262,316 research outputs found
Chemical and thermal characterization of wood biomass from non-native tree species in the steppe zone of Ukraine
No full textSytnyk S, Rula I, Holoborodko K, Ivanko I, Lovynska V. Chemical and thermal characterization of wood biomass from non-native tree species in the steppe zone of Ukraine. Regulatory Mechanisms in Biosystems. 2025;16(3): e25113.The growing demand for sustainable and renewable energy sources highlights the importance of exploring biomass from non-native tree species in Ukraine's steppe zone. This study aims to investigate the chemical composition and the r mal decomposition characteristics of wood from non-native tree species ( Acer negundo , Robinia pseudoacacia , Quercus r & uacute;bra , Ailanthus altissima ) to evaluate their potential as biomass for energy production. Key wood parameters such as pH, buffering capacity, extractive content, and structural polymers (cellulose, hemicellulose, lignin) were analyzed, revealing significant interspecies variation linked to their biochemical traits and adaptation levels. Thermogravimetric analysis ide n tified three main stages of thermal decomposition and demonstrated differences in thermal stability and decomposition rates among species. Notably, A. negundo exhibited the highest thermal decomposition rate, while R. pseudoacacia showed superior buffering capacity. Correlations between chemical composition and thermal degradation energy requir e ments suggest that species with higher cellulose and lignin content demand greater activation energy for thermo-oxidative breakdown. These findings indicate that non-native tree species, including invasive ones, represent promising biomass sources for energy generation. Moreover, their utilization could serve as a sustainable strategy for controlling species with invasive characteristics, thereby contributing to biodiversity preservation and ecological balance in the region
Dynamic programming method in bottleneck tasks distribution problem with equal agents
No full textE.E. Ivanko, Institute of Mathematics and Mechanics, Ural Branch, Russian Academy
of Sciencies, Ekaterinburg, Russian Federation, [email protected]В работе рассмотрен ряд специфических вариантов метода динамического программирования, используемых для решения минимаксной задачи распределения заданий при условии, что исполнители равноценны, и их порядок не важен. Для разработанных рекурсивных схем метода динамического программирования показана корректность, проводится сравнение вычислительной трудоемкости классической и предложенных схем. Демонстрируется, что использование специфики условия равноценности исполнителей позволяет сократить количество операций в рассмотренном методе динамического программирования по сравнению с классическим более чем в 4 раза, при этом при увеличении размерности исходной задачи относительный выигрыш лишь увеличивается. Одна из использованных техник сокращения вычислений - «встречное » динамическое программирование - по-видимому является общей для целого класса задач, допускающих использование при решении принципа Беллмана. Применение данной техники связано с неполным расчетом значений функции Беллмана в задаче, обладающей некоторой внутренней симметрией, после чего решение исходной задачи получается склеиванием полученных массивов значений функции Беллмана. The paper considers a number of specific variants of dynamic programming method used to solve the bottleneck problem of tasks distribution in case when the performers are the same and their order is not important. Developed schemes for recursive dynamic programming method is shown to be correct, the comparison of computational complexity of the classical and the proposed schemes is done. We demonstrate that the usage of the specific conditions of performers equivalence can reduce the number of operations in the above dynamic programming method compared to the classical method more than 4 times Herewith increase of the dimension of the original problem leads only to the increase in the relative gain. One of the techniques used to reduce computing ≪counter≫ dynamic programming apparently is common to a whole class of problems that allow use of the Bellman principle. The application of this technique bases on incomplete calculation of the Bellman function in problem that has some internal symmetry, then the original problem is obtained by gluing the resulting array of values of Bellman
Two-level optimization of sensors reposition
No full textЕвгений Евгеньевич Иванко, доктор физико-математических наук, старший научный сотрудник отдела управляемых систем, Институт математики и механики им. И.И. Красовского УрО РАН; старший научный сотрудник лаборатории оптимального раскроя промышленных материалов и оптимальных маршрутных технологий, Механико-машиностроительный институт, Уральский федеральный университет им. первого Президента России Б.И. Ельцина (г. Екатеринбург, Российская Федерация), [email protected].
