A Data Analysis of the Irradiation Parameter D10 for Bacteria and Spores under Various Conditions

1999 ◽  
Vol 62 (9) ◽  
pp. 1024-1032 ◽  
Author(s):  
SUZANNE J. C. van GERWEN ◽  
FRANK M. ROMBOUTS ◽  
KLAAS van't RIET ◽  
MARCEL H. ZWIETERING
Keyword(s):  
Low Temperatures ◽  
Deinococcus Radiodurans ◽  
Specific Question ◽  
Factors Influencing ◽  
Specific Factors ◽  
Irradiation Parameter ◽  
Irradiation Process ◽  
Very High ◽  
Relevant Factors

This paper provides approximate estimates for the irradiation parameter D10 to globally predict the effectiveness of any irradiation process. D10 is often reported to depend on many specific factors, implying that D10 cannot be estimated without exact knowledge of all factors involved. For specific questions these data can of course be useful but only if the conditions reported exactly match the specific question. Alternatively, this study determined the most relevant factors influencing D10, by quantitatively analyzing data from many references. The best first step appeared to be a classification of the data into vegetative bacteria and spores. As expected, spores were found to have significantly higher D10 values (average 2.48 kGy) than vegetative bacteria (average 0.762 kGy). Further analyses of the vegetative bacteria confirmed the expected extreme irradiation resistance of nonpathogenic Deinococcus radiodurans (average 10.4 kGy). Furthermore the analysis identified Enterococcus faecium, Alcaligenes spp., and several members of the Moraxella–Acinetobacter group as having very high resistance at very low temperatures (average 3.65 kGy). After exclusion of high- and low-resistance spores and some specific conditions showing relevant high or low D10 values, the average for spores was estimated to be 2.11 kGy. For vegetative bacteria this average was estimated to be 0.420 kGy. These approximate estimates are not definite, as they depend on the data used in the analyses. It is expected that inclusion of more data will not change the estimates to a great extent. The approximate estimates are therefore useful tools in designing and evaluating irradiation processes.

scholarly journals CORRELATION OF COVID-19 IN THE ONLINE PURCHASING PROCESS

2021 ◽  
Author(s):  
Saso Josimovski ◽  
◽  
Lidija Pulevska Ivanovska ◽  
Martin Kiselicki ◽  
Brankica Boceva ◽  
...  
Keyword(s):  
Empirical Research ◽  
Contact Interactions ◽  
Purchasing Decisions ◽  
The Past ◽  
Factors Influencing ◽  
Online Retailers ◽  
Specific Factors ◽  
Near Future ◽  
Relevant Factors ◽  
Purchasing Process

The paper establishes the central point for researching factors that influence buying decisions in the online purchasing process. The benefits of e-commerce for both buyers and sellers place it as the default method of shopping in the near future. Through empirical research, e-commerce growth is being established as rapidly rising through recent years, which has been accelerated by specific factors introduced by the COVID-19 pandemic. Data shows that e-commerce is dependent on several different factors during normal circumstances, which also include the level of development of the country as one of the main precursors. The beginning of the COVID-19 pandemic influenced greatly the importance of these established factors for online purchasing, rendering many of them obsolete. The paper structures the research to outline the most relevant factors influencing online purchasing decisions pre-pandemic and during pandemic times, and to draw relevant conclusions and recommendations for future practical implementations of e-commerce models. Research shows that new factors need to be introduce in these types of abnormal times, as the nature of the pandemic made non-contact interactions the norm in the past year. By introducing the six stages of pandemic behavior, online retailers can better understand the factors influencing online purchasing process in pandemic times. Finally, specific recommendations can be made to improve the e-commerce acceptance both at industry and company levels.

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

Adapting Gravity Model for Predicting the Risk of COVID -19 in Nigeria

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Olanrewaju Samson Olaitan ◽  
Olowoporoku Oluwaseun
Keyword(s):  
High Risk ◽  
Gross Domestic Product ◽  
Gravity Model ◽  
Infection Risk ◽  
Risk Level ◽  
Ogun State ◽  
Factors Influencing ◽  
Government Data ◽  
Housing Standards ◽  
Very High

Background: It is against the background of the emerging incidence of coronavirus pandemic in Nigeria, and the need for its management that this study adapts gravity model for predicting the risk of the disease across states of the country. Methods: The paper relied on published government data on population, and gross domestic product, while the distance of town to the nearest international airport was also obtained. These data were log transformed and further used in the calculation of gravity scores for each state of the federation. Results: The study discovered that with the gravity score ranging from 2.942 to 4.437, all the states of the federation have the risk of being infected with the pandemic. Meanwhile Ogun State (4.837) has a very high risk of being infected with the disease. Other states with high risks are Oyo (4.312), Jigawa (4.235), Niger (4.148) and Katsina (4.083). However, Taraba State has the least infection risk of the pandemic in Nigeria. Factors influencing the risk level of the pandemic are proximity, porous boundary between states, and elitism. Conclusion: The paper advocates border settlement planning, review of housing standards, and advocacy for sanitation in different states. It therefore concludes that adequate urban planning in unison with economic and epidemiology techniques will provide a strong strategy for the management of the disease.

Small Bowel Obstruction

2010 ◽  
Vol 21 (2) ◽  
pp. 187-194
Author(s):  
Colleen Trevino
Keyword(s):  
Small Bowel ◽  
Physical Examination ◽  
Surgical Intervention ◽  
Signs And Symptoms ◽  
Bowel Ischemia ◽  
Key Factors ◽  
The Past ◽  
Factors Influencing ◽  
Imaging Response

Strategies for the management of small bowel obstructions have changed significantly over the years. Nonoperative medical management has become the mainstay of treatment of many small bowel obstructions. However, the key to the management of small bowel obstructions is identifying those patients who need surgical intervention. Identification of those at risk for bowel ischemia and bowel death is an art as much as it is a science. Using the current literature and the past knowledge regarding small bowel obstructions, the clinician must carefully identify the signs and symptoms that suggest the need for operative intervention. Classification of the obstruction, history and physical examination, imaging, response to decompression and resuscitation, and resolution or progression of symptoms are the key factors influencing the management of small bowel obstructions.

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