfowtKW3+Ks/3RO42nEoDD0dTF6aY/JSak9mfRMOMkvgVrxUJSGBGAvnDnvEUD5eABJYQWHoxehX7S1+MtsWHPBJo6rl88g0yQ2HyDbaj7JLSt6CrJAvrbo1APQUbANTT17a0XQK5HZ3b4325HT3JzP8Czb4zOqvsywmTEQfJqOdlUcksjX157FIUhJVLoCkCBgBNkbQcCVxJIM/i+5SQlpELn8O1/ILP4wo2NyqZBCl3EJJR34c5ByaJl/fD69KJl7igjJ1ATe0zAKipt21rlwRyAc2QtAdQaZ6dY4rJZHa+k/DgnWiGyS1NFsz2vdj/LnSS2V/6uyGLBh2MPwlg+jD0ElcUCYyLQOk/8nHRtDUSWJ/A+9iViYQyYuACtktKsvj/BAc+jmaK3IxgiGb7o+zLnYscw2YxOZeaM2d/HjuUXqERV5S6CNTVWgOAuvrb1pYhkMTApSMG+jIt7Y3BEcUUl0y/nPUXdsKTzNlfevpl3FAkMG4CBgDj7l9b1y8C+aU9Gb4We3m/3CviTVbmS3CUIX1Zf6H0AkxFIFhpPwjU5oUBQG09bnv7QOD7OJG5A3bG5uKXhWvYrEoyaU8m79mVVufxyIVYRQIS6JCAAUCHsK1KAssIfIfXufjdAftptBbJYj0ZZpicg2/V0mjb2XcC9flnAFBfn9vi/hHIwj53x61k538VO1bJKIQM50s7jx9rI22XBIZCwABgKD2lnzUQyC/jLKebX8bfHlGDz6EtudOxJzYT+mAUCfSLQI3eGADU2Ou2uc8Ekg+QZ+O74GQWurkEO1T5AY4n1yGZ/cl1MLMfIIoE+kLAAKAvPaEfEliXQLLjs9BNsuMzYuCydd/u9av4nnURhuh7r8HqXFsE6izXAKDOfrfVwyEwpF/Rk7sXGd2QdRGGfPdiOJ8QPZXAnAQMAOYE52kS6JjA5Dn6HtSbRwSYXknyF/bGo+QvnIVVJDAYArU6agBQa8/b7qESOBnHc5G9B7YPmfTH4EcWDUpm/9fYViQggYEQMAAYSEfppgSWEchSvZOx9Gcue6+Ll5nD4JFUlDkMPoNVJDBQAvW6bQBQb9/b8uETmMymtztNeTraxTP3zGL4ZOq6NXoEGh8wigQkMDQCBgBD6zH9lcD6BLKmwCvYnWl1j8K2JR+j4NTxGuwvUUUCgydQcwMMAGrufds+NgLfpUH3Qr+CNi0fosCD0YtQRQISGAEBA4ARdKJNkMASArkb8CBeN3mhPpfyHoZmWWOMIoGxEKi7HQYAdfe/rR8ngVywX95g0w6lrC7yC6hGkYAEuiJgANAVaeuRQLcE3kR1Tcwe+CPKeSeqSGB0BGpvkAFA7Z8A2z9WAhfTsKPRReWzFNBEIEExigQk0CcCBgB96g19kUCzBE5voLgScww04LZFSGA1Ar5vAOBnQALjJXBpA037aQNlWIQEJNBDAgYAPewUXZJAQwSamKSniTIaao7FSKA5Apa0Zo0BgJ8CCUhAAhKQQIUEDAAq7HSbLAEJSKBuArY+BAwAQkGVgAQkIAEJVEbAAKCyDre5EpCABGonYPuvJGAAcCUH/5eABCQgAQlURcAAoKrutrESkIAEaidg+ycEDAAmJLQSkIAEJCCBiggYAFTU2TZVAhKQQO0EbP9VBAwArmLhlgQkIAEJSKAaAgYA1XS1DZWABCRQOwHbv5SAAcBSGm5LQAISkIAEKiFgAFBJR9tMCUhAArUTsP3rEjAAWJeHryQgAQlIQAJVEDAAqKKbbaQEJCCB2gnY/uUEDACWE/G1BCQgAQlIoAICBgAVdLJNlIAEJFA7Adu/PgEDgPWZuEcCEpCABCQwegIGAKPvYhsoAQlIoHYCtn9DBAwANkTFfRKQgAQkIIGREzAAGHkH