 o laitėjų, žaidėjų, nes ką laikėjų, šiandiena labiau kai kūros matematikus. Aš laikėjų, turime dėl laimėti laimėti laikėje, ir laimėti laikėjų, jie peržaikėjų. Žodžėjų viskas laikėje, nes ne adžiūrės, bet jau nekkia kai pasiprasiu, ir taip ir malėkui buvo te silicone. Bujau buvo plastvome, galite, patieri ne tik", dar lai dičiauλη, štiant ats Environment malaikai byoloju, jis jino žaidu liarpa inkoliskas. The unavieračio посalio to «Non-Math Maßand Spart prohib pasalamė ne Magnropuss respective tik pralikas military regioju. Tai buvo benditoris per kėlis titios patėjų, aki dičioji įviedė αποjo dmonebau øntuangas aňėjo consi, tai, savo prieš perspektivę, mes tai prieš perspektivą, ką jie žaidėse žaidėse, kas tų promieštų žaidėse. Tai jis diržiai, suprinėjo, jis turėjau, kad visus matomateitės. Tai buvo pirmą, kad dar matomateitės. Žinėjo, bet šiandien, bet tai turėjau 34, bet yra nekada, kad ir prasėjau, nesmėjo nesmėjo. Taip yra mūsų rungtynių priežiūtų metimatikį, jie peržiūrės, kaip žodžių norės, jie peržiūrės, kaip biologijos sestimatikai, jie nėvau, kaip patakšių. Jis mūsų žodžių iš Fibonacčių. Opsivės, ką reibės, generacijos reibės. Jis Meganose gerai ten ir jiems jiems. Tad prieči daug, daug naroitte atsarčiai atsarčiai eichų jės. Darbėjau – galiu tovatas iš elefantų. Žinūrės, bet yra tai ir pasikas, bet yra kiekštą priečios žaidėjų. So, of course I'm kind of a joke, but then you see this quotation. And so the point of the Tonightche was a kind of particularly nice formula. And Darwin also computing how many elephants will be in say in 600 years or something like that. Taken to account to some of them die. I think if the Tonightche wouldn't make that correction. And Darwin made an error. But for some reason he made instead of making it smaller, jie reikėjo 1.000 bėgai, jis žaidėjome 1.000 mes jie reikia prieš dėjomės. Tai šiandien ir reikiai komputėtų komputčios visi reikiai. Pirmalių pirmalių, kaip galėtų generasijos, ką pradėjome darynų, kuo, yra komputas. Jis eikės rungtynėjų 3.000 ir 1.000. Jis rungtynėje laikėjų, kad pradėjome darynių ir darynių. Čia iš negalės, kurie mėgau, kad visas rungtynėjų. Taip, taip, kad buvo darbina, perčiau. Esk Sufas, štieko štieku, buvo labai labai, nesiparės ir ką, kad jis pasirės, pasirės, ką buvo labai visi patėmėje. Pėkėjau, kad jei pėkti su įvartiką, bet galėjau, kad labai, kad pradūs, kad jis pasirės, nežinėjau, kad pasirės, kad ant, kad jis perčiau. Iš kai, kad tai, kai, kad nesiparės, nesiparės, kad nesiparės, bet jie taip viskas priešsakos kontekstų. Oje turėjome Benžiminę Franklininį, jie pergūdamas, žaidimą, yra kaip atveikiau, jie nesėgome, yra populėtumą lėstėjo, Yra gerėjo, yra pradžiausiai, yra turėjo nežinio, jie nežinio, jie nesėgome, nesėgome 8000 gala, ir jie nesėgome, ir apie reikėjo. ir žinome surikiau miltas buvo kanavutą. Mano įvėta, kad žinome šiandien žomės, būtų įvėtų nebūtų, kaip žinome rungtynės. Mano žinome, kad geriausiai įvėtų, kad žinome galei. Taip žinome, kad mūsų žinome tarpų. Kaip įvėtų, kad žinome rungtynės, nes geriausiai rungtynės. Čia jiems įvėtų našsų Australiai, ne visu savo rungtynės, kai aš žinome. Darvini, ką jis dar gerai, o savo komandas. Jis visu pasakės, kad jis visu komandas, kad darvinės. Jis visu komandas, kad tai jis visu komandas. Ir tai, kad darvinės, kad darvės, kad darvės, bet jis visus komandos, kad ir 99% matematikus, jis visus komandos, kad jis visus komandos, kad jis visus komandos, ir buvo adžiūros komandos nesikas ir o poėjauškėje atėjų. Nežinau, kad jis turime kodėlės komandos priežčių, ar gynybėje, kad jis visus esu, kuris buvo nesikas, bet tikrai ir reikiai, ką reikiai reikiai, kuras reikiai perrūčiau. Jis viena, kad jis visus rungtynes, ir taip ir tikrai, ką pasiprūčiau, ir ar jie pasakyti, kad jie priešuotėjome, jie priešuotėjome, kad jie priešuotėjo, ir neskėlėjome tos dalyvėse. Jis visiežiai žaidėjo darbėjo, nevarėjome, kiek visus. Jis sužiūrėjome tos dalyvėse, bet jie irant mūsų komandos priešių, dar man reikia sužiūrės, tai neveikėjome, kad aš visus, kad mūsų reikiai ir pėlėjome, ir pėlėjome, kad priešių, ir pėlėjome, kad pėlėjome, ir komandos. Ivo turiu, kad atsidede, apsidėjome atsidėje. Įvėl jie neveikas, daug nesiprumės, kad matematikų. Apsidėjo kartu, kaip viskas viskas pasiriu. Sveikai, ir sužinau, šitą viską pėjų. Apsidėjo, kad ir yra kontrolės. Apsidėjo, kad yra kontrolės, ką kaip, kad yra kontrolės. Apsidėjo, kad yra kontrolės, ką yra kontrolės, ką yra kilbėje viskas. Apsidėjo, ką yra kontrolės. Ir ant posinės, kurias nodžiasi ohinau, ir rungtynėjų komputicijų ir jau mėgų komputaaa, bet žaidėme su vojome rungtynėji, bet ne kai tos žaisti skalėtų komputatų ir nesėdome, ant turėbėjome. Tai, padėjo, nes povėti, pask own rungtynėje. Nes turėbėjome, kad nesėdome,kti iš vienė, kad yra skinkios piley pirmėjo nesisekitas. Viena kritisikai darvim, iš jis visus visos laipgaša mėthimų. Jis man viena mėthimai sančiai, bet jis žinau, ir šiek aižinoje. Desi, apie Fibonacčiai, žinėjome buvo dy này delai miškėčių, Ir iš darbęs iš adžiūrė, pasižinė, kad man žinėti, kaip taipomet žinėti ačiais komanda daugiai lėnių. Turės, kurie pasik patientlyti, kaipms ir nascopės. Yris meništas turės, tad yra su žinėtai paskas ir rungtyndą visai apnūrės. ir iškoje priežiūrės, kurie priežiausiai, kurie priežiausiai. Jis žalgirės, kad ir nekonečiau, kad ir įsveikės, bet taip, kad metabolėje kuriuoje žaisti, kad priežiausiai, kad ir jų juoje išsatėje, kad jų jų išėjų žaisti, kad jų ir komandai, kad jų ir galiu, atvejau, kad jų yra, kad man, kad jų ir išsatėje, start failed creat of growth depending on the mass of an animal of the length of all of the total blood system. There are lots of it's very long it goes problem kilometers and how it grows and it's particular exponent and this exponent can be divine by pure mathematical thinking right. It's tree growth and limitation with the tree and that's kind of mathematical problem ir žinus, kuriems šeikės, aš laimėjome, pirmas, bet buvo matematikus. Aš buvo, kuriems, ir gali, pirmas. Aš pirmas, kuriems, ir pirmas. Aš pirmas, kuriems, ir gali, pirmas. Aš pirmas, kuriems, ir gali, pirmas. Atvykėjo, kad buvo mėsų matės, ir atvykėjo, kad rungčiųčių puikės pabūsų pabūsų rungtynių, apėrti, kad jie buvo turės įvėmės, važčiausiai žaidžiausiai. Taip, kad jie nesitei, bet visi vienu, kad mūsų turės teiko, aš nesitei, kad rungtynių jau rungtynių jau mėsų, jei nebiūs pabūsų, dar jie mūsų priešsų dalykės. Ir bet yra tai tiek tai, kad jo pabūsų metu. ir jis ir žodžiausiai žaidėjai kvaustsų, ką jis galėjų iš agas reikas. Iš žodžiausiai ir jis kažkas daug. Likėjai ir ar darbėju dvienas. Aš jis žodžiausiai žodžiausiai, ir jis pėdų, kad darbėja nerėme, bet turi, darbėja, darbėja, bet ir tai ir rungtynės. Daven galėjote peržiūrų nesimėjo po lidių, because he was very much influenced by Lavarckyne, by Blufonne. If you read them, you see how much in common they say, but he hated accepting that. Which is suffer the same problem. But this one purty, and so when I put it in the net, you see I have references, you can read them more. Pertukėti, kad kurį nesimėjome darvinės. Jis žaidės žaidės, kad nesimėjome darvinės. Nesimėjome rungtynių rungtynių, tai mėgantose mūsų žaidės. Nebūtų ir sėkėjome darvinės. Pertukėjome, kad jis žaidės, kad mūsų į necessarilys, nesimėjome darvinės, bet nuvojome. Esa svarbėje atumėje, kurį labai nesimėjome mes į visą, ir žinėjai to galiu, kad man tai mūsų. Manu, bet jie patėjo, kad jie galėjo, kad bet jie labai tikrame nekant. Tai viena įvėl, kad jie viena įvėl, turime Žraukiai. Parybdėjome, ką jie viena įvėl, kad jie viena įvėl, kad jie visus gerai, bet jie nekant, kad mūsų priežlėjų, jie nekant jie viena įvėl. Esa jie viena įvėl. O kai jie viena įvėl, kad jie viena įvėl, kad jie viena įvėl. ir atsėdytų ką laitų, aš ką Kaumeogorovą. Jis turbirės iš pabūsėjoje ką ką. Man jis ir jau jis ir�ių, jis ir patėjų. Jei ir įrėjų žaidės, jis žaidės rungčiai. Jis visus pasalė su internetų. Jis ir dar reikia. Tik visai, ir jis visus, jis ir ir galėjų pasalės atsėdyti neto atsėdyti, bet jis ir patėjų, ir jis ir patėjų. Ir gali, kad jis metumas... Man jis ir ant, kad jis atsėdyti neto atsėdyti. ir jis žaidimės, kad jis galiu, jie pasakyti, kurie nėžiaimės. Žinome, kad jis žaidimės nėžiaimės. Čia. Nes, ar prieš šias, mės nėžiaimės. Neš, nėžiaimės, kad kaip žaidimės, kurie jis ir dėl. Nes, jis jis žaidimės. Jis žaidimės į Lotkų ekvejami. Į oje, jis, kad jis žaidimės jis, ar yra, jis yra, jis yra, jis yra, jis lygai, Kaip mūsų mūsų nuorių lėgai retėjų, ir ką laikės, bet tiesiose, kaip žaidės, kaip žaidės, taip nuoti taip rungtynėse ir bet tyriškai vietėjų. O lėgai jie supriešant, ir jie ir įvėdėse, nesinaugės ir nuotėtės. Nes, kad mūsų mūsų mūsų mūsų mūsų rungtynėse, Balsmeninį, Maxwell, nesimėjo, nesimėjo nesimėjo. Ir jis žaisti, būdės ir vaikos pergalėje. Manau, kad prasėjų, kad jis laukėjų, kad tokia prasėjų. Dalykėse jo, kad jis žaidėjo. Manau, kad prasėjų, kad prasėjų. Jie pergalėjų, nesimėjo. Yra 100 dar iš jų. Manau, kad prasėjų, kad prasėjų, kad ir aš mūsų modelęs, ir jis žaidėjo, o jis žaidėjo. Poblokėjo, ką tai. Bet yra. Tai, ką ir buvo dėl, ir esu dar atsėjote sėką. Tai mūsime žaidės, aš taip, ką to galiu. Tai aš daug jie juokas, kaip o galbėje nuvojės, galbėje nuvojės. Jis žaidės ir katerą galbėjų. Galbėje galbėje nuvojės, jis žaidės rungtynes. Jis žaidės ir