Attenuation coefficient for surface acoustic waves in fluid region

In recent years, surface acoustic wave devices used in bio-sensing applications have demonstrated high sensitivity in the detection of fluid properties such as density, viscosity, stream velocity. In this paper, a more effective measurement of the SAWsensorstructure is presented. It is reported that at density of 6 g/cm3, the amplitude of mechanical wave is excited while for electrical signal, attenuation at 3 g/cm3 reaches a peak.In our analysis, single–crystal Aluminium Nitride substrate is used. Several parameters of leaky waves including displacement, decay constant in the liquid media are analyzed

Improvement of adherence and anticorrosion properties of an epoxy-polyamide coating on steel by incorporation of an indole-3 butyric acid-modified nanomagnetite

In this study, synthesized magnetite (Fe 3 O 4 ) nanoparticles were treated with a corrosion inhibitor, indole-3 butyric acid (IBA) and incorporated in an epoxy-polyamide coating. The coating was applied on a carbon steel substrate. For comparison, coatings with- out particles or with nontreated Fe 3 O 4 particles were also prepared. The IBA-modified nanomagnetite (IBA–Fe 3 O 4 ) was characterized by infrared spec- troscopy and Zeta potential measurements. The inhibitive action of IBA was shown by electrochemical measurements (polarization curves) performed for a bare carbon steel in 0.1 M NaCl solution containing Fe 3 O 4 or IBA–Fe 3 O 4 nanoparticles. Adherence and anticorrosion properties of the epoxy-based coatings containing Fe 3 O 4 or IBA–Fe 3 O 4 were compared to those of the pure epoxy-polyamide resin by dry and wet adherence measurements and by salt spray test. The results showed significant improvement of the film adherence and higher corrosion protection of the carbon steel in the presence of IBA–Fe 3 O 4 . It was concluded that the IBA effect was restricted to the metal/coating interface

HIGH PROTECTION PERFORMANCE OF COATING SYSTEMS BASED ON ZINC RICH PRIMER AND FLUOROPOLYMER COATING

Coating systems based on zinc rich primer and fluoropolymer top coat were exposed for 8 years at different atmospheric stations in Vietnam: Hanoi, Ha Long and Nha Trang. For comparison the coating system with zinc rich primer and polyurethane topcoat was also tested. The degradations of coating systems were evaluated by gloss measurement and electrochemical impedance spectroscopy. The obtained results show that coating systems with zinc rich primer and top coatings based on fluoropolymer  and polyurethane topcoats show very high weather resistance and corrosion protection performance, but the systems with fluoropolymer are better than coating system with polyurethane topcoat

8-hydroxyquinoline-modified clay incorporated in an epoxy coating for the corrosion protection of carbon steel

In the present work, a well-known corrosion inhibitor (8-hydroxyquinoline (8HQ)) was inserted within the montmorillonite platelets (8HQ-MMT) and the modified clay was incorporated (3 wt.%) into a solvent-free epoxy coating which was afterwards deposited on carbon steel substrates. First, the inhibitive action of 8HQ was investigated by electrochemical methods carried out on a bare carbon steel rotating disk electrode in a 0.1 M NaCl solution. Then, electrochemical impedance measurements were performed to assess the effect of the 8HQ-MMT in the epoxy coating for the corrosion protection. The results were compared with a reference sample constituted by the epoxy coating containing an ammonium quaternary salt-modified clay. It was shown that the two coatings presented good barrier properties. Dry and wet adherence measurements revealed an improvement of the adherence when the 8HQ-MMT was incorporated into the coating by comparison with the reference sample. It was concluded that the 8HQ mainly had an effect at the metal/coating interface but its concentration was too low to afford significant corrosion protection of the carbon steel

Numerical study and experimental investigation of an electrohydrodynamic device for inertial sensing

We present a multi-physics simulation associated with experimental investigation for an electrohydrodynamic gyroscope based on ion wind corona discharge. The present device consisting of multiple point-ring electrodes generates a synthetic jet flow of ions for inertial sensing applications. Meanwhile the residual charge of jet is neutralized by an external ring electrode to guarantee the ion wind stable while circulating inside the device's channels. The working principle including the generation and then circulation of jet flow within the present device is firstly demonstrated by a numerical simulation and the feasibility and stability of the device are then successfully investigated by experimental work. Results show owing to the ion wind corona discharge based approach associated with new configuration, the present device is robust and consumes low energy

The immunogenicity of plant-based COE-GCN4pII protein in pigs against the highly virulent porcine epidemic diarrhea virus strain from genotype 2

