scholarly journals Radiation Reduction of Carbon Dioxide: A New Chemical Industry?

2020 ◽  
Author(s):  
Peter Livingston
Keyword(s):  
Carbon Dioxide ◽  
Carbon Footprint ◽  
Chemical Industry ◽  
Petrochemical Industry ◽  
The Novel ◽  
Spent Fuel ◽  
Radiation Reduction ◽  
Fuel Rods ◽  
Novel Approach ◽  
Reduce Carbon Dioxide

A novel approach to use waste radiation from spent fuel rods to reduce carbon dioxide to produce various feedstock chemicals for the chemical industry.<div>The basic radiochemistry has been known for at least four decades. The novel element is how this all can be accomplished safely using spent-fuel assembly radiation. The latter is carbon footprint-free and the product materials are also very pure. There is no residual contamination requiring expensive 'clean-up' unlike chemical industry feedstocks produced by the petrochemical industry.</div>

scholarly journals Radiation Reduction of Carbon Dioxide: A New Chemical Industry?

2020 ◽  
Author(s):  
Peter Livingston
Keyword(s):  
Carbon Dioxide ◽  
Carbon Footprint ◽  
Chemical Industry ◽  
Petrochemical Industry ◽  
The Novel ◽  
Spent Fuel ◽  
Radiation Reduction ◽  
Fuel Rods ◽  
Novel Approach ◽  
Reduce Carbon Dioxide

A novel approach to use waste radiation from spent fuel rods to reduce carbon dioxide to produce various feedstock chemicals for the chemical industry.<div>The basic radiochemistry has been known for at least four decades. The novel element is how this all can be accomplished safely using spent-fuel assembly radiation. The latter is carbon footprint-free and the product materials are also very pure. There is no residual contamination requiring expensive 'clean-up' unlike chemical industry feedstocks produced by the petrochemical industry.</div>

Exploring normative perceptions and misperceptions of private, environmentally impactful behaviours

2020 ◽  
Author(s):  
Elaine Gallagher ◽  
Bas Verplanken ◽  
Ian Walker
Keyword(s):  
Social Norms ◽  
Behaviour Change ◽  
Social Contexts ◽  
The Novel ◽  
Normative Influence ◽  
Change Mechanism ◽  
Novel Approach ◽  
Classical Studies ◽  
Referent Group

Social norms have been shown to be an effective behaviour change mechanism across diverse behaviours, demonstrated from classical studies to more recent behaviour change research. Much of this research has focused on environmentally impactful actions. Social norms are typically utilised for behaviour change in social contexts, which facilitates the important element of the behaviour being visible to the referent group. This ensures that behaviours can be learned through observation and that deviations from the acceptable behaviour can be easily sanctioned or approved by the referent group. There has been little focus on how effective social norms are in private or non-social contexts, despite a multitude of environmentally impactful behaviours occurring in the home, for example. The current study took the novel approach to explore if private behaviours are important in the context of normative influence, and if the lack of a referent groups results in inaccurate normative perceptions and misguided behaviours. Findings demonstrated variance in normative perceptions of private behaviours, and that these misperceptions may influence behaviour. These behaviours are deemed to be more environmentally harmful, and respondents are less comfortable with these behaviours being visible to others, than non-private behaviours. The research reveals the importance of focusing on private behaviours, which have been largely overlooked in the normative influence literature.

scholarly journals Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ming Fang ◽  
Yoann Altmann ◽  
Daniele Della Latta ◽  
Massimiliano Salvatori ◽  
Angela Di Fulvio
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Image Resolution ◽  
Emission Tomography ◽  
Nuclear Safeguards ◽  
Activity Levels ◽  
Spent Fuel ◽  
Gamma Emission ◽  
Cross Sectional ◽  
Fuel Rods

AbstractCompliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

scholarly journals A Novel Approach to EEG Speech Activity Detection with Visual Stimuli and Mobile BCI

2021 ◽  
Vol 11 (2) ◽  
pp. 674
Author(s):  
Marianna Koctúrová ◽  
Jozef Juhár
Keyword(s):  
Visual Stimuli ◽  
Computer Interface ◽  
Single Subject ◽  
Detection Accuracy ◽  
The Novel ◽  
Activity Detection ◽  
Speech Activity ◽  
Novel Approach ◽  
Eeg Data ◽  
Speech Activity Detection

With the ever-progressing development in the field of computational and analytical science the last decade has seen a big improvement in the accuracy of electroencephalography (EEG) technology. Studies try to examine possibilities to use high dimensional EEG data as a source for Brain to Computer Interface. Applications of EEG Brain to computer interface vary from emotion recognition, simple computer/device control, speech recognition up to Intelligent Prosthesis. Our research presented in this paper was focused on the study of the problematic speech activity detection using EEG data. The novel approach used in this research involved the use visual stimuli, such as reading and colour naming, and signals of speech activity detectable by EEG technology. Our proposed solution is based on a shallow Feed-Forward Artificial Neural Network with only 100 hidden neurons. Standard features such as signal energy, standard deviation, RMS, skewness, kurtosis were calculated from the original signal from 16 EEG electrodes. The novel approach in the field of Brain to computer interface applications was utilised to calculated additional set of features from the minimum phase signal. Our experimental results demonstrated F1 score of 86.80% and 83.69% speech detection accuracy based on the analysis of EEG signal from single subject and cross-subject models respectively. The importance of these results lies in the novel utilisation of the mobile device to record the nerve signals which can serve as the stepping stone for the transfer of Brain to computer interface technology from technology from a controlled environment to the real-life conditions.