2zwJSEACtROw/RsmYACwYS7ulYAEJCABCYyagAHAqLvXxklAAhKonYDtX4mAAcBKZNwvAQlIQAISGDEBA4ARd65Nk4AEJFA7Adu/MgEDgJXZ+I4EJCABCUhgtAQMAEbbtTZMAhKQQO0EbP/GCBgAbIyO70lAAhKQgARGSsAAYKQda7MkIAEJ1E7A9m+cgAHAxvn4rgQkIAEJSGCUBAwARtmtNkoCEpBA7QRs/2oEDABWI+T7EpCABCQggRESMAAYYafaJAlIQAK1E7D9qxMwAFidkUdIQAISkIAERkfAAGB0XWqDJCABCdROwPZPQ8AAYBpKHiMBCUhAAhIYGYGhBwDXoT/+Cn0vegJ6MvoZ9B/Q3VBFAhKQgAQqI9Bwc3ehvBejH0OPRb+MHoE+Ar02OlgZagBwNYg/Cf0O+jr0Qehe6K7oQehz0BPRN6CboYoEJCABCUhgFgK5dvwbJ3wD/Tv099F90NujD0ffhp6LPgodpAwxAIjPb4b2a9DroStJjvtL3jwS3RJVJCABCUhg9AQaaWCuGbmb/HhK2wRdSbbijbegb0LzwxQzHMlFcjjeXunpYZhZIq5Ea//FOYPrHHxWJCABCUigewLvoMo7oNPKYzjwJeigZGgBQG6/PG0OwvflnIehigQkIAEJjJhAA03LteLgOcr5G865HToYGVoAkGf7G7sdszHweYYztPZurD2+JwEJSEACzRLIneJD5ywy16bnznlukdOGdEHcAkL3RueVnTjxLqgiAQlIQAKjJLBwo3KNyLVi3oLuw4m5VmH6L0MKAHYGZ7IyMXPLXec+0xMlIAEJSGDsBBa9RuQalWvVIDgNKQC4aQNEF4nsGqjeIiQgAQlIoC0CDZTbxMV7mwb86KSIIQUAmzZA5IYNlGEREpCABCQwTgLXb6BZTVyrGnBj9SKGFACs3prVj7j66od4hAQkIAEJDI9AIx5XdY2oLQBo5BNiIRKQgAQkIIGhEzAAGHoP6r8EJCABCawRwewEDABmZ+YZEpCABCQggcETMAAYfBfaAAlIQAK1E7D98xAwAJiHmudIQAISkIAEBk7AAGDgHaj7EtgIgd9s5L1p32qijGnr8jgJzEXAk+YjYAAwHzfPksAQCFzcgJPfa6AMi5CABHpIwACgh52iSxJoiMDpDZRzRgNlWIQEWiRg0fMSMACYl5znSaD/BD6Bi5ej88pPOPEoVJGABEZIwABghJ1qkySwlkAu4G9euz2P+VdOugxVJNBbAjo2PwEDgPnZeaYEhkDghTj5XXRWOZsTXooqEpDASAkYAIy0Y22WBNblAWrtAAAQAElEQVQSSBLfA9m+FJ1WLuHAP0J/iCoS6DEBXVuEgAHAIvQ8VwLDIHA0bt4JPQ1dTU7kgDuiJ6CKBCQwYgIGACPuXJsmgSUEcmG/La+fgH4evQKdSLaT7PcYdtwOnSZQ4DBFAmUJWPtiBAwAFuPn2RIYEoFf4uzr0f3RzdHt0e3QbB+ETcJgggE2FQlIYOwEDADG3sO2TwIbJpDhgd/mrbPQbGMUCQyJgL4uSsAAYFGCni8BCUhAAhIYIAEDgAF2mi5LQAISqJ2A7V+cgAHA4gwtQQISkIAEJDA4AgYAg+syHZaABCRQOwHb3wQBA4AmKFqGBCQgAQlIYGAEDAAG1mG6KwEJSKB2Ara/GQIGAM1wtBQJSEACEpDAoAgYAAyqu3RWAhKQQO0EbH9TBAwAmiJpORKQgAQkIIEBETAAGFBn6aoEJCCB2gnY/uYIGAA0x9KSJCABCUhAAoMhYAAwmK7SUQlIQAK1E7D9TRIwAGiSpmVJQAISkIAEBkLAAGAgHaWbEpCABGonYPubJWAA0CxPS5OABCQgAQkMgoABwCC6SSclIAEJ1E7A9jdNwACgaaKWJwEJSEACEhgAAQOAAXSSLkpAAhKonYDtb56AAUDzTC1RAhKQgAQk0HsCBgC97yIdlIAEJFA7AdvfBgEDgDaoWqYEJCABCUig5wQMAHreQbonAQlIoHYCtr8dAgYA7XC1VAlIQAISkECvCRgA9Lp7dE4CEpBA7QRsf1sEDADaImu5EpCABCQggR4TMADocefomgQkIIHaCdj+9ggYALTH1pIlIAEJSEACvSVgANDbrtExCUhAArUTsP1tEjAAaJOuZUtAAhKQgAR6SsAAoKcdo1sSkIAEaidg+9slYADQLl9Ll4AEJCABCfSSgAFAL7tFpyQgAQnUTsD2t03AAKBtwpYvAQlIQAIS6CEBA4AedoouSUACEqidgO1vn4ABQPuMrUECEpCABCTQOwIGAL3rEh2SgAQkUDsB298FAQOALihbhwQkIAEJSKBnBAwAetYhuiMBCUigdgK2vxsCBgDdcLYWCUhAAhKQQK8IGAD0qjt0RgISkEDtBGx/VwQMALoibT0SkIAEJCCBHhEwAOhRZ+iKBCQggdoJ2P7uCBgAdMfamiQgAQlIQAK9IVBbALBpb8jriAQkIAEJLCNQ/OW1invQoQO1BQDbdsjWqiQgAQlIYFgEqrpG1BYA3JLPYlUdTHsVCUhAAoMgUNjJXBtuVdiHTquvLQAI3EfmP1UCEpCABCSwhMAjlmxXsVljAPA0enZrVJGABCQggd4QKOrITag91wZMPVJjAHADuvct6CaoIgEJSEACdRO4Bs1/F3pDtCqpMQBIB9+X/96BboYqEpCABCRQmECh6pP1/x/UfQBandQaAKSjH8J/J6D3RBUJSEACEqiLwN1obq4BuRawWZ/UHACkt3fmv4+jn0D3RhUJSEACEuicQKcV7kZt70Y/he6CViu1BwCTjr8HG8ei+VBsj1UkIAEJSGBcBDLM7/U06evog9HqxQDgqo/A1djMh+IUbD4kN8IqEpCABCTQMoGWi9+K8l+KfhN9HGoCOBAiQwoAfhaHO9BrUkc+JKdhn4WaKAgERQISkMDACCTB7xn4fAba5Xf55dQ3CBlSAHBWx0SvR32JGk/HJiAwagSEIgEJSKBZAo2Xluta7uaeRMn/hF4f7VK+1WVli9QVUIuc3+W5uRCf02WFa+vaBptHAl/FZvggRpGABCQggR4S+AN8Oh4tlc91AXXn7jGm/zKkAOBX4HwNWkpuQ8UfRD+D3h5VJCABCUhgQQINnb4P5XwS/Qi6J1pKXkfFv0QHIUMKAAL05fx3JFpSDqLyL6MfQG+NKhKQgAQkUIbALag2d2i/gr07WlKOpvKXoYORoQUAuQvwQOj+L1paDsaBPGN6NdYRA0BQJCABCcxGYO6jM23v4ZydR8PJ0Sp9Lfsovtwf/QU6GCkNbR5QP+SkB6CPQc9HS0rmkP5rHEiW6aHYzVFFAhKQgATaIXBtin0Omu/cQ7AZtYUpJt+l5ieg90EvRgclQwwAAvg3/PdmNLfgn429BC0pW1L5i9CMVMhwk9IfSlxRJCABCfSbwAze5VqVzP6TOecf0OuiJeWnVH4Ymtlk8wgi1yReDksCdVger+tt5gZIJ+zA7tjLsCUlt6UydHAy01QmFyrpj3VLQAISGDqBzNSaOfuT2X/Lwo1Jgt8b8GFHND8+f4wdrAw9AJiA/wEb6YxEY+mcX/O6pMSPfFi/hBMHoooEJCABCaxDYNUXGW2VpO+s1bLHqke3f0BGge1ONY9Hc+sfM2wZSwAw6YWz2UjnZBjIh9guLX37AJfmYf0SkIAEViOwEwf06QdUsvv3x6f7oUk6xIxDxhYATHrlG2wkSz9L/ebWES+LyuQW1hF4cTNUkYAEJFA1gQ00fvII9UTey/P+0o9Qsy7MQ/DlTujn0dHJWAOASUdlYoh9eZFOLD09Y1g/HF8SQSZPoHQSC64oEpCABIoTyOipJE+fiSexpZOoz8OP3Em+LfY96GglF6XRNm5tw5IPkE7cldfp1IuwJSXDWPIhn3zYNy3pjHVLQAIS6J7Ab2vMMOqM4c+Qvvwous5v95b771KqfiGa0WXJJbuC7VFLDQHApAMzQUM6NQl6GTHw88kbhewNqDcf+skSlTX1BU1XJCCBignkeXomUssQupsU5jC5NmQ02QvwpfS1ARe6kRovOplIKCMGkmiSgKB0lDeZyjLTC9+tm263FglIQAJFCOxHrZ9D34/mlzammGTs/tK7wxcW86RQxTUGABPU57KRRwJ9ec6TXIVP4VOGvOyFVSQgAQmMhcAuNCSZ/V/E3gUtLX3KDyvGouYAYAJ9kul5Z3Z8AS0tGTFwHE7kj2U7rCIBCUhgqAQmy6lPMvvXrFlTtCl57JDHDxkhdnxRT3pQuQHAVZ2QyDRjPTNiIEkpV73T/Vb6JcNgTqXqPCPbGqtIQAISGAqBLXA0z9Mz6imJflfndUk5h8pzxzdzxGRCH14qudBI4SoCk2dCu7ErH5bvYUtKhsPkj+c0nMjIgc2wigQkIIG+Ephk9meU0/Nxcr3vLPZ1KZNZYvuS89Vl21etywBgw4gm8z0nKzQJgz/Z8GGd7d2KmpaOGNiE14oEJCCBvhDIpD25a5lHqrlreaPCjiWz/1X4kO/wjPoqvU4MrvRPDAA23ieTFZ/yIcqH6VcbP7z1d7elhvxxTRYb4qUiAQlIoCiB5C0diwfJW8p3JZsrSev7J/O+ZLj3IdR2CaqsQMAAYAUwy3Zn8qB8mG7D/gwbyaMCNotJHlHkjy3TU2aaymKOWLEEJFAtgSyMk++hjFzauwcUktkfP5LHdVYP/Om9C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;" 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diff --git a/images/predictive_analyticsv3.pdf b/images/predictive_analyticsv3.pdf
new file mode 100644
index 0000000..0f3ce57
--- /dev/null
+++ b/images/predictive_analyticsv3.pdf
Binary files differ
diff --git a/indent.log b/indent.log
index f675d51..7bb1c43 100644
--- a/indent.log
+++ b/indent.log
@@ -1,6 +1,6 @@
INFO: latexindent version 3.24.7, 2025-08-15, a script to indent .tex files
latexindent lives here: /usr/share/texmf-dist/scripts/latexindent/
- Tue Jun 23 16:29:56 2026
+ Wed Jun 24 14:50:55 2026
Reading input from STDIN
INFO: Processing switches:
INFO: Directory for backup files and log file indent.log:
diff --git a/main.tex b/main.tex
index a6194ca..2b767f2 100644
--- a/main.tex
+++ b/main.tex
@@ -33,7 +33,7 @@
\tiny
\textbf{Figure 1.2:} Where does our work fit within the field of datacenter digital twinning?
