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Phoebe Apperson Hearst měla velmi úspěšného vlastního syna Williama, který byl ale více jako jeho otec: tvrdý obchodník. Našla však jemnou, uměleckou duši v malíři Orrinu Peckovi (1860–1921), který byl údajně gay a který ji, ještě za života své vlastní matky, začal oslovovat „má druhá mámo.“ Na základě podrobného výzkumu jejich vzájemné korespondence v Peckově pozůstalosti se můžeme ptát, jak moc si byla progresivní, bohatá žena 19. století, jakou byla Phoebe Hearst, vědoma Peckovy sexuality a pokud ano, jestli s tím neměla problém, nebo šlo o nevyřčené tajemství mezi nimi? Jejich příběh představí historik umění Ladislav Zikmund-Lender. Phoebe Apperson Hearst had a very successful son of William, but he was more like his father: a tough businessman. However, she found a delicate, artistic soul in the painter Orrin Peck (1860–1921), who was allegedly gay and who, while still his own mother's life, began to address her as “my second mother.” Based on a detailed study of their correspondence in Peck's estate, we may ask how much a progressive, rich 19th-century woman like Phoebe Hearst was aware of Peck's sexuality, and if so, if she had no problem with it, or was it an unspoken secret between them? Their story will be presented by art historian Ladislav Zikmund-Lender.

Heritage preservation is a broad topic that affects virtually all fields of human activity. One of them is industrial heritage which is, among others, represented by the construction of dams. The a...

The Late Neolithic palafitte site, Ustie na Drim, in the northern part of Lake Ohrid (North Macedonia), excavated in 1962, offered ceramic fragments of large, flat, elongated pans. These artifacts could be dated by relative chronology to roughly around 5200–5000 BC. According to their shape and technological traits, the ceramic pans were probably used for baking. The attached materials on the surface of studied pan fragments were sampled for consequent chemical and microscopical analyses (i.e., analyses of starch, phytoliths, and microscopic animal remains). An immunological method revealed the presence of pork proteins in samples. The presence of organic residues of animal origin was, moreover, confirmed by the detection of cholesterol using gas chromatography coupled to mass spectrometry. Analysis of detected microscopic botanical objects revealed starch grains of several plants (i.e., oak, cattail, and grasses). An interesting find was the hair of a beetle larva, which could be interpreted contextually as the khapra beetle, a pest of grain and flour. Based on our data, we suppose that the ceramic pans from Ustie na Drim were used for the preparation of meals containing meat from common livestock in combination with cereals and wild plants.

Abstract Chalk has been used since Antiquity for various purposes, and since Gothic for preparatory layers of painted cultural heritage objects. Several materials are called chalk in Cultural Heritage, but this work especially focuses on chalk composed of calcareous nannofossils (up to 98%). These are fossil remains of photoautotrophic algae generally smaller than 30 μm. They are mainly visible as platelets of various shapes under a cross-polarised or scanning electron microscope. The provenance of chalk can be determined using calcareous nannofossils due to their well-known paleobiogeographic localities. They are already used as proxies since the 90s in Cultural Heritage, but rarely for paintings. In this work, 6 chalk historical mining areas were chosen: Germany (Ruegen), France (Champagne, Meudon), Belgium (Mons), England (Norfolk) and Italy (Bologna). Natural and processed chalk were used as reference materials and compared to 3 original paintings. The difference between the chalks calcareous nannofossil assemblages was shown using multivariate statistical analysis based on species relative abundance. Marker nannofossil species were defined for each chalk locality. One painting material could not be originated due to the preservation of its nannofossils assemblage, but the origins of the rock chalk material from the two other paintings could be geographically located in France.

An innovative approach to a non-destructive lock mechanism examination by means of X-ray computed tomography (CT) was involved in a careful opening of a locked 19th century chest missing the key, as an interdisciplinary cooperation with the restorers. In regard of the exploration and conservation of such locked objects, their opening is important to the restorers. However, the opening may be complicated, if not impossible, without damaging the object when the key is missing. Moreover, the historical locks might be equipped with protective mechanisms. Despite the exceeding dimensions and the weight of the steel chest, a CT analysis was performed, which enabled a detailed exploration of the lock based on a system of levers and bolts handled by a single key, located in a case on the inside of the chest lid, including the dimensions essential for manufacturing of a new key copy. Moreover, two secret protective mechanisms were revealed, as well as all the damages of the object.

The effort to achieve a balance between industrial development, environment, human health and economic growth in the world represents a driving engine of the latest strategies for resource usage and carbon footprint reduction, which include the application of the Circular Economy (CE) concept. The central idea of the CE concept is to increase the value of resources within a closed system to enable the use of a minimum number of natural resources while providing sustainable economic growth. The aim of this paper is to map the history and evolution of the CE concept to highlight its current application. Historical literary sources and scientific studies were used to map the CE concept evolution while policy instruments provided information mainly on current development. The overview indicates both success and failure of the CE projects over time listed by regions. Successful applications of the CE in the Czech Republic have been identified. The results provide useful information for further research seeking to define the CE concept in practical terms and consider potential opportunities that arise during its implementation.

Parkinson's disease dysgraphia (PDYS), one of the earliest signs of Parkinson's disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive approach to monitoring the progress of the disease. However, although several approaches to supportive PDYS diagnosis have been proposed (mainly based on handcrafted features (HF) extracted from online handwriting or the utilization of deep neural networks), it remains unclear which approach provides the highest discrimination power and how these approaches can be transferred between different datasets and languages. This study aims to compare classification performance based on two types of features: features automatically extracted by a pretrained convolutional neural network (CNN) and HF designed by human experts. Both approaches are evaluated on a multilingual dataset collected from 143 PD patients and 151 healthy controls in the Czech Republic, United States, Colombia, and Hungary. The subjects performed the spiral drawing task (SDT; a language-independent task) and the sentence writing task (SWT; a language-dependent task). Models based on logistic regression and gradient boosting were trained in several scenarios, specifically single language (SL), leave one language out (LOLO), and all languages combined (ALC). We found that the HF slightly outperformed the CNN-extracted features in all considered evaluation scenarios for the SWT. In detail, the following balanced accuracy (BACC) scores were achieved: SL—0.65 (HF), 0.58 (CNN); LOLO—0.65 (HF), 0.57 (CNN); and ALC—0.69 (HF), 0.66 (CNN). However, in the case of the SDT, features extracted by a CNN provided competitive results: SL—0.66 (HF), 0.62 (CNN); LOLO—0.56 (HF), 0.54 (CNN); and ALC—0.60 (HF), 0.60 (CNN). In summary, regarding the SWT, the HF outperformed the CNN-extracted features over 6% (mean BACC of 0.66 for HF, and 0.60 for CNN). In the case of the SDT, both feature sets provided almost identical classification performance (mean BACC of 0.60 for HF, and 0.58 for CNN).