penekstos, ir dienos rungtynės, jis žaidės, žaidės, ir rungtynės reikštos. Manau, kad pradėjome iš išleidėjome. Jis turėjome jau ką visą formiūlį, kuris negaliu. Aš visus nalėjome jau pirmis, ir jau nežaudėjo pasalėje, kai jau ir bet ir jau kaip jau jau galiu. Taip, bet jau jau ką įvėlėjo, pasalėjo 15 vienu, bet jau jau ką ką įvyrių. Aš jau nesžiūrėjo, kad nesžiūrėjo. Ir jau galėjome biologijos, kurį pradėjome neko visą reikėti. Esame, kad tos visu metamarijas žaidu, matemarijas žaidu, esame, ir matemarijas žaidu, ir matemarijas žaidu, kurie prieš metamarijas žaidu. Ir jie neklausė, kad 19% šeikos nažai žaidu ir dažgai, kad mums eikės, dažgai, mažai, kad vietačiau, bet jau metamarijas žaidu, ir taip yra lūdžiai, tykai, kad jau sugeriu, kurie metamarijas žaidu, bet jau manau, bet visi šeikus žaidu, kurie metamarijas žaidu, ir Žinoma, kad turime išiniu tos. Aš antraukiu pasibūtų kuusių moudu bytai. Aš argintite dvieni ir tos. Taip, kurie taip, o reikiju dėl į kurimtą. Esa, kad jų visiei prieš reaktiją reikbti, t.d., kočiuoje, betrayedėjome, kad mūsų vaidu į artis į bento į įmūtimtą, mūsų vaidu tos, iesai įmūtumas ir įmūtumas kažą, kaž bites mačinas duoti. Tai aš galėte jų, kad jų mūsų vaidus ir daugti, Ne tikrų, kad buvo štai jau žaidimo. Ne tikrų, kad apžiūrėtų galėje, bet ką jau padėlės ir įvėlės statystikų modelų, bet ką epidemėlės, tai, kuriuo, įžvausiai, ir įvėlės, kad ir būsų eukinės. Ir pavėčių mėgų gerinės, ir jau mūsų bus matių mūsų rungtų. Ačiūrės, kad jau mūsų reikės, iš priežgalės, ir dar būsų rungtynių. Ačiūrės ir jau mūsų reikės. Tai esu, kad jis buvo buvo metamarika, tai buvo buvo reguos, kuriems ir nekoškos mūsų, ką. Mani, kad užsikojome tos metamarikų. Aš priečiausiai, kad mūsų jau, kad skatūjo metamarika. Jis tikrai, kad mūsų metamarika. Jis gerai, kad mūsų metamarika jau. Bet, nes jau įvinkai, ne taip rungtynių, kad mūsų rungtynių ką. Renauja, pasirūsų pasirūsų rungtynių savo vietų, nekada. Tai išpaštų rungtynių, kaip ir bernūlai. Na, dar aš žodžiai, ir tai mūsų žodžiai gerai. Jis žodžiai, kad mūsų žodžiai. Tai yra betrų mūsų įmūsų pasirūsų, nors žodžiai, bet lūtėjome priežių matematikų. ir dar jau pasakyti rungtynis. Ar jau buvo gerės. Iš iš sėrės, bet nesveikės frydymis, nes jau pat vienas kodėjų, ir kaip pradėjų darmenų ir valis. O kai jau turėjome, pirmas, bet jau įstūrė, darmenų rungtynės rungtynės. O rungtynės, gali, bet tai poje ir jau rungtynės daug, jis vaikia, kuriai rungtynės rungtynės. padakintėjės būtų, mačiau, maluotio reikšoje, ir ką apie seniorų pamatęs darbinkų. Bet sbg, kokią reikęs rungtynių. O reikėje buvo, bet dar viena armeninėje, nes nekaip reikės, nes neveikiuosi reikia, nės mučius. Perveikiai, nes pralaimiai. Valiūčių nesikant šiekvieto, matematikai jau pasakyti. Jis nekant mūsų balutės, jis žaisėje, bet žaisėje balutės. Taip savo balutės, o gerbės nesiprašu, o šiūsų pasakyti. Ako balutė, o taip nekant, jeigu jau savo dėl buvo rungtynėje. Vos vienas darmeni, jis pataikės, kad prieš nekant. Yra metu. Jis pradžiausiai, kuriai žinėjo. Išspite, tiesiose. Jis vyriau komandos konjekcijos, mes jis jis žinėjo, bet jis peržiausiai, jis pėdavo, kad ir mažiuotiai, kad komandos kainos, nes kainos, ir komandos konjekcijos, šiandien, ką laikšės, ne visi, ir galėsime miškite. Jis yra ką komandos konjekcijos. Ir jis važiuos manėlė. Ne esumėjo,tiems, Jie jis dar suprinuos žaidės ir atveikas, bet ne viso būdų kaip man žaidės. Tai, kuris buvo lėgais, jis juokės dėl iki žaidiaus. Tai jis žaidės ir žaidės, kompletėlčiau, kad ir sužinu. Nes, jis žaidės, yra laikas, bet jis yra atveikės ir naikos peros 3 – 1. And that... And then with R he created, pointed toward genetic, modern genetic and molecular biology. And this idea that there is molecular interpretation of genetics was already in my per psi. He looked at, he looked at the statistic of people having six fingers in different families. And his conclusion were not exactly Mendelian. Ar viena k paintingas, daug laukingi ir jis žaidėjo ar diskursčiai, jis žodėjo iš ir jis kai tungo 0 iškaidu su teamą. Čia sėlėjo. Taip yra, kaip patikai iš iš momoje, taip nekatėjome, bet yra aplikos aiškot ar nekeliu. Ar kai kai yra aplikos ant jaunė su pysty, kad yra netite iškaidų pralin iškaidų, mūsų puolėjų, kai taip, Tai ir atreikia, tai daugiai daugiai, aš apie propošti 1 – 2 – 3. Aš jis kažkas visi esant mesimatimartų. Įrėjome, kad nesimtų, ir jis atreikiai mesimartų. Man jis turėjome įpūršėtų. Jis nebūtų, jis žaidėjome nebūtų matimartų iš Viena. Man iš visus, bet jis atreikiai toliausias pradžių. Jis nesimtų, kad nesimtų, nesimtų pasikuntas kabilas. Vienaip, kad jis atsigau, kiekvienės visus, rungtynėse, bet kiekvienės, kad mūsų žaidėjai, kiekvienės, kiekvienės. Ir tai buvo ir ir sužinėse, kad ir laimėti, kad ar ne. Kaip, galėjo, ne tik, kaip, savočiau, kai matematišinės, ir ir rungtynės, kai, gerai, kad rungtynės, šiandien, taip yra 5 yra pažinės. Aš kad man, ne visus, ir taip, kad yra, kad rungtynės, nesusimės, kaip, ne visus, Sveikintas, kurie nesimėjo, nesimėjo, kad mūsų eikės, neklausėjo. Pėkino, kad man mūsų ir pabėjo, ir bet darbino ir priežbūjo, kurie mūsų ir reikėjo. Nesimėjo, kad man žaidėjo, kad ir labai pabėjo, ir jie jau mūsų mūsų ekipas ir pabėjo. Pabėjo, kad man mūsų ekipas ir pabėjo. Gaudėjo, kad mūsų ekipas ir pabėjo, bet jau susikyti, kad mūsų ir pabėjo. ir manau, kad peresitimas niegu. Laiduovo, kad žaidėte labai, kad apie norėjo, jis ir jis ir dar, ir galbėme balčų, kuris netą visą, bet... Taip, kai, na, Vanbergas.Maybe, ir jie nusiai sluvojaamą. Turėme jis atvaikinome matematiką. Iš taip, kas tai, tiek pati, kur jau rungtyvai kartęs, yra šiandien. pardžių kiekvienas, jie neveikėjo thekti ar reactsivų, ir apinu apie prieš dėl metu, reikiai, kad apinu pradžių ir jie diversite reikiai. Į kiekvieną, kad mūsų mėsų pranaujau, jie pardžiu – tai visai viena ayojio, ir keli į pardžau jie taip mėgų. Taip ir cantčiu, ir jie nesrėdstes patrindės se ji, ir esimas dar, tiek kėlą. Ne mano točių, ir į vieno. Tai metu buvo sūrės, ir, jie netiek, Tandien, esim, kad pėdėjo ar ir glasbūsiaių, tiesim, kad patėjome reikia, aš nebūsėme, žaidėjo ši희 mūsų, savo hasnėjome atdėjote 50 taškių atsų, kurias esimpėjo įsvėtų matemateksų, bet, kad mums nesik+, pasusiasbėjo šiandien ir rungtyniai, taip, dar rungtynu, kai yra metiirkumės šiandien syvėmą, Taip, kur j Beltiui nesimėti, kad pirmą kovę iš visą pasakėlėje, ką taip ir mūsų seksim läuftim į prieš mūsų prieš sėlėje. Ves, jis yra prieš gerai View하지, kokis nevykšėtyvome ir jų prieš žaisti jau antos metus. Nesimėti, kad jau kažkarpai esias yra prieš mūsų prieš prieš metus, ... inlandi, but he didn't he never try to understand what happens. What happens at the following phenomenon and I thing is what I'm using and it is not written and text books in genetics, the genetics are never found. These people are not mathematicians and as follows, you have a matrix in here there are some entries. If you take some element, you take some here, you multiply them, and then imagine the sum of the entries was one. ir dažiandų, ant tai nebūsai pėjai mūsų sužaižai. Aš, ką lai džiūrėti padžianti, o nebūsai, tai džiūrėti, tai džiūrėti. Pūkintas šį antrių, ir ir rungtynių rungtynių. Pūkintas šį metodą, tai džiūrėti kąlėti, tai džiūrėti, tai džiūrėti. Iš to, mėsau, ir tai džiūrėti. Jis ir kaip dažių, Lo, jis suprinomėlė, jis prieš prinomėlė, rungtynės komandos, bet šiandienas, kaip ar jiems suprinomėlės jau apie. Nu, nės nės net, kad prinomėlės, nės nės reikia. Iš komandos, kuriems šiandienas, nės prinomėlės. Ir jiems, kuriems, dar kūrintų matemarių, pradžių šį svarbė lesekėjo, pradžių, kurės pradžių, pradžių svarbė, Bet tai metimai jie nekoti at clearly quasi atveju. Tai baigus, bet tai būsi galbūtės, kad jie paklokėme mėsės ir rungtynes. Tai žin eternių, ikite k šeitą ir jamčių. Tai taip toliu, kad žinoje naltrų įvaikos žinomai. Manau iš žodžiausiausiausiausiai vs. žodžiausiausiausiausiausiai. PARO Y otras, bet iš jokiu, kai의ūsio alžiūras. Kol сказалio tų rungtynių apologijų. Todėl šiandiena, kai planetu. Nu, ne palaikio. Jų šiandai tarbių, kuriga peržodė dalas alžiūrus vabūsios. Turip, bet visau, kur yra každomu penkintas su Vaasbūnėjo. Aš prieš kažkas, kad jau žaidėjų naumai, bet jau su Google, jo referensau, kad Harry Weinberg, kurio ir nežinau žaisti savo, o Harry lėti, ir Harry suprinė, atengnėjame matematikų. Aš važiuoja, kad, jis žaidėjų, nežinau žaidėjų. Aš visi, bet jis žaidėja, kad apie aš aš apos B, ir žaisti. Taip yra jas labai rungtynių ir jis labai mušinės, ir kai jis iš jeigu, jis visus, jis yra žaisti, jis žaisti. Tai visus, ir žmonės, jis žmonės, jis žmonės, jis žmonės. Jis žmonės, jis žmonės, Jiseariai, kad, jie, jas, dar jis, jis, jis, jis, jis visus dalybiu doma, visi daug jų rungtynių ir dalybų komputčių, ys visus dalybų toriu komputčių. Galiu, ar taip toriu, visi daug bet, rungtynių, vaikip, buvo, mūsio, monikų jau, atžaisti, lūtėjume jaunų. Taip, suprėjome, kaip tai mūsų žaidėjų. Tams rungtynėse, kad fysio, ir fysio daug, bet jis žaidėjome, rungtynėse, kad fysio buvo matimatišus, yra nėgau, kad jų aš jau suprėjome priežavė įrės ir rungtynės bet jų mūsų žaidėjų. Jis buvo buvo matimatys, bet buvo turės rungtynės. Ir ir visi. Jis žaidės su eksplanacijos antripeių, žaidės kąlės, ir kąlės, žaidės. Pūkau, kad tai, vienės atsėjome, nekai ir antripeių. Esau, kad nesiparės nesiparės, ir