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2022 ◽  
Author(s):  
Julie De Groot

How did citizens in Bruges create a home? What did an ordinary domestic interior look like in the sixteenth century? And more importantly: how does one study the domestic culture of bygone times by analysing documents such as probate inventories? These questions seem straightforward, yet few endeavours are more challenging than reconstructing a sixteenth-century domestic reality from written sources. This book takes full advantage of the inventory and convincingly frames household objects in their original context of use. Meticulously connecting objects, people and domestic spaces, the book introduces the reader to the rich material world of Bruges citizens in the Renaissance, their sensory engagement, their religious practice, the role of women, and other social factors. By weaving insights from material culture studies with urban history, At Home in Renaissance Bruges offers an appealing and holistic mixture of in-depth socio-economic, cultural and material analysis. In its approach the book goes beyond heavy-handed theories and stereotypes about the exquisite taste of aristocratic elites, focusing instead on the domestic materiality of Bruges’ middling groups. Evocatively illustrated with contemporary paintings from Bruges and beyond, this monograph shows a nuanced picture of domestic materiality in a remarkable European city.


Author(s):  
Zoleikha Jahanbakhsh-Nagadeh ◽  
Mohammad-Reza Feizi-Derakhshi ◽  
Arash Sharifi

During the development of social media, there has been a transformation in social communication. Despite their positive applications in social interactions and news spread, it also provides an ideal platform for spreading rumors. Rumors can endanger the security of society in normal or critical situations. Therefore, it is important to detect and verify the rumors in the early stage of their spreading. Many research works have focused on social attributes in the social network to solve the problem of rumor detection and verification, while less attention has been paid to content features. The social and structural features of rumors develop over time and are not available in the early stage of rumor. Therefore, this study presented a content-based model to verify the Persian rumors on Twitter and Telegram early. The proposed model demonstrates the important role of content in spreading rumors and generates a better-integrated representation for each source rumor document by fusing its semantic, pragmatic, and syntactic information. First, contextual word embeddings of the source rumor are generated by a hybrid model based on ParsBERT and parallel CapsNets. Then, pragmatic and syntactic features of the rumor are extracted and concatenated with embeddings to capture the rich information for rumor verification. Experimental results on real-world datasets demonstrated that the proposed model significantly outperforms the state-of-the-art models in the early rumor verification task. Also, it can enhance the performance of the classifier from 2% to 11% on Twitter and from 5% to 23% on Telegram. These results validate the model's effectiveness when limited content information is available.


2022 ◽  
pp. e90202134
Author(s):  
Heitor Bissoli-Silva ◽  
Edú Baptista Guerra ◽  
Thamila Barcellos Lemes ◽  
Mattheus Torrezani Silveira ◽  
Monique Pereira Nascimento ◽  
...  

Biological collections are the basis of the Earth’s biodiversity knowledge and most of them are regional collections. Here we present two collections from the Federal University of Espírito Santo—Mammal Collection (UFES-MAM) and the associated Animal Tissue Collection (UFES-CTA)—which have been the main repository for mammal specimens collected in Espírito Santo, mostly georeferenced (~ 90%), and available in public databases. Thus, our objective with this essay was to point out the contributions of these collections to the knowledge of the diversity of mammals in the Atlantic Forest. At the same time, we present the contributions they return to society and the scientific community, highlighting the main obstacles and challenges those regional collections face. Despite being regional, UFES-MAM and UFES-CTA stand out nationally for having biological material from a wide variety of species—mainly rodents, marsupials, and bats—also counting on a series of primate tissues collected during the outbreak of wild yellow fever in Southeastern Brazil from 2017 to 2018. These collecting efforts contributed to 42 new mammal species records for Espírito Santo, and 25 species that had already been registered in the state but were listed only in out-of-state collections or reported in literature without voucher specimens. We hope that the information reported here are examples of good practices and increase knowledge and visibility of the rich collection that these regional collections house.


