Molecular phylogeny of the hominoids

Početci istraživanja ljudskog filogenetskog stabla su se zasnivali na subjektivnoj metodi koja je koristila morfološka obilježja za njegovu rekonstrukciju. U 20. st. genetika i molekularna biologija uvode ljudski genom kao osnovu istraživanja evolucijskih odnosa. Osnovne metode postaju DNA hibridizacija i sekvencioniranje genoma. Zahvaljujući tim metodama za našu najbližu sestrinsku grupu stavljamo čimpanze. Pažnja se posvećuje i manjim DNA sekvencama poput mitohondrijske DNA ili Y kromosoma. To nam je omogućilo ne samo bolji uvid u našu evolucijsku granu rodoslovnog stabla, već i praćenje ekspanzije ljudskih populacija kroz povijest. Korijen naše civilizacije se nalazi u Africi te se preko Europe i Azije širi u ostatak svijeta. To je potkrijepljeno i teorijom „out of Africa“ koja sugerira razvoj i ekspanziju modernih ljudi iz Afrike u ostatak svijeta. Danas se najveće polemike vode oko “karike koja nedostaje” i njenih dosad pronađenih kandidata.The beginning of scientific research of human phylogenetic tree was based upon the subjective method which applied morphologic characteristics for its reconstruction. In 20. century genetic and molecular biology introduced human genome as the base for evolution relationship research. DNA hybridization and genome sequencing became basic methods. Owing to those methods we put chimpanzee as our nearest sister group. We also put our focus on smaller DNA sequences such as mitochondrial DNA or Y chromosome. That provided not only a better insight to our evolution branch of human family tree, but also to track expansions of human populations during history. The root of our civilization lies in Africa and spreads over Europe and Asia to the rest of the world. That point of view is also supported by „out of Africa“ theory which suggested that modern humans developed in Africa and then spread to the rest of the world. Today, the biggest controversy is the “missing link” and the candidates that represent it

Facial nerve paralysis caused by a parotid haemagi- oma: a case report

Haemagiomas, benign vascular tumors, are the most common tumor found in children. They can occur in any location including the salivary glands, most often the parotid. Most haemagiomas involute spontaneously, requiring only conservative management. Active treatment of parotid haemangiomas is needed in the rare case of disfigurement, airway obstruction, hemorrhaging or other severe complications

Fungus Balls in the Ureter of a Patient with Generalized Candida Mycosis

The morbidity and mortality associated with opportunistic fungal infections is continually rising which has been attributed to an increase of at-risk patients. Risk factors include recent surgery, broadspectrum antibacterial therapy, corticosteroid or cytotoxic drug therapy, compromised physical barriers and underlying diseases such as diabetes mellitus, renal failure or neoplasia

Limitations of Agricultural Land UsePlanning Tools in Rural Wisconsin

Recent opinion polls suggest that farmland preservation is one of the most widely shared goals for local land use planning in Wisconsin. Although the state has long been a leader in the use of tax and zoning policy tools to protect agricultural lands from residential or commercial development, continued high rates of farmland loss have cast doubt on their effectiveness. This paper critically examines statistical evidence for the effectiveness of farmland tax credit and exclusive agricultural zoning policies in Wisconsin. Using data collected at the township level (the local unit of land use decision-making in most counties), and controlling for the influence of other factors, the findings suggest that tax credits and zoning have had very limited success at mediating spatial patterns of farmland loss. Evidence from case studies of town government decision-making is then used to help explain why traditional land use policies have been unimpressive. Among the findings is the fact that local communities often fail to embrace or rigorously enforce land use plans or zoning districts

Spontaneous renal artery dissection possibly associated with antiphospholipid syndrome

Spontaneous renal artery dissection (SRAD) is a rare clinical event which most commonly presents with nonspecific symptoms such as acute flank pain, hypertension, fever, hematuria. It rarely occurs as an isolated, non-traumatic event and in those cases the underlying causes include atherosclerosis, fibromuscular dysplasia, collagen vascular disease and severe exertion. Only a few case reports suggest a possible connection between SRAD and antiphospholipid syndrome (APS)