pūkau, vai jis apie vykant, nekai mėgau, Boles hungry by plank, interpreting's and work by bolesum. Or if formula was not... This computational formula for entropy, entropy defined, not like that. This is another story. But once you accept it, looking at that, what's so special about that? And then you can say, uh huh, so let's understand what it is. So it's some function of PI. So what PI, some positive number, is sum equal to one. This is a simplex, right, in the occlusion space. So it's a function in a simple. The fundamental property of this function, known of course by Boltzmann, but usually attributed to Shannon, who wrote it in a special case, is that the function is, keep hanging from convixed to concave Dodėjome.Dadėjome, kąiranėti povigusote, o užkių žaidėjome. Ano, viskas mėnygi, būgaučiausiai pėtis, esu, jie prasimėtų prasimės. Rėgog jų žaidėjome laiko katėjo. Nes savo laimntavės, to jinu, tai rungtynės. Dėl kažkas šeikinės, to svoje kitą, buvo yra metra. Tai galime, bet jis jaustalės ir manaižinės. Atsas, o iš surybė, tai yra metra. Šiandą kartą, jums bei tokie sėkęs. Aš smėgant metrikę, aš ne, ne. Šiandie metriką, kad jis taip žiūrės, kad mūsų žiūrosi, kur'ešės. Ideni metrią? Yra labai, grūba. Mūsų ne pigyro, buvo. Ir jis pat, kad nesakant žaidės kitų išliaux. Galiu, atėjame metru. Ir puckavo. Nes mus, kad jie visus rungtynes, Atestų mondėjo, kiek tiek tikrai rungty내 atvėjo. Čia viskas lab athletes iš viskas tikrai viskas netrobėjo. 5, 6, 7, 10 žodžiai apie iš ekipairi, jie labai kuris užsurfėse? Na, turime aš iš iš reikiai, iš mūsų matematių labai, aš turime aš iš iš reikiai. Awai aš Žiausio atveju yra turime aš aš iš – 20ies. Bet drugį metrižimų solime tos, tos turbien kovicės, ir nebūvai mūsų metriščiau, ir šis metu, kurie patie, kaip ir, tikrų, buvo, tikrų, tikrų, tikrų, tikrų. Aš tos. Aš ašori, nėjau, bet galėjau, ir atkūmau, kad buvo. Jis kuris, ir jis atkūmau, kad aš jis kėlėjau, kad kėlėjau, kad aš spėjau. Žinome, kad tevi, kad jis pati, kad mūsų laiko, kad jis pati, kad buvo. Jis pati, kad tu, kad tu, kad mūsų laiko, kad kėlėjau, kad kėlėjau. ir jis kažkas, bet jis sužažėjome kompleksijos, kad mūsų žaidu ir aržiausiai. Jis žaidu kažkas, kad oveikėtų komandos megojų, ir sužažiausiai. Taip, tai mūsų rungtynės, kad jis žaidu, jis žaidu, kad jis žaidu, kad mūsų rungtynės mums ir mums ir mums ir mums, taip visi palažiausiai ar bažai, jis žaidu, kad mums ir mums ir mums, ir ir taip ir matemarikus. Aš įvėlėjo, yra atsėjai, ir dabar jiems duotas. Pultūrės ir svėtų, nes kvantiteitės nebaimės, kad jis tai yra geruovojume. Tai yra atvykti, jiems dienės, yra matemarikus, jiems nes vietėjo, ir jiems pomekštės, jiems buvo, ir jiems žodženės, komisji, biologijų, bet jeitų matemarikus. Ir jiems... jiems jiems, nesumės, nežaisti jis iš genetikalis ir nesimpaštai, aš žinus dėl, kad jis šeistėl laimėtų prasės, žaisti, kad galėjo, komandos prasės, kad žaisti, kad mums įvėlėjo į darbą, kad jis pasikės mūsų prasės. Aš dar laimėjo, ką buvo prasės ir jiems, Nes now,ime,Kinda bloody by, by willnt, I think his name, which is called probely approximately correct, if you know computation computer science invented some probely approximately correct pack theory which is,was meant to make more quantitative argument in biology, but if you look at this article, there is nothing biological there. Pustinės komputerai. Pustinės, kuriuo ir vieno. Jis viena, kurėjo, kad prasėjome. Jis daug ir būdėjo, savo kaip būdėjo biologijų. Jis turėjo su išmės ir, tai, ką, į visi man yra visus problemas matematikų, o visus ir būdėjo biologijų, ir kai pradėjo. O, ką, nebūdėjome, galėjome buvo. Kaip jūsų žaidės, kuriems sėkai, kad jau žaidės mūsų mulikus žaidės, jis žaidės, kad nekant pasiklės su turėse ir dalis. Jis galėjo viskas žaisti. Jis žaidės, kad jau žaidės, kad jau lėgau, būtų, kuriems jau pasiklės, tai jau pergalės, jis pergalės pergalės, kad jau pasiklės, kad jau pergalės, Hon like proving with numerical theorem really makes some non trivial prediction in chemistry. So it justifies or introduce the excluded volume principle. And this was, so he didn't use the word percalation. And it was not invented by mathematician. He was a chemist. And one of his work was great work. He imagined all this percalation theory in different contexts. It's called, look at how colloys become transition, phase transition colloys. And another of these ones was studying polymers, how polymers behave there. But he was not concerned in folding. He was just concerned how in random, how random chain, what would be the shape of this chain. And he raised this major problem, which now called this self-avoiding random block. And he analyzed it in a non trivial fashion. But still the main problem about this random block open. Nobody knows. So of course if it allows self-intersections, then the average diameter of a random molecule will be square root, constant square root, the length of the molecule. And he gave another formula. They are saying it will be slightly longer. But nobody knows what is true or not. Nobody proved anything close to that. Just absolutely, there is no in my view, non trivial results about that. Lots of work, very difficult mathematical theorem. But the question was on the same level as was left before. It's amazingly both in dimension 2 and dimension 3. In dimension 3 crucial for folding. If you think about that, so what make this folding? And so why it is mathematics, why it is actually biology. And physicists can say nothing about that. Because if you're a physicist, how you approach problem. Okay, it has some interactions, so I write this energy. Which sequence to take? Of course you take random sequence and do something. You can may or may not prove something, it's still very difficult to prove anything. Because you can't even evaluate the length of the thing. But it's absolutely irrelevant. Because sequences in biology, biology, anti random. It is not random. And you don't know what is anti random means. And this is the whole point. And the best for the moment, mathematical methods. For evaluating, understanding how they were shaped. What would be the shape of this folded stuff. Is done by artificial intelligence methods. While they called artificial intelligence as just a trained artificial neural network. And it's not surprising why to so. It's certainly predictable. It is exactly where our brain is not so good. There are some masses of people having gifts, getting that. But machine do this job much better. But we still don't understand it. It's look at very many examples of proteins following which you know. Train your network and then extrapolate it. Well, maybe I'll say in some later points how these things work. But that's absolutely fascinating question. And if you go into biology, it's not just, even formulation of it is not so simple. Because you have to know protein is not just random sequence. It's sequence with certain functions. And it has certain history. And there are lots of variations how you have to formulate the problem. Which makes my view much more interesting. You cannot just isolate it and say something and solve it and be happy. Because even that is impossible. If you do it, it will be completely off target. You have to learn much more. You have to learn volumes what you know about proteins to be understanding. And of course, for example, this scale. It only works, whatever you prove. When you have this protein chain, what most three may be 400 mean as residues. If it's too long, it's not asymptotic statement. It's asymptotic, it will be horrible. Nothing will work. And nature knows that. These long proteins don't fold. And they serve different functions. And it's the exam. When we come to the next level, all that is essential for what life is. It's not accidentally like that. In a way, it's not accidentally. Main thing, of course, is accidental. But now we come to the first preamble. So, okay, we can make now a little interruption. We have five minutes, and then actually this was a good preamble. And then we start with the first lecture. Here is again Buffon, who knew mathematics as good as we do. He was translating Newton. He was probably reading it. It was not so easy. And he invented this famous experiment with Buffon needle. It was absolutely beautiful piece of mathematics. He created integral geometry and geometric probability. And then, so, we can roughly divide problem in two kinds. Two extreme cases. One on the molecular level, which I mentioned, like protein folding. Protein folding is not related to biology. It's signal biology, kind of biochemistry. It's one molecule. It's not alive yet. It's just one remarkable molecule. And we shall discuss philosophically what happened there. It's an incredible step. One of the incredible steps in the structure of life. And this was so exciting. And at some moment I will give you a more mathematical example. And second, it's opposite. What happens on the whole earth, how animal plants and human bacteria coexist here, how they interact. And then there is something in between. And then there are indeed kind of relation between that. For example, at some moment, if you may be right assumption like this. And then there is this number. So what is the relation? For example, if this number, it would be at most that you add a little bit and then... So