E.E. Ivanko, Krasovskii Institute of Mathematics and Mechanics, Ural Branch, Russian Academy of Sciences; Ural Federal University, Ekaterinburg, Russian Federation, [email protected]В работе рассматривается задача оптимального планирования измерений, проводимых с помощью регулярно перемещаемых сенсоров. Рассматриваемая абстрактная постановка может служить математической моделью для целого ряда различных прикладных проблем, связанных с оптимизацией трудозатрат при использовании технических устройств для оценки параметров окружающей среды на большой площади. В задаче выделяется два уровня оптимизации: оптимизация перемещений при перестановке сенсоров с одного набора позиций на другой и оптимизация порядка, в котором расстановки (наборы позиций) сменяют друг друга. В статье предлагается точное решение двухуровневой задачи и приводятся результаты вычислительного эксперимента. The problem of optimal measurements planning with regularly repositioning sensors is considered. This abstract problem may serve as a mathematical model for a variety of different applied problems connected with cost optimization in the experiments where sensors are used for the estimation of the environment parameters. There are two levels of optimization in the considered problem: movement optimization in the process of sensors reposition from one group of points to another and order optimization in which the groups of positions follow each other. The exact solution of the two-level problem is proposed and supported by the results of computation experiment
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Identifying important variables and profiles of domestic hot tap water energy use in Norwegian buildings by using statistical methods
No full textDomestic hot water (DHW) systems are an integral component of buildings and a substantial consumer of energy. Due to the introduction of highly insulated structures, the share of DHW heat use in the total energy balance of buildings is continuously increasing. In modern passive houses, DHW heat use already exceeds the energy need for space heating. Despite this fact, the application of sustainable and energy efficient solutions in DHW systems is not widespread in Norway. The significant opportunities for energy savings have yet to be realized. Therefore, improving energy efficiency in DHW systems offers substantial potential for further energy savings in buildings in Norway.
Utilization of demand side management, better design and sizing, progressive tariffs, low-temperature heating systems, wastewater technologies, combined DHW systems based on traditional and renewable energy sources, and other sustainable technologies and management solutions in DHW systems are essential for achieving energy efficiency in buildings. The proper implementation of these solutions requires the use of advanced data analysis, representative profiles, and accurate predictive models of DHW heat use. Nevertheless, the regulations applied for DHW heat use analysis and modeling, as well as knowledge about actual DHW heat use in buildings in Norway, contain many gaps. This PhD work aimed to improve the methods of DHW heat use analysis and achieve a better understanding of the DHW heat use in buildings in Norway.
The thesis starts with the consideration of the problems associated with the collection and preprocessing of the DHW heat use data. Firstly, the attention in this thesis was paid to the issue of restoring information about the DHW heat use in conditions when only the total heat use in buildings is measured. Further, the selection of influencing variables and prediction modeling for DHW heat use were investigated. Finally, the methods for development and analysis of representative DHW heat use profiles for residential and nonresidential buildings were presented. At the end of the thesis, the work addressed the problems of total heating and DHW heat use planning and profiles analyses for buildings in Norway in normal conditions and during the COVID-lockdown.
In this thesis, the study of DHW heat use was carried out based on data measured in hotels, nursing homes, schools, and apartment blocks. The periods of data collection varied for different buildings. In most cases, the hourly values over 1-3 years were received. However, for the particular buildings, only the monthly DHW heat use and 2-second measurements for several months were collected. Therefore, depending on the data availability, different data processing techniques were used to analyze DHW heat use. The data handling and modeling in the presented work were performed with the Python software tools.
The obtained from different sources data revealed that imperfection of measurement systems in buildings was a serious obstacle for DHW heat use analysis. Unfortunately, in many buildings in Norway, the heat meters measure the total heat use only, typically not divided into space heating (SH) and DHW. Therefore, the method for splitting the hourly total heat use into SH and DHW heat use was proposed. The method was based on the energy signature curve and the singular spectrum analysis. The results showed that the application of this method allowed us to extract useful information about hourly DHW heat use.
Further, the PhD thesis addressed the DHW heat use prediction modeling in two widespread situations. The first situation considers the prediction based only on historical data of DHW heat use. In the second situation, additional variables that affect DHW heat use were selected and applied for the modeling. These variables were identified by using the Wrapper approach. The most accurate model for DHW heat use was selected from different time series and machine learning techniques. For a hotel building, the Prophet model performed best for accurate prediction in both situations.
The comparison of the actual DHW heat use in building with existing national and international standards showed that the standards commonly used in Norway are not accurate enough and cannot correctly express the daily variation of DHW heat use. Application of these profiles in building simulation tools may lead to significant overestimation of the heat use.
To improve the existing approaches for profiles development, the methods that allowed us to build unified profiles for the months and days of the week with similar characteristics of the DHW heat use were recommended. The profiles based on measurements for different categories of the building were proposed. After, the method for statistical grouping of the DHW hourly heat use was applied to recognize the timing of the peak, average, and low heat use in the considered buildings.