Exploring Canadian-American Cross Border Articulation in South Western Ontario

In 2011, the College University Consortium Council (CUCC) provided funding to the University of Windsor to explore the competition between United States (US) and Canadian post-secondary degree-granting institutions located in border cities that wished to attract college transfer students. The cities chosen for the exploration included Sault Ste. Marie, Niagara Falls & St. Catherines, Sarnia, and Windsor. During the 2011/2012 Ontario college to university recruitment travel season, the first author encountered some Ontario colleges that referenced “2+2” agreements with US universities (two years at college plus two years at university for an honours degree) as a more favourable route to articulation into a degree program than transfer pathways currently available at Ontario universities. There were also a considerable number of US universities at both the St. Clair College and Niagara College fairs, suggesting a heightened US institutional interest in Canadian students. The visits to Lambton College and Sault College where the Student Recruitment Officer met with administrative staff also suggested that there is increasing student interest in US transfer opportunities. Ontario post-secondary institutions in border regions must constantly benchmark the goods and services offered in their cities to be competitive with what is offered in the US. The neighbouring US competition mixed with fluctuating currency creates unique and complex economic systems that can create challenges and/or opportunities for border city institutions

Sigurnost informacijskih sustava

U današnje vrijeme privatne i državne organizacije posjeduju velike količine povjerljivih informacija koje je potrebno adekvatno zaštititi kako bi se sačuvala njihova povjerljivost. Informacija se danas smatra resursom te gubitkom povjerljivosti neke informacije to ima štetno djelovanje na samu organizaciju. U ovom radu objasniti ću glavne pojmove koji su sadržani u sigurnosti informacijskih sustava i približiti čitatelja važnosti sigurnosti informacija i informacijskih sustava

Predviđanje parametara rada brodskog dizelskog motora primjenom neuronskih mreža : doktorska disertacija