what are these numbers? The whole world depends on this. This billion are all the number of people on earth. Eight billion. But imagine this because this is slightly below thousand. It would be slightly above thousand. It would be impossible. We depend on that. Very, very, very serious. Again, this would be in the end of my lectures. So this molecule, not even molecule, but just elementary chemistry related to our biology. And is a nitrogen. And this is essential part of our body. We have about... In your body, I forgot how many... Of nitrogen. I forgot 50 grams of 5 kilograms or something. I forgot. You have some nitrogen in your body. In your proteins. Mostly. And this nitrogen came from where? Where nitrogen put this nitrogen from the air. This is energy. In joules. In joules. It's some units. Energy of this connection. Very hard to break this molecules. You have to break them in order to put them to your body. And half of them. And this is slightly bigger than when it's being synthesized from ammonia synthesized from hydrogen. And nitrogen. And half of that in the body of us come from some chemical process. And this is of course... Most people are not aware of that. Why they are alive? And they are alive because this harbor... Harbor Bosch process. Everybody here would not be here. If not for that process. Because half of they need to take it away from you die. Of course it will not do you die. Population would collapse. At most of this number. Or even below. And on random some of us here died. And we don't know that. It's a fantastic kind of situation. We live in knowledge of the world. By far below the Neanderthals. Who better understood the world. We live in this incredible situation. And mathematician is better than anybody else. We don't know what feeds us. What supports us. And what this supports is about disappear in about 56 years. Because we don't even don't aware of that. For example that you know. This is a major fact of existence of the earth as we know it today. But this will come in the last lecture. So there will be three lectures here. So I will be returned to that. And so there will be the following. First is just what is life. First was impreambul. Now what about life. And about this. I explain different perspective what we are. And secondly it will be genetic molecular by engineering. So what happens today. And what changes developed. And this is fantastically interesting things happening. And new things happens every couple of years. And then perspective what will be in 60 years. And then it's questionable. It depends what we shall do. And what we shall do depends on our knowledge. And if you know as little as we know now. As humanity it is an end with that. By the end of the century there will be no civilization. Absolutely no chance. If we continue the way we do. It will be close to. Exponential goes to the end. And as happens already you see some little places like Haiti. Or the same happened in this. In Africa there was this where there was horrible genocide. And that's for the same reason. There was no around enough food. Where people were killing in millions. And if continue people are killing each other in billions. If we don't make right decisions. And to make right decisions we have to know what we are. And we don't. We are very scary. Ok. But now I have a major problem. As mathematicians we can forget about that. Enjoy biology and intellectual. Intellectual. So. So there is one. There is two. In between where the most tricky thing is embryology. And it was already said by Morgan at some moment. Who didn't care for molecular biology. He just only worked in genetics. And they actually will also quite remarkable mathematical ideas. If I have time to explain. Especially some idea of Surtjevan. Who suggest completely new kind of geometry. Which we don't have. If you properly develop it. But we will be still speaking to molecular biology. And so we want to understand what it is. Ah, one second. I missed. Something of some time. Go. Some time not. Yeah, it's more. Yeah, so this beautiful. Who emphasizes point. That we don't understand the living matter. And why I say it's very important. Statement. Because in order to understand something. You start from non understanding. If you don't understand anything. You just saw the idiot. You understand nothing. You start understanding, you realize. You understand so little. And then payment sacrate statement. And this, and this he doesn't know. He can say what you don't know. And this is understanding what you know. And what you don't know. And Bufon, who was a mathematician. Partly, partly. He understood from mathematical or physical point of view. Life is impossible. So as a mathematician you must accept. Life is impossible. If you think otherwise. You never thought about that. Because you cannot make even in your mind. A reasonable model of that. And then you want to do it. Once you understood. Then you can start moving ahead. Even before. You can start to formulate reasonable questions. Even before that. You have to realize there is something to ask. So this is journal thing. Which I said. And I wrote. And then we come to the next point. What is life? So this was definition. Suggested by Spiekard Sagan. Who was anastrophysis, astronomer. And was used by Gaffa. And this is a... Well, I think. In my view, well. I don't want to be critical. I don't think it's adequate definition. And so one of the point. Whatever you're saying. That the whole idea. And it's not exactly only my idea. But shared by other people. Of certain point. The whole idea to give definition of life. Put mildly. Not correct idea. In why? So I shall explain it. But what we can do. At least look what looks like life. And then immediately it must be understood. Because what we see is not what is there. This is a classical example. We see the strangles there. There is no strangles. So our brain. Both... Our mind eye. I didn't see what was before your eyes. It sees what was already in your head. 90% of what you had. And that reconstructs on the basis of what he was seen before. And this is a very good way to think. And... And this is a... Again. A principle of... If you... People try to make. And this is a very interesting problem. Which is part of what I say anyway. At least this might be taken into account. You are not supposed to do straightforwardly. You have to learn from biology. Right? But still look at that. Where is life? Where is non-life? So... So I recognize this of course as a life. I don't know why but you know it's life. Even if you were in a different world. And so this pattern kind of... Now what is that? On this right hand side. Yeah. Mathematicians. Yeah. So we have to show everything. This you know. It's E. It's number E. But you start from one. And by the way... So how you can remember that? One. Eight. I'm using things for myself. So what about this number? I'm supposed to know this number. It's the date of birth of Leia Tolstoy. And so in somebody rose away. So I could never remember number pi. But then he realized that I was stupid. Twice repeated this number. And I must say I never remember of course when Leia Tolstoy was born. But when you know these two things. You remember both of them. Because now it's interesting. I don't remember. How many... Do you use number E? I say pi in E. Or how many when he was born. This or not person. So if you see this number. You bet on the next planet. You see something like that. You can't have it without life around. This is unquestionable. There is no known physical process. Which can produce this number. You can change like this symbol. But here about 120 symbols. Ten symbol 120 things. So it can be accidental arrangement. But you see this depends on your perception as living creature. So one living creature. Look at that and realize there is another living creature. Intellectual intelligence minor issue. Minor point. So life is there. But here there is no life. It's Mars. So it's dead. So the point is that life kind of kind of random. But random in a very different way. And one of the point. Each I want to say to develop mathematical, perceptual mathematics. You have to develop new probability theory. You have to understand the physical way of thinking. About probability is not appropriate in biology. Up to some extent appropriate. And many things of course work. But not all. And here is the examples. Next example. Now what can you say about that? What is life, what is not life? You see here is zebra. Here is a brain. This of course you see is life. This cannot be accidental. It's hard to say why, but it can be. If you find such and they come to a plane and see this kind of pattern. It again has too much structure mixed with randomness. And this is human brain. Folding of the human brain. However all these three. Of course they are not life. I mean it accidentally happens to a brain. Accidentally there is some pattern. And they actually solution with the same question. And it's not especially biological about that. And people on the other hand. There is a lot of mathematicians, biologists exploiting that. It's called shooting diffusion. Reaction equation. Reaction equation. Reaction every member counts. This is the equation. For mathematicians they take touchy derivative. And then you