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International Review of Financial Analysis ; 86, 2023.
Article in English | Web of Science | ID: covidwho-2237480

ABSTRACT

This paper examines return and volatility spillover effects among the clean energy (electric vehicles, solar and wind), electricity and 8 energy metals (silver, tin, nickel, cobalt, lead, zinc, aluminum and copper) markets and their drivers under the conditions of the mean and extreme quantiles. The results show moderate spillovers among the clean energy, electricity and energy metals markets, and greater connectivity among the three markets under extreme quantile conditions. Among them, the clean energy markets always play the role of the transmitter, and the electricity market always plays the role of the receiver of spillover effects. In addition, the return and volatility spillovers among the three markets have remarkable time-varying features, and they in-crease dramatically when extreme events occur, especially under extreme quantile conditions. Finally, we reveal the drivers of return and volatility spillovers among these markets by the OLS and quantile regression methods. The COVID-19 and the Arca Tech 100 (PSE) index are found to be important drivers.

2.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi ; 34(1): 36-40, 2022 Feb 23.
Article in Chinese | MEDLINE | ID: covidwho-1893447

ABSTRACT

OBJECTIVE: To evaluate the diagnostic efficiency of four anti-cysticercus IgG, IgG4 or IgM antibody test kits (enzyme-linked immunosorbent assay, ELISA) by different manufacturers, so as to provide insights into the epidemiological investigation and clinical detection of cysticercosis. METHODS: Forty serum samples from cerebral cysticercosis patients, 100 serum samples from healthy volunteers, 30 serum samples from paragonimiasis skrjabini patients, 17 serum samples from cystic echinococcosis and 19 serum samples from subcutaneous or cerebral sparganosis patients were collected and detected using anti-cysticercus IgG, IgG4 or IgM antibody test kits (brand A) and the anti-cysticercus IgG antibody test kit (brand B). The sensitivity, specificity and false negative rate of the four kits for detection of cysticercosis were estimated. RESULTS: The anti-cysticercus IgG, IgG4 or IgM antibody test kits (brand A) showed 95.00% (38/40), 87.50% (35/40), 7.50% (3/40) sensitivities and 98.00% (98/100), 100.00% (100/100) and 100.00% (100/100) for detection of cysticercosis, while the anti-cysticercus IgG antibody test kit (brand B) presented a 75.00% (30/40) sensitivity and 100.00% (100/100) specificity for detection of cysticercosis. The sensitivity for detection of cysticercosis was significantly higher by the anti-cysticercus IgG antibody test kit (brand A) than by the anti-cysticercus IgG antibody test kit (brand B) (χ2 = 6.28, P < 0.05); however, no significant difference was seen in the specificity by two kits (χ2 = 2.01, P > 0.05). The four ELISA kits showed overall false positive rates of 37.88% (25/66), 22.73% (15/66), 62.12% (41/66) and 15.15% (10/66) for detection of paragonimiasis, echinococcosis and sparganosis (χ2 = 37.61, P < 0.05), and the anti-cysticercus IgG antibody test kit (brand A) presented the highest overall false positive rate for detection of paragonimiasis, echinococcosis and sparganosis (χ2 = 7.56, P' < 0.008), while a higher overall false positive rate was seen for detection of paragonimiasis, echinococcosis and sparganosis by the anti-cysticercus IgG antibody test kit (brand A) than by the anti-cysticercus IgG antibody test kit (brand B) (χ2 = 8.75, P' < 0.008). The four ELISA kits showed false positive rates of 40.00% (12/30), 16.67% (5/30), 76.67% (23/30) and 13.33% (4/30) for detection of paragonimiasis (χ2 = 32.88, P < 0.05) and 21.05% (4/19), 26.32% (5/19), 73.68% (14/19) and 15.79% (3/19) for detection of sparganosis (χ2 = 19.97, P < 0.05), and the highest false positive rates were found by the anti-cysticercus IgM antibody test kit (brand A) for detection of paragonimiasis and sparganosis (all P' < 0.008). However, the four ELISA kits showed comparable false positive rates of 52.94% (9/17), 29.41% (5/17), 23.53% (4/17) and 17.65% (3/17) for detection of echinococcosis (χ2 = 8.24, P > 0.05). In addition, the anti-cysticercus IgM anti-body test kit (brand A) showed false positive rates of 76.67% (23/30), 23.53% (4/17) and 73.68% (14/19) for detection of paragonimiasis, echinococcosis and sparganosis (χ2 = 14.537, P < 0.05), with the lowest false positive rate seen for detection of echinococcosis (χ2 = 14.537, P' < 0.014), while no significant differences were seen in the false positive rate for detection of paragonimiasis, echinococcosis and sparganosis by other three ELISA kits (all P > 0.05). CONCLUSIONS: The four anti-cysticercus IgG, IgG4 or IgM antibody test kits exhibit various efficiencies for serodiagnosis of cysticercosis. The anti-cysticercus IgG antibody test kit (brand A) has a high sensitivity for serodiagnosis of cysticercosis; however, it still needs to solve the problems of cross-reaction with other parasitic diseases and stability.


Subject(s)
Cysticercosis , Cysticercus , Animals , Antibodies, Helminth , Cysticercosis/diagnosis , Enzyme-Linked Immunosorbent Assay , Humans , Reagent Kits, Diagnostic , Sensitivity and Specificity , Serologic Tests
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