Sulfolane: Magic Extractor or Bad Actor? Pilot-Scale Study on Solvent Corrosion Potential

The sulfur-containing derivatives and their metabolites, regarded as ‘old devils of green’ chemistry, constitute a relevant class of air/water/soil contaminants in over-polluted world. In fact, some industrially-engineered solvents have become environmentally unfavorable. An attractive alternative to commonly used industrial liquids is sulfolane (C4H8SO2), an anthropogenic medium. The main objective of this paper is the comprehensive review focusing mainly on the state-of-the-art aspects of the sulfolane synthesis, application of sulfolane as an extractive solvent due to its ‘unique’ physicochemical properties as well as the potential of sulfolane to cause equipment corrosion and subsequent spills. The potential risk for groundwater contamination, danger for human health and ways of sulfolane biodegradation were briefly reviewed as well. Interestingly, the analysis performed on data stored in the Reaxys database revealed an alternating tendency of waxing and waning interest in sulfolane during the space of the last fifty years. Moreover, the primary goal of the presented case study was to verify applicability of industrial, multi-electrochemical technique for reliable detection of corrosion in low conductive process fluids. Several aspects of corrosion measurement including the impact of process parameters (temperature) and impurities (oxygen and chlorides) on stainless steel corrosion in pure sulfolane were investigated briefly.

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Deepfake-Image Anti-Forensics with Adversarial Examples Attacks

Future Internet ◽

10.3390/fi13110288 ◽

2021 ◽

Vol 13 (11) ◽

pp. 288

Author(s):

Li Fan ◽

Wei Li ◽

Xiaohui Cui

Keyword(s):

State Of The Art ◽

Poisson Noise ◽

Future Research ◽

Detection Accuracy ◽

Generalization Performance ◽

Image Forensic ◽

Adversarial Examples ◽

Adversarial Example ◽

The Impact

Many deepfake-image forensic detectors have been proposed and improved due to the development of synthetic techniques. However, recent studies show that most of these detectors are not immune to adversarial example attacks. Therefore, understanding the impact of adversarial examples on their performance is an important step towards improving deepfake-image detectors. This study developed an anti-forensics case study of two popular general deepfake detectors based on their accuracy and generalization. Herein, we propose the Poisson noise DeepFool (PNDF), an improved iterative adversarial examples generation method. This method can simply and effectively attack forensics detectors by adding perturbations to images in different directions. Our attacks can reduce its AUC from 0.9999 to 0.0331, and the detection accuracy of deepfake images from 0.9997 to 0.0731. Compared with state-of-the-art studies, our work provides an important defense direction for future research on deepfake-image detectors, by focusing on the generalization performance of detectors and their resistance to adversarial example attacks.

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Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

Proceedings on Privacy Enhancing Technologies ◽

10.1515/popets-2015-0021 ◽

2015 ◽

Vol 2015 (2) ◽

pp. 171-187 ◽

Cited By ~ 7

Author(s):

Joshua Juen ◽

Aaron Johnson ◽

Anupam Das ◽

Nikita Borisov ◽

Matthew Caesar

Keyword(s):

State Of The Art ◽

Autonomous Systems ◽

Path Selection ◽

Prediction Errors ◽

Accurate Picture ◽

Path Prediction ◽

Prediction Techniques ◽

Inference Techniques ◽

The Impact

Abstract The Tor anonymity network has been shown vulnerable to traffic analysis attacks by autonomous systems (ASes) and Internet exchanges (IXes), which can observe different overlay hops belonging to the same circuit. We evaluate whether network path prediction techniques provide an accurate picture of the threat from such adversaries, and whether they can be used to avoid this threat. We perform a measurement study by collecting 17.2 million traceroutes from Tor relays to destinations around the Internet. We compare the collected traceroute paths to predicted paths using state-of-the-art path inference techniques. We find that traceroutes present a very different picture, with the set of ASes seen in the traceroute path differing from the predicted path 80% of the time. We also consider the impact that prediction errors have on Tor security. Using a simulator to choose paths over a week, our traceroutes indicate a user has nearly a 100% chance of at least one compromise in a week with 11% of total paths containing an AS compromise and less than 1% containing an IX compromise when using default Tor selection. We find modifying the path selection to choose paths predicted to be safe lowers total paths with an AS compromise to 0.14% but still presents a 5–11% chance of at least one compromise in a week while making 5% of paths fail, with 96% of failures due to false positives in path inferences. Our results demonstrate more measurement and better path prediction is necessary to mitigate the risk of AS and IX adversaries to Tor.

