catastrophic events
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2021 ◽  
Vol 4 (40) ◽  
Laura Cánepa ◽  
Jamer Mello

In this paper, we suggest a speculative comparison between the short story The Color Out of Space (Howard Phillips Lovecraft, 1927) and the documentary film Fireball: Visitors From Darker Worlds (Werner Herzog and Clive Oppenheimer, 2020). We explore the similarities between Herzog’s specific interest in extreme phenomena of Nature and Lovecraftian Cosmicism. We observe that both authors have, to a certain extent, compatible views on the relationship between humans and nature: Herzog and Lovecraft seem to be interested in identifying and investigating humanity’s difficulty in coping with their insignificance when facing catastrophic events caused by indifferent Nature; both chose the same kind of landscape (iced lands, volcanic areas) and extreme natural phenomena (like meteorite falls); and they show a particular interest in characters connected to scientific experiences, and obsessed (even sometimes driven to madness) with the mysteries of nature. Our analysis does not suggest a direct influence of Lovecraft on Herzog, but a productive coincidence that can shed light on the film Fireball and its possible Lovecraftian resonances.

Bansal S. K.

Abstract: Forensic dentistry is the field which is a combination of forensic and dentistry. In this we go for principles used in dentistry or dentistry forthe use in judiciary. It is one field inwhich we collectthe evidence related to dentistry and analyze them for the purpose of investigation. In a crime scene or a disaster situation a lot of destruction occurs. It becomes important to determine the identity of an individual and we can say it is the identity of the deceased. This study is being conducted based on previous research and literature presented by various research scholars. When it comes to a crime scene where we do not get the victim or culprit but we find the dentalevidence and also in cases of mass disasters, catastrophic events, industrial disasters where identification is necessary if we found the dental evidence, they can help a lot in determining age, gender partial identity can be known through this evidence. Many methods are there to determine identity through dental evidence and also apart from dental evidence we have orthometric methods but dental evidence is found to be more cheap, easy, fast methods. In this we have discussed how DNA is extracted from the teeth and it's further processing so that it will help in establishing someone's identity. Keywords: Dentistry, Forensic Dentistry, Dental Evidence, Extraction, DNA Profiling etc

2021 ◽  
Vol 8 ◽  
Robert C. Lacy ◽  
Randall S. Wells ◽  
Michael D. Scott ◽  
Jason B. Allen ◽  
Aaron A. Barleycorn ◽  

Population models, such as those used for Population Viability Analysis (PVA), are valuable for projecting trends, assessing threats, guiding environmental resource management, and planning species conservation measures. However, rarely are the needed data on all aspects of the life history available for cetacean species, because they are long-lived and difficult to study in their aquatic habitats. We present a detailed assessment of population dynamics for the long-term resident Sarasota Bay common bottlenose dolphin (Tursiops truncatus) community. Model parameters were estimated from 27 years of nearly complete monitoring, allowing calculation of age-specific and sex-specific mortality and reproductive rates, uncertainty in parameter values, fluctuation in demographic rates over time, and intrinsic uncertainty in the population trajectory resulting from stochastic processes. Using the Vortex PVA model, we projected mean population growth and quantified causes of variation and uncertainty in growth. The ability of the model to simulate the dynamics of the population was confirmed by comparing model projections to observed census trends from 1993 to 2020. When the simulation treated all losses as deaths and included observed immigration, the model projects a long-term mean annual population growth of 2.1%. Variance in annual growth across years of the simulation (SD = 3.1%) was due more to environmental variation and intrinsic demographic stochasticity than to uncertainty in estimates of mean demographic rates. Population growth was most sensitive to uncertainty and annual variation in reproduction of peak breeding age females and in calf and juvenile mortality, while adult survival varied little over time. We examined potential threats to the population, including increased anthropogenic mortality and impacts of red tides, and tested resilience to catastrophic events. Due to its life history characteristics, the population was projected to be demographically stable at smaller sizes than commonly assumed for Minimum Viable Population of mammals, but it is expected to recover only slowly from any catastrophic events, such as disease outbreaks and spills of oil or other toxins. The analyses indicate that well-studied populations of small cetaceans might typically experience slower growth rates (about 2%) than has been assumed in calculations of Potential Biological Removal used by management agencies to determine limits to incidental take of marine mammals. The loss of an additional one dolphin per year was found to cause significant harm to this population of about 150 to 175 animals. Beyond the significance for the specific population, demographic analyses of the Sarasota Bay dolphins provide a template for examining viability of other populations of small cetaceans.

Mohammad Khani ◽  
Morteza Abdar Esfahani ◽  
Fariba Bayat ◽  
Alireza Khalaj ◽  
Abdolhamid Bagheri

  Tricuspid valve myxomas are very uncommon tumors that could be found after the occurrence of pulmonary thromboembolism, symptomatic tricuspid obstruction, and right-sided heart failure.  Herein, we describe a 42-year-old woman evaluated for an abdominal mass. In preoperative consultation, a tricuspid valve mass was detected in echocardiography. She underwent the removal of a benign uterine myoma and a myxoma of the tricuspid valve. Tricuspid valve myxomas constitute a scarce diagnosis. They could be asymptomatic, occurring in unusual locations and in association with benign tumors in other organs. Our patient was asymptomatic, underscoring the significance of the early diagnosis of this type of tumor to prevent further catastrophic events.

