Selective inspection planning with ageing forecast for sewer types

2002 ◽  
Vol 46 (6-7) ◽  
pp. 389-396 ◽  
Author(s):  
R. Baur ◽  
R. Herz
Keyword(s):  
Environmental Risks ◽  
Small Sample ◽  
Storm Water ◽  
Actual Condition ◽  
Inspection Planning ◽  
Transition Functions ◽  
Sewer Network ◽  
Different Types ◽  
Sewer Rehabilitation ◽  
Water Profile

Investments in sewer rehabilitation must be based on inspection and evaluation of sewer conditions with respect to the severity of sewer damage and to environmental risks. This paper deals with the problems of forecasting the condition of sewers in a network from a small sample of inspected sewers. Transition functions from one into the next poorer condition class, which were empirically derived from this sample, are used to forecast the condition of sewers. By the same procedure, transition functions were subsequently calibrated for sub-samples of different types of sewers. With these transition functions, the most probable date of entering a critical condition class can be forecast from sewer characteristics, such as material, period of construction, location, use for waste and/or storm water, profile, diameter and gradient. Results are shown for the estimates about the actual condition of the Dresden sewer network and its deterioration in case of doing nothing about it. A procedure is proposed for scheduling the inspection dates for sewers which have not yet been inspected and for those which have been inspected before.

scholarly journals Non-Negligible Effects of UV Irradiation on Transformation and Environmental Risks of Microplastics in the Water Environment

2021 ◽  
Vol 12 (1) ◽  
pp. 1-12
Author(s):  
Fangyuan Cheng ◽  
Tingting Zhang ◽  
Yue Liu ◽  
Yanan Zhang ◽  
Jiao Qu
Keyword(s):  
Environmental Factors ◽  
Uv Irradiation ◽  
Water Environment ◽  
Oxidative Degradation ◽  
Environmental Risks ◽  
Important Process ◽  
Environmental Behaviors ◽  
Environmental Media ◽  
Different Types ◽  
Harmful Effects

Microplastics (MPs) are ubiquitous in environmental media, and their harmful effects on MPs on the ecosystem have attracted more and more attention. Once released into the environment, MPs can trigger oxidative degradation through ultraviolet (UV) to cause photoaging. Photoaging significantly affects the properties of MPs, which leads to changing their environmental behaviors and increasing environmental risks. In this review, the generation of MPs under UV irradiation and the influence of environmental factors on the photoaging of MPs were discussed. Photoaging of MPs is an important process affecting the migration, transformation and interaction of pollutants in water and soil. In order to fully predict the fate and environmental interaction of MPs, more researches are needed in the future to explore the photoaging behavior of different types of MPs under natural environmental conditions.

scholarly journals Prevalence of Blood Groups in Eastern UP Population

2020 ◽  
Author(s):  
Pradeep Kumar ◽  
Vandana Rai
Keyword(s):  
Small Sample Size ◽  
Uttar Pradesh ◽  
Allelic Frequency ◽  
Blood Groups ◽  
Small Sample ◽  
Blood Type ◽  
Allele Frequency Distribution ◽  
Abo Blood Groups ◽  
Male And Female ◽  
Different Types

Approximately 300 different types of blood groups are identified so far, the ABO and Rh antigens are still the clinically most significant and genetically most polymorphic of all human blood group systems to date. A total of 200 unrelated individuals from Uttar Pradesh were studied for the phenotype and allele frequency distribution of ABO and Rh (D) blood groups. In total 200 samples analyzed, phenotype B blood type has the highest frequency 36.5% (n=73), followed by O (34.5%; n=69), A (20.5%; n=41) and AB (8.5%; n=17). The O, A and B frequencies were 0.5849, 0.1571 and 0.2580 respectively. The overall phenotypic frequencies of ABO blood groups were B>O>A>AB. The variation in phenotypic frequencies between male and female might be due to small sample size of male sample. The allelic frequency of Rh-negative was 0.2.

scholarly journals Narratives of cooperation, resilience and resistance: workers’ self-recovery in times of crisis

2019 ◽  
Vol 39 (9/10) ◽  
pp. 851-864 ◽  
Author(s):  
Luca Antonazzo
Keyword(s):  
Small Sample ◽  
Workplace Democracy ◽  
Cross Sectional ◽  
International Debate ◽  
Content Type ◽  
The Great Recession ◽  
Different Types ◽  
Multi Level ◽  
Sectional Analysis ◽  
Opening Up

Purpose Worker-recuperated enterprises have appeared in Europe with increasing frequency since 2008, following the Great Recession that hit the western economies. The purpose of this paper is to depict the phenomenon of worker-recuperated enterprises in Italy, focusing on two different types of business recovery, that of workers buyouts and that of recovered social spaces. The paper compares these on the basis of four analytical dimensions: resilience/resistance, relationship with the market, relationship with the territory and workplace democracy. Design/methodology/approach The corpus of the research is based on the cross-sectional analysis of workers’ narratives. These were collected, within a small sample of theoretically relevant cases, in order to retrace and analyse the path from the crisis of the former companies to establishment of the workers’ cooperatives and their social and economic features. Findings The collected narratives allowed for a multi-level comparison between different types of worker-recuperated enterprises, providing some insights on their emergence, their features in terms of resilience and resistance, their relationship with the market economy and their outcomes in terms of workplace democracy and support to employment. Originality/value Worker buyouts are gaining ground in Europe as an effective mechanism to oppose the fall of the employment rate in consequence of economic crises. This research intends to offer some data and arguments to the current international debate on the effectiveness of these mechanisms in coping with economic shocks and opening up to a sustainable and cooperative work-driven economy.

