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(searched for: 10.29328/journal.ijcv.1001030)
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International Journal of Clinical Virology, Volume 5, pp 011-021; https://doi.org/10.29328/journal.ijcv.1001030

Abstract:
Introduction - the perennial pandemic: It is being increasingly realised that the COVID-19 may have become the new reality associated with human existence world over and the mankind may have to live with it for years or even decades. Further, the grievous nature of the disease is evolving further with the genomic changes in the virus in form of mutations and evolution of variants, with enhanced infectivity and probably virulence. There are serious challenges posed by the SARS-CoV-2 virus and COVID-19 as the disease. COVID-19 as acute and chronic disease: On exposure to the SARS-CoV-2 virus, not all patients develop a disease. Further, for those who develop the disease, there is a large variation in disease severity. The known factors including the constituent factors and several still unknown factors influence the disease manifestations, its course, and later the convalescent phase as well. In fact, substantial continuing morbidity after resolution of the infection indicates persisting multisystem effects of COVID-19. The ‘long COVID-19’ or ‘long haulers’: The patients who continue to suffer with persisting symptoms have been described as long haulers and the clinical condition has been called post-COVID-19 or ‘long COVID-19’. The diagnosis should be entertained if various symptoms and signs linger well beyond the period of convalescence in COVID-19. With the chronicity, there occur inflammatory changes and damage in various organs, and the extent of organ damage determines the long-term effects. Management of ‘long COVID’ syndrome: The ‘long COVID’ syndrome has multi-system involvement, variable presentation, and unpredictable course. Following clinical and investigational assessment, the patients should be managed as per clinical manifestations, extent of organ damage and associated complications. The findings from various studies indicate that preventing further organ damage in ‘long COVID’ is crucial. The long COVID’s prognostic challenges: As apparent, the ‘long COVID’ afflictions are more common than realized earlier. The symptoms can escalate in patients with co-morbid conditions. The persistent symptoms among COVID-19 survivors pose new challenges to the healthcare providers and may be suitably managed with a combination of pharmacological and non-pharmacological treatments, and holistic healthcare.
, Soma Shirakabe, Yun He, Shunya Ueta, Teppei Suzuki, Kaori Abe, Asako Kanezaki, Shin'ichiro Morita, Toshiyuki Yabe, Yoshihiro Kanehara, et al.
Published: 20 July 2017
Abstract:
The paper gives futuristic challenges disscussed in the cvpaper.challenge. In 2015 and 2016, we thoroughly study 1,600+ papers in several conferences/journals such as CVPR/ICCV/ECCV/NIPS/PAMI/IJCV.
Yun R. Fu
Manifold Learning for 3D Shape Description and Classification; https://doi.org/10.21236/ada606874

Abstract:
Periodically, the US Army conducts detailed measurement surveys of its soldiers as a way to understand the impact that changes in soldier body size have for the design, fit and sizing of virtually every piece of clothing and equipment that Soldiers wear and use in combat. Recently finished US Army Anthropometric Survey (ANSUR II) has collected 3D body scan data of soldiers at the Natick Solider Center (NSC), as shown in Figure 1. By applying new techniques for shape analysis and classification to these 3D body scan data will help designers of clothing and personal protection equipment to understand and fit Army population. The overall research goal of this proposal is to create a new manifold learning framework for large-scale graph decomposition and approximation problems by low-rank approximation and guarantee computable, stable and fast optimizations for 3D shape description and classification. The PI's group has published (or accepted for publication) 1 book through Springer and 13 scientific papers partially supported by this grant. In particular, these papers are in top journals and conference proceedings such as TPAMI, IJCV, TCSVT, ICCV, AAAI, SDM, ACM MM, etc. One paper, 1 out of 384, receives the Best Paper Award in SDM 2014. The PI, Dr. Y. Raymond Fu has received the 2014 INNS Young Investigator Award, from International Neural Networks Society (INNS), 2014. Leveraged by this grant, the PI has been granted an ARO Young Investigator Program (YIP) Award and a Defense University Research Instrumentation Program (DURIP) award.
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