have Laplacin. And some vector field. Some ordinary differential equation. So you have ordinary differential equation plus diffusion term. And then in mathematics there are lots of different forms. Where you have Laplacin. Or which kind of vector fields you have. But in this situation. Your space is Euclidean space. Laplacin, ordinary Laplacin. And these are. These vector fields correspond to exactly to mass, mass this kinetic equation. Mass action equation. This is a sort of polynomial of certain kind. And very special kind of chemical reactions go there. And then choosing particular R. You may have various patterns of this type. And there are quite a whole. Bleed of mathematical biologists writing this equation. And see what happens. It's not biology. It's physical. So you move and you fall like a stone. It doesn't make the folding of people from airplanes. It's no more biological than throwing stones. Not exactly. People can move like that. But it's minor issue. So this is not. This is not. But this for example, this is more biological. Why the hell is that? This is biology. And understanding that. Mathematically, why presence of such sequence make general statement, which would be applicable to that. So if you want to define life and pattern of life, you must include that. And that's very difficult. We don't have a chance to do it. And of course, about Darwinian evolution, what Bruce said is rather funny. So if you find that, by NASA say, no, no, it's not life. Forget it. It's a discussion of these people. You can participate with them, though you know nothing about biology. This is not serious discussion. But there are some more serious ones in the second we come to that. What about that? That's another more interesting pattern. You probably know what it is. This is actually electron, this electron micrograph of a part of the cell. Namely, in the practical theorem, how pronounce correctly, I don't know. And the plasma reticulum. And this is actually a very interesting structure inside of your cell. So there is a schematic picture, how it looks. It's really like a picture of a membrane folded in a very tricky folder, membrane, and I don't know if there was serious mathematical study of that. Because this is one of the essential parts of your cell, where proteins are being synthesized. And occupies much part of your cell. And there are much of that, which just pictures. But this, of course, still doesn't look, although it's really biological stuff, it's not specifically biological. It's just about membranes. And this is interesting, but it's not mathematics. It's mathematically, but it's not biologically. And here is the point, which I have to make. I will make a little history of applying mathematics. But biology, at least from certain point of view, and this point of view of mathematicians, start from microscopes. It's cellular and molecular biology. And usually what you see outside, you can't organize mathematically. But this kind of have nothing to do with this biology. Organizm interaktsink in a relatively simple way, but described, effectively described way, correctly incorrectly, and then you do mathematics here. But mathematically interesting structure, which is not kind of applying physical style mathematics, start appearing on molecular level. Molecular level started with microscopy. And microscopy, as you know today, started with the work by Levenhuk. No, but now you will come to how biology understood biology. And so the main point of modern biology that dislike diversity, which we see of animals and plants, on the molecular level, there is some unity of the structure. And this kind of universality of the structure. And that's from mathematical point of view is exactly interesting. So there is not as elementary as you have in physics when there is one set of equations, but there are a few basic principles and they are being the same for all organisms. Organisms starting from bacteria on, and up to some point even in viruses. And then as Monoch said, if you know bacterium most common, should you say coli bacterium, you know anything about elephants, which is not quite true, right? But still close to the truth. So it's tremendous universality. And this one of the points in life, that life on the basic level, life understood as a life of a cell. We can forget about big organism, bigger, minor variations, and these are cells. And cells run by molecules, filled by molecules, active molecules. And this what is life in genetic terms. But now it might be specialized. And so what people say, I don't want to... So it divided in these points, which are here. So this is this matter, energy and information. And matter in energy related to metabolism of homeostasis energetic balance of the cells. And then there is reproduction, reproduction related to information. Information appears in two parts. First information being translated to your progeny. And secondly information translated from the source information to building these instructions, how to build the organism cell in particular. And then there is next level, how to make multicellular organism. This is another story, which is we don't touch upon. But what we have before our eyes is these three aspects of that. And in different people look at this very differently. It's amusingly people's genities are working in evolution, the emphasize, of course the production and transport flow of information. But if people working biochemistry, especially biophysicists, they would speak first about energy balance and how energy being produced distributed in your organism, particularly your cells. And both are rather complicated, but still logically and mathematically more attractive is information. And this because it's more specific for life. And all the chemical processes, well, they are less mysterious, how they appeared, but they were tremendously complicated on the other hand. But I think it's missing some pages. Yeah, this we have to eliminate. So here is the major things inside of the cell. We define the work of the aspect related to information. This is what is related to information. In second they say what it is. If you don't know. But then there are the cells, schematic picture of the cell. This more realistic picture of bacteria. This is prokaryotic, this eukaryotic cells. They differ in size, they differ in color. I'm joking, because there is no color. And this is an actual micrograph of the animal cell. Just to have this picture, but I want to show you something else in a second and then come back. I hope it is not lost. The gas was there and go. No, it's a good. Here it is. Here is a metabolic, one second. Something happened, which I don't like. It disappeared. It was there, where it disappeared, I have some problem. The second I go, it was here and then disappeared. So I'm funny. I see what's happening. I don't understand. Probably the same happens to living room. The same way here. Here is metabolic network. There are hundreds of chemical reactions going in your cell, in your body. The most important one is energy. One which creates energy uses. There are two mechanisms, two chemical processes. And one of them is breathing using oxygen. And there is a kind of, which actually biophysical process, which creates some potential, electric potential membrane of your cell in this tremendous mass. And I don't know who knows that. Except for people who work on that, knows what they are. What do you say about that? Is there anybody who knows that? It's impossible. Huge amount of knowledge. Each circle there is roughly Nobel Prize. Nobel Prize is a big group of people, very, very smart people. So this Nobel Prize is by chemistry, this thing, the serious prizes, they don't give them for some nonsense. Well, the right exception by the way. Some of them will be given, not maybe here, but accidentally. But most of them, to show you it's a mess. And this we don't touch it. And in a way you can live without exactly knowing it. You don't have to know exactly what happens with your digestion, you don't have to do mathematics, you just eat. And this is how we take this. I know actually I was nothing about that, even about the most basic things. I know it's justifiable not to know it. Because it complicated. On the other hand, this is a little bit of structure of cell, very schematic. But the basic points, also something disappeared. Something happening funny in here. Ah, well, we haven't come this. Don't quite understand how things are. Appear and disappear on the screen. Because pictures are the main, maybe look at this, because this is also concerning patterns of life before you go and understand what is life. So none of them, all of them coming from life. And I think if you look at each of the meat, any one of them you will see that. Even for example for that one, so if you make this molecule as a sequence, and it's a rather simple sequence, and still the way there are these bonds and they, I don't want to explain what they are, it's insulin by the way. Insulin is a hormone which we all need and if you suffer, you have diabetes. Diabetes is a rather common disease. I think about two people for the first thousand, suffering diabetes one. And so one remarkable progress recently due to molecular engineering, artificial bacteria made insulin. And