Utemeljenje austrijske Vojne krajine u Transilvaniji i njeni kratkoročni te srednjoročni utjecaji

Establishing the Austrian military border in Transylvania was not only a military, but also a political, economic and, up to a point, religious decision, taken by the Crown near the end of a long and costly war, under specific circumstances and events taking place in the province. It was also probably the main reason why Empress Maria Theresa was remembered by several generations of Transylvanians, and remains one of the most celebrated acts of her reign according to Romanian historical writing. This paper seeks to provide a synthetic overview of the topic, based on both the international (mainly German and Austrian) and the Romanian historical literature, given the highly limited accessibility of the latter in terms of language and range of dissemination. It opens with short introductory historiographical considerations, followed by a presentation of the prerequisites and reasons for the border regiments’ creation, alongside the main steps in the establishment process. The second part provides a short analysis of the mutual benefits brought about by the military border for both the empire and the locals, as well as the difficulties and resistance encountered during the establishment, along with the short- and medium-term social implications.Utemeljenje transilvanijskih vojnokrajiških pukovnija nije bila samo vojna već i politička, ekonomska te do određene mjere i vjerska odluka koju je Bečki dvor donio potkraj dugog i skupog Sedmogodišnjeg rata (1756. – 1763.) i to pod specifičnim uvjetima i događajima koji su se događali u Transilvaniji. Ovo utemljenje vojnog sustava i pukovnija je vrlo vjerojatno glavni razlog zašto je carica Marija Terezija upamćena od strane nekoliko generacija stanovnika Transilvanije, a također ova caričina odluka pripada prema rumunjskoj historiografiji među najpoznatije i najhvaljenije poteze njezine vladavine. Sintetski pregled navedene teme u radu se temelji na relevantnim radovima rumunjske historiografije koju autor obilato upotpunjuje, obzirom na ograničenost šireg korištenja iste od strane povjesničara poradi jezika i slabe diseminacije, najrelevantnijim radovima međunarodne (uglavnom njemačke i austrijske) historiografije. U radu se nakon kratkog uvoda i osvrta na spomenute relevantne historiografske radove, prikazuje kronološkim slijedom razvoj preduvjeta i razloga za stvaranje transilvanijskih krajiških pukovnija s osvrtom na glavne korake tog procesa. Drugi dio rada donosi kratku analizu obostranih koristi i beneficija koje su, kako za Habsburšku Monarhiju i Bečki dvor tako i za lokalno stanovništvo Transilvanije, proizašle iz uspostave vojnokrajiških pukovnija. Dodatno, donosi se i prikaz poteškoća te otpora s kojima su se vlasti susretale prilikom utemeljenja navedenih pukovnija zajedno s osvrtom na kratkoročne i srednjoročne implikacije uspostave ove vojne organizacije na društvo

ŽUPNE MATIČNE KNJIGE IZ TRANSILVANIJE – IZVORI ZA POVIJEST MEDICINE (OD KASNOG 18. DO RANOG 20. STOLJEĆA)

This paper aims to analyse the typology of medical-historical information provided by parish registers from Transylvania – a category of primary sources used mainly by historical demographers. The approach is descriptive and prospective in character: it creates a typology of the medical information to be found in the sources, while highlighting possible research directions and approaching a series of methodological and interpretation issues. The parish registers contain references to medical actors (the midwife, the physician, the death inspector), to medical activities (vaccination), and to events regarding the history of medicine (multiple births, infant mortality, death-causing diseases and accidents, epidemics, etc.). Despite the fact that they provide mainly demographic data, some epidemiological and medicine-related information can prove interesting for researchers in the field of the historyof medicine. Such information is suitable for serial analyses and in some cases even for collective biography studies of the medical staff (e.g., the birth assistants and midwives), thus cross-referencing in many respects with cultural and social history. However, probably for reasons related to the sources’ accessibility, medical historians have not seemed very interested in these data, a situation which will hopefully change in the near future due to the newly compiled historical population databases. The conclusions reached in this paper point towards the variety of medical-historical information contained in parish registers, highlighting the need for reconsidering them as sources not only for historical demography, but also for medical history.Ovaj rad ima za cilj analizirati tipologiju medicinsko-povijesnih informacija koje nude župne matice iz Transilvanije – kategoriju primarnih izvora koje koristi uglavnom povijesni demografi. Pristup je po naravi deskriptivan i prospektivan: on stvara tipologiju medicinskih informacija koje se mogu naći u izvorima, pritom naglašavajući moguće istraživačke pravce i pristupajući nizu metodoloških i interpretacijskih problema. Župne matice sadrže reference o medicinskim akterima (primalja, liječnik, inspektor smrti), medicinskim djelatnostima (cijepljenje) te događajima vezanih za povijest medicine (višestruka rođenja, smrtnost dojenčadi, smrtonosne bolesti i nesreće, epidemije, itd.). Unatoč činjenici da one pružaju uglavnom demografske podatke, neke epidemiološke i za medicinu vezane informacije se dokazuju kao zanimljive za znanstvenike iz područja povijesti medicine. Takve informacije pogodne su za serijske analize, a u nekim slučajevima čak i za istraživanja kolektivne biografije medicinskog osoblja (npr. asistenata pri porodu i primalja), presijecajući se tako u mnogočemu s kulturnom i društvenom poviješću. Međutim, a vjerojatno zbog razloga koji se odnose na pristupačnost izvora, čini se da medicinski povjesničari nisu bili jako zainteresirani za ove podatke. Nadamo se da će se takva situacija promijeniti u bliskoj budućnosti zbog svježe prikupljenih povijesnih baza podataka stanovništva. Zaključak do kojega se dolazi u ovom radu upućuje prema različitim medicinskopovijesnim informacijama koje su sadržane u župnim matičnim knjigama, naglašavajući potrebu za njihovo preispitivanje kao izvora ne samo za povijesnu demografiju, već i za medicinsku povijest