The data from the educational institutions in Norway were used for the analysis of the total heat use in normal conditions and during the COVID-lockdown. The investigation found that the shape of the heat use profiles on weekdays before and during the COVID-lockdown remains almost unchanged, although the occupancy was largely reduced. This fact showed that some buildings during the COVID-lockdown were using energy inefficiently. Moreover, the month after the reopening of the buildings was characterized by a remarkable increase in heat use, regardless of the warmer weather conditions. For heat use planning in educational institutions, the following scenarios were developed: operation according to a normal year setting; reducing the heating to the level of the night heat use; and using settings that were applied during the lockdown. The study showed that applying the proper setting of the heating system during a pandemic may help us to reduce energy use in buildings.
This thesis proposed methods for DHW heat use analysis, predictive models, and profiles prediction to provide the basis for further implementation of energy saving measures and improving the energy efficiency of DHW systems in Norway.Sammendrag
Varmtvannssystemer er en integrert komponent i bygninger og en betydelig forbruker av energi. På grunn av strengere byggtekniske krav som medfører sterkt isolerte konstruksjoner, øker andelen varmtvannsbruk i det totale energiforbruket til bygninger kontinuerlig. I moderne passivhus overstiger bruk av varmtvann allerede energibehovet for romoppvarming. Til tross for dette er anvendelsen av bærekraftige og energieffektive løsninger i varmtvannssystemer ikke utbredt i Norge. De betydelige mulighetene for energibesparelser har ennå ikke blitt realisert. Forbedring av energieffektivitet i varmtvannssystemer gir derfor et betydelig potensiale for ytterligere energibesparelser i bygninger i Norge.
Utnyttelse av ulike teknologier som såkalt behov-utnyttelse (demand response) i bygninger, bedre design og dimensjonering, progressive tariffer, lavtemperatursystemer, spillvarme, kombinerte varmtvannssystemer basert på tradisjonelle og fornybare energikilder, og andre bærekraftige teknologier samt med styringsløsninger i varmtvannssystemer er avgjørende for å oppnå energieffektivitet i bygninger. Riktig implementering av disse løsningene krever bruk av avansert dataanalyse, representative profiler og nøyaktige prediktive modeller for varmtvannsbruk. Likevel er det fortsatt nødvendig å forbedre regelverket som benyttes som underlag for analyser og modellering av varmtvannsbruk, samt kunnskap om faktisk varmtvannsbruk i bygninger i Norge. Dette doktorgradsarbeidet hadde som mål å forbedre metodene for varmtvannsanalyse og oppnå en bedre forståelse av varmtvannsbruken i bygninger i Norge.
Oppgaven starter med å vurdere problemene knyttet til innsamling og forbehandling av varmtvannsforbruksdataene. Deretter ble spesiell oppmerksomhet gitt til spørsmålet om å hente igjen informasjon om varmtvannsbruk under forhold der kun det totale varmeforbruket i bygninger måles. Videre ble det valgt ut påvirkningsvariabler og prediksjonsmodellering for varmtvannsbruk ble undersøkt. Følgelig ble metodene for utvikling og analyse av representative varmtvannsforbruksprofiler for bolig og andre bygningstyper presentert. Til slutt tok arbeidet for seg problemene med total oppvarming og planlegging av varmtvannsbruk, og profilanalyser for bygninger i Norge under vanlige forhold og under COVID-nedstengning.
I denne oppgaven ble studien av varmtvannsforbruk basert på måledata fra hotell, sykehjem, skoler og boligblokker. Perioden for datainnsamling varierte for de forskjellige bygningene. I de fleste tilfellene ble data over 1-3 år mottatt. For de utvalgte bygningene ble det imidlertid bare samlet inn månedlige varmtvannsforbruk og 2-sekunders målinger for flere måneder. Avhengig av datatilgjengelighet, ble de forskjellige databehandlingsteknikkene brukt til å analysere varmtvannsforbruk. Datahåndteringen og modelleringen i det presenterte arbeidet ble utført med Python sine programvareverktøy.
De innhentede dataene avslørte at ufullkommenhet i målesystemer i bygningene var en alvorlig hindring for varmtvannsanalyse. Dessverre er det slik at i mange bygninger i Norge måler varmemålere bare det totale varmeforbruket, og det er vanligvis ikke delt inn på romoppvarming og varmtvann. Derfor ble det foreslått en metode for oppdeling av det totale timebruken av varme på romoppvarming og varmtvannsforbruk. Metoden var basert på energisignaturkurven og singular spektrumanalyse. Resultatene viste at anvendelsen av denne metoden gjør det mulig å hente ut nyttig informasjon om bruk av varmtvann hver time.
