scholarly journals Diel Variation of Viral Production in a Coastal Subtropical Marine System

Diversity ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 426
Author(s):  
Pei-Chi Ho ◽  
Gwo-Ching Gong ◽  
Chih-Hao Hsieh ◽  
Patrichka Wei-Yi Chen ◽  
An-Yi Tsai
Keyword(s):  
Linear Regression ◽  
Coastal Region ◽  
Cell Types ◽  
Linear Regression Method ◽  
Diel Variation ◽  
Viral Production ◽  
Viral Lysis ◽  
Bacterial Mortality ◽  
Marine System ◽  
Classical Linear Regression

Viral production (VP) and bacterial mortality by viral lysis critically influence the production and mortality of aquatic bacteria. Although bacterial production, mortality by viral lysis, and viral density have been found to exhibit diel variations, the diel change in viral production has rarely been investigated. In this study, we conducted two diel dilution incubation experiments in a semi-enclosed, nutrient-rich coastal region in northeastern Taiwan to estimate the diel viral production and the mortality by viral lysis. We also compared two methods (linear regression between viral density and time versus arithmetic mean of VP during incubation) of estimating viral production. We found that viral production estimated by linear regression and bacterial mortality by viral lysis were higher during the daytime than during the nighttime. A possible explanation for the high viral production at daytime is that the bacterial community was composed of cell types with higher burst sizes at daytime. We further argued that the classical linear regression method can be used only when viral density significantly linearly increases with time, which does not always occur in dilution incubations. This study offered observations of diel variation in viral dynamics and discussed the methods estimating viral production in a marine environment.

scholarly journals Viral Lysis and Bacterivory during a Phytoplankton Bloom in a Coastal Water Microcosm

1999 ◽  
Vol 65 (5) ◽  
pp. 1949-1958 ◽  
Author(s):  
Núria Guixa-Boixereu ◽  
Kristine Lysnes ◽  
Carlos Pedrós-Alió
Keyword(s):  
Steady State ◽  
Bacterial Production ◽  
Phytoplankton Bloom ◽  
Decay Rates ◽  
Heterotrophic Nanoflagellates ◽  
Viral Production ◽  
Viral Lysis ◽  
Bacterial Growth Rate ◽  
Bacterial Assemblage ◽  
Bacterial Mortality

ABSTRACT The relative importance of viral lysis and bacterivory as causes of bacterial mortality were estimated. A laboratory experiment was carried out to check the kind of control that viruses could exert over the bacterial assemblage in a non-steady-state situation. Virus-like particles (VLP) were determined by using three methods of counting (DAPI [4′,6-diamidino-2-phenylindole] staining, YOPRO staining, and transmission electron microscopy). Virus counts increased from the beginning until the end of the experiment. However, different methods produced significantly different results. DAPI-stained VLP yielded the lowest numbers, while YOPRO-stained VLP yielded the highest numbers. Bacteria reached the maximal abundance at 122 h (3 × 107 bacteria ml−1), after the peak of chlorophyll a (80 μg liter−1). Phototrophic nanoflagellates followed the same pattern as for chlorophylla. Heterotrophic nanoflagellates showed oscillations in abundance throughout the experiment. The specific bacterial growth rate increased until 168 h (2.6 day−1). The bacterivory rate reached the maximal value at 96 hours (0.9 day−1). Bacterial mortality due to viral infection was measured by using two approaches: measuring the percentage of visibly infected bacteria (%VIB) and measuring the viral decay rates (VDR), which were estimated with cyanide. The %VIB was always lower than 1% during the experiment. VDR were used to estimate viral production. Viral production increased 1 order of magnitude during the experiment (from 106 to 107 VLP ml−1h−1). The percentage of heterotrophic bacterial production consumed by bacterivores was higher than 60% during the first 4 days of the experiment; afterwards, this percentage was lower than 10%. The percentage of heterotrophic bacterial production lysed by viruses as assessed by the VDR reached the highest values at the beginning (100%) and at the end (50%) of the experiment. Comparing both sources of mortality at each stage of the bloom, bacterivory was found to be higher than viral lysis at days 2 and 4, and viral lysis was higher than bacterivory at days 7 and 9. A balance between bacterial losses and bacterial production was calculated for each sampling interval. At intervals of 0 to 2 and 2 to 4 days, viral lysis and bacterivory accounted for all the bacterial losses. At intervals of 4 to 7 and 7 to 9 days, bacterial losses were not balanced by the sources of mortality measured. At these time points, bacterial abundance was about 20 times higher than the expected value if viral lysis and bacterivory had been the only factors causing bacterial mortality. In conclusion, mortality caused by viruses can be more important than bacterivory under non-steady-state conditions.

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

2018 ◽  
Vol 6 (6) ◽  
pp. 119
Author(s):  
Mohammad Shohidul Islam ◽  
Sultana Easmin Siddika ◽  
S M Injamamul Haque Masum
Keyword(s):  
Linear Regression ◽  
Correlation Coefficients ◽  
Rain Gauge ◽  
Regression Method ◽  
Linear Regression Method ◽  
Climate Data ◽  
Rainfall Forecasting ◽  
Statistical Parameters ◽  
Time Duration ◽  
Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

An alternative model of the vibronic coupling in octahedral complexes

1988 ◽  
Vol 53 (6) ◽  
pp. 1134-1140
Author(s):  
Martin Breza ◽  
Peter Pelikán
Keyword(s):  
Linear Regression ◽  
Alternative Model ◽  
Potential Surface ◽  
Analytical Formula ◽  
Coupling Model ◽  
Regression Method ◽  
Vibronic Coupling ◽  
Linear Regression Method ◽  
Active Systems ◽  
Jahn Teller

It is suggested that for some transition metal hexahalo complexes, the Eg-(a1g + eg) vibronic coupling model is better suited than the classical T2g-(a1g + eg) model. For the former, alternative model, the potential constants in the analytical formula are evaluated from the numerical map of the adiabatic potential surface by using the linear regression method. The numerical values for 29 hexahalo complexes of the 1st row transition metals are obtained by the CNDO/2 method. Some interesting trends of parameters of such Jahn-Teller-active systems are disclosed.