Exfiltration from gravity sewers: a pilot scale study

2003 ◽  
Vol 47 (4) ◽  
pp. 69-76 ◽  
Author(s):  
J. Vollertsen ◽  
T. Hvitved-Jacobsen
Keyword(s):  
Groundwater Pollution ◽  
Pilot Scale ◽  
Storm Events ◽  
Sewer Network ◽  
Leakage Factor ◽  
Different Types ◽  
Different Soils

Pilot-scale experiments were conducted on exfiltration of wastewater from gravity sewers. The effect of storm events, flushing of pipes and alternating infiltration/exfiltration were simulated. Exfiltration through different types of sewer leaks and into different soils were studied. It was found that the exfiltration rate became constant after some days of exfiltration. It stayed constant for the duration of the experiments, which typically spanned over some weeks. The exfiltration was governed by the development of a clogging zone at the sewer leak and could be characterized by a leakage factor. The leakage factor may then be used to estimate the risk of groundwater pollution from a sewer network.

Recommended urban storm water infiltration devices for different types of run-off under varying hydrogeological conditions

2008 ◽  
Vol 8 (4) ◽  
pp. 231-238 ◽  
Author(s):  
Patricia Göbel ◽  
Julia Zimmermann ◽  
Christoph Klinger ◽  
Holger Stubbe ◽  
Wilhelm G. Coldewey
Keyword(s):  
Water Infiltration ◽  
Storm Water ◽  
Hydrogeological Conditions ◽  
Run Off ◽  
Different Types ◽  
Urban Storm

scholarly journals The Impact of Improved Thermistor Calibration on the Expendable Bathythermograph Profile Data

2017 ◽  
Vol 34 (9) ◽  
pp. 1947-1961 ◽  
Author(s):  
Marlos Goes ◽  
Elizabeth Babcock ◽  
Francis Bringas ◽  
Peter Ortner ◽  
Gustavo Goni
Keyword(s):  
Small Sample Size ◽  
Heat Content ◽  
Small Sample ◽  
Profile Data ◽  
Expendable Bathythermograph ◽  
Different Types ◽  
Long Term Trends ◽  
The Mean ◽  
The Impact

AbstractExpendable bathythermograph (XBT) data provide one of the longest available records of upper-ocean temperature. However, temperature and depth biases in XBT data adversely affect estimates of long-term trends of ocean heat content and, to a lesser extent, estimates of volume and heat transport in the ocean. Several corrections have been proposed to overcome historical biases in XBT data, which rely on constantly monitoring these biases. This paper provides an analysis of data collected during three recent hydrographic cruises that utilized different types of probes, and examines methods to reduce temperature and depth biases by improving the thermistor calibration and reducing the mass variability of the XBT probes.The results obtained show that the use of individual thermistor calibration in XBT probes is the most effective calibration to decrease the thermal bias, improving the mean thermal bias to less than 0.02°C and its tolerance from 0.1° to 0.03°C. The temperature variance of probes with screened thermistors is significantly reduced by approximately 60% in comparison to standard probes. On the other hand, probes with a tighter weight tolerance did not show statistically significant reductions in the spread of depth biases, possibly because of the small sample size or the sensitivity of the depth accuracy to other causes affecting the analysis.

scholarly journals ANALYSES OF GENE FREQUENCIES

Genetics ◽  
1973 ◽  
Vol 74 (4) ◽  
pp. 679-700
Author(s):  
C Clark Cockerham
Keyword(s):  
Variance Components ◽  
Small Sample ◽  
Gene Frequencies ◽  
F Test ◽  
Estimable Functions ◽  
Intraclass Correlations ◽  
Different Types ◽  
Informational System ◽  
Tests Of Hypotheses

ABSTRACT Models of variance components and their intraclass correlational equivalences are developed for genes falling into various categories of subdivisions within a population. Estimable functions are elaborated demonstrating that intraclass correlations can be estimated only relative to that for the least related genes in the informational system. The effects of different types of subdivisions-and of ignoring them-on the parameters are demonstrated. Small sample estimators are formulated for all of the parameters by three different methods, including both a weighted and an unweighted method of analysis of the variation among subpopulations. How estimators change with assumptions about the parameters is illustrated. Various tests of hypotheses are outlined in X2 and F-test terminology. Discussed are factors which may affect the correlations and the manner in which their effects are manifest, hopefully in clarification of some of the misconceptions that have arisen in this connection.