Author(s):  
Bob Goldstein

Experimentally tractable organisms like C. elegans, Drosophila, zebrafish, and mouse are popular models for addressing diverse questions in biology. In 1997, two of the most valuable invertebrate model organisms to date – C. elegans and Drosophila – were found to be much more closely related to each other than expected. C. elegans and Drosophila belong to the nematodes and arthropods respectively, and these two phyla and six other phyla make up a clade of molting animals referred to as the Ecdysozoa. The other ecdysozoan phyla could be valuable models for comparative biology, taking advantage of the rich and continual sources of research findings as well as tools from both C. elegans and Drosophila. But when the Ecdysozoa was first recognized, few tools were available for laboratory studies in any of these six other ecdysozoan phyla. In 1999 I began an effort to develop tools for studying one such phylum, the tardigrades. Here, I describe how the tardigrade species Hypsibius exemplaris and tardigrades more generally have emerged over the past two decades as valuable new models for answering diverse questions. To date, these questions have included how animal body plans evolve and how biological materials can survive some remarkably extreme conditions.


Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 599
Author(s):  
Yongsheng Li ◽  
Tengfei Tu ◽  
Hua Zhang ◽  
Jishuai Li ◽  
Zhengping Jin ◽  
...  

In the field of video action classification, existing network frameworks often only use video frames as input. When the object involved in the action does not appear in a prominent position in the video frame, the network cannot accurately classify it. We introduce a new neural network structure that uses sound to assist in processing such tasks. The original sound wave is converted into sound texture as the input of the network. Furthermore, in order to use the rich modal information (images and sound) in the video, we designed and used a two-stream frame. In this work, we assume that sound data can be used to solve motion recognition tasks. To demonstrate this, we designed a neural network based on sound texture to perform video action classification tasks. Then, we fuse this network with a deep neural network that uses continuous video frames to construct a two-stream network, which is called A-IN. Finally, in the kinetics dataset, we use our proposed A-IN to compare with the image-only network. The experimental results show that the recognition accuracy of the two-stream neural network model with uesed sound data features is increased by 7.6% compared with the network using video frames. This proves that the rational use of the rich information in the video can improve the classification effect.


Author(s):  
Maria V. Wilde ◽  
Mikhail V. Golub ◽  
Artem A. Eremin

Laminate structures composed of stiff plates and thin soft interlayers are widely used in aerospace, automotive and civil engineering encouraging the development of reliable non-destructive strategies for their condition assessment. In the paper, elastodynamic behaviour of such laminate structures is investigated with emphasis on its application in ultrasonic based NDT and SHM for the identification of interlayer mechanical and interfacial contact properties. A particular attention is given to the practically important frequency range, in which the wavelength considerably exceeds the thickness of the film. Three layer model with spring-type boundary conditions employed for imperfect contact simulation is used for numerical investigation. Novel effective boundary conditions are derived via asymptotic expansion technique and used for analysis of the peculiar properties of elastic guided waves in considered laminates. It is revealed that the thin and soft film influences the behaviour of the laminate mainly via the effective stiffnesses being a combination of the elastic moduli of the film, its thickness and interface stiffnesses. To evaluate each of these parameters separately (or to figure out that the available experimental data are insufficient), a step-wise procedure employing the effective boundary conditions is proposed and tested versus the laser Doppler vibrometry data for Lamb waves in Aluminium/Polymer film/Alumunium structure. The possibility of using film-related thickness resonance frequencies to estimate the film properties and contact quality is also demonstrated. Additionally, the rich family of edge waves is also investigated, and the splitting of fundamental edge waves into pairs is revealed.


2022 ◽  
Author(s):  
◽  
Maharani Allan

<p>This study focused on reviewing a student's music therapy practice at an acute assessment unit for people living with dementia and mental health issues, finding links between the placement philosophy, and new ideas about practice. Kitwood's (1997) book on personhood and the needs of people who are living with dementia and other mental health issues appeared to resonate with the student music therapists' practice. This was supported by the active use of his model of needs by nursing staff at the placement. Investigations looked specifically at Kitwood's model of needs; how music therapy links with his philosophy and how interventions during practice connected to those needs. The data was draw from descriptive clinical notes using secondary analysis. The rich qualitative data was analysed using deductive and inductive methods. Findings are presented under Kitwood's model of needs, forming the five categories for the study. The main themes within these categories were then summarised and explanations given under both Kitwood's model of needs and music therapy interventions used to meet them. Though the findings are qualitative, specific to this study and not necessarily generalisable, several links within music therapy practice, and nursing practice revealed the importance and need for more person-centred individualised care programmes for patients in mental health settings.</p>