Videre adresserte avhandlingen modellering av forutsigelse av varmtvannsforbruk i to utbredte typer situasjoner. Den første situasjonen er prediksjonen kun basert på historiske data om varmtvannsbruk. I den andre situasjonen ble flere variabler som påvirker varmtvannsbruk brukt og valgt for modelleringen. Disse variablene ble identifisert ved hjelp av Wrapper-tilnærmingen. Den mest nøyaktige modellen for varmtvannsbruk ble valgt fra forskjellige tidsserier og maskinlæringsmetoder. For en hotellbygning fungerte Profetmodellen best i begge situasjoner.
Sammenligningen av faktisk varmeforbruk for varmtvann i bygging med eksisterende nasjonale og internasjonale standarder viste at standardene som ofte brukes i Norge ikke er nøyaktige nok og ikke kan uttrykke den daglige variasjonen av varmtvannsbruk. Anvendelse av disse profilene i bygningssimuleringsverktøyet kan føre til betydelig overvurdering av varmebruk til varmtvannssystemer.
For å forbedre eksisterende metoder for profilutvikling, ble det anbefalt å bruke metodene som tillot oss å utvikle lignende profiler for månedene og ukedagene med lignende egenskaper ved varmtvannsforbruk. Profilene basert på målinger for forskjellige kategorier av bygningen ble foreslått. Deretter ble metoden for statistisk gruppering av varmtvannsforbruk for hver time brukt for å gjenkjenne tidspunktet for topp-, gjennomsnitts og lavvarebruk i de aktuelle bygningene.
Data fra utdanningsinstitusjoner i Norge ble brukt til analysen av den totale varmebruken under normale forhold og under COVID-nedstengning. Undersøkelsen fant at formen på varmebrukprofilene på ukedager før og etter COVID-nedstengning forble nesten uforandret, til tross for at belegget ble svært redusert. I tillegg var det slik at måneden etter gjenåpning av bygningene var karakterisert av en formidabel økning av varmebruk, uavhengig av værforholdene. For planlegging av varmebruk i utdanningsinstitusjonene, ble følgende scenario utviklet: styring i tråd med et normalt år, redusere varmen til nivå for nattbruk, bruk av innstillingene som ble brukt under nedstengningen. Studien viste at anvendelse av rett innstilling på varmesystemet under en pandemi kan hjelpe oss å redusere energibruk i bygninger.
Denne oppgaven foreslo metoder for analyse av varmtvannsforbruk, utvikling av prediktive modeller samt med profileringsprognoser for å gi grunnlag for videre implementering av energisparetiltak og forbedring av energieffektiviteten til varmtvannsanlegg i Norge
Protecting Animals 36: Author Witi Ihimaera
No full textIn this very special episode of Knowing Animals I am joined by beloved New Zealand author Witi Ihimaera. Witi has written many books featuring nonhuman animals. He offers us a non-colonial lens through which to think about the human/nonhuman relationship
Использование больших данных в оценке численности индивидуально неидентифицируемых животных с помощью камер-ловушек на привлекательных стратах
No full textE.E. Ivanko, Institute of Mathematics and Mechanics, Ural Branch of the Russian Academy of Sciences, Yekaterinburg, Russian Federation; Ural Federal University, Yekaterinburg, Russian Federation, [email protected]
Е.Е. Иванко, Институт математики и механики УрО РАН, г. Екатеринбург, Российская Федерация; Уральский федеральный университет, г. Екатеринбург, Российская ФедерацияCamera-traps is a relatively new but already popular instrument in the estimation of abundance of non-identifiable animals. Although camera-traps are convenient in application, there remain both theoretical complications (such as spatial autocorrelation or false negative problem) and practical difficulties, for example, laborious random sampling. In the article I propose an alternative way to bypass the mentioned problems. In the proposed approach, the raw video information collected from the camera-traps situated at the spots of natural attraction is turned into the frequency of visits, and the latter is transformed into the desired abundance estimate. The key for such a transformation is the application of the correction coefficients, computed for each particular observation environment using the Bayesian approach and the massive database (DB) of observations under various conditions. The proposed method is based on automated video-capturing at a moderate number of easy to reach spots, so in the long term many laborious census works may be conducted easier, cheaper and cause less disturbance for the wild life. Information post-processing is strictly formalized, which leaves little chance for subjective alterations. However, the method heavily relies on the volume and quality of the DB, which in its turn heavily relies on the efforts of the community. Although the construction of such DB