The Accuracy Assessment of Weapon System Using Grey Linear Regression Method

2012 ◽  
Vol 268-270 ◽  
pp. 1809-1813
Author(s):  
Dai Yu Zhang ◽  
Bao Wei Song ◽  
Zhou Quan Zhu
Keyword(s):  
Linear Regression ◽  
Fuzzy Theory ◽  
Accuracy Assessment ◽  
Regression Method ◽  
Small Sample ◽  
Easy Access ◽  
Linear Regression Method ◽  
Grey Theory ◽  
Weapon System ◽  
Complex Engineering

The accuracy assessment of weapon system is always a complex engineering. How to make the most of the information given in only a few tests and obtain reasonable estimate is always a problem. Based on the fuzzy theory and grey theory, a grey linear regression method is presented. From the numerical example, we can see that this method provides an easy access to deal with data in small sample case and may have potential use in the analysis of weapon performance.

scholarly journals Demineralization Depth Using QLF and a Novel Image Processing Software

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Jun Wu ◽  
Zachary R. Donly ◽  
Kevin J. Donly ◽  
Steven Hackmyer
Keyword(s):  
Image Processing ◽  
Linear Regression ◽  
Polarized Light ◽  
Region Of Interest ◽  
Linear Regression Method ◽  
Percent Loss ◽  
Significant Linear Correlation ◽  
Processing Software ◽  
Image Processing Software ◽  
Imagej Software

Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model wasY=0.32X+0.17, whereXwas the percent loss of fluorescence andYwas the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating theP-value=.0014. TheFtest for the entire model was 62.86, which shows theP-value=.0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization.

Perancangan Aplikasi Prediksi Jumlah Pendaftar Siswa Baru Dengan Metode Regresi Linier (Studi Kasus: SMA RK Deli Murni Bandar Baru)

2020 ◽  
Vol 3 (3) ◽  
pp. 330-334
Author(s):  
Novita Ria Lase ◽  
Fristi Riandari
Keyword(s):  
Linear Regression ◽  
Regression Method ◽  
Point Of View ◽  
Computational Techniques ◽  
Linear Regression Method ◽  
Simple Linear Regression ◽  
Tuition Fees ◽  
Use Of Data ◽  
New Students ◽  
New Student

The problem of the SMA RK Deli Murni Bandar Baru school is to predict how many facilities that need to be provided for new students such as chairs, tables and others. This study discusses the prediction of the number of new student registrants at SMA RK Deli Murni Bandar Baru based on the amount of tuition fees using a simple linear regression method. From a commercial point of view, the use of data mining can be used to handle the explosion of data volumes, using computational techniques can be used to produce information needed which is an asset that can increase the competitiveness of an institution. Prediction is almost the same as classification and estimation, except that in the prediction the value of the results will be in the future. This system can be used to predict the number of applicants in the following year to help the school. The advantage is that this simple linear regression method is very simple so that it is easy to calculate and use. Saves the time needed to solve problems, especially those that are very complex.

An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids

2019 ◽  
Vol 164 ◽  
pp. 681-689 ◽  
Author(s):  
Mariusz Zapadka ◽  
Mateusz Kaczmarek ◽  
Bogumiła Kupcewicz ◽  
Przemysław Dekowski ◽  
Agata Walkowiak ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

A NEW PARAMETER ESTIMATION METHOD FOR ONLINE SOFT TISSUE CHARACTERIZATION

2016 ◽  
Vol 16 (08) ◽  
pp. 1640019 ◽  
Author(s):  
JAEHYUN SHIN ◽  
YONGMIN ZHONG ◽  
JULIAN SMITH ◽  
CHENGFAN GU
Keyword(s):  
Soft Tissue ◽  
Linear Regression ◽  
Tissue Characterization ◽  
Soft Tissues ◽  
Unscented Kalman Filter ◽  
Estimation Method ◽  
Regression Method ◽  
Linear Regression Method ◽  
Non Linear

Dynamic soft tissue characterization is of importance to robotic-assisted minimally invasive surgery. The traditional linear regression method is unsuited to handle the non-linear Hunt–Crossley (HC) model and its linearization process involves a linearization error. This paper presents a new non-linear estimation method for dynamic characterization of mechanical properties of soft tissues. In order to deal with non-linear and dynamic conditions involved in soft tissue characterization, this method improves the non-linearity and dynamics of the HC model by treating parameter [Formula: see text] as independent variable. Based on this, an unscented Kalman filter is developed for online estimation of soft tissue parameters. Simulations and comparison analysis demonstrate that the proposed method is able to estimate mechanical parameters for both homogeneous tissues and heterogeneous and multi-layer tissues, and the achieved performance is much better than that of the linear regression method.

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