when people started this genetic manipulations, they were very much concerned that something wrong may happen and trying to put some limits and some rules how not to overdo that. However smart people just either for fame or for money has done it and then there were rules and now this insulin came up and lots of people were saved, yeah. Experience shows that usually all serious adventure in science they may be dangerous, but people they save life rather than. And on the contrary, all this action against it, very destructive. You know how many people say in Germany died because of the movement against atomic power, estimate about two million. All action about nuclear power, just hundreds or thousand people die because nuclear power goes down. Because replaced, of course, by burning. This stuff is about one million times, one million times more dangerous than atomic power. One million times more dangerous, not two times, not three times, but million times. Because people die, die, die, develop all kind of diseases on all levels from burning. St. Paris here, yeah. It's here in Bure slightly better. The number of people dying from not using nuclear power goes in ten thousand every year, between thousand. It's interesting, there are people who kind of fall. Humanity usually exactly those who are more extremely, extremely dangerous because they ignorant. Partly, but partly because their purpose is just to fight not to do something better. And this is another very interesting square is Voynich. And here is, if you look at this page, do you think it is come from life, what is there? And this is the whole book written like that, and nobody knows what is there. It's called Voynich manuscript. It's about three or four hundred pages book discovered, found rather recently, 100 years ago. And nobody knows what's written there, if it's language or it's a joke or what. And so when you say pattern of life and non-life, here it's whether it's actually language or it's kind of a joke. And we cannot decide. And then even in this simple example, indicate how we can save what is life. When you can solve this problem. And this is, of course, the same nation, the problem. How random and how structural it is. So life is something, boss, having structurally organized randomness. And we don't know exactly the level of the structure. And of course, for languages, which is much easier because there are many languages, we study there, they are much more open, we still don't know. So how we can save what is life. We have only one example at our hands. And also even this kind of pattern, which I made myself, you can see that cannot happen accidentally. So very much life is something, which is not... Ah, here is... I brought here, by the way, this little book. Okay, so now we see it. It just was divided, but the pictures just were immersed completely wrong way. And when I was making these pictures. Yeah, and then about these days, which were big events, was happening in one which I want to emphasize, was Haber-Bor process, which I think exactly the date is known as one. And this specific moment was known, when Haber was demonstrating his process, or synthesizing ammonia out of nitrogen and hydrogen. And the essential part when you have, when you burn, when you hydrate nitrogen, they make ammonia and a number of energy separated slightly more than that. The one which connect to say, roughly says 1000, which is likely not quite right. So here, and it's about 1000, but if you burn H2, so you need right, you have this N2, H2 and N2, then it goes two times NH3, right? Correct? And so if you look at the energy here, or this connection and burning, you have slightly more than that, but of course you lose in the entropy because you have two. You slightly lose in the entropy. And because here, there are more molecules than here, and so the only way to make this process work, you need rather, you need strong volume, you have to bring them together to allow the entropy of the, of the improvements. It was achieved by Haber and the boss who was present there, who was industrial engineer, realized you can do it industrially. You can make sufficiently high, high pressure. And this is a moment, sooner thereafter it was become a process and if you look at the curve of human population, this exactly more or less where it started going exponentially up. So the major factor, the major event which happened in the human history, after we separated from chimpanzee about six million years ago, is that. If you don't quite realize it. Ecologically speaking, well, first humanoid appeared, then it's like we modified and became chemo sapiens about six million years, then there was brief preparation and then this happened. And this is where we live, it's called antra percent. Now life on earth is dominated by human. We outweighed all animals, animals like ourselves. And not insects. And certainly our stock even more. We use almost all resources food wise which are possible in us. Maybe close to one half, maybe two thirds, on the verge of completely using it. Exactly because here this energy, here is slightly more than one hundred. So it's two times, yeah. So it's more. So the major was problem, this H2 was not so hard to divide, but major problem is in that. And then before, of course before that, this nitrogen was connected by some kind of bacteria using on particular plants. And that could not produce as much as that. And then this in my last lecture explained what is the problem related to that. It's all fine. So I have so many people, we can feed them, but this will not last for long for some principle. It was a temporal solution beating kind of your beaten maltus. So maltus was beaten by this difference between these two energies. And certainly it postponed this effect, maltusian effect by about 100 or 200 years. But you see these maltuses, when you speak about maltusian, people who are against maltus, if you start talking to them, they are against, they have argument insulting you, say if you say, ah, exponential goes so fast and whatever you do it grows. They become very excited and just insult you and all bad words so I don't want to repeat them. It's an interesting point, psychological point. And then another important event which happened, and then historically very amusing was Beckerl. And this is just accidentally looking at this, I was looking at what other key moment in history was Beckerl's counteractivity. And this of course was big event. And then let's make some quotation. Here I hope it will be easy. Yeah, exactly what many things are hidden, yeah. So what you can learn from biology, it's what kind of fun you may have. And there is the collection of books I suggest reading. And now we come to these patterns. Now everything goes in the right order. And so indeed the quotation will best stir that if you don't know what is bacteria, then you know nothing and without bacteria life is impossible. And the essence of life is bacteria and sometimes you can say it's 100%. But of course not, it's always was and probably always will be the world of bacteria. They are dominant life and forever will be dominant life and we are long gone. So you should be noticed and then you see everything, all this history. And it's great main hook who discovered cells and was very much mistreated by Newton and then kind of the last thing which happens. And recently was discovery of CRISPR it was fantastic thing machinery bacteria used for the immunity like our immune system and I will talk about this more in certain level but now I wanted to discuss important events. So what are the turning point of the human history. So this is the second return to that. This is amusing thing about Beckerl. So Beckerl according to story he once, according to what his diary he just came home after vacation and there was some piece of uranium which was not exposed to light and still there was an effect on the photographic plate and so in this way he discovered radioactivity, how flaming discovered penicillin. However somebody said that all histories are just lies people agreed upon who said that we don't know who said it but it attributed to Napoleon Bonaparte and I don't know what he probably never said it but this will look the history of science exactly like that. So now see if you look slightly carefully of course if you look this more carefully you see something funny because what was the name of the Beckerl who discovered radioactivity he was Henri Beckerl and this was kind of major discovery of course in science which determines our life because you see I point them as thing which changed radically our life for example with this hybrid boss process little would have changed because people were working on that it was a technical achievement he didn't do it, haven't done it it was done by somebody else in a matter of years but there were less kind of obvious things which were done and could have been done earlier and discovery of boss of penicillin and radioactivity could be different and so you see here is what he written in the back at this person who discovered it in his diary or whatever but the name he says at Mont Beckerl, can you read it? Can you explain it? Isn't it funny? Can you explain that? You can read French, how? This Henri Beckerl discovered received Nobel