Bactericidal vertically aligned graphene networks derived from renewable precursor

Graphene nanostructures exhibit a wide range of remarkable properties suitable for many applications, including those in the field of biomedical engineering. In this work, plasma-enhanced chemical vapor deposition was utilized at different applied RF power for the fabrication of vertical graphene nanowalls on silicon and quartz substrates from an inherently volatile carbon precursor without the use of any catalyst. AFM confirmed the presence of very sharp exposed graphene edges, with associated high surface roughness. The hydrophobicity of the material increased with the power of deposition, reaching the water contact angle of 123 ˚ for 500 W. Confocal scanning laser microscopy demonstrated that the viability of gram-negative Escherichia coli and gram-positive Staphylococcus aureus cells were 33% and 37% when incubated on graphene samples, respectively, compared to controls (quartz) that showed the viability of 82% and 84%, respectively. SEM verified significant morphological damage to bacterial cell walls by the sharp edges of graphene walls, with cells appearing abnormal and deformed. The presented data clearly contributed to the current understanding of the mechanical-bactericidal mechanism of vertically oriented graphene nanowalls upon direct contact with microorganisms

Using Authorship Verification to Mitigate Abuse in Online Communities

Social media has become an important method for information sharing. This has also created opportunities for bad actors to easily spread disinformation and manipulate public opinion. This paper explores the possibility of applying Authorship Verification on online communities to mitigate abuse by analyzing the writing style of online accounts to identify accounts managed by the same person. We expand on our similarity-based authorship verification approach, previously applied on large fanfictions, and show that it works in open-world settings, shorter documents, and is largely topic-agnostic. Our expanded model can link Reddit accounts based on the writing style of only 40 comments with an AUC of 0.95, and the performance increases to 0.98 given more content. We apply this model on a set of suspicious Reddit accounts associated with the disinformation campaign surrounding the 2016 U.S. presidential election and show that the writing style of these accounts are inconsistent, indicating that each account was likely maintained by multiple individuals. We also apply this model to Reddit user accounts that commented on the WallStreetBets subreddit around the 2021 GameStop short squeeze and show that a number of account pairs share very similar writing styles. We also show that this approach can link accounts across Reddit and Twitter with an AUC of 0.91 even when training data is very limited

“Because... I was told... so much”: Linguistic Indicators of Mental Health Status on Twitter

Recent studies have shown that machine learning can identify individuals with mental illnesses by analyzing their social media posts. Topics and words related to mental health are some of the top predictors. These findings have implications for early detection of mental illnesses. However, they also raise numerous privacy concerns. To fully evaluate the implications for privacy, we analyze the performance of different machine learning models in the absence of tweets that talk about mental illnesses. Our results show that machine learning can be used to make predictions even if the users do not actively talk about their mental illness. To fully understand the implications of these findings, we analyze the features that make these predictions possible. We analyze bag-of-words, word clusters, part of speech n-gram features, and topic models to understand the machine learning model and to discover language patterns that differentiate individuals with mental illnesses from a control group. This analysis confirmed some of the known language patterns and uncovered several new patterns. We then discuss the possible applications of machine learning to identify mental illnesses, the feasibility of such applications, associated privacy implications, and analyze the feasibility of potential mitigations

Enhanced Antimicrobial Activity through Synergistic Effects of Cold Atmospheric Plasma and Plant Secondary Metabolites: Opportunities and Challenges

The emergence of antibiotic resistant microorganisms possesses a great threat to human health and the environment. Considering the exponential increase in the spread of antibiotic resistant microorganisms, it would be prudent to consider the use of alternative antimicrobial agents or therapies. Only a sustainable, sustained, determined, and coordinated international effort will provide the solutions needed for the future. Plant secondary metabolites show bactericidal and bacteriostatic activity similar to that of conventional antibiotics. However, to effectively eliminate infection, secondary metabolites may need to be activated by heat treatment or combined with other therapies. Cold atmospheric plasma therapy is yet another novel approach that has proven antimicrobial effects. In this review, we explore the physiochemical mechanisms that may give rise to the improved antimicrobial activity of secondary metabolites when combined with cold atmospheric plasma therapy