Rgtsp: a generalized top scoring pairs package for class prediction

Summary: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. Availability and Implementation: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries. Contact: [email protected]

An Explorative Analysis of ABCG2/TOP-1 mRNA Expression as a Biomarker Test for FOLFIRI Treatment in Stage III Colon Cancer Patients: Results from Retrospective Analyses of the PETACC-3 Trial

Biomarker-guided treatment for patients with colon cancer is needed. We tested ABCG2 and topoisomerase 1 (TOP1) mRNA expression as predictive biomarkers for irinotecan benefit in the PETACC-3 patient cohort. The present study included 580 patients with mRNA expression data from Stage III colon cancer samples from the PETACC-3 study, which randomized the patients to Fluorouracil/leucovorin (5FUL) +/- irinotecan. The primary end-points were recurrence free survival (RFS) and overall survival (OS). Patients were divided into one group with high ABCG2 expression (above median) and low TOP-1 expression (below 75 percentile) ("resistant") (n = 216) and another group including all other combinations of these two genes ("sensitive") (n = 364). The rationale for the cut-offs were based on the distribution of expression levels in the PETACC-3 Stage II set of patients, where ABCG2 was unimodal and TOP1 was bimodal with a high expression level mode in the top quarter of the patients. Cox proportional hazards regression was used to estimate the hazard ratios and the association between variables and end-points and log-rank tests to assess the statistical significance of differences in survival between groups. Kaplan-Meier estimates of the survival functions were used for visualization and estimation of survival rates at specific time points. Significant differences were found for both RFS (Hazard ratio (HR): 0.63 (0.44-0.92); p = 0.016) and OS (HR: 0.60 (0.39-0.93); p = 0.02) between the two biomarker groups when the patients received FOLFIRI (5FUL+irinotecan). Considering only the Microsatellite Stable (MSS) and Microsatellite Instability-Low (MSI-L) patients (n = 470), the differences were even more pronounced. In contrast, no significant differences were observed between the groups when patients received 5FUL alone. This study shows that the combination of ABCG2 and TOP1 gene expression significantly divided the Stage III colon cancer patients into two groups regarding benefit from adjuvant treatment with FOLFIRI but not 5FUL

Joint analysis of histopathology image features and gene expression in breast cancer

BACKGROUND Genomics and proteomics are nowadays the dominant techniques for novel biomarker discovery. However, histopathology images contain a wealth of information related to the tumor histology, morphology and tumor-host interactions that is not accessible through these techniques. Thus, integrating the histopathology images in the biomarker discovery workflow could potentially lead to the identification of new image-based biomarkers and the refinement or even replacement of the existing genomic and proteomic signatures. However, extracting meaningful and robust image features to be mined jointly with genomic (and clinical, etc.) data represents a real challenge due to the complexity of the images. RESULTS We developed a framework for integrating the histopathology images in the biomarker discovery workflow based on the bag-of-features approach - a method that has the advantage of being assumption-free and data-driven. The images were reduced to a set of salient patterns and additional measurements of their spatial distribution, with the resulting features being directly used in a standard biomarker discovery application. We demonstrated this framework in a search for prognostic biomarkers in breast cancer which resulted in the identification of several prognostic image features and a promising multimodal (imaging and genomic) prognostic signature. The source code for the image analysis procedures is freely available. CONCLUSIONS The framework proposed allows for a joint analysis of images and gene expression data. Its application to a set of breast cancer cases resulted in image-based and combined (image and genomic) prognostic scores for relapse-free survival

On Performance Evaluation of Face Detection and Localization Algorithms

When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a correct detection/localization means. This paper addresses exactly this problem, proposing an objective measure for the goodness of a detection/localization for the case of frontal faces. The usage of the proposed technique insures a fair and unbiased way of reporting the results, making the experiment repeatable, measurable, and comparable by anybody else

Extraction of audio features specific to speech production for multimodal speaker detection

A method that exploits an information theoretic framework to extract optimized audio features using video information is presented. A simple measure of mutual information (MI) between the resulting audio and video features allows the detection of the active speaker among different candidates. This method involves the optimization of an MI-based objective function. No approximation is needed to solve this optimization problem, neither for the estimation of the probability density functions (pdf) of the features, nor for the cost function itself. The pdf are estimated from the samples using a non-parametric approach. The challenging optimization problem is solved using a global method: the Differential Evolution algorithm. Two information theoretic optimization criteria are compared and their ability to extract audio features specific to speech is discussed. Using these specific speech audio features, candidates video features are then classified as membership of the "speaker" or "non-speaker" class, resulting in a speaker detection scheme. As a result, our method achieves a speaker detection rate of 100% on home- grown test sequences, and of 85% on most commonly used sequences