Prize about ten years afterwards together with Marie Curie for discovery of radioactivity of uranium and this is what was there the idea was even when there is no light it was not exposed to light it was still exposing some rays Can you explain that? What do you think? Why is it different name? No idea? Is it easier to say with a ticket? If you look at Wikipedia and say easier to say they always say what it is in textbooks and some people in mathematics approve theorem or something like that Absolutely none History, see how to say it Mathematicians and scientists say oh well, it doesn't, who cares However, the way I feel it you cannot say and believe into the wrong things whether it's history or something if you say something it's supposed to know what you say Actually I remember there was some year of physics and some great physicists Nobel Prize was emphasizing that thesis should know their history they have to remember that Brownian motion was discovered by Brown which was not Brown was a good biologist he discovered I think nucleus or nucleolus what exactly he discovered in the cell some part of the cell he never discovered Brownian motion he studied Brownian motion he was not the first, not the last the people before him this young in house who was a great scientist discovered it and gave better explanation then Brown Brown knew about his work and he only Brown proved it it would not move by angels this was some people conjectured they believed because it was pollen so it was alive because it moved he realized it doesn't depend on that but this is background is Brown the one story, but this is another story is background was the father of Henry Beckerl and this is written by the person called Claude Felix Abellype how it pronounce it here is the name you see it here and this was done in 40 years before in 1861 and he quotes the father of Henry Beckerl for some reason especially in optics because he discovered that phenomenon and Beckerl has little to do with that I mean he studied this he neither discovered it nor gave correct explanation correct explanation with Beckerl experiments was done by Marie Curie Roosevelt but not by Beckerl and according to what I read realizing that Beckerl just was very active when he promoted himself and Nobel committee was not aware of the story but if you look at what Beckerl wrote first he discovered it 40 years after and secondly he didn't give better explanation he understood less than this guy though in many other conclusions he made very incorrect because he was serious scientist but he was not discoverer of of rejectivity in no way discovered depending how defined connection discovery he was one of the people involved into that but there were other people by the way making this observation before but he neither made correct explanation and so this tricky story so history is history of science is quite amusing because you see just for so when you think about say true discoveries people who made discovery like like Mendel imagine some even more pronounce when people discovering like atoms or something in molecular biology how excited that should become you see something in there nobody saw before and this is interesting to imagine if you look at that you can imagine how remarkable it is it give you way to feel greatness of those discoveries for example with radioactive material you do it and then you realize it is makes this race regardless of the light completely impossible new things and this didn't happen to beckereau he was not that level understanding he was just serious scientist but not that level to realize something impossible happens accept it and start doing from that right and then it is because people who make the discovery I think they either they were before that or after that they actually move to different psychological level making that and then another phenomenon actually is flaming I am quoting something else because there was somebody and chance whatever who discovered similar effect in 1896 and there was an article explaining what he's done and he was done very close to what flaming done but he was not really much interested in that he was not he was working in the lab of Ru he was Ernst Ru famous biologist who was some student of Pasteur in the Pasteur Institute and he perceived different function he didn't discover penicillin definitely he worked with some antibiotic which could not be penicillin because you know interesting thing about penicillin when he was discovered accidentally flaming never tried it on on guinea pig because penicillin is deadly for guinea pig for interesting reason because it destroys the flora, bacterial flora and they understand completely and they die and it's ok with rabbits and mice but the shampoo made experiments with guinea pig and they survived and he treated some people also with some extract from there and one of the major role of flaming of course he was not the first in either the last discovered this effect of penicillin but he realized clearly there is some chemical component there and he couldn't try to extract but he failed but he kept that in his lab and about 20 years later Flory who decided to study the subject matter studied the literature found that flaming had this experiments asked flaming to give him that and he created modern penicillin and this was not just in two words it was very big activity and he really created the whole new technology, new style to making science he organized several scientists some of them biochemists and the diameter was fantastic achievement and run by Flory who in other Flory not the same name not the same who discovered percalation not discovered but identified discovered phenomenon was kind of known of course but not identified and then another interesting story so you can imagine what would happen if this what was done in 30 years later the earlier would take would take growth and the penicillin would be discovered 10 years earlier and we will be living in completely different world of course it's incomparable the number of people saved by created by this process of hyperbore but still certainly hundreds of millions many of us would be not here if not for penicillin, either we or our parents or our grandparents would die in some surgery trauma of war whatever we were dependent on that but if it were discovered some time earlier the world would go into completely different route it's completely kind of clear it would change could move development of chemistry by 5 years give it a push and so everything would change and it's hard to say what would happen and there is another instance of a similar again think it didn't happen and this was due to Newton Newton was a great scientist but very obnoxious person not just obnoxious but probably his negative contribution to science was negative rather than positive for example he completely stopped development of mathematics in England for hundreds of years because he didn't like Leibniz he didn't like his notation so he just didn't allow that and so England was 100 years before behind, behind Europe in development of calculus but what even worse he blocked there was a very fantastic person there and this name was Gray you know Stefan Gray and this was a man similar by carrot by his biography to Faraday he had no education but he started making experiments in electricity and he was about 50 years 100 years ahead of his time and he was supported by some astronomer I forgot his name so you can hear it's a known story and Flam Stidia but Newton when he learned about that he made everything to stop it and the same he done as to preventive also of other people he just if he see any competition any good idea from somebody try to stem them out again maybe not true this what you take from books maybe it was not exactly like that but it agrees from many sources he was very very unpleasant person and there were some personal reason he was certainly very unhappy man for some reason and this again if electricity would develop say 20 or 30 years earlier it's also in England say imagine it would develop this industry it would be very different world as we know many things it was happening on the verge of kind of could move this way that way now we are seeing something in politics happening so we are happening with the war in Ukraine and just the way things not happening and it could have happened and will happen we don't know kind of accidental up to large extent and this not directly related to some scientific discoveries but they may in some moment change so what happens in unpredictable direction combination usually combination of political and scientific phenomenon because this by the way this way however he also after that he also produced this gases chemical weapons in the first world war and so was less significant all the number of people killed during the war was negligible in this exponential picture tens of millions just pin us even the people who tried the best for the sake of humanity killing people in hundreds of millions like communism, China they couldn't beat how much was saved by by penicillin and by the way both flaming and flurry insisted that they were not doing it for the sake of humanity just for fun this must be realized people who do something for the sake of humanity usually kill people yes the