2022 ◽  
Vol 12 ◽  
Author(s):  
Barnaby E. Walker ◽  
Allan Tucker ◽  
Nicky Nicolson

The mobilization of large-scale datasets of specimen images and metadata through herbarium digitization provide a rich environment for the application and development of machine learning techniques. However, limited access to computational resources and uneven progress in digitization, especially for small herbaria, still present barriers to the wide adoption of these new technologies. Using deep learning to extract representations of herbarium specimens useful for a wide variety of applications, so-called “representation learning,” could help remove these barriers. Despite its recent popularity for camera trap and natural world images, representation learning is not yet as popular for herbarium specimen images. We investigated the potential of representation learning with specimen images by building three neural networks using a publicly available dataset of over 2 million specimen images spanning multiple continents and institutions. We compared the extracted representations and tested their performance in application tasks relevant to research carried out with herbarium specimens. We found a triplet network, a type of neural network that learns distances between images, produced representations that transferred the best across all applications investigated. Our results demonstrate that it is possible to learn representations of specimen images useful in different applications, and we identify some further steps that we believe are necessary for representation learning to harness the rich information held in the worlds’ herbaria.


Author(s):  
Ka Hong ◽  
Elena Solana ◽  
Mauro Coduri ◽  
Clemens Ritter ◽  
Paul Attfield

Abstract A new CaFe3O5-type phase NiFe3O5 (orthorhombic Cmcm symmetry, cell parameters a = 2.89126(7), b = 9.71988(21) and c = 12.52694(27) Å) has been synthesised under pressures of 12-13 GPa at 1200 °C. NiFe3O5 has an inverse cation site distribution and reveals an interesting evolution from M2+(Fe3+ )2Fe2+O5 to Fe2+(M2+ 0.5Fe3+ 0.5)2Fe3+O5 distributions over three distinct cation sites as M2+ cation size decreases from Ca to Ni. Magnetic susceptibility measurements show successive transitions at 275, ~150, and ~20 K and neutron diffraction data reveal a series of at least three spin-ordered phases with evolving propagation vectors k = [0 0 0] [0 ky 0]  [½ ½ 0] on cooling. The rich variety of magnetically ordered phases in NiFe3O5 likely results from frustration of Goodenough-Kanamori exchange interactions between the three spin sublattices, and further interesting magnetic materials are expected to be accessible within the CaFe3O5-type family.


2022 ◽  
Vol 14 (1) ◽  
pp. 29-44
Author(s):  
Setiadi Alim Lim

In response to the decline in tax revenue due to the Covid-19 pandemic, the government has issued a regulation to collect a new tax, namely the Carbon Tax through Law Number 7 of 2021 concerning Harmonization of Tax Regulations. Because this Carbon Tax is being implemented for the first time in Indonesia and its calculation is also not simple, it is estimated that the successful collection of it will take a long time. Whereas the need to explore new sources of tax revenue is needed at this time in the short term to cope with sharply increasing expenditures in order to overcome the medical and social impacts of the Covid-19 pandemic. The government could consider implementing a Wealth Tax in addition to existing taxes including the Carbon Tax. Wealth Tax in addition to increasing tax revenues can also be used as a means of redistribution of wealth in order to reduce the wide gap between the rich and the poor. The proposed Wealth Tax is a Wealth Tax that is levied only once, intended for individuals, with a threshold as well as Non-Taxable Wealth (NTW) of Rp21,000,000,000.00 for unmarried taxpayers and Rp22,500,000,000.00 for marriage taxpayers, using progressive rates of 0.2%, 0.4%, 0.6%, and 0.75%, and can be repaid in installments for 5 years. The basis for imposition of Wealth Tax is net assets, namely the total assets minus the total liabilities reported in the Annual Income Tax Return (SPT) of the previous year's individual taxpayers minus the Non-Taxable Wealth (NTW). Using data on the wealth of the Indonesian population in 2018, it is estimated that thecollection of this Wealth Tax can generate additional tax revenues of around 0.83% of the Gross Domestic Product in 2020.


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