could be rather difficult and controversial, it is much easier than the solution of the initial abundance estimation problem. Moreover, such a rich DB of visits might benefit not only censuses, but also many behavioral studies. Камеры-ловушки являются относительно новым, но уже популярным инструментом оценки численности индивидуально неидентифицируемых животных. Хотя камеры-ловушки удобны, при их применении остается как ряд теоретических трудностей (таких как пространственная автокорреляция или проблема ложноотрицательных наблюдений), так и чисто практические сложности, связанные, например, с трудоемкостью сбора рандомизированных данных. В данной статье автор предлагает альтернативный метод организации учета, позволяющий избежать указанных проблем. Предложенный подход основан на сборе видеоматериала с помощью камер-ловушек, расположенных в местах естественного притяжения животных. По собранным видеоданным рассчитывается частота посещений, преобразуемая далее в оценку численности животных в исследуемой области. Ключом к такому преобразованию служат корректирующие коэффициенты, вычисляемые для совокупности конкретных условий наблюдения с помощью применения Байесовского классификатора к масштабной базе данных наблюдений в различных условиях. В долгосрочной перспективе предложенный подход позволит проводить трудоемкие работы по оценке численности индивидуально неидентифицируемых животных легче и дешевле, а также приводить к меньшим вмешательствам в дикую среду обитания. Обработка полученных видеоданных строго формализована, так что предмета для субъективных разногласий при учете практически не остается. Изложенный в работе метод существенно зависит от объема и качества базы данных наблюдений, которая, в свою очередь, существенно зависит от усилий заинтересованного сообщества. Хотя конструирование подобной базы данных может быть сложной и противоречивой задачей, ее решение представляется существенно более легким, чем решение исходной задачи оценки численности отдельно для каждого конкретного случая. Создание подобной базы поможет не только при учете численности неидентифицируемых животных, но также обеспечит богатый источник данных для различных поведенческих исследований.Acknowledgements. The author wants to thank Dr. Nikolay Markov (Institute of Plants and Animals, Ural Branch of Russian Academy of Sciences) for the fruitful discussions and critics and Evgeny Larin (Nature Park “Kondinskie Lakes”) for practical insights
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
O ČEMU RAZMIŠLJA OBRISANO LICE. ARISTOTEL I HEIDEGGER O MIŠLJENJU
No full textHeideggerovo razmatranje pojma mišljenja i načina na koji čovjek shvaća i razumijeva ima metafizički karakter. Dvojba koju Heidegger iznosi u djelu Što se zove mišljenje? vezana je uz način na koji čovjek misli. Čak štoviše, način na koji čovjek ne misli, jer prema Heideggeru, čovjek još uvijek ne misli. Potrebno je svojevrsno osviještenje. Čovjek mora napustiti ustaljen način mišljenja, koji ima karakter proračunatosti i koristi, te se osposobiti za autentično mišljenje, koje Heidegger naziva osvještavanjem (Besinnung). Osvještavanje se ispostavlja kao autentična ljudska djelatnost koja čovjeka dovodi do istine njegova Bitka. Za takvu aktivnost potreban je korak u kojemu čovjek napušta ustaljen način mišljenja i predmete toga mišljenja. Takvu vrstu otpuštanja kao opuštanja Heidegger naziva opuštenost (Gelassenheit). Čovjek treba ostvariti određenu opuštenost da bi mogao misliti na način osvještavanja. Čovjek treba čuti zov koji ga zove misliti, a taj je zov upućen od Bitka samog. S druge strane, ni Aristotelovo razumijevanje pojmova nous te noesis nije lišeno metafizičkih karakteristika. Svojim razlaganjem pojma nous te dolazeći do najvišeg bića, božanskog bića koje naziva nepokrenutim pokretačem, Aristotel pronalazi vrstu mišljenja koja nadilazi ustaljeno razumsko mišljenje te ju određuje kao najvišu ljudsku djelatnost. Ta djelatnost je ona koja čovjeku omogućava najvišu sreću ili blaženstvo (eudaimonia), a ona je takozvana theoria ili misaono promatranje koje uključuje promatranje najvišeg božanskog bića, nepokrenutog pokretača
Vještačenje i očevid prometne nesreće
No full textU radu su prikazane sve bitne pojedinosti vezane uz vještačenje i očevid prometnih
nesreća. Očevid prometne nesreće ključan je u kasnijem sudskom postupku kod utvrđivanja
odgovornosti za nastanak prometne nesreće. Cilj očevida je prikupljanje podataka o događaju
o kojima treba raspravljati, a do kojih se može doći na mjestu nesreće. Tu je bitno i
vještačenje koje provode ovlašteni sudski vještaci kako bi se razjasnili pojedine elementi kod
nastanka premetne nesreće bitne za sudski postupak
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