Fossil Fuels

2020 ◽  
pp. 21-41
Author(s):  
Azra N. Tutuncu
Keyword(s):  
Fossil Fuels ◽  
Fossil Fuel ◽  
Primary Source ◽  
Environmental Risks ◽  
Foreseeable Future ◽  
Economic Costs ◽  
Social Scientists ◽  
Heating And Cooling ◽  
Production And Consumption ◽  
Different Types

While experts agree that some fossil fuels will be left in the ground due to economic costs, environmental risks, or political concerns, these resources are likely to remain the primary source of energy for generating electricity, heating and cooling, and transportation for the foreseeable future. This chapter provides an overview of the different types of fossil fuels and their histories, production and consumption trends, and future opportunities and challenges for the fossil fuel sector. Its purpose is to provide a technical background for social scientists working on energy issues.

Export injury early warning of the new energy industries in China

2017 ◽  
Vol 7 (2) ◽  
pp. 272-285 ◽  
Author(s):  
Jinjin Wang ◽  
Zhengxin Wang ◽  
Qin Li
Keyword(s):  
Smart Grid ◽  
Early Warning ◽  
Nuclear Power ◽  
Indicator System ◽  
Small Sample ◽  
Energy Industry ◽  
Actual Condition ◽  
Content Type ◽  
Forecast Result ◽  
New Energy

Purpose In recent years, continuous expansion of the scale of the new energy export industry in China caused a boycott of American and European countries. Export injury early warning research is an urgent task to develop the new energy industry in China. The purpose of this paper is to build an indicator system of exports injury early warning of the new energy industry in China and corresponding quantitative early warning models. Design/methodology/approach In consideration of the actual condition of the new energy industry in China, this paper establishes an indicator system according to four aspects: export price, export quantity, impact on domestic industry and impact on macro economy. Based on the actual data of new energy industry and its five sub-industries (solar, wind, nuclear power, smart grid and biomass) in China from 2003 to 2013, GM (1,1) model is used to predict early warning index values for 2014-2018. Then, the principal component analysis (PCA) is used to obtain the comprehensive early warning index values for 2003-2018. The 3-sigma principle is used to divide the early warning intervals according to the comprehensive early warning index values for 2003-2018 and their standard deviation. Finally, this paper determines alarm degrees for 2003-2018. Findings Overall export condition of the new energy industry in China is a process from cold to normal in 2003-2013, and the forecast result shows that it will be normal from 2014 to 2018. The export condition of the solar energy industry experienced a warming process, tended to be normal, and the forecast result shows that it will also be normal in 2014-2018. The biomass and other new energy industries and nuclear power industry show a similar development process. Export condition of the wind energy industry is relatively unstable, and it will be partially hot in 2014-2018, according to the forecast result. As for the smart grid industry, the overall export condition of it is normal, but it is also unstable, in few years it will be partially hot or partially cold. The forecast result shows that in 2014-2018, it will maintain the normal state. In general, there is a rapid progress in the export competitiveness of the new energy industry in China in the recent decade. Practical implications Export injury early warning research of the new energy industry can help new energy companies to take appropriate measures to reduce trade losses in advance. It can also help the relevant government departments to adjust industrial policies and optimize the new energy industry structure. Originality/value This paper constructs an index system that can measure the alarm degrees of the new energy industry. By combining the GM (1,1) model and the PCA method, the problem of warning condition detection under small sample data sets is solved.

scholarly journals Identification of Navel Orange Diseases and Pests Based on the Fusion of DenseNet and Self-Attention Mechanism

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yin’e Zhang ◽  
Yong Ping Liu
Keyword(s):  
Small Sample ◽  
Small Samples ◽  
Data Sets ◽  
Navel Orange ◽  
Pests And Diseases ◽  
Sample Data ◽  
Different Types ◽  
High Recognition Accuracy ◽  
Intelligent Recognition ◽  
And Control

The prevention and control of navel orange pests and diseases is an important measure to ensure the yield of navel oranges. Aiming at the problems of slow speed, strong subjectivity, high requirements for professional knowledge required, and high identification costs in the identification methods of navel orange pests and diseases, this paper proposes a method based on DenseNet and attention. The power mechanism fusion (DCPSNET) identification method of navel orange diseases and pests improves the traditional deep dense network DenseNet model to realize accurate and efficient identification of navel orange diseases and pests. Due to the difficulty in collecting data of navel orange pests and diseases, this article uses image enhancement technology to expand. The experimental results show that, in the case of small samples, compared with the traditional model, the DCPSNET model can accurately identify different types of navel orange diseases and pests images and the accuracy of identifying six types of navel orange diseases and pests on the test set is as high as 96.90%. The method proposed in this paper has high recognition accuracy, realizes the intelligent recognition of navel orange diseases and pests, and also provides a way for high-precision recognition of small sample data sets.

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