scholarly journals Decarbonization of Residential Building Energy Supply: Impact of Cogeneration System Performance on Energy, Environment, and Economics

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2538
Author(s):  
Praveen K. Cheekatamarla
Keyword(s):  
Carbon Dioxide ◽  
Power Generation ◽  
Energy Consumption ◽  
Carbon Footprint ◽  
Residential Buildings ◽  
Building Energy ◽  
Primary Energy ◽  
Primary Energy Consumption ◽  
Cogeneration System ◽  
The Impact

Electrical and thermal loads of residential buildings present a unique opportunity for onsite power generation, and concomitant thermal energy generation, storage, and utilization, to decrease primary energy consumption and carbon dioxide intensity. This approach also improves resiliency and ability to address peak load burden effectively. Demand response programs and grid-interactive buildings are also essential to meet the energy needs of the 21st century while addressing climate impact. Given the significance of the scale of building energy consumption, this study investigates how cogeneration systems influence the primary energy consumption and carbon footprint in residential buildings. The impact of onsite power generation capacity, its electrical and thermal efficiency, and its cost, on total primary energy consumption, equivalent carbon dioxide emissions, operating expenditure, and, most importantly, thermal and electrical energy balance, is presented. The conditions at which a cogeneration approach loses its advantage as an energy efficient residential resource are identified as a function of electrical grid’s carbon footprint and primary energy efficiency. Compared to a heat pump heating system with a coefficient of performance (COP) of three, a 0.5 kW cogeneration system with 40% electrical efficiency is shown to lose its environmental benefit if the electrical grid’s carbon dioxide intensity falls below 0.4 kg CO2 per kWh electricity.

ChemInform Abstract: The Novel Approach to Indole Alkaloids by Using Pd(II)-Catalyzed Cyclization.

ChemInform ◽  
2015 ◽  
Vol 46 (17) ◽  
pp. no-no
Author(s):  
Hajime Yokoyama ◽  
Takayoshi Kubo ◽  
Yosuke Matsumura ◽  
Junichi Hosokawa ◽  
Masahiro Miyazawa ◽  
...  
Keyword(s):  
Indole Alkaloids ◽  
The Novel ◽  
Novel Approach

The Fatigue Analysis of Pressure Vessels Based on Workbench

2012 ◽  
Vol 550-553 ◽  
pp. 3082-3087
Author(s):  
Xing Ye Su ◽  
Qin Li ◽  
Hong Mei Wang
Keyword(s):  
Fatigue Failure ◽  
Chemical Industry ◽  
Pressure Vessel ◽  
Petrochemical Industry ◽  
Rapid Development ◽  
Fatigue Analysis ◽  
Pressure Vessels ◽  
Operation Condition ◽  
Key Steps

With the rapid development of petrochemical industry, the operation condition of pressure vessels under the alternating load was increasing and the probability of fatigue failure was also on the rise. As a result, pressure vessel fatigue analysis is gaining the designer's attention. This paper describes the key steps and techniques of the fatigue analysis of pressure vessel based on Workbench platform using the lock hopper of the coal chemical industry as an example.

scholarly journals Caffeine-Induced Effects on Human Skeletal Muscle Contraction Time and Maximal Displacement Measured by Tensiomyography

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 815
Author(s):  
Przemysław Domaszewski ◽  
Paweł Pakosz ◽  
Mariusz Konieczny ◽  
Dawid Bączkowicz ◽  
Ewa Sadowska-Krępa
Keyword(s):  
Skeletal Muscle ◽  
Muscle Activation ◽  
Electric Pulse ◽  
Professional Athletes ◽  
Mechanical Activity ◽  
The Novel ◽  
Contraction Time ◽  
Novel Approach ◽  
Skeletal Muscle Contraction ◽  
Maximal Displacement

Studies on muscle activation time in sport after caffeine supplementation confirmed the effectiveness of caffeine. The novel approach was to determine whether a dose of 9 mg/kg/ body mass (b.m.) of caffeine affects the changes of contraction time and the displacement of electrically stimulated muscle (gastrocnemius medialis) in professional athletes who regularly consume products rich in caffeine and do not comply with the caffeine discontinuation period requirements. The study included 40 professional male handball players (age = 23.13 ± 3.51, b.m. = 93.51 ± 15.70 kg, height 191 ± 7.72, BMI = 25.89 ± 3.10). The analysis showed that in the experimental group the values of examined parameters were significantly reduced (p ≤ 0.001) (contraction time: before = 20.60 ± 2.58 ms/ after = 18.43 ± 3.05 ms; maximal displacement: before = 2.32 ± 0.80 mm/after = 1.69 ± 0.51 mm). No significant changes were found in the placebo group. The main achievement of this research was to demonstrate that caffeine at a dose of 9 mg/kg in professional athletes who regularly consume products rich in caffeine has a direct positive effect on the mechanical activity of skeletal muscle stimulated by an electric pulse.

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