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Sustainable Circular Micro Index for Evaluating Virtual Substitution Using Machine Learning with the Path Planning Problem as a Case Study

Sustainability ◽

10.3390/su132313436 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13436

Author(s):

Javier Maldonado-Romo ◽

Mario Aldape-Pérez

Keyword(s):

Machine Learning ◽

Path Planning ◽

Business Models ◽

Attractive Alternative ◽

Planning Problem ◽

Five Dimensions ◽

Circular Model ◽

Physical Elements ◽

The Impact

Due to the problems resulting from the COVID-19 pandemic, for example, semiconductor supply shortages impacting the technology industry, micro-, small-, and medium-sized enterprises have been affected because the profitability of their business models depends on market stability. Therefore, it is essential to propose alternatives to mitigate the various consequences, such as the high costs. One attractive alternative is to replace the physical elements using resource-limited devices powered by machine learning. Novel features can improve the embedded devices’ (such as old smartphones) ability to perceive an environment and be incorporated in a circular model. However, it is essential to measure the impact of substituting the physical elements employing an approach of a sustainable circular economy. For this reason, this paper proposes a sustainable circular index to measure the impact of the substitution of a physical element by virtualization. The index is composed of five dimensions: economic, social, environmental, circular, and performance. In order to describe this index, a case study was employed to measure the path-planning generator for micro aerial vehicles developed using virtual simulation using machine-learning methods. The proposed index allows considering virtualization to extend the life cycle of devices with limited resources based on suggested criteria. Thus, a smartphone and the Jetson nano board were analyzed as replacements of specialized sensors in controlled environments.

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Electrochemical Corrosion Monitoring in Low Conductive Fluid: Pilot-Scale Study on Sulfolane Corrosion Potential

Proceedings ◽

10.3390/proceedings2019016005 ◽

2019 ◽

Vol 16 (1) ◽

pp. 5

Author(s):

Aleksandra Świetlicka ◽

Agnieszka Środa ◽

Violetta Kozik ◽

Andrzej Bąk ◽

Krzysztof Barbusiński ◽

...

Keyword(s):

Saturated Hydrocarbon ◽

Electrochemical Corrosion ◽

Pilot Scale ◽

Electrochemical Technique ◽

Attractive Alternative ◽

Corrosion Monitoring ◽

Vapor Extraction ◽

Extraction Processes ◽

Higher Temperature ◽

By Products

Solvents are a group of chemical compounds that are widely used in organic synthesis. Taking into account the chemical nature, solvents are divided into protic and aprotic ones. An attractive alternative to commonly used industrial extractive liquids is an anthropogenic, organosulfur medium—sulfolane. Sulfolane is a five-membered heterocyclic sulfur–organic compound from the group of sulfones (R-SO2-R’, where R/R’ is alkyl, alkenyl, or aryl), which contains an apolar hydrocarbon backbone and a polar functional group. It is a selective solvent in the liquid–liquid and liquid–vapor extraction processes used for the removal of close-boiling alkanes from cycloalkanes or for the separation of compounds with different degrees of saturation and polarity in the extractive rectification of arenes from non-aromatic saturated hydrocarbon mixtures. In standard conditions sulfolane is not an aggressive solvent for steel, but at higher temperature (170–180 °C) and oxygen availability, it may be decomposed and subsequently some corrosive (by-)products can be formed. The primary purpose of the presented pilot-case examination was to verify applicability of the industrial, multi-electrochemical technique for reliable detection of the corrosion processes in low conductive fluids.

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The impact of the city skyline on pleasantness; state of the art and a case study

Heliyon ◽

10.1016/j.heliyon.2021.e07009 ◽

2021 ◽

Vol 7 (5) ◽

pp. e07009

Author(s):

Mehrdad Karimimoshaver ◽

Mastooreh Parsamanesh ◽

Farshid Aram ◽

Amir Mosavi

Keyword(s):

State Of The Art ◽

The Impact ◽

The City

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Assessing Impact of Bus Traffic on Pavement Maintenance Costs: City of Los Angeles

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1853-04 ◽

2003 ◽

Vol 1853 (1) ◽

pp. 29-36

Author(s):

M. Y. Shahin ◽

James A. Crovetti ◽

Kurt A. Keifer

Keyword(s):

Los Angeles ◽

State Of The Art ◽

Maintenance Cost ◽

Maintenance Costs ◽

Pavement Condition ◽

Pavement Maintenance ◽

The Impact ◽

The City ◽

Evaluation Techniques

Engineers for the city of Los Angeles have observed that lanes carrying Mass Transit Authority (MTA) bus traffic deteriorate at a faster rate than similar lanes without bus traffic. The increased rate of deterioration results in greater maintenance costs in these lanes. To properly apportion the increased maintenance costs, city engineers need an objective method for quantifying the impact of MTA bus traffic. Multiple evaluation techniques are presented that may be used to quantify the effect of buses in terms of increased deterioration rates and greater rehabilitation costs. State-of-the-art techniques that use the results of deflection testing and pavement condition surveys are presented. Data collection procedures, methods for condition and structural analyses, and life-cycle costing procedures are provided. A case study that uses data collected from the city is presented. This study indicates an average yearly additional maintenance cost of $800 per lane-mile caused by MTA bus traffic, excluding associated costs for curb and gutter or maintenance hole adjustments.

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