only way to make people happy so they will disappear okay so it is we stop here this is our first lecture and the way I projected I continue this so I have to put it on the net clean it a little bit to be sure it's correct so we can see what happens afterwards but the history of science is extremely kind of the only way you can imagine what can happen looking at the history though history never repeat itself and just people invented things for different reasons but the author tells you it may happen and so you may encourage you to do something unusual this is the point of looking at the history it is certainly quite exciting now the moment is crisper and relating things I think it's most exciting this which we will be talking in the third lecture so I explain some elementary basic not elementary but basic facts so you can speak about what comes and then I will talk about this genetic engineering there was a big progress recently and I explained so what was happening crisper or phase assisted continuously evolution or something we all interact now this new kind of vaccines which you have there was remarkable progress with vaccines they developed this new RNA mRNA vaccines we should process it's quite remarkable how it happened so now we can make vaccines for the most anything at least for viral infections maybe for bacterial infections it will not work so well in a matter of weeks I can make a vaccine in two weeks rather than in six or three months as was before it can do everything chemically at a point and so so how it happened this again very interesting book not only scientifically but also kind of kind of economically because the idea is that you have to insert mRNA into your cells into your immune cells and they don't want to go there there was this idea a long time ago and actually the people who were coming to this idea people believed that what they were doing was nonsense and this probably would never develop not for this infection we have of covid and then the covid come and then it became interesting to do it but there was some obstacle because in order to make this insertion which I repeat it again if you never heard of that this thing strangely enough it takes some time to absorb they don't want to take inside of RNA and put RNA into your cells RNA usually degraded very fast so we have to put some particular package you have to cover it by by something by some kind of lipids and so we have to develop this technology and looks look complicated however I think it will develop of course in the United States because money and then immediately this company in a matter of a year they develop this production of this process now it's available you know it took some time to develop it and it was power of the free market I would say yeah that's another point it's incredible how it works see in France I believe they couldn't make it because market was not officially free but in America they could do that they tried in England but they didn't work it well there was some other problem but my understanding is that to do things fast you need people who could do it for money not for fun not for your sake and that saves so many lives and this is a kind of paradoxical situation like fighting against nuclear energy fighting for basically kind of socialistic society deadly because things don't develop the way you want to that it follow some rules and we don't quite know them and this was a most experts at some moment estimated this as impossible economically because it was very expensive to develop the technology because it was big risk to do that and it was done. I don't know details of that but that was the major kind of progress which happened because of this COVID and so we have this new technology and it's very good in some in future I think there will be much more first new vaccines will be discovered or may now have been discovered by new vaccines and some other application of this method because you now can insert insert RNA into your cells develop this technology and it's very powerful technology and then it will be see result will come maybe in the following years along with other things like CRISPR and all this CRISPR and the third one this phage assisted evolution it's not remarkable thing progress done in biotechnology and so and I think the most interesting productive way would be for mathematicians to participate in that and I think you can do something but not just sitting like that but you have to go years learning thinking and just like for solving realizing what the problem are and trying to solve it developing idea but working on that and I think it's very interesting mathematically and gratifying because we can do something great and because the future there are this negative part of the future which because the world ecology may decay decaying and this is kind of very unhappy happy about that and what people do as if to save ecology destroys it you know for example be a fuel it's horribly destructive how could invent a horrible idea there is one of the most destructive thing for ecology fighting against nuclear power this is exactly destroying ecology destroying our life along on the other hand there are this new technology coming like genetic engineering and that certainly will make things better but again there are people who fight against it just not at all pretext of doing good things and they are not motivated by that and so but this is a part which we can myself but younger people can participate and do something interesting and probably compensate for destruction which is caused by just excess of our consumption and to many people but then ecology should be understood and then again it's extremely interesting story which is not covered by all this classical population genetics because it depends on much deeper knowledge how things are connected in biology for example one thing which I learned recently from my friends you already know there are for example problem with bees bees dying partly because there are some chemicals spreading over and if there is no bees or some other kind of insects there will be no food if you throw away all people from the earth then little happens but if you have no bees or no bumble bees or whatever amount production of food goes down by 20-30% which means 20-30% of this 8 million billion people will die and they will not die quietly horrible thing will happen and there is another kind of thing which may happen that some of our chemical may destroy east and if you destroy east in the nature or not partly at least then it also will have similar effect because it was discovered recently that much of the pollination by insects or by plant done because of the east because east give particular flavor and produce pheromones which attracts insects in the same way as this the same products attracts people eating cheese taste of cheese smells produced by east and the same happens to insects and so this if you destroy this chain and you don't know how stable it is there will be no pollination tremendous drop of course in vegetation and in our food and this you have to know and we kind of live in that we are supposed to know that if you are a mathematician, we all eat and if you don't know where food comes from you have to understand where it comes and this is one with the motivation to talking about that and then there is a book what is the name of the author it is a physics which is every future president should know so president nothing about physics every layman any responsibility I must know and when I look at that I must say that many things I didn't know I was really ashamed of that maybe 30% I didn't know and I think the same applies to a level biology but the politicians are supposed to know not to be an idiot, you are supposed to know basic things about everything which is relevant for our life we are not presidents but we should not be stupider than presidents as you know Americans we are not especially bright people and we don't suppose to be stupider than we expected president some of them could have known that so I am moralizing and stupid but I think it's nice to know things and be responsible for a life of the humanity because it depends on the culture not only scientific but part of the scientific culture we carry and we are supposed to know that because as mathematicians we are kind of ignorant of many things which happen and they are very very interesting if you learn them they are extremely interesting but you have to overcome some barrier to terminologically learn some basics and then start learning very fast and it's very interesting this is my invitation so I will try to explain something but now it will be better this very funny thing was happening with previous page it was jumping and losing things and this history is not very important just you can see there are interesting phenomena in the history of science and again they don't tell you what happens in the future but it tells you that things do happen interesting things do happen and you have to be ready for them but what they are of course this discussion is saying that different people discover things for different reasons and you cannot imitate that it's partly true, partly not true but the only thing of course that you have to try I can switch it off, right? Thank you