Evaluation of silages of hybrids of napier grass and sorghum in the low country wet zone of Sri Lanka

Silages of hybrids of napier grass (CO-3 or CO-4) and sorghum and their combinations (50% napier grass hybrid + 50% of sorghum) were tested under three cutting intervals (4, 6 and 8 weeks). Sorghum silage had a leafy and soft texture with a fruity smell, which proved its desirable character with normal lactic acid fermentation. As such, it was with its comparatively higher dry matter content at the 6 or 8 weeks cutting interval, more suitable for ensiling. The crude protein concentration was not modified by the ensiling process, which was proved by the low ammoniacal nitrogen content. Sorghum silage had lower pH values at all three cutting intervals. On the basis of the NH3-N/TN content (3% could be obtained at the 6-week cutting interval

Bactericidal silver nanoparticles by atmospheric pressure solution plasma processing

Silver nanoparticles have applications in plasmonics, medicine, catalysis and electronics. We report a simple, cost-effective, facile and reproducible technique to synthesise silver nanoparticles via plasma-induced non-equilibrium liquid chemistry with the absence of a chemical reducing agent. Silver nanoparticles with tuneable sizes from 5.4 to 17.8 nm are synthesised and characterised using Transmission Electron Microscopy (TEM) and other analytic techniques. A mechanism for silver nanoparticle formation is also proposed. The antibacterial activity of the silver nanoparticles was investigated with gram-positive and gram-negative bacteria. The inhibition of both bacteria types was observed. This is a promising alternative method for the instant synthesis of silver nanoparticles, instead of the conventional chemical reduction route, for numerous applications.</p

Insights into amoxicillin degradation in water by non-thermal plasmas

Antibiotics have been extensively used as pharmaceuticals for diverse applications. However, their overuse and indiscriminate discharge to water systems have led to increased antibiotic levels in our aquatic environments, which poses risks to human and livestock health. Non-thermal plasma water. However, the issues of process scalability and the mechanisms towards understanding the plasma-induced degradation remain. This study addresses these issues by coupling a non-thermal plasma jet with a continuous flow reactor to reveal the effective mechanisms of amoxicillin degradation. Four industry-relevant feeding gases (nitrogen, air, argon, and oxygen), discharge voltages, and frequencies were assessed. Amoxicillin degradation efficiencies achieved using nitrogen and air were much higher compared to argon and oxygen and further improved by increasing the applied voltage and frequency. The efficiency of plasma-induced degradation depended on the interplay of hydrogen peroxide (H2O2) and nitrite (NO2−), validated by mimicked chemical solutions tests. Insights into prevailing degradation pathways were elucidated through the detection of intermediate products by advanced liquid chromatography-mass spectrometry.</p

Non-thermal plasma enhances performances of biochar in wastewater treatment and energy storage applications

Surface functionalization or modification to introduce more oxygen-containing functional groups to biochar is an effective strategy for tuning the physico-chemical properties and promoting follow-up applications. In this study, non-thermal plasma was applied for biochar surface carving before being used in contaminant removal and energy storage applications. The results showed that even a low dose of plasma exposure could introduce a high number density of oxygen-functional groups and enhance the hydrophilicity and metal affinity of the pristine biochar. The plasma-treated biochar enabled a faster metal-adsorption rate and a 40% higher maximum adsorption capacity of heavy metal ion Pb2+. Moreover, to add more functionality to biochar surface, biochar with and without plasma pre-treatment was activated by KOH at a temperature of 800 °C. Using the same amount of KOH, the plasma treatment resulted in an activated carbon product with the larger BET surface area and pore volume. The performance of the treated activated carbon as a supercapacitor electrode was also substantially improved by > 30%. This study may provide guidelines for enhancing the surface functionality and application performances of biochar using non-thermal-based techniques.[Figure not available: see fulltext.]</p