2021 ◽  
Vol 21 ◽  
pp. S4-S5
Vincenza Solli ◽  
Andrea Poletti ◽  
Enrica Borsi ◽  
Marina Martello ◽  
Lucia Pantani ◽  

2021 ◽  
Christy John ◽  
Rajesh Kumar ◽  
Anil Kumar Sivan ◽  
Sangeetha Jithin ◽  
Rojin Abraham ◽  

Abstract Vaccine induced thrombotic thrombocytopenia (VITT) is a rare but devastating adverse event following adenoviral vector based vaccinations for COVID-19. Guidance statements and available reports lack clarity on the choice of imaging modalities and emphasize on the need for specialized tests as a requisite criterion. Such tests have practical limitations of availability likely to restrict the treatment and reporting of such catastrophic events and need reconsideration. We describe two young men with VITT who had no other contributory cause besides a recent ChAdOx1 nCoV-19 vaccination. They were treated with IVIG and full dose anticoagulation. In both our cases the primary neuroimaging was normal and the recommended PF-4 testing was not reported due to technical limitations. Diagnosis was based on a 4T inspired score. Clinicians should report and though counter intuitive; not delay the institution of full dose anticoagulation, IVIG and limit platelet transfusion in the appropriate setting.

Marcus De Almeida ◽  
Ângelo Pinto ◽  
Alcimar Carvalho

Natural history collections (NHC) are guardians of biodiversity (Lane 1996) and essential to understand the natural world and its evolutionary processes. They hold samples of morphological and genetic heritages of living and extinct biotas, helping to reconstruct the timeline of life over the centuries (Gardner 2014). Primary data from specimens in NHC are crucial elements for research in many areas of biological sciences, considered the “bricks” of systematics and therefore one of the pillars for evolutionary studies (Troudet 2018). For this reason, studies carried out in NHC are essential for the development of the scientific knowledge and are pivotal for the scientific-technological progress of a nation (Camargo 2015). The digitization and availability of primary data on biodiversity from NHC represents a inexpensive, practical and secure means of exchanging information, allowing collaboration between institutions and researchers. In this sense, initiatives such as the Sistema de Informação sobre a Biodiversidade Brasileira (SiBBr), a country-level branch of the Global Biodiversity Information Facility (GBIF) platform, aim to encourage and establish ways for the informatization of biological collections and their type specimens. Known for housing one of the largest and oldest collections of insects in the world focused on Neotropical fauna, the Entomological Collection of the Museu Nacional of Federal University of Rio de Janeiro (MNRJ) had more than 3,000 primary types and approximately 12,005,000 specimens, of which about 96% were lost in the tragic fire occurred at the institution on September 2, 2018. The SiBBr project was active in that collection from 2016 to 2019 and enabled the digitization and preservation of data from the type material of many insect orders, including the charismatic dragonflies (order Odonata). Due to the end of the agreement between SiBBr and the Museu Nacional, most of the obtained primary data are pending full curation and, therefore, are not yet available to the public and researchers. The MNRJ housed the biggest and most important collection of dragonflies among all Central and South American institutions. It assembled most of the physical records of neotropical dragonfly fauna gathered over the last 80 years, many of which are of undescribed taxa. Unfortunately, almost all material was permanently lost. This study aims to gather, analyze and publicize primary data of the type material of dragonflies housed in the MNRJ, ensuring the preservation of its history, as well as providing data on the taxonomy and diversity of this marvelous group of insects. A total of 11 families, 50 genera and 131 species were recorded, belonging to the suborders Anisoptera and Zygoptera with distributional records widespread in South America. The MNRJ housed 105 holotypes of dragonflies' nomina representing 11.7% of the richness of the Brazilian Odonata fauna (901 spp.), a country with the highest number of species of the biosphere. The impact of the loss of this collection to studies of these insects is unprecedented, since some enigmatic and monotypic genera such as Brasiliogomphus, Fluminagrion and Roppaneura lost 100% of their type series, while others most diverse such as Lauromacromia, Oxyagrion and Neocordulia lost 50%, 35% and 31% of their holotypes. Therefore, due to the registration and preservation of primary biodiversity data, this work reiterates the importance of curating and digitizing biological scientific collections. Furthermore, it shows extreme relevance for preserving information on existing biodiversity permanently and providing support for future research. Digitization and interconnecting digital extended specimen data proves to be one of the main and most effective ways to protect NHC heritage and their primary data against catastrophic events.

2021 ◽  
Vol 206 (Supplement 3) ◽  
Vanessa Lukas ◽  
Lauren Neal ◽  
Sarah Mccain ◽  
Mary Silvia ◽  
Jane Boggs ◽  

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255615 ◽  
Rohitash Chandra ◽  
Aswin Krishna

Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic event that has raised a number of psychological issues such as depression given abrupt social changes and lack of employment. Advancements of deep learning-based language models have been promising for sentiment analysis with data from social networks such as Twitter. Given the situation with COVID-19 pandemic, different countries had different peaks where rise and fall of new cases affected lock-downs which directly affected the economy and employment. During the rise of COVID-19 cases with stricter lock-downs, people have been expressing their sentiments in social media. This can provide a deep understanding of human psychology during catastrophic events. In this paper, we present a framework that employs deep learning-based language models via long short-term memory (LSTM) recurrent neural networks for sentiment analysis during the rise of novel COVID-19 cases in India. The framework features LSTM language model with a global vector embedding and state-of-art BERT language model. We review the sentiments expressed for selective months in 2020 which covers the major peak of novel cases in India. Our framework utilises multi-label sentiment classification where more than one sentiment can be expressed at once. Our results indicate that the majority of the tweets have been positive with high levels of optimism during the rise of the novel COVID-19 cases and the number of tweets significantly lowered towards the peak. We find that the optimistic, annoyed and joking tweets mostly dominate the monthly tweets with much lower portion of negative sentiments. The predictions generally indicate that although the majority have been optimistic, a significant group of population has been annoyed towards the way the pandemic was handled by the authorities.

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