U usporedbi s drugim strojevima za pogon broda dvotaktni sporohodni dizelski motori s prednabijanjem imaju prednosti zbog svog visokog stupnja djelovanja i pouzdanosti. Suvremeni sporohodni brodski dizelski motori imaju veliku fleksibilnost u radu obzirom na varijabilne strategije ubrizgavanja goriva i upravljanja ispušnih ventila. Kod tih ”inteligentnih” motora moguće je tijekom rada (bez zaustavljanja motora) mijenjati strategiju ubrizgavanja goriva i pogona ispušnog ventila, čime se značajno mogu mijenjati vanjske karakteristike motora. Uvjeti proizvođača motora, nužni za pouzdanost rada i priznavanje garantnih uvjeta, koji definiraju strategiju gradijenta opterećenja i vođenje rada motora, ugrađeni su u sustav regulacije i zaštite rada motora. Modeli za numeričke simulacije rada motora u stanju su vrlo pouzdano prognozirati karakteristike i ponašanje motora u različitim pogonskim uvjetima. Uz to što omogućuju bolji uvid u različite aspekte rada motora, daju i dodatne informacije iz ograničeno dostupnih eksperimentalnih podataka. U ovoj disertaciji provedene su numeričke simulacije za izračunavanje stacionarnih stanja rada motora. U simulaciji se motor se postupno dovodi u stacionarnu radnu točku za što je potrebno određeno vrijeme koje zna biti i višestruko duže nego kod stvarnog rada motora. Rezultati numeričkih simulacija za uvjete rada brodskog dizelskog motora primjenjeni su za odabir vrste i strukture neuronske mreže koja je korištena u ovom radu, njeno učenje i validaciju. Izrada modela s neuronskom mrežom iz simulacijskog modela radi postizanja određenih performansi, a i novih mogućnosti analize podataka koje je bi inače teško postigli, nije jednostavan zadatak. Pri obradi podataka neuronska mreža je pokazala velike dijagnostičke mogućnosti za prepoznavanje problematičnih podataka. Odabrana neuronska mreža zadovoljila je unaprijed zadanu točnost i spremna je za prihvat budućih eksperimentalnih podataka i njihovu obradu. Razvijeni model neuronske mrežu u stanju je dati tražene podatke karakteristika motora više od 3000 puta u kraćem vremenu nego numeričke simulacije za zadanu stacionarnu radnu točku. Brzina rada neuronske mreže čini je pogodnom za brze proračune u iznalaženju optimalnih uvjeta po različitim kriterijima koje možemo proizvoljno nametati. U radu se istražuje efikasno predviđanje radnih parametara u svrhu optimalnog upravljanja. Istražena je i mogućnost da se izlazni rezultati naučenih neuronskih mreža koriste kao ulazni podaci za optimizaciju traženih radnih uvjeta. Isto tako istraživanje pokazuje značajan utjecaj turbopuhala na rad motora. U radu su pokazani primjeri primjene opisane neuronske mreže za optimizaciju mogućih podešenja suvremenih brodskih ”inteligentnih” dizelskih motora, s ciljem dovođenja traženog toplinskog toka ispušnih plinova u radne uvjete za potrebe utilizacije otpadne topline, uz minimalnu specifičnu potrošnju goriva na motoru, te za optimizaciju maksimalne temperature procesa motora u svrhu smanjenja emisija NOx-a. Ovim istraživanjem razvijen je model, baziran na neuronskim mrežama, koji omogućuje predviđanje parametara rada brodskog dizelskog motora. Namjera prikazanih istraživanja bila je u izradi modela neuronskih mreža za implementaciju u suvremenim i inteligentnim sustavima vođenja glavnog brodskog dizelskog motora. Razvijeni model neuronske mreže u potpunosti je pripremljen za prihvat novih podataka izmjerenih tijekom eksploatacije motora. Prvim usporedbama izmjerenih podataka i podataka neuronske mreže moći će se ocijeniti kvaliteta izmjerenih podataka i cijelog mjernog sustava. Ta ocjena je preduvjet za kasnije analize mogućih odstupanja sustava od očekivanih normalnih stanja za potrebe dijagnostike nadolazećih kvarova.Compared to the other machines for ship propulsion, two-stroke low speed diesel engines with supercharging have advantages due to its high efficiency and reliability. Modern low speed marine diesel engines have a lot of flexibility in operation due to the variable fuel injection strategy and management of the exhaust valve. During operation in these ”intelligent” engine it is possible to change the strategy of the fuel injection and exhaust valve operation (without stopping the engine), which can significantly change the external characteristics of the engine. Terms of engine manufacturers, necessary for the reliable operation and recognition of warranty conditions which define the policy gradient of loading and running the engine, were built into the regulation and protection system of the engine. Models for the engine numerical simulations are able to very reliably predict characteristics and behaviour of the engine in a variety of operating conditions. They provide greater insight into the various aspects of engine operation and additional information from limited available experimental data. This dissertation carried out numerical simulations to calculate the stationary operation states. In the simulations, engine was gradually led to steady state operating point This takes some time and can be several times longer than the actual operation. The results of numerical simulations for heavy duty marine diesel engines were applied to select the type and structure of the neural network that is used in this paper, also for its learning and validation. It is not an easy task to develop neural network models with used simulation model in order to achieve certain performance and new opportunities to analyse data that would otherwise be difficult to achieve. Neural network data processing has shown diagnostic capabilities to identify problematic data. Selected neural network satisfy the required accuracy and is ready to accept future experimental data and their analysis. Developed neural network model is able to provide the required engine data characteristics more than 3000 times faster than the numerical simulations for a given stationary operating point. This paper explores efficient prediction of operating parameters for optimal control and the possibility that the outputs of learned neural networks are used as input data required for operating conditions optimization. Also, research shows that turbochargers have a significant effect on the engine performance. The dissertation presents examples of the neural networks application to optimize the potential of modern marine diesel engines, with the aim of achieving the required exhaust gases heat flow for waste heat utilization in the working conditions . As well, minimization of the engine specific fuel consumption, and optimization of the maximum process temperature to reduce emissions of NOx ’s. This research developed a model, based on neural networks, in order to predict the operating parameters of marine diesel engines. The intention was to develop the neural network model for implementation in intelligent systems running modern main ship diesel engines. The developed neural network model is fully prepared to accept new data measured during engine operation. After first comparison between measured data and the neural network results it will be possible to estimate the quality of measured data and the entire measurement system. This estimation is a prerequisite for the subsequent analysis of possible deviations from the expected normal situation for diagnostic upcoming failures