There are 5 core elements to any Digital Twin: \myCircled{A} The Digital $\rightarrow$ Physical Twin link, \myCircled{B} the Physical Twin (\emph{e.g.,} the datacenter), \myCircled{C} the Physical $\rightarrow$ Digital Twin link, \myCircled{D} the Digital Twin, \myCircled{E} the features necessary to any Digital Twin.
- \textcolor{ForestGreen}{\faHighlighter~Highlighted areas are the contributions from this thesis, which include the autonomous actions resulting from predictive insights \myCircledGreen{A} and the predictive analysis itself within \myCircledGreen{E}.}
+ \textcolo{Green}{\faHighlighter~Highlighted areas are the contributions from this thesis, which include the autonomous actions resulting from predictive insights \myCircledGreen{A} and the predictive analysis itself within \myCircledGreen{E}.}
\end{frame}
\begin{frame}\frametitle{Research Questions}
@@ -94,13 +94,17 @@
\begin{frame}\frametitle{\textbf{RQ2}: Reference Architecture}
\begin{minipage}[b]{0.45\linewidth}
- \begin{tcolorbox}[title=Use cases]
-
+ \begin{tcolorbox}[title=Implementation]
+ %Add the _implementation_ figure here instead.
+ % I.e., the Kafka, the broker, PostgreSQL, Redis.
+ % In the implementation graph: keep the datacenter "just" a datacenter -- don't yet mention we use OpenDC.
+ % Make Kafka logos clearly defined --> add a legend with icons?
\end{tcolorbox}
\vspace{1cm}
\end{minipage}
\begin{minipage}[b]{0.45\linewidth}
\begin{center}
+ % Change to Datacenter (Physical Twin)
\includegraphics[width=1.25\textwidth]{images/ref_architecture.pdf}
\end{center}
\vspace{-0.2cm}
@@ -117,30 +121,25 @@
%The time-series data flows first to the \texttt{Grafana} dashboard, \texttt{PostgreSQL} database and \texttt{Redis} cache, as advised in~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24}.
\begin{minipage}[b]{0.45\linewidth}
- \begin{tcolorbox}[title=Setup Recipe]
+ \begin{tcolorbox}[title=Problem, colbacktitle=red!70!black,colback=red!20!white]
+ We don't have large systems at hand.
+ \end{tcolorbox}
+ \begin{tcolorbox}[title=Solution, colbacktitle=Green!70!black, colback=Green!20!white]
\scriptsize
- \textbf{Step 1.} Ensure Redis and PostgreSQL servers are up and alive.\newline
-
- \textbf{Step 2.} Run a Confluent Kafka setup: Kafka Connect, Schema Registry and a Kafka server.\newline
-
- \textbf{Step 3.} Start the Python HTTP Server, and the Python Redis Monitor.\newline
-
- \textbf{Step 4.} Run the (modified) OpenDC (physical twin) with example experiment.\newline
-
- \textbf{Step 5.} \emph{Sunfish} will automatically start a second OpenDC instance, and start the data analysis.
+ Use a second simulator
\end{tcolorbox}
\vspace{0.5cm}
\end{minipage}
- \hspace{0.35cm}
+ \hspace{0.25cm}
\begin{minipage}[b]{0.45\linewidth}
\vspace{-0.2cm}
\begin{center}
- \includegraphics[width=1.2\linewidth]{images/predictive_analyticsv2.pdf}
+ \includegraphics[width=1.2\linewidth]{images/predictive_analyticsv3.pdf}
\end{center}
\tiny
- \vspace{-0.4cm}
- \textbf{Figure 1.5:} We can't just go and test digital twins on large systems as large systems often aren't at hand.
- Answering \textbf{RQ3} we provide a novel way to evaluate datacenter digital twins through discrete-event simulation instead.
+ \vspace{-0.2cm}
+ \textbf{Figure 1.5:} The experimental setup.
+ Answering \textbf{RQ3} we provide a novel way to evaluate datacenter digital twins through discrete-event simulation.
\end{minipage}
\end{frame}
generated by cgit v1.2.3 (git 2.25.1) at 2026-06-24 21:27:41 +0000