Porcine epidemic diarrhea virus (PEDV) is a serious infectious causative agent in swine, especially in neonatal piglets. PEDV genotype 2 (G2) strains, particularly G2a, were the primary causes of porcine epidemic diarrhea (PED) outbreaks in Vietnam. Here, we produced a plant-based CO-26K-equivalent epitope (COE) variant from a Vietnamese highly virulent PEDV strain belonging to genotype 2a (COE/G2a) and evaluated the protective efficacy of COE/G2a-GCN4pII protein (COE/G2a-pII) in piglets against the highly virulent PEDV G2a strain following passive immunity. The 5-day-old piglets had high levels of PEDV-specific IgG antibodies, COE-IgA specific antibodies, neutralizing antibodies, and IFN-γ responses. After virulent challenge experiments, all of these piglets survived and had normal clinical symptoms, no watery diarrhea in feces, and an increase in their body weight, while all of the negative control piglets died. These results suggest that the COE/G2a-pII protein produced in plants can be developed as a promising vaccine candidate to protect piglets against PEDV G2a infection in Vietnam

A novel diagnostic model for tuberculous meningitis using Bayesian latent class analysis

Background Diagnosis of tuberculous meningitis (TBM) is hampered by the lack of a gold standard. Current microbiological tests lack sensitivity and clinical diagnostic approaches are subjective. We therefore built a diagnostic model that can be used before microbiological test results are known. Methods We included 659 individuals aged ≥ 16 years with suspected brain infections from a prospective observational study conducted in Vietnam. We fitted a logistic regression diagnostic model for TBM status, with unknown values estimated via a latent class model on three mycobacterial tests: Ziehl–Neelsen smear, Mycobacterial culture, and GeneXpert. We additionally re-evaluated mycobacterial test performance, estimated individual mycobacillary burden, and quantified the reduction in TBM risk after confirmatory tests were negative. We also fitted a simplified model and developed a scoring table for early screening. All models were compared and validated internally. Results Participants with HIV, miliary TB, long symptom duration, and high cerebrospinal fluid (CSF) lymphocyte count were more likely to have TBM. HIV and higher CSF protein were associated with higher mycobacillary burden. In the simplified model, HIV infection, clinical symptoms with long duration, and clinical or radiological evidence of extra-neural TB were associated with TBM At the cutpoints based on Youden’s Index, the sensitivity and specificity in diagnosing TBM for our full and simplified models were 86.0% and 79.0%, and 88.0% and 75.0% respectively. Conclusion Our diagnostic model shows reliable performance and can be developed as a decision assistant for clinicians to detect patients at high risk of TBM. Summary Diagnosis of tuberculous meningitis is hampered by the lack of gold standard. We developed a diagnostic model using latent class analysis, combining confirmatory test results and risk factors. Models were accurate, well-calibrated, and can support both clinical practice and research

A novel diagnostic model for tuberculous meningitis using Bayesian latent class analysis.

BACKGROUND: Diagnosis of tuberculous meningitis (TBM) is hampered by the lack of a gold standard. Current microbiological tests lack sensitivity and clinical diagnostic approaches are subjective. We therefore built a diagnostic model that can be used before microbiological test results are known. METHODS: We included 659 individuals aged [Formula: see text] years with suspected brain infections from a prospective observational study conducted in Vietnam. We fitted a logistic regression diagnostic model for TBM status, with unknown values estimated via a latent class model on three mycobacterial tests: Ziehl-Neelsen smear, Mycobacterial culture, and GeneXpert. We additionally re-evaluated mycobacterial test performance, estimated individual mycobacillary burden, and quantified the reduction in TBM risk after confirmatory tests were negative. We also fitted a simplified model and developed a scoring table for early screening. All models were compared and validated internally. RESULTS: Participants with HIV, miliary TB, long symptom duration, and high cerebrospinal fluid (CSF) lymphocyte count were more likely to have TBM. HIV and higher CSF protein were associated with higher mycobacillary burden. In the simplified model, HIV infection, clinical symptoms with long duration, and clinical or radiological evidence of extra-neural TB were associated with TBM At the cutpoints based on Youden's Index, the sensitivity and specificity in diagnosing TBM for our full and simplified models were 86.0% and 79.0%, and 88.0% and 75.0% respectively. CONCLUSION: Our diagnostic model shows reliable performance and can be developed as a decision assistant for clinicians to detect patients at high risk of TBM. Diagnosis of tuberculous meningitis is hampered by the lack of gold standard. We developed a diagnostic model using latent class analysis, combining confirmatory test results and risk factors. Models were accurate, well-calibrated, and can support both clinical practice and research

Effects of water scarcity awareness and climate change belief on recycled water usage willingness: Evidence from New Mexico, United States

The global water crisis is being exacerbated by climate change, even in the United States. Recycled water is a feasible alternative to alleviate the water shortage, but it is constrained by humans’ perceptions. The current study examines how residents’ water scarcity awareness and climate change belief influence their willingness to use recycled water directly and indirectly. Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of 1831 residents in Albuquerque, New Mexico, an arid inland region in the US. We discovered that residents’ willingness to use direct recycled potable water is positively affected by their awareness of water scarcity, but the effect is conditional on their belief in the impacts of climate change on the water cycle. Meanwhile, the willingness to use indirect recycled potable water is influenced by water scarcity awareness, and the belief in climate change further enhances this effect. These findings implicate that fighting climate change denialism and informing the public of the water scarcity situation in the region can contribute to the effectiveness and sustainability of long